Similarity of markers identified from cancer gene expression studies: observations from GEO.
Shi, Xingjie; Shen, Shihao; Liu, Jin; Huang, Jian; Zhou, Yong; Ma, Shuangge
2014-09-01
Gene expression profiling has been extensively conducted in cancer research. The analysis of multiple independent cancer gene expression datasets may provide additional information and complement single-dataset analysis. In this study, we conduct multi-dataset analysis and are interested in evaluating the similarity of cancer-associated genes identified from different datasets. The first objective of this study is to briefly review some statistical methods that can be used for such evaluation. Both marginal analysis and joint analysis methods are reviewed. The second objective is to apply those methods to 26 Gene Expression Omnibus (GEO) datasets on five types of cancers. Our analysis suggests that for the same cancer, the marker identification results may vary significantly across datasets, and different datasets share few common genes. In addition, datasets on different cancers share few common genes. The shared genetic basis of datasets on the same or different cancers, which has been suggested in the literature, is not observed in the analysis of GEO data. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Integrative Analysis of Prognosis Data on Multiple Cancer Subtypes
Liu, Jin; Huang, Jian; Zhang, Yawei; Lan, Qing; Rothman, Nathaniel; Zheng, Tongzhang; Ma, Shuangge
2014-01-01
Summary In cancer research, profiling studies have been extensively conducted, searching for genes/SNPs associated with prognosis. Cancer is diverse. Examining the similarity and difference in the genetic basis of multiple subtypes of the same cancer can lead to a better understanding of their connections and distinctions. Classic meta-analysis methods analyze each subtype separately and then compare analysis results across subtypes. Integrative analysis methods, in contrast, analyze the raw data on multiple subtypes simultaneously and can outperform meta-analysis methods. In this study, prognosis data on multiple subtypes of the same cancer are analyzed. An AFT (accelerated failure time) model is adopted to describe survival. The genetic basis of multiple subtypes is described using the heterogeneity model, which allows a gene/SNP to be associated with prognosis of some subtypes but not others. A compound penalization method is developed to identify genes that contain important SNPs associated with prognosis. The proposed method has an intuitive formulation and is realized using an iterative algorithm. Asymptotic properties are rigorously established. Simulation shows that the proposed method has satisfactory performance and outperforms a penalization-based meta-analysis method and a regularized thresholding method. An NHL (non-Hodgkin lymphoma) prognosis study with SNP measurements is analyzed. Genes associated with the three major subtypes, namely DLBCL, FL, and CLL/SLL, are identified. The proposed method identifies genes that are different from alternatives and have important implications and satisfactory prediction performance. PMID:24766212
Nwosu, Amara Callistus; Mayland, Catriona R; Mason, Stephen R; Khodabukus, Andrew F; Varro, Andrea; Ellershaw, John E
2013-09-01
Decisions surrounding the administration of clinically assisted hydration to patients dying of cancer can be challenging because of the limited understanding of hydration in advanced cancer and a lack of evidence to guide health care professionals. Bioelectrical impedance analysis (BIA) has been used to assess hydration in various patient groupings, but evidence for its use in advanced cancer is limited. To critically appraise existing methods of hydration status assessment in advanced cancer and review the potential for BIA to assess hydration in advanced cancer. Searches were carried out in four electronic databases. A hand search of selected peer-reviewed journals and conference abstracts also was conducted. Studies reporting (de)hydration assessment (physical examination, biochemical measures, symptom assessment, and BIA) in patients with advanced cancer were included. The results highlight how clinical examination and biochemical tests are standard methods of assessing hydration, but limitations exist with these methods in advanced cancer. Furthermore, there is disagreement over the evidence for some commonly associated symptoms with dehydration in cancer. Although there are limitations with using BIA alone to assess hydration in advanced cancer, analysis of BIA raw measurements through the method of bioelectrical impedance vector analysis may have a role in this population. The benefits and burdens of providing clinically assisted hydration to patients dying of cancer are unclear. Bioelectrical impedance vector analysis shows promise as a hydration assessment tool but requires further study in advanced cancer. Innovative methodologies for research are required to add to the evidence base and ultimately improve the care for the dying. Copyright © 2013 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.
Van der Bij, Sjoukje; Vermeulen, Roel C H; Portengen, Lützen; Moons, Karel G M; Koffijberg, Hendrik
2016-05-01
Exposure to asbestos fibres increases the risk of mesothelioma and lung cancer. Although the vast majority of mesothelioma cases are caused by asbestos exposure, the number of asbestos-related lung cancers is less clear. This number cannot be determined directly as lung cancer causes are not clinically distinguishable but may be estimated using varying modelling methods. We applied three different modelling methods to the Dutch population supplemented with uncertainty ranges (UR) due to uncertainty in model input values. The first method estimated asbestos-related lung cancer cases directly from observed and predicted mesothelioma cases in an age-period-cohort analysis. The second method used evidence on the fraction of lung cancer cases attributable (population attributable risk (PAR)) to asbestos exposure. The third method incorporated risk estimates and population exposure estimates to perform a life table analysis. The three methods varied substantially in incorporated evidence. Moreover, the estimated number of asbestos-related lung cancer cases in the Netherlands between 2011 and 2030 depended crucially on the actual method applied, as the mesothelioma method predicts 17 500 expected cases (UR 7000-57 000), the PAR method predicts 12 150 cases (UR 6700-19 000), and the life table analysis predicts 6800 cases (UR 6800-33 850). The three different methods described resulted in absolute estimates varying by a factor of ∼2.5. These results show that accurate estimation of the impact of asbestos exposure on the lung cancer burden remains a challenge. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Single-Cell Sequencing for Precise Cancer Research: Progress and Prospects.
Zhang, Xiaoyan; Marjani, Sadie L; Hu, Zhaoyang; Weissman, Sherman M; Pan, Xinghua; Wu, Shixiu
2016-03-15
Advances in genomic technology have enabled the faithful detection and measurement of mutations and the gene expression profile of cancer cells at the single-cell level. Recently, several single-cell sequencing methods have been developed that permit the comprehensive and precise analysis of the cancer-cell genome, transcriptome, and epigenome. The use of these methods to analyze cancer cells has led to a series of unanticipated discoveries, such as the high heterogeneity and stochastic changes in cancer-cell populations, the new driver mutations and the complicated clonal evolution mechanisms, and the novel identification of biomarkers of variant tumors. These methods and the knowledge gained from their utilization could potentially improve the early detection and monitoring of rare cancer cells, such as circulating tumor cells and disseminated tumor cells, and promote the development of personalized and highly precise cancer therapy. Here, we discuss the current methods for single cancer-cell sequencing, with a strong focus on those practically used or potentially valuable in cancer research, including single-cell isolation, whole genome and transcriptome amplification, epigenome profiling, multi-dimensional sequencing, and next-generation sequencing and analysis. We also examine the current applications, challenges, and prospects of single cancer-cell sequencing. ©2016 American Association for Cancer Research.
NASA Astrophysics Data System (ADS)
Meksiarun, Phiranuphon; Ishigaki, Mika; Huck-Pezzei, Verena A. C.; Huck, Christian W.; Wongravee, Kanet; Sato, Hidetoshi; Ozaki, Yukihiro
2017-03-01
This study aimed to extract the paraffin component from paraffin-embedded oral cancer tissue spectra using three multivariate analysis (MVA) methods; Independent Component Analysis (ICA), Partial Least Squares (PLS) and Independent Component - Partial Least Square (IC-PLS). The estimated paraffin components were used for removing the contribution of paraffin from the tissue spectra. These three methods were compared in terms of the efficiency of paraffin removal and the ability to retain the tissue information. It was found that ICA, PLS and IC-PLS could remove the paraffin component from the spectra at almost the same level while Principal Component Analysis (PCA) was incapable. In terms of retaining cancer tissue spectral integrity, effects of PLS and IC-PLS on the non-paraffin region were significantly less than that of ICA where cancer tissue spectral areas were deteriorated. The paraffin-removed spectra were used for constructing Raman images of oral cancer tissue and compared with Hematoxylin and Eosin (H&E) stained tissues for verification. This study has demonstrated the capability of Raman spectroscopy together with multivariate analysis methods as a diagnostic tool for the paraffin-embedded tissue section.
How Do the Metabolic Effects of Chronic Stress Influence Breast Cancer Biology
2013-04-01
meta - analysis . International Journal of Cancer. 2003;107:1023-9. 3. Song M, Lee K-M, Kang D. Breast Cancer Prevention Based on Gene- Environment...7 PCR system. Details of the statistical analysis are provided in supplemental methods 1 section. 2 Adipocyte glucose consumption and...life events and breast cancer risk: a meta - analysis . International Journal of Cancer. 7 2003;107:1023-9. 8 3. Song M, Lee K-M, Kang D. Breast
A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing
Alioto, Tyler S.; Buchhalter, Ivo; Derdak, Sophia; Hutter, Barbara; Eldridge, Matthew D.; Hovig, Eivind; Heisler, Lawrence E.; Beck, Timothy A.; Simpson, Jared T.; Tonon, Laurie; Sertier, Anne-Sophie; Patch, Ann-Marie; Jäger, Natalie; Ginsbach, Philip; Drews, Ruben; Paramasivam, Nagarajan; Kabbe, Rolf; Chotewutmontri, Sasithorn; Diessl, Nicolle; Previti, Christopher; Schmidt, Sabine; Brors, Benedikt; Feuerbach, Lars; Heinold, Michael; Gröbner, Susanne; Korshunov, Andrey; Tarpey, Patrick S.; Butler, Adam P.; Hinton, Jonathan; Jones, David; Menzies, Andrew; Raine, Keiran; Shepherd, Rebecca; Stebbings, Lucy; Teague, Jon W.; Ribeca, Paolo; Giner, Francesc Castro; Beltran, Sergi; Raineri, Emanuele; Dabad, Marc; Heath, Simon C.; Gut, Marta; Denroche, Robert E.; Harding, Nicholas J.; Yamaguchi, Takafumi N.; Fujimoto, Akihiro; Nakagawa, Hidewaki; Quesada, Víctor; Valdés-Mas, Rafael; Nakken, Sigve; Vodák, Daniel; Bower, Lawrence; Lynch, Andrew G.; Anderson, Charlotte L.; Waddell, Nicola; Pearson, John V.; Grimmond, Sean M.; Peto, Myron; Spellman, Paul; He, Minghui; Kandoth, Cyriac; Lee, Semin; Zhang, John; Létourneau, Louis; Ma, Singer; Seth, Sahil; Torrents, David; Xi, Liu; Wheeler, David A.; López-Otín, Carlos; Campo, Elías; Campbell, Peter J.; Boutros, Paul C.; Puente, Xose S.; Gerhard, Daniela S.; Pfister, Stefan M.; McPherson, John D.; Hudson, Thomas J.; Schlesner, Matthias; Lichter, Peter; Eils, Roland; Jones, David T. W.; Gut, Ivo G.
2015-01-01
As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy. PMID:26647970
A method for generating new datasets based on copy number for cancer analysis.
Kim, Shinuk; Kon, Mark; Kang, Hyunsik
2015-01-01
New data sources for the analysis of cancer data are rapidly supplementing the large number of gene-expression markers used for current methods of analysis. Significant among these new sources are copy number variation (CNV) datasets, which typically enumerate several hundred thousand CNVs distributed throughout the genome. Several useful algorithms allow systems-level analyses of such datasets. However, these rich data sources have not yet been analyzed as deeply as gene-expression data. To address this issue, the extensive toolsets used for analyzing expression data in cancerous and noncancerous tissue (e.g., gene set enrichment analysis and phenotype prediction) could be redirected to extract a great deal of predictive information from CNV data, in particular those derived from cancers. Here we present a software package capable of preprocessing standard Agilent copy number datasets into a form to which essentially all expression analysis tools can be applied. We illustrate the use of this toolset in predicting the survival time of patients with ovarian cancer or glioblastoma multiforme and also provide an analysis of gene- and pathway-level deletions in these two types of cancer.
Wu, Zheng; Zeng, Li-bo; Wu, Qiong-shui
2016-02-01
The conventional cervical cancer screening methods mainly include TBS (the bethesda system) classification method and cellular DNA quantitative analysis, however, by using multiple staining method in one cell slide, which is staining the cytoplasm with Papanicolaou reagent and the nucleus with Feulgen reagent, the study of achieving both two methods in the cervical cancer screening at the same time is still blank. Because the difficulty of this multiple staining method is that the absorbance of the non-DNA material may interfere with the absorbance of DNA, so that this paper has set up a multi-spectral imaging system, and established an absorbance unmixing model by using multiple linear regression method based on absorbance's linear superposition character, and successfully stripped out the absorbance of DNA to run the DNA quantitative analysis, and achieved the perfect combination of those two kinds of conventional screening method. Through a series of experiment we have proved that between the absorbance of DNA which is calculated by the absorbance unmixxing model and the absorbance of DNA which is measured there is no significant difference in statistics when the test level is 1%, also the result of actual application has shown that there is no intersection between the confidence interval of the DNA index of the tetraploid cells which are screened by using this paper's analysis method when the confidence level is 99% and the DNA index's judging interval of cancer cells, so that the accuracy and feasibility of the quantitative DNA analysis with multiple staining method expounded by this paper have been verified, therefore this analytical method has a broad application prospect and considerable market potential in early diagnosis of cervical cancer and other cancers.
Analysis of cancer-related fatigue based on smart bracelet devices.
Shen, Hong; Hou, Honglun; Tian, Wei; Wu, MingHui; Chen, Tianzhou; Zhong, Xian
2016-01-01
Fatigue is the most common symptom associated with cancer and its treatment, and profoundly affects all aspects of quality of life for cancer patients. It is very important to measure and manage cancer-related fatigue. Usually, the cancer-related fatigue scores, which estimate the degree of fatigue, are self-reported by cancer patients using standardized assessment tools. But most of the classical methods used for measurement of fatigue are subjective and inconvenient. In this study, we try to establish a new method to assess cancer-related fatigue objectively and accurately by using smart bracelet. All patients with metastatic pancreatic cancer wore smart bracelet for recording the physical activity including step count and sleep time before and after chemotherapy. Meantime, their psychological state was assessed by completing questionnaire tables as cancer-related fatigue scores. Step count record by smart bracelet reflecting the physical performance dramatically decreased in the initial days of chemotherapy and recovered in the next few days. Statistical analysis showed a strong and significant correlation between self-reported cancer-related fatigue and physical performance (P= 0.000, r=-0.929). Sleep time was also significantly correlated with fatigue (P= 0.000, r= 0.723). Multiple regression analysis showed that physical performance and sleep time are significant predictors of fatigue. Measuring activity using smart bracelets may be an appropriate method for quantitative and objective measurement of cancer-related fatigue by using smart bracelet devices.
Kageyama, Shinji; Shinmura, Kazuya; Yamamoto, Hiroko; Goto, Masanori; Suzuki, Koichi; Tanioka, Fumihiko; Tsuneyoshi, Toshihiro; Sugimura, Haruhiko
2008-04-01
The PCR-based DNA fingerprinting method called the methylation-sensitive amplified fragment length polymorphism (MS-AFLP) analysis is used for genome-wide scanning of methylation status. In this study, we developed a method of fluorescence-labeled MS-AFLP (FL-MS-AFLP) analysis by applying a fluorescence-labeled primer and fluorescence-detecting electrophoresis apparatus to the existing method of MS-AFLP analysis. The FL-MS-AFLP analysis enables quantitative evaluation of more than 350 random CpG loci per run. It was shown to allow evaluation of the differences in methylation level of blood DNA of gastric cancer patients and evaluation of hypermethylation and hypomethylation in DNA from gastric cancer tissue in comparison with adjacent non-cancerous tissue.
Qualitative Improvement Methods Through Analysis of Inquiry Contents for Cancer Registration
Boo, Yoo-Kyung; Lim, Hyun-Sook; Kim, Jung-Eun; Kim, Kyoung-Beom; Won, Young-Joo
2017-06-25
Background: In Korea, the national cancer database was constructed after the initiation of the national cancer registration project in 1980, and the annual national cancer registration report has been published every year since 2005. Consequently, data management must begin even at the stage of data collection in order to ensure quality. Objectives: To determine the suitability of cancer registries’ inquiry tools through the inquiry analysis of the Korea Central Cancer Registry (KCCR), and identify the needs to improve the quality of cancer registration. Methods: Results of 721 inquiries to the KCCR from 2000 to 2014 were analyzed by inquiry year, question type, and medical institution characteristics. Using Stata version 14.1, descriptive analysis was performed to identify general participant characteristics, and chi-square analysis was applied to investigate significant differences in distribution characteristics by factors affecting the quality of cancer registration data. Results: The number of inquiries increased in 2005–2009. During this period, there were various changes, including the addition of cancer registration items such as brain tumors and guideline updates. Of the inquirers, 65.3% worked at hospitals in metropolitan cities and 60.89% of hospitals had 601–1000 beds. Tertiary hospitals had the highest number of inquiries (64.91%), and the highest number of questions by type were 353 (48.96%) for histological codes, 92 (12.76%) for primary sites, and 76 (10.54%) for reportable. Conclusions: A cancer registration inquiry system is an effective method when not confident about codes during cancer registration, or when confronting cancer cases in which previous clinical knowledge or information on the cancer registration guidelines are insufficient. Creative Commons Attribution License
Bonan, Brigitte; Martelli, Nicolas; Berhoune, Malik; Maestroni, Marie-Laure; Havard, Laurent; Prognon, Patrice
2009-02-01
To apply the Hazard analysis and Critical Control Points method to the preparation of anti-cancer drugs. To identify critical control points in our cancer chemotherapy process and to propose control measures and corrective actions to manage these processes. The Hazard Analysis and Critical Control Points application began in January 2004 in our centralized chemotherapy compounding unit. From October 2004 to August 2005, monitoring of the process nonconformities was performed to assess the method. According to the Hazard Analysis and Critical Control Points method, a multidisciplinary team was formed to describe and assess the cancer chemotherapy process. This team listed all of the critical points and calculated their risk indexes according to their frequency of occurrence, their severity and their detectability. The team defined monitoring, control measures and corrective actions for each identified risk. Finally, over a 10-month period, pharmacists reported each non-conformity of the process in a follow-up document. Our team described 11 steps in the cancer chemotherapy process. The team identified 39 critical control points, including 11 of higher importance with a high-risk index. Over 10 months, 16,647 preparations were performed; 1225 nonconformities were reported during this same period. The Hazard Analysis and Critical Control Points method is relevant when it is used to target a specific process such as the preparation of anti-cancer drugs. This method helped us to focus on the production steps, which can have a critical influence on product quality, and led us to improve our process.
Breast cancer histopathology image analysis: a review.
Veta, Mitko; Pluim, Josien P W; van Diest, Paul J; Viergever, Max A
2014-05-01
This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients.
Rizzardi, Anthony E; Zhang, Xiaotun; Vogel, Rachel Isaksson; Kolb, Suzanne; Geybels, Milan S; Leung, Yuet-Kin; Henriksen, Jonathan C; Ho, Shuk-Mei; Kwak, Julianna; Stanford, Janet L; Schmechel, Stephen C
2016-07-11
Digital image analysis offers advantages over traditional pathologist visual scoring of immunohistochemistry, although few studies examining the correlation and reproducibility of these methods have been performed in prostate cancer. We evaluated the correlation between digital image analysis (continuous variable data) and pathologist visual scoring (quasi-continuous variable data), reproducibility of each method, and association of digital image analysis methods with outcomes using prostate cancer tissue microarrays (TMAs) stained for estrogen receptor-β2 (ERβ2). Prostate cancer TMAs were digitized and evaluated by pathologist visual scoring versus digital image analysis for ERβ2 staining within tumor epithelium. Two independent analysis runs were performed to evaluate reproducibility. Image analysis data were evaluated for associations with recurrence-free survival and disease specific survival following radical prostatectomy. We observed weak/moderate Spearman correlation between digital image analysis and pathologist visual scores of tumor nuclei (Analysis Run A: 0.42, Analysis Run B: 0.41), and moderate/strong correlation between digital image analysis and pathologist visual scores of tumor cytoplasm (Analysis Run A: 0.70, Analysis Run B: 0.69). For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99). Further, ERβ2 staining was significantly associated with increased risk of prostate cancer-specific mortality (PCSM) when quantified by cytoplasmic digital image analysis (HR 2.16, 95 % CI 1.02-4.57, p = 0.045), nuclear image analysis (HR 2.67, 95 % CI 1.20-5.96, p = 0.016), and total malignant epithelial area analysis (HR 5.10, 95 % CI 1.70-15.34, p = 0.004). After adjusting for clinicopathologic factors, only total malignant epithelial area ERβ2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012). Digital methods of immunohistochemical quantification are more reproducible than pathologist visual scoring in prostate cancer, suggesting that digital methods are preferable and especially warranted for studies involving large sample sizes.
The Tracer Method of Curriculum Analysis in Cancer Education
ERIC Educational Resources Information Center
Mahan, J. Maurice; And Others
1976-01-01
To assist faculty involved in cancer education in various courses in the curriculum, rather than instituting a new course in oncology, a method was developed for identifying and assessing cancer-related content (a clinical clerk attended lectures, interviewed instructors, reviewed syllibi etc.) and a comprehensive description was produced and…
Dong, Skye T; Costa, Daniel S J; Butow, Phyllis N; Lovell, Melanie R; Agar, Meera; Velikova, Galina; Teckle, Paulos; Tong, Allison; Tebbutt, Niall C; Clarke, Stephen J; van der Hoek, Kim; King, Madeleine T; Fayers, Peter M
2016-01-01
Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.
2016-01-01
Abstract Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z -score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z -score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z -score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications. PMID:26504096
Szarvas, Tibor
2009-12-01
Bladder cancer is the second most common malignancy affecting the urinary system. Currently, histology is the only tool that determines therapy and patients' prognosis. As the treatment of non-invasive (Ta/T1) and muscle invasive (T2-T4) bladder tumors are completely different, correct staging is important, although it is often hampered by disturbing factors. Molecular methods offer new prospects for early disease detection, confirmation of unclear histological findings and prognostication. Applying molecular biological methods, the present study is searching for answers to current diagnostic and prognostic problems in bladder carcinoma. We analyzed tumor, blood and/or urine samples of 334 bladder cancer patients and 117 control individuals. Genetic alterations were analyzed in urine samples of patients and controls, both by PCR-based microsatellite loss of heterozigosity (LOH) analysis using 12 fluorescently labeled primers and by DNA hybridization based UroVysion FISH technique using 4 probes, to assess the diagnostic values of these methods. Whole genome microsatellite analysis (with 400 markers) was performed in tumor and blood specimens of bladder cancer patients to find chromosomal regions, the loss of which may be associated with tumor stage. Furthermore, we assessed the prognostic value of Tie2, VEGF, Angiopoietin-1 and -2. We concluded that DNA analysis of voided urine samples by microsatellite analysis and FISH are sensitive and non-invasive methods to detect bladder cancer. Furthermore, we established a panel of microsatellite markers that could differentiate between non-invasive and invasive bladder cancer. However, further analyses in a larger cohort of patients are needed to assess their specificity and sensitivity. Finally, we identified high Ang-2 and low Tie2 gene expression as significant and independent risk factors of tumor recurrence and cancer related survival.
NASA Astrophysics Data System (ADS)
Huang, Shaohua; Wang, Lan; Chen, Weisheng; Feng, Shangyuan; Lin, Juqiang; Huang, Zufang; Chen, Guannan; Li, Buhong; Chen, Rong
2014-11-01
Non-invasive esophagus cancer detection based on urine surface-enhanced Raman spectroscopy (SERS) analysis was presented. Urine SERS spectra were measured on esophagus cancer patients (n = 56) and healthy volunteers (n = 36) for control analysis. Tentative assignments of the urine SERS spectra indicated some interesting esophagus cancer-specific biomolecular changes, including a decrease in the relative content of urea and an increase in the percentage of uric acid in the urine of esophagus cancer patients compared to that of healthy subjects. Principal component analysis (PCA) combined with linear discriminant analysis (LDA) was employed to analyze and differentiate the SERS spectra between normal and esophagus cancer urine. The diagnostic algorithms utilizing a multivariate analysis method achieved a diagnostic sensitivity of 89.3% and specificity of 83.3% for separating esophagus cancer samples from normal urine samples. These results from the explorative work suggested that silver nano particle-based urine SERS analysis coupled with PCA-LDA multivariate analysis has potential for non-invasive detection of esophagus cancer.
Moon, Myungjin; Nakai, Kenta
2018-04-01
Currently, cancer biomarker discovery is one of the important research topics worldwide. In particular, detecting significant genes related to cancer is an important task for early diagnosis and treatment of cancer. Conventional studies mostly focus on genes that are differentially expressed in different states of cancer; however, noise in gene expression datasets and insufficient information in limited datasets impede precise analysis of novel candidate biomarkers. In this study, we propose an integrative analysis of gene expression and DNA methylation using normalization and unsupervised feature extractions to identify candidate biomarkers of cancer using renal cell carcinoma RNA-seq datasets. Gene expression and DNA methylation datasets are normalized by Box-Cox transformation and integrated into a one-dimensional dataset that retains the major characteristics of the original datasets by unsupervised feature extraction methods, and differentially expressed genes are selected from the integrated dataset. Use of the integrated dataset demonstrated improved performance as compared with conventional approaches that utilize gene expression or DNA methylation datasets alone. Validation based on the literature showed that a considerable number of top-ranked genes from the integrated dataset have known relationships with cancer, implying that novel candidate biomarkers can also be acquired from the proposed analysis method. Furthermore, we expect that the proposed method can be expanded for applications involving various types of multi-omics datasets.
Cancer Imaging Phenomics Toolkit (CaPTk) | Informatics Technology for Cancer Research (ITCR)
CaPTk is a software toolkit to facilitate translation of quantitative image analysis methods that help us obtain rich imaging phenotypic signatures of oncologic images and relate them to precision diagnostics and prediction of clinical outcomes, as well as to underlying molecular characteristics of cancer. The stand-alone graphical user interface of CaPTk brings analysis methods from the realm of medical imaging research to the clinic, and will be extended to use web-based services for computationally-demanding pipelines.
A Mass Spectrometric Analysis Method Based on PPCA and SVM for Early Detection of Ovarian Cancer.
Wu, Jiang; Ji, Yanju; Zhao, Ling; Ji, Mengying; Ye, Zhuang; Li, Suyi
2016-01-01
Background. Surfaced-enhanced laser desorption-ionization-time of flight mass spectrometry (SELDI-TOF-MS) technology plays an important role in the early diagnosis of ovarian cancer. However, the raw MS data is highly dimensional and redundant. Therefore, it is necessary to study rapid and accurate detection methods from the massive MS data. Methods. The clinical data set used in the experiments for early cancer detection consisted of 216 SELDI-TOF-MS samples. An MS analysis method based on probabilistic principal components analysis (PPCA) and support vector machine (SVM) was proposed and applied to the ovarian cancer early classification in the data set. Additionally, by the same data set, we also established a traditional PCA-SVM model. Finally we compared the two models in detection accuracy, specificity, and sensitivity. Results. Using independent training and testing experiments 10 times to evaluate the ovarian cancer detection models, the average prediction accuracy, sensitivity, and specificity of the PCA-SVM model were 83.34%, 82.70%, and 83.88%, respectively. In contrast, those of the PPCA-SVM model were 90.80%, 92.98%, and 88.97%, respectively. Conclusions. The PPCA-SVM model had better detection performance. And the model combined with the SELDI-TOF-MS technology had a prospect in early clinical detection and diagnosis of ovarian cancer.
Jin, Rong; Xia, Yiqun; Chen, Qiuxiang; Li, Wulan; Chen, Dahui; Ye, Hui; Zhao, Chengguang; Du, Xiaojing; Shi, Dengjian; Wu, Jianzhang; Liang, Guang
2016-01-01
Background The transcription factor nuclear factor-κB (NF-κB) is constitutively activated in a variety of human cancers, including gastric cancer. NF-κB inhibitors that selectively kill cancer cells are urgently needed for cancer treatment. Curcumin is a potent inhibitor of NF-κB activation. Unfortunately, the therapeutic potential of curcumin is limited by its relatively low potency and poor cellular bioavailability. In this study, we presented a novel NF-κB inhibitor named Da0324, a synthetic asymmetric mono-carbonyl analog of curcumin. The purpose of this study is to research the expression of NF-κB in gastric cancer and the antitumor activity and mechanism of Da0324 on human gastric cancer cells. Methods The expressions between gastric cancer tissues/cells and normal gastric tissues/cells of NF-κB were evaluated by Western blot. The inhibition viability of compounds on human gastric cancer cell lines SGC-7901, BGC-823, MGC-803, and normal gastric mucosa epithelial cell line GES-1 was assessed with the 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide assay. Absorption spectrum method and high-performance liquid chromatography method detected the stability of the compound in vitro. The compound-induced changes of inducible NF-κB activation in the SGC-7901 and BGC-823 cells were examined by Western blot analysis and immunofluorescence methods. The antitumor activity of compound was performed by clonogenic assay, matrigel invasion assay, flow cytometric analysis, Western blot analysis, and Hoechst 33258 staining assay. Results High levels of p65 were found in gastric cancer tissues and cells. Da0324 displayed higher growth inhibition against several types of gastric cancer cell lines and showed relatively low toxicity to GES-1. Moreover, Da0324 was more stable than curcumin in vitro. Western blot analysis and immunofluorescence methods showed that Da0324 blocked NF-κB activation. In addition, Da0324 significantly inhibited tumor proliferation and invasion, arrested the cell cycle, and induced apoptosis in vitro. Conclusion The asymmetric mono-carbonyl analog of curcumin Da0324 exhibited significantly improved antigastric cancer activity. Da0324 may be a promising NF-κB inhibitor for the selective targeting of cancer cells. However, further studies are needed in animals to validate these findings for the therapeutic use of Da0324. PMID:27042000
[Screening for cancer - economic consideration and cost-effectiveness].
Kjellberg, Jakob
2014-06-09
Cost-effectiveness analysis has become an accepted method to evaluate medical technology and allocate scarce health-care resources. Published decision analyses show that screening for cancer in general is cost-effective. However, cost-effectiveness analyses are only as good as the clinical data and the results are sensitive to the chosen methods and perspective of the analysis.
Fafin-Lefevre, Mélanie; Morlais, Fabrice; Guittet, Lydia; Clin, Bénédicte; Launoy, Guy; Galateau-Sallé, Françoise; Plancoulaine, Benoît; Herlin, Paulette; Letourneux, Marc
2011-08-01
To identify which morphologic or densitometric parameters are modified in cell nuclei from bronchopulmonary cancer based on 18 parameters involving shape, intensity, chromatin, texture, and DNA content and develop a bronchopulmonary cancer screening method relying on analysis of sputum sample cell nuclei. A total of 25 sputum samples from controls and 22 bronchial aspiration samples from patients presenting with bronchopulmonary cancer who were professionally exposed to cancer were used. After Feulgen staining, 18 morphologic and DNA content parameters were measured on cell nuclei, via image cytom- etry. A method was developed for analyzing distribution quantiles, compared with simply interpreting mean values, to characterize morphologic modifications in cell nuclei. Distribution analysis of parameters enabled us to distinguish 13 of 18 parameters that demonstrated significant differences between controls and cancer cases. These parameters, used alone, enabled us to distinguish two population types, with both sensitivity and specificity > 70%. Three parameters offered 100% sensitivity and specificity. When mean values offered high sensitivity and specificity, comparable or higher sensitivity and specificity values were observed for at least one of the corresponding quantiles. Analysis of modification in morphologic parameters via distribution analysis proved promising for screening bronchopulmonary cancer from sputum.
Texture analysis of tissues in Gleason grading of prostate cancer
NASA Astrophysics Data System (ADS)
Alexandratou, Eleni; Yova, Dido; Gorpas, Dimitris; Maragos, Petros; Agrogiannis, George; Kavantzas, Nikolaos
2008-02-01
Prostate cancer is a common malignancy among maturing men and the second leading cause of cancer death in USA. Histopathological grading of prostate cancer is based on tissue structural abnormalities. Gleason grading system is the gold standard and is based on the organization features of prostatic glands. Although Gleason score has contributed on cancer prognosis and on treatment planning, its accuracy is about 58%, with this percentage to be lower in GG2, GG3 and GG5 grading. On the other hand it is strongly affected by "inter- and intra observer variations", making the whole process very subjective. Therefore, there is need for the development of grading tools based on imaging and computer vision techniques for a more accurate prostate cancer prognosis. The aim of this paper is the development of a novel method for objective grading of biopsy specimen in order to support histopathological prognosis of the tumor. This new method is based on texture analysis techniques, and particularly on Gray Level Co-occurrence Matrix (GLCM) that estimates image properties related to second order statistics. Histopathological images of prostate cancer, from Gleason grade2 to Gleason grade 5, were acquired and subjected to image texture analysis. Thirteen texture characteristics were calculated from this matrix as they were proposed by Haralick. Using stepwise variable selection, a subset of four characteristics were selected and used for the description and classification of each image field. The selected characteristics profile was used for grading the specimen with the multiparameter statistical method of multiple logistic discrimination analysis. The subset of these characteristics provided 87% correct grading of the specimens. The addition of any of the remaining characteristics did not improve significantly the diagnostic ability of the method. This study demonstrated that texture analysis techniques could provide valuable grading decision support to the pathologists, concerning prostate cancer prognosis.
NASA Astrophysics Data System (ADS)
Liu, Ping; Qi, Chu-Bo; Zhu, Quan-Fei; Yuan, Bi-Feng; Feng, Yu-Qi
2016-02-01
Precursor ion scan and multiple reaction monitoring scan (MRM) are two typical scan modes in mass spectrometry analysis. Here, we developed a strategy by combining stable isotope labeling (IL) with liquid chromatography-mass spectrometry (LC-MS) under double precursor ion scan (DPI) and MRM for analysis of thiols in 5 types of human cancer urine. Firstly, the IL-LC-DPI-MS method was applied for non-targeted profiling of thiols from cancer samples. Compared to traditional full scan mode, the DPI method significantly improved identification selectivity and accuracy. 103 thiol candidates were discovered in all cancers and 6 thiols were identified by their standards. It is worth noting that pantetheine, for the first time, was identified in human urine. Secondly, the IL-LC-MRM-MS method was developed for relative quantification of thiols in cancers compared to healthy controls. All the MRM transitions of light and heavy labeled thiols were acquired from urines by using DPI method. Compared to DPI method, the sensitivity of MRM improved by 2.1-11.3 folds. In addition, the concentration of homocysteine, γ-glutamylcysteine and pantetheine enhanced more than two folds in cancer patients compared to healthy controls. Taken together, the method demonstrated to be a promising strategy for identification and comprehensive quantification of thiols in human urines.
Liu, Ping; Qi, Chu-Bo; Zhu, Quan-Fei; Yuan, Bi-Feng; Feng, Yu-Qi
2016-01-01
Precursor ion scan and multiple reaction monitoring scan (MRM) are two typical scan modes in mass spectrometry analysis. Here, we developed a strategy by combining stable isotope labeling (IL) with liquid chromatography-mass spectrometry (LC-MS) under double precursor ion scan (DPI) and MRM for analysis of thiols in 5 types of human cancer urine. Firstly, the IL-LC-DPI-MS method was applied for non-targeted profiling of thiols from cancer samples. Compared to traditional full scan mode, the DPI method significantly improved identification selectivity and accuracy. 103 thiol candidates were discovered in all cancers and 6 thiols were identified by their standards. It is worth noting that pantetheine, for the first time, was identified in human urine. Secondly, the IL-LC-MRM-MS method was developed for relative quantification of thiols in cancers compared to healthy controls. All the MRM transitions of light and heavy labeled thiols were acquired from urines by using DPI method. Compared to DPI method, the sensitivity of MRM improved by 2.1–11.3 folds. In addition, the concentration of homocysteine, γ-glutamylcysteine and pantetheine enhanced more than two folds in cancer patients compared to healthy controls. Taken together, the method demonstrated to be a promising strategy for identification and comprehensive quantification of thiols in human urines. PMID:26888486
Levman, Jacob E D; Gallego-Ortiz, Cristina; Warner, Ellen; Causer, Petrina; Martel, Anne L
2016-02-01
Magnetic resonance imaging (MRI)-enabled cancer screening has been shown to be a highly sensitive method for the early detection of breast cancer. Computer-aided detection systems have the potential to improve the screening process by standardizing radiologists to a high level of diagnostic accuracy. This retrospective study was approved by the institutional review board of Sunnybrook Health Sciences Centre. This study compares the performance of a proposed method for computer-aided detection (based on the second-order spatial derivative of the relative signal intensity) with the signal enhancement ratio (SER) on MRI-based breast screening examinations. Comparison is performed using receiver operating characteristic (ROC) curve analysis as well as free-response receiver operating characteristic (FROC) curve analysis. A modified computer-aided detection system combining the proposed approach with the SER method is also presented. The proposed method provides improvements in the rates of false positive markings over the SER method in the detection of breast cancer (as assessed by FROC analysis). The modified computer-aided detection system that incorporates both the proposed method and the SER method yields ROC results equal to that produced by SER while simultaneously providing improvements over the SER method in terms of false positives per noncancerous exam. The proposed method for identifying malignancies outperforms the SER method in terms of false positives on a challenging dataset containing many small lesions and may play a useful role in breast cancer screening by MRI as part of a computer-aided detection system.
Sherman, Recinda L; Henry, Kevin A; Tannenbaum, Stacey L; Feaster, Daniel J; Kobetz, Erin; Lee, David J
2014-03-20
Epidemiologists are gradually incorporating spatial analysis into health-related research as geocoded cases of disease become widely available and health-focused geospatial computer applications are developed. One health-focused application of spatial analysis is cluster detection. Using cluster detection to identify geographic areas with high-risk populations and then screening those populations for disease can improve cancer control. SaTScan is a free cluster-detection software application used by epidemiologists around the world to describe spatial clusters of infectious and chronic disease, as well as disease vectors and risk factors. The objectives of this article are to describe how spatial analysis can be used in cancer control to detect geographic areas in need of colorectal cancer screening intervention, identify issues commonly encountered by SaTScan users, detail how to select the appropriate methods for using SaTScan, and explain how method selection can affect results. As an example, we used various methods to detect areas in Florida where the population is at high risk for late-stage diagnosis of colorectal cancer. We found that much of our analysis was underpowered and that no single method detected all clusters of statistical or public health significance. However, all methods detected 1 area as high risk; this area is potentially a priority area for a screening intervention. Cluster detection can be incorporated into routine public health operations, but the challenge is to identify areas in which the burden of disease can be alleviated through public health intervention. Reliance on SaTScan's default settings does not always produce pertinent results.
Integrative Analysis of High-throughput Cancer Studies with Contrasted Penalization
Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Shia, BenChang; Ma, Shuangge
2015-01-01
In cancer studies with high-throughput genetic and genomic measurements, integrative analysis provides a way to effectively pool and analyze heterogeneous raw data from multiple independent studies and outperforms “classic” meta-analysis and single-dataset analysis. When marker selection is of interest, the genetic basis of multiple datasets can be described using the homogeneity model or the heterogeneity model. In this study, we consider marker selection under the heterogeneity model, which includes the homogeneity model as a special case and can be more flexible. Penalization methods have been developed in the literature for marker selection. This study advances from the published ones by introducing the contrast penalties, which can accommodate the within- and across-dataset structures of covariates/regression coefficients and, by doing so, further improve marker selection performance. Specifically, we develop a penalization method that accommodates the across-dataset structures by smoothing over regression coefficients. An effective iterative algorithm, which calls an inner coordinate descent iteration, is developed. Simulation shows that the proposed method outperforms the benchmark with more accurate marker identification. The analysis of breast cancer and lung cancer prognosis studies with gene expression measurements shows that the proposed method identifies genes different from those using the benchmark and has better prediction performance. PMID:24395534
KRAS, NRAS and BRAF mutations in Greek and Romanian patients with colorectal cancer: a cohort study
Negru, Serban; Papadopoulou, Eirini; Apessos, Angela; Stanculeanu, Dana Lucia; Ciuleanu, Eliade; Volovat, Constantin; Croitoru, Adina; Kakolyris, Stylianos; Aravantinos, Gerasimos; Ziras, Nikolaos; Athanasiadis, Elias; Touroutoglou, Nikolaos; Pavlidis, Nikolaos; Kalofonos, Haralabos P; Nasioulas, George
2014-01-01
Objectives Treatment decision-making in colorectal cancer is often guided by tumour tissue molecular analysis. The aim of this study was the development and validation of a high-resolution melting (HRM) method for the detection of KRAS, NRAS and BRAF mutations in Greek and Romanian patients with colorectal cancer and determination of the frequency of these mutations in the respective populations. Setting Diagnostic molecular laboratory located in Athens, Greece. Participants 2425 patients with colorectal cancer participated in the study. Primary and secondary outcome measures 2071 patients with colorectal cancer (1699 of Greek and 372 of Romanian origin) were analysed for KRAS exon 2 mutations. In addition, 354 tumours from consecutive patients (196 Greek and 161 Romanian) were subjected to full KRAS (exons 2, 3 and 4), NRAS (exons 2, 3 and 4) and BRAF (exon 15) analysis. KRAS, NRAS and BRAF mutation detection was performed by a newly designed HRM analysis protocol, followed by Sanger sequencing. Results KRAS exon 2 mutations (codons 12/13) were detected in 702 of the 1699 Greek patients with colorectal carcinoma analysed (41.3%) and in 39.2% (146/372) of the Romanian patients. Among the 354 patients who were subjected to full KRAS, NRAS and BRAF analysis, 40.96% had KRAS exon 2 mutations (codons 12/13). Among the KRAS exon 2 wild-type patients 15.31% harboured additional RAS mutations and 12.44% BRAF mutations. The newly designed HRM method used showed a higher sensitivity compared with the sequencing method. Conclusions The HRM method developed was shown to be a reliable method for KRAS, NRAS and BRAF mutation detection. Furthermore, no difference in the mutation frequency of KRAS, NRAS and BRAF was observed between Greek and Romanian patients with colorectal cancer. PMID:24859998
Pattern Analysis and Decision Support for Cancer through Clinico-Genomic Profiles
NASA Astrophysics Data System (ADS)
Exarchos, Themis P.; Giannakeas, Nikolaos; Goletsis, Yorgos; Papaloukas, Costas; Fotiadis, Dimitrios I.
Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment.
MUFFINN: cancer gene discovery via network analysis of somatic mutation data.
Cho, Ara; Shim, Jung Eun; Kim, Eiru; Supek, Fran; Lehner, Ben; Lee, Insuk
2016-06-23
A major challenge for distinguishing cancer-causing driver mutations from inconsequential passenger mutations is the long-tail of infrequently mutated genes in cancer genomes. Here, we present and evaluate a method for prioritizing cancer genes accounting not only for mutations in individual genes but also in their neighbors in functional networks, MUFFINN (MUtations For Functional Impact on Network Neighbors). This pathway-centric method shows high sensitivity compared with gene-centric analyses of mutation data. Notably, only a marginal decrease in performance is observed when using 10 % of TCGA patient samples, suggesting the method may potentiate cancer genome projects with small patient populations.
Analysis of Content Shared in Online Cancer Communities: Systematic Review
van de Poll-Franse, Lonneke V; Krahmer, Emiel; Verberne, Suzan; Mols, Floortje
2018-01-01
Background The content that cancer patients and their relatives (ie, posters) share in online cancer communities has been researched in various ways. In the past decade, researchers have used automated analysis methods in addition to manual coding methods. Patients, providers, researchers, and health care professionals can learn from experienced patients, provided that their experience is findable. Objective The aim of this study was to systematically review all relevant literature that analyzes user-generated content shared within online cancer communities. We reviewed the quality of available research and the kind of content that posters share with each other on the internet. Methods A computerized literature search was performed via PubMed (MEDLINE), PsycINFO (5 and 4 stars), Cochrane Central Register of Controlled Trials, and ScienceDirect. The last search was conducted in July 2017. Papers were selected if they included the following terms: (cancer patient) and (support group or health communities) and (online or internet). We selected 27 papers and then subjected them to a 14-item quality checklist independently scored by 2 investigators. Results The methodological quality of the selected studies varied: 16 were of high quality and 11 were of adequate quality. Of those 27 studies, 15 were manually coded, 7 automated, and 5 used a combination of methods. The best results can be seen in the papers that combined both analytical methods. The number of analyzed posts ranged from 200 to 1,500,000; the number of analyzed posters ranged from 75 to 90,000. The studies analyzing large numbers of posts mainly related to breast cancer, whereas those analyzing small numbers were related to other types of cancers. A total of 12 studies involved some or entirely automatic analysis of the user-generated content. All the authors referred to two main content categories: informational support and emotional support. In all, 15 studies reported only on the content, 6 studies explicitly reported on content and social aspects, and 6 studies focused on emotional changes. Conclusions In the future, increasing amounts of user-generated content will become available on the internet. The results of content analysis, especially of the larger studies, give detailed insights into patients’ concerns and worries, which can then be used to improve cancer care. To make the results of such analyses as usable as possible, automatic content analysis methods will need to be improved through interdisciplinary collaboration. PMID:29615384
2012-01-01
Background For complex diseases like cancer, pooled-analysis of individual data represents a powerful tool to investigate the joint contribution of genetic, phenotypic and environmental factors to the development of a disease. Pooled-analysis of epidemiological studies has many advantages over meta-analysis, and preliminary results may be obtained faster and with lower costs than with prospective consortia. Design and methods Based on our experience with the study design of the Melanocortin-1 receptor (MC1R) gene, SKin cancer and Phenotypic characteristics (M-SKIP) project, we describe the most important steps in planning and conducting a pooled-analysis of genetic epidemiological studies. We then present the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease. Within the M-SKIP project, data on 10,959 skin cancer cases and 14,785 controls from 31 international investigators were checked for quality and recoded for standardization. We first proposed to fit the aggregated data with random-effects logistic regression models. However, for the M-SKIP project, a two-stage analysis will be preferred to overcome the problem regarding the availability of different study covariates. The joint contribution of MC1R variants and phenotypic characteristics to skin cancer development will be studied via logic regression modeling. Discussion Methodological guidelines to correctly design and conduct pooled-analyses are needed to facilitate application of such methods, thus providing a better summary of the actual findings on specific fields. PMID:22862891
Teng, Shizhu; Jia, Qiaojuan; Huang, Yijian; Chen, Liangcao; Fei, Xufeng; Wu, Jiaping
2015-10-01
Sporadic cases occurring in mall geographic unit could lead to extreme value of incidence due to the small population bases, which would influence the analysis of actual incidence. This study introduced a method of hierarchy clustering and partitioning regionalization, which integrates areas with small population into larger areas with enough population by using Geographic Information System (GIS) based on the principles of spatial continuity and geographical similarity (homogeneity test). This method was applied in spatial epidemiology by using a data set of thyroid cancer incidence in Yiwu, Zhejiang province, between 2010 and 2013. Thyroid cancer incidence data were more reliable and stable in the new regionalized areas. Hotspot analysis (Getis-Ord) on the incidence in new areas indicated that there was obvious case clustering in the central area of Yiwu. This method can effectively solve the problem of small population base in small geographic units in spatial epidemiological analysis of thyroid cancer incidence and can be used for other diseases and in other areas.
Gavrilyuk, Oxana; Braaten, Tonje; Skeie, Guri; Weiderpass, Elisabete; Dumeaux, Vanessa; Lund, Eiliv
2014-03-25
Coffee and its compounds have been proposed to inhibit endometrial carcinogenesis. Studies in the Norwegian population can be especially interesting due to the high coffee consumption and increasing incidence of endometrial cancer in the country. A total of 97 926 postmenopausal Norwegian women from the population-based prospective Norwegian Women and Cancer (NOWAC) Study, were included in the present analysis. We evaluated the general association between total coffee consumption and endometrial cancer risk as well as the possible impact of brewing method. Multivariate Cox regression analysis was used to estimate risks, and heterogeneity tests were performed to compare brewing methods. During an average of 10.9 years of follow-up, 462 incident endometrial cancer cases were identified. After multivariate adjustment, significant risk reduction was found among participants who drank ≥8 cups/day of coffee with a hazard ratio of 0.52 (95% confidence interval, CI 0.34-0.79). However, we did not observe a significant dose-response relationship. No significant heterogeneity in risk was found when comparing filtered and boiled coffee brewing methods. A reduction in endometrial cancer risk was observed in subgroup analyses among participants who drank ≥8 cups/day and had a body mass index ≥25 kg/m2, and in current smokers. These data suggest that in this population with high coffee consumption, endometrial cancer risk decreases in women consuming ≥8 cups/day, independent of brewing method.
2014-01-01
Background Coffee and its compounds have been proposed to inhibit endometrial carcinogenesis. Studies in the Norwegian population can be especially interesting due to the high coffee consumption and increasing incidence of endometrial cancer in the country. Methods A total of 97 926 postmenopausal Norwegian women from the population-based prospective Norwegian Women and Cancer (NOWAC) Study, were included in the present analysis. We evaluated the general association between total coffee consumption and endometrial cancer risk as well as the possible impact of brewing method. Multivariate Cox regression analysis was used to estimate risks, and heterogeneity tests were performed to compare brewing methods. Results During an average of 10.9 years of follow-up, 462 incident endometrial cancer cases were identified. After multivariate adjustment, significant risk reduction was found among participants who drank ≥8 cups/day of coffee with a hazard ratio of 0.52 (95% confidence interval, CI 0.34-0.79). However, we did not observe a significant dose-response relationship. No significant heterogeneity in risk was found when comparing filtered and boiled coffee brewing methods. A reduction in endometrial cancer risk was observed in subgroup analyses among participants who drank ≥8 cups/day and had a body mass index ≥25 kg/m2, and in current smokers. Conclusions These data suggest that in this population with high coffee consumption, endometrial cancer risk decreases in women consuming ≥8 cups/day, independent of brewing method. PMID:24666820
Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset.
Seashore-Ludlow, Brinton; Rees, Matthew G; Cheah, Jaime H; Cokol, Murat; Price, Edmund V; Coletti, Matthew E; Jones, Victor; Bodycombe, Nicole E; Soule, Christian K; Gould, Joshua; Alexander, Benjamin; Li, Ava; Montgomery, Philip; Wawer, Mathias J; Kuru, Nurdan; Kotz, Joanne D; Hon, C Suk-Yee; Munoz, Benito; Liefeld, Ted; Dančík, Vlado; Bittker, Joshua A; Palmer, Michelle; Bradner, James E; Shamji, Alykhan F; Clemons, Paul A; Schreiber, Stuart L
2015-11-01
Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2). We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses. ©2015 American Association for Cancer Research.
Yu, Hwa-Lung; Chiang, Chi-Ting; Lin, Shu-De; Chang, Tsun-Kuo
2010-02-01
Incidence rate of oral cancer in Changhua County is the highest among the 23 counties of Taiwan during 2001. However, in health data analysis, crude or adjusted incidence rates of a rare event (e.g., cancer) for small populations often exhibit high variances and are, thus, less reliable. We proposed a generalized Bayesian Maximum Entropy (GBME) analysis of spatiotemporal disease mapping under conditions of considerable data uncertainty. GBME was used to study the oral cancer population incidence in Changhua County (Taiwan). Methodologically, GBME is based on an epistematics principles framework and generates spatiotemporal estimates of oral cancer incidence rates. In a way, it accounts for the multi-sourced uncertainty of rates, including small population effects, and the composite space-time dependence of rare events in terms of an extended Poisson-based semivariogram. The results showed that GBME analysis alleviates the noises of oral cancer data from population size effect. Comparing to the raw incidence data, the maps of GBME-estimated results can identify high risk oral cancer regions in Changhua County, where the prevalence of betel quid chewing and cigarette smoking is relatively higher than the rest of the areas. GBME method is a valuable tool for spatiotemporal disease mapping under conditions of uncertainty. 2010 Elsevier Inc. All rights reserved.
Integrative Analysis of Cancer Diagnosis Studies with Composite Penalization
Liu, Jin; Huang, Jian; Ma, Shuangge
2013-01-01
Summary In cancer diagnosis studies, high-throughput gene profiling has been extensively conducted, searching for genes whose expressions may serve as markers. Data generated from such studies have the “large d, small n” feature, with the number of genes profiled much larger than the sample size. Penalization has been extensively adopted for simultaneous estimation and marker selection. Because of small sample sizes, markers identified from the analysis of single datasets can be unsatisfactory. A cost-effective remedy is to conduct integrative analysis of multiple heterogeneous datasets. In this article, we investigate composite penalization methods for estimation and marker selection in integrative analysis. The proposed methods use the minimax concave penalty (MCP) as the outer penalty. Under the homogeneity model, the ridge penalty is adopted as the inner penalty. Under the heterogeneity model, the Lasso penalty and MCP are adopted as the inner penalty. Effective computational algorithms based on coordinate descent are developed. Numerical studies, including simulation and analysis of practical cancer datasets, show satisfactory performance of the proposed methods. PMID:24578589
Rodrigues, Ramon Gouveia; das Dores, Rafael Marques; Camilo-Junior, Celso G; Rosa, Thierson Couto
2016-01-01
Cancer is a critical disease that affects millions of people and families around the world. In 2012 about 14.1 million new cases of cancer occurred globally. Because of many reasons like the severity of some cases, the side effects of some treatments and death of other patients, cancer patients tend to be affected by serious emotional disorders, like depression, for instance. Thus, monitoring the mood of the patients is an important part of their treatment. Many cancer patients are users of online social networks and many of them take part in cancer virtual communities where they exchange messages commenting about their treatment or giving support to other patients in the community. Most of these communities are of public access and thus are useful sources of information about the mood of patients. Based on that, Sentiment Analysis methods can be useful to automatically detect positive or negative mood of cancer patients by analyzing their messages in these online communities. The objective of this work is to present a Sentiment Analysis tool, named SentiHealth-Cancer (SHC-pt), that improves the detection of emotional state of patients in Brazilian online cancer communities, by inspecting their posts written in Portuguese language. The SHC-pt is a sentiment analysis tool which is tailored specifically to detect positive, negative or neutral messages of patients in online communities of cancer patients. We conducted a comparative study of the proposed method with a set of general-purpose sentiment analysis tools adapted to this context. Different collections of posts were obtained from two cancer communities in Facebook. Additionally, the posts were analyzed by sentiment analysis tools that support the Portuguese language (Semantria and SentiStrength) and by the tool SHC-pt, developed based on the method proposed in this paper called SentiHealth. Moreover, as a second alternative to analyze the texts in Portuguese, the collected texts were automatically translated into English, and submitted to sentiment analysis tools that do not support the Portuguese language (AlchemyAPI and Textalytics) and also to Semantria and SentiStrength, using the English option of these tools. Six experiments were conducted with some variations and different origins of the collected posts. The results were measured using the following metrics: precision, recall, F1-measure and accuracy The proposed tool SHC-pt reached the best averages for accuracy and F1-measure (harmonic mean between recall and precision) in the three sentiment classes addressed (positive, negative and neutral) in all experimental settings. Moreover, the worst accuracy value (58%) achieved by SHC-pt in any experiment is 11.53% better than the greatest accuracy (52%) presented by other addressed tools. Finally, the worst average F1 (48.46%) reached by SHC-pt in any experiment is 4.14% better than the greatest average F1 (46.53%) achieved by other addressed tools. Thus, even when we compare the SHC-pt results in complex scenario versus others in easier scenario the SHC-pt is better. This paper presents two contributions. First, it proposes the method SentiHealth to detect the mood of cancer patients that are also users of communities of patients in online social networks. Second, it presents an instantiated tool from the method, called SentiHealth-Cancer (SHC-pt), dedicated to automatically analyze posts in communities of cancer patients, based on SentiHealth. This context-tailored tool outperformed other general-purpose sentiment analysis tools at least in the cancer context. This suggests that the SentiHealth method could be instantiated as other disease-based tools during future works, for instance SentiHealth-HIV, SentiHealth-Stroke and SentiHealth-Sclerosis. Copyright © 2015. Published by Elsevier Ireland Ltd.
The risk of lung cancer among cooking adults: a meta-analysis of 23 observational studies.
Jia, Peng-Li; Zhang, Chao; Yu, Jia-Jie; Xu, Chang; Tang, Li; Sun, Xin
2018-02-01
Cooking has been regarded as a potential risk factor for lung cancer. We aim to investigate the evidence of cooking oil fume and risk of lung cancer. Medline and Embase were searched for eligible studies. We conducted a meta-analysis to summarize the evidences of case-control or cohort studies, with subgroup analysis for the potential discrepancy. Sensitivity analysis was employed to test the robustness. We included 23 observational studies, involving 9411 lung cancer cases. Our meta-analysis found that, for cooking female, the pooled OR of cooking oil fume exposure was 1.98 (95% CI 1.54, 2.54, I 2 = 79%, n = 15) among non-smoking population and 2.00 (95% CI 1.46, 2.74, I 2 = 75%, n = 10) among partly smoking population. For cooking males, the pooled OR of lung cancer was 1.15 (95% CI 0.71, 1.87; I 2 = 80%, n = 4). When sub grouped by ventilation condition, the pooled OR for poor ventilation was 1.20 (95% CI 1.10, 1.31, I 2 = 2%) compared to good ventilation. For different cooking methods, our results suggested that stir frying (OR = 1.89, 95% CI 1.23, 2.90; I 2 = 66%) was associated with increased risk of lung cancer while not for deep frying (OR = 1.41, 95% CI 0.87, 2.29; I 2 = 5%). Sensitivity analysis suggested our results were stable. Cooking oil fume is likely to be a risk factor for lung cancer for female, regardless of smoking status. Poor ventilation may increase the risk of lung cancer. Cooking methods may have different effect on lung cancer that deep frying may be healthier than stir frying.
Integrative prescreening in analysis of multiple cancer genomic studies
2012-01-01
Background In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost. Results An integrative prescreening approach is developed for the analysis of multiple cancer genomic datasets. Simulation shows that the proposed integrative prescreening has better performance than alternatives, particularly including prescreening with individual datasets, an intensity approach and meta-analysis. We also analyze multiple microarray gene profiling studies on liver and pancreatic cancers using the proposed approach. Conclusions The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies. It can be coupled with existing analysis methods to identify cancer markers. PMID:22799431
Sawabe, Michi; Ito, Hidemi; Oze, Isao; Hosono, Satoyo; Kawakita, Daisuke; Tanaka, Hideo; Hasegawa, Yasuhisa; Murakami, Shingo; Matsuo, Keitaro
2017-01-01
Alcohol consumption is an established risk factor, and also a potential prognostic factor, for squamous cell carcinoma of the head and neck (HNSCC). However, little is known about whether the prognostic impact of alcohol consumption differs by treatment method. We evaluated the association between alcohol drinking and survival by treatment method to the primary site in 427 patients with HNSCC treated between 2005 and 2013 at Aichi Cancer Center Central Hospital (Nagoya, Japan). The impact of alcohol on prognosis was measured by multivariable Cox regression analysis adjusted for established prognostic factors. Among all HNSCC patients, the overall survival rate was significantly poorer with increased levels of alcohol consumption in multivariable analysis (trend P = 0.038). Stratification by treatment method and primary site revealed that the impact of drinking was heterogeneous. Among laryngopharyngeal cancer (laryngeal, oropharyngeal, and hypopharyngeal cancer) patients receiving radiotherapy (n = 141), a significant dose-response relationship was observed (trend P = 0.034). In contrast, among laryngopharyngeal cancer patients treated with surgery (n = 80), no obvious impact of alcohol was observed. This heterogeneity in the impact of alcohol between surgery and radiotherapy was significant (for interaction, P = 0.048). Furthermore, among patients with oral cavity cancer treated by surgery, a significant impact of drinking on survival was seen with tongue cancer, but not with non-tongue oral cancer. We observed a significant inverse association between alcohol drinking and prognosis among HNSCC patients, and its impact was heterogeneous by treatment method and primary site. © 2016 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.
ERIC Educational Resources Information Center
Bollinger, Sarah; Kreuter, Matthew W.
2012-01-01
In a randomized experiment using moment-to-moment audience analysis methods, we compared women's emotional responses with a narrative versus informational breast cancer video. Both videos communicated three key messages about breast cancer: (i) understand your breast cancer risk, (ii) talk openly about breast cancer and (iii) get regular…
Pathway and network analysis of cancer genomes.
Creixell, Pau; Reimand, Jüri; Haider, Syed; Wu, Guanming; Shibata, Tatsuhiro; Vazquez, Miguel; Mustonen, Ville; Gonzalez-Perez, Abel; Pearson, John; Sander, Chris; Raphael, Benjamin J; Marks, Debora S; Ouellette, B F Francis; Valencia, Alfonso; Bader, Gary D; Boutros, Paul C; Stuart, Joshua M; Linding, Rune; Lopez-Bigas, Nuria; Stein, Lincoln D
2015-07-01
Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations.
Chen, Chen Hsiu; Kuo, Su Ching; Tang, Siew Tzuh
2017-05-01
No systematic meta-analysis is available on the prevalence of cancer patients' accurate prognostic awareness and differences in accurate prognostic awareness by publication year, region, assessment method, and service received. To examine the prevalence of advanced/terminal cancer patients' accurate prognostic awareness and differences in accurate prognostic awareness by publication year, region, assessment method, and service received. Systematic review and meta-analysis. MEDLINE, Embase, The Cochrane Library, CINAHL, and PsycINFO were systematically searched on accurate prognostic awareness in adult patients with advanced/terminal cancer (1990-2014). Pooled prevalences were calculated for accurate prognostic awareness by a random-effects model. Differences in weighted estimates of accurate prognostic awareness were compared by meta-regression. In total, 34 articles were retrieved for systematic review and meta-analysis. At best, only about half of advanced/terminal cancer patients accurately understood their prognosis (49.1%; 95% confidence interval: 42.7%-55.5%; range: 5.4%-85.7%). Accurate prognostic awareness was independent of service received and publication year, but highest in Australia, followed by East Asia, North America, and southern Europe and the United Kingdom (67.7%, 60.7%, 52.8%, and 36.0%, respectively; p = 0.019). Accurate prognostic awareness was higher by clinician assessment than by patient report (63.2% vs 44.5%, p < 0.001). Less than half of advanced/terminal cancer patients accurately understood their prognosis, with significant variations by region and assessment method. Healthcare professionals should thoroughly assess advanced/terminal cancer patients' preferences for prognostic information and engage them in prognostic discussion early in the cancer trajectory, thus facilitating their accurate prognostic awareness and the quality of end-of-life care decision-making.
Analysis of Content Shared in Online Cancer Communities: Systematic Review.
van Eenbergen, Mies C; van de Poll-Franse, Lonneke V; Krahmer, Emiel; Verberne, Suzan; Mols, Floortje
2018-04-03
The content that cancer patients and their relatives (ie, posters) share in online cancer communities has been researched in various ways. In the past decade, researchers have used automated analysis methods in addition to manual coding methods. Patients, providers, researchers, and health care professionals can learn from experienced patients, provided that their experience is findable. The aim of this study was to systematically review all relevant literature that analyzes user-generated content shared within online cancer communities. We reviewed the quality of available research and the kind of content that posters share with each other on the internet. A computerized literature search was performed via PubMed (MEDLINE), PsycINFO (5 and 4 stars), Cochrane Central Register of Controlled Trials, and ScienceDirect. The last search was conducted in July 2017. Papers were selected if they included the following terms: (cancer patient) and (support group or health communities) and (online or internet). We selected 27 papers and then subjected them to a 14-item quality checklist independently scored by 2 investigators. The methodological quality of the selected studies varied: 16 were of high quality and 11 were of adequate quality. Of those 27 studies, 15 were manually coded, 7 automated, and 5 used a combination of methods. The best results can be seen in the papers that combined both analytical methods. The number of analyzed posts ranged from 200 to 1,500,000; the number of analyzed posters ranged from 75 to 90,000. The studies analyzing large numbers of posts mainly related to breast cancer, whereas those analyzing small numbers were related to other types of cancers. A total of 12 studies involved some or entirely automatic analysis of the user-generated content. All the authors referred to two main content categories: informational support and emotional support. In all, 15 studies reported only on the content, 6 studies explicitly reported on content and social aspects, and 6 studies focused on emotional changes. In the future, increasing amounts of user-generated content will become available on the internet. The results of content analysis, especially of the larger studies, give detailed insights into patients' concerns and worries, which can then be used to improve cancer care. To make the results of such analyses as usable as possible, automatic content analysis methods will need to be improved through interdisciplinary collaboration. ©Mies C van Eenbergen, Lonneke V van de Poll-Franse, Emiel Krahmer, Suzan Verberne, Floortje Mols. Originally published in JMIR Cancer (http://cancer.jmir.org), 03.04.2018.
Jordá Aragón, Carlos; Peñalver Cuesta, Juan Carlos; Mancheño Franch, Nuria; de Aguiar Quevedo, Karol; Vera Sempere, Francisco; Padilla Alarcón, José
2015-09-07
Survival studies of non-small cell lung cancer (NSCLC) are usually based on the Kaplan-Meier method. However, other factors not covered by this method may modify the observation of the event of interest. There are models of cumulative incidence (CI), that take into account these competing risks, enabling more accurate survival estimates and evaluation of the risk of death from other causes. We aimed to evaluate these models in resected early-stage NSCLC patients. This study included 263 patients with resected NSCLC whose diameter was ≤ 3 cm without node involvement (N0). Demographic, clinical, morphopathological and surgical variables, TNM classification and long-term evolution were analysed. To analyse CI, death by another cause was considered to be competitive event. For the univariate analysis, Gray's method was used, while Fine and Gray's method was employed for the multivariate analysis. Mortality by NSCLC was 19.4% at 5 years and 14.3% by another cause. Both curves crossed at 6.3 years, and probability of death by another cause became greater from this point. In multivariate analysis, cancer mortality was conditioned by visceral pleural invasion (VPI) (P=.001) and vascular invasion (P=.020), with age>50 years (P=.034), smoking (P=.009) and the Charlson index ≥ 2 (P=.000) being by no cancer. By the method of CI, VPI and vascular invasion conditioned cancer death in NSCLC >3 cm, while non-tumor causes of long-term death were determined. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.
Hyperspectral Imaging and SPA-LDA Quantitative Analysis for Detection of Colon Cancer Tissue
NASA Astrophysics Data System (ADS)
Yuan, X.; Zhang, D.; Wang, Ch.; Dai, B.; Zhao, M.; Li, B.
2018-05-01
Hyperspectral imaging (HSI) has been demonstrated to provide a rapid, precise, and noninvasive method for cancer detection. However, because HSI contains many data, quantitative analysis is often necessary to distill information useful for distinguishing cancerous from normal tissue. To demonstrate that HSI with our proposed algorithm can make this distinction, we built a Vis-NIR HSI setup and made many spectral images of colon tissues, and then used a successive projection algorithm (SPA) to analyze the hyperspectral image data of the tissues. This was used to build an identification model based on linear discrimination analysis (LDA) using the relative reflectance values of the effective wavelengths. Other tissues were used as a prediction set to verify the reliability of the identification model. The results suggest that Vis-NIR hyperspectral images, together with the spectroscopic classification method, provide a new approach for reliable and safe diagnosis of colon cancer and could lead to advances in cancer diagnosis generally.
Designing a Micromixer for Rolling Circle Amplification in Cancer Biomarker Detection
NASA Astrophysics Data System (ADS)
Altural, Hayriye
2015-03-01
Rolling circle amplification (RCA) is an alternative method to the Polymerase Chain Reaction based amplification for point-of-care (POC) diagnosis. In future personalized cancer diagnostic for POC applications, smaller, faster and cheaper methods are needed instead of costly and time-consuming laboratory tests. Microfluidic chips can perform the detection of cancer biomarkers within less analysis time, and provide for improvement in the sensitivity and specificity required for biochemical analysis as well. Rapid mixing is essential in the chips used in cancer diagnostic. The goal of this study is to design a micromixer for rapid RCA-based analysis and develop the assay time in cancer biomarker detection. By combining assays with micromixers, multi-step bioreactions in microfluidic chips may be achieved with minimal external control. Here, simulation results related to the micromixer are obtained by COMSOL software. The Scientific and Technological Research Council of Turkey (TUBITAK) is acknowledged for granting of H. Altural postdoctoral study in the framework of TUBITAK-BIDEB 2219-International Postdoctoral Research Scholarship Program.
Adjacent slice prostate cancer prediction to inform MALDI imaging biomarker analysis
NASA Astrophysics Data System (ADS)
Chuang, Shao-Hui; Sun, Xiaoyan; Cazares, Lisa; Nyalwidhe, Julius; Troyer, Dean; Semmes, O. John; Li, Jiang; McKenzie, Frederic D.
2010-03-01
Prostate cancer is the second most common type of cancer among men in US [1]. Traditionally, prostate cancer diagnosis is made by the analysis of prostate-specific antigen (PSA) levels and histopathological images of biopsy samples under microscopes. Proteomic biomarkers can improve upon these methods. MALDI molecular spectra imaging is used to visualize protein/peptide concentrations across biopsy samples to search for biomarker candidates. Unfortunately, traditional processing methods require histopathological examination on one slice of a biopsy sample while the adjacent slice is subjected to the tissue destroying desorption and ionization processes of MALDI. The highest confidence tumor regions gained from the histopathological analysis are then mapped to the MALDI spectra data to estimate the regions for biomarker identification from the MALDI imaging. This paper describes a process to provide a significantly better estimate of the cancer tumor to be mapped onto the MALDI imaging spectra coordinates using the high confidence region to predict the true area of the tumor on the adjacent MALDI imaged slice.
Wu, Dingming; Wang, Dongfang; Zhang, Michael Q; Gu, Jin
2015-12-01
One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data. In this study, we proposed a novel low-rank approximation based integrative probabilistic model to fast find the shared principal subspace across multiple data types: the convexity of the low-rank regularized likelihood function of the probabilistic model ensures efficient and stable model fitting. Candidate molecular subtypes can be identified by unsupervised clustering hundreds of cancer samples in the reduced low-dimensional subspace. On testing datasets, our method LRAcluster (low-rank approximation based multi-omics data clustering) runs much faster with better clustering performances than the existing method. Then, we applied LRAcluster on large-scale cancer multi-omics data from TCGA. The pan-cancer analysis results show that the cancers of different tissue origins are generally grouped as independent clusters, except squamous-like carcinomas. While the single cancer type analysis suggests that the omics data have different subtyping abilities for different cancer types. LRAcluster is a very useful method for fast dimension reduction and unsupervised clustering of large-scale multi-omics data. LRAcluster is implemented in R and freely available via http://bioinfo.au.tsinghua.edu.cn/software/lracluster/ .
Das, Debanjan; Shiladitya, Kumar; Biswas, Karabi; Dutta, Pranab Kumar; Parekh, Aditya; Mandal, Mahitosh; Das, Soumen
2015-12-01
The paper presents a study to differentiate normal and cancerous cells using label-free bioimpedance signal measured by electric cell-substrate impedance sensing. The real-time-measured bioimpedance data of human breast cancer cells and human epithelial normal cells employs fluctuations of impedance value due to cellular micromotions resulting from dynamic structural rearrangement of membrane protrusions under nonagitated condition. Here, a wavelet-based multiscale quantitative analysis technique has been applied to analyze the fluctuations in bioimpedance. The study demonstrates a method to classify cancerous and normal cells from the signature of their impedance fluctuations. The fluctuations associated with cellular micromotion are quantified in terms of cellular energy, cellular power dissipation, and cellular moments. The cellular energy and power dissipation are found higher for cancerous cells associated with higher micromotions in cancer cells. The initial study suggests that proposed wavelet-based quantitative technique promises to be an effective method to analyze real-time bioimpedance signal for distinguishing cancer and normal cells.
Kim, Young Zoon; Kwon, Jae Hyun; Lim, Soyi
2015-01-01
This study analyzes the clinical characteristics of the brain metastasis (BM) of gynecologic cancer based on the type of cancer. In addition, the study examines the factors influencing the survival. Total 61 BM patients of gynecologic cancer were analyzed retrospectively from January 2000 to December 2012 in terms of clinical and radiological characteristics by using medical and radiological records from three university hospitals. There were 19 (31.1%) uterine cancers, 32 (52.5%) ovarian cancers, and 10 (16.4%) cervical cancers. The mean interval to BM was 25.4 months (21.6 months in ovarian cancer, 27.8 months in uterine cancer, and 33.1 months in cervical cancer). The mean survival from BM was 16.7 months (14.1 months in ovarian cancer, 23.3 months in uterine cancer, and 8.8 months in cervical cancer). According to a multivariate analysis of factors influencing survival, type of primary cancer, Karnofsky performance score, status of primary cancer, recursive partitioning analysis class, and treatment modality, particularly combined therapies, were significantly related to the overall survival. These results suggest that, in addition to traditional prognostic factors in BM, multiple treatment methods such as neurosurgery and combined chemoradiotherapy may play an important role in prolonging the survival for BM patients of gynecologic cancer.
Meta-Analysis of Tumor Stem-Like Breast Cancer Cells Using Gene Set and Network Analysis
Lee, Won Jun; Kim, Sang Cheol; Yoon, Jung-Ho; Yoon, Sang Jun; Lim, Johan; Kim, You-Sun; Kwon, Sung Won; Park, Jeong Hill
2016-01-01
Generally, cancer stem cells have epithelial-to-mesenchymal-transition characteristics and other aggressive properties that cause metastasis. However, there have been no confident markers for the identification of cancer stem cells and comparative methods examining adherent and sphere cells are widely used to investigate mechanism underlying cancer stem cells, because sphere cells have been known to maintain cancer stem cell characteristics. In this study, we conducted a meta-analysis that combined gene expression profiles from several studies that utilized tumorsphere technology to investigate tumor stem-like breast cancer cells. We used our own gene expression profiles along with the three different gene expression profiles from the Gene Expression Omnibus, which we combined using the ComBat method, and obtained significant gene sets using the gene set analysis of our datasets and the combined dataset. This experiment focused on four gene sets such as cytokine-cytokine receptor interaction that demonstrated significance in both datasets. Our observations demonstrated that among the genes of four significant gene sets, six genes were consistently up-regulated and satisfied the p-value of < 0.05, and our network analysis showed high connectivity in five genes. From these results, we established CXCR4, CXCL1 and HMGCS1, the intersecting genes of the datasets with high connectivity and p-value of < 0.05, as significant genes in the identification of cancer stem cells. Additional experiment using quantitative reverse transcription-polymerase chain reaction showed significant up-regulation in MCF-7 derived sphere cells and confirmed the importance of these three genes. Taken together, using meta-analysis that combines gene set and network analysis, we suggested CXCR4, CXCL1 and HMGCS1 as candidates involved in tumor stem-like breast cancer cells. Distinct from other meta-analysis, by using gene set analysis, we selected possible markers which can explain the biological mechanisms and suggested network analysis as an additional criterion for selecting candidates. PMID:26870956
2013-01-01
Background Many large-scale studies analyzed high-throughput genomic data to identify altered pathways essential to the development and progression of specific types of cancer. However, no previous study has been extended to provide a comprehensive analysis of pathways disrupted by copy number alterations across different human cancers. Towards this goal, we propose a network-based method to integrate copy number alteration data with human protein-protein interaction networks and pathway databases to identify pathways that are commonly disrupted in many different types of cancer. Results We applied our approach to a data set of 2,172 cancer patients across 16 different types of cancers, and discovered a set of commonly disrupted pathways, which are likely essential for tumor formation in majority of the cancers. We also identified pathways that are only disrupted in specific cancer types, providing molecular markers for different human cancers. Analysis with independent microarray gene expression datasets confirms that the commonly disrupted pathways can be used to identify patient subgroups with significantly different survival outcomes. We also provide a network view of disrupted pathways to explain how copy number alterations affect pathways that regulate cell growth, cycle, and differentiation for tumorigenesis. Conclusions In this work, we demonstrated that the network-based integrative analysis can help to identify pathways disrupted by copy number alterations across 16 types of human cancers, which are not readily identifiable by conventional overrepresentation-based and other pathway-based methods. All the results and source code are available at http://compbio.cs.umn.edu/NetPathID/. PMID:23822816
Byers, Helen; Wallis, Yvonne; van Veen, Elke M; Lalloo, Fiona; Reay, Kim; Smith, Philip; Wallace, Andrew J; Bowers, Naomi; Newman, William G; Evans, D Gareth
2016-11-01
The sensitivity of testing BRCA1 and BRCA2 remains unresolved as the frequency of deep intronic splicing variants has not been defined in high-risk familial breast/ovarian cancer families. This variant category is reported at significant frequency in other tumour predisposition genes, including NF1 and MSH2. We carried out comprehensive whole gene RNA analysis on 45 high-risk breast/ovary and male breast cancer families with no identified pathogenic variant on exonic sequencing and copy number analysis of BRCA1/2. In addition, we undertook variant screening of a 10-gene high/moderate risk breast/ovarian cancer panel by next-generation sequencing. DNA testing identified the causative variant in 50/56 (89%) breast/ovarian/male breast cancer families with Manchester scores of ≥50 with two variants being confirmed to affect splicing on RNA analysis. RNA sequencing of BRCA1/BRCA2 on 45 individuals from high-risk families identified no deep intronic variants and did not suggest loss of RNA expression as a cause of lost sensitivity. Panel testing in 42 samples identified a known RAD51D variant, a high-risk ATM variant in another breast ovary family and a truncating CHEK2 mutation. Current exonic sequencing and copy number analysis variant detection methods of BRCA1/2 have high sensitivity in high-risk breast/ovarian cancer families. Sequence analysis of RNA does not identify any variants undetected by current analysis of BRCA1/2. However, RNA analysis clarified the pathogenicity of variants of unknown significance detected by current methods. The low diagnostic uplift achieved through sequence analysis of the other known breast/ovarian cancer susceptibility genes indicates that further high-risk genes remain to be identified.
NASA Astrophysics Data System (ADS)
Bukreeva, Ekaterina B.; Bulanova, Anna A.; Kistenev, Yurii V.; Kuzmin, Dmitry A.; Tuzikov, Sergei A.; Yumov, Evgenii L.
2013-02-01
It is important to identify patients with chronic obstructive pulmonary disease (COPD) and lung cancer in the early stages of the disease. The method of laser opto-acoustic gas analysis, in this case, can act as a promising tool for diagnostics. The material for this study were the gas emission samples collected from patients and healthy volunteers - samples of exhaled air, swabs from teeth and cheeks. A set of material was formed three groups: healthy volunteers, patients with COPD, lung cancer patients. The resulting samples were analyzed by means of laser opto-acoustic gas analyzers: with intracavity location detector (ILPA-1), with extracavity location detector (LGA-2). Presentation of the results in an easy to visual form was performed using the method of elastic maps, based on the principal component analysis. The results of analysis show potentialities of usage of laser optoacoustic spectroscopy application to assess the status of patients with chronic obstructive pulmonary disease and lung cancer.
Massage Therapy in Outpatient Cancer Care: A Metropolitan Area Analysis.
Cowen, Virginia S; Miccio, Robin Streit; Parikh, Bijal
2017-10-01
Massage offers cancer patients general quality of life benefits as well as alleviation of cancer-related symptoms/cancer-treatment-related symptoms including pain, anxiety, and fatigue. Little is known about whether massage is accessible to cancer patients who receive treatment in the outpatient setting and how massage is incorporated into the overall cancer treatment plan. Outpatient cancer centers (n = 78) in a single metropolitan area were included this mixed-methods project that included a systematic analysis of website information and a telephone survey. Massage was offered at only 40 centers (51.3% of total). A range of massage modalities were represented, with energy-based therapies (Reiki and Therapeutic Touch) most frequently provided. Although massage therapists are licensed health care providers in the states included in this analysis, massage was also provided by nurses, physical therapists, and other health care professionals.
The antagonistic effect between STAT1 and Survivin and its clinical significance in gastric cancer.
Deng, Hao; Zhen, Hongyan; Fu, Zhengqi; Huang, Xuan; Zhou, Hongyan; Liu, Lijiang
2012-01-01
In previous studies, we observed that STAT1 and Survivin correlated negatively with gastric cancer tissues, and that the functions of the IFN-γ-STAT1 pathway and Survivin in gastric cancer are the same as those reported for other types of cancer. In this study, the SGC7901 gastric cancer cell line and 83 gastric cancer specimens were used to confirm the relationship between STAT1 and Survivin, as well as the clinical significance of this relationship in gastric cancer. IFN-γ and STAT1 and Survivin antisense oligonucleotides (ASONs) were used to knock down the expression in SGC7901 cells. The protein expression of STAT1 and Survivin was tested by immunocytochemical and image analysis methods. A gastric cancer tissue microarray was prepared and tested by immunohistochemical methods. Data were analyzed by the Spearman's rank correlation analysis, the χ(2) test and Cox's multivariate regression analysis. Upon knockdown of IFN-γ, STAT1 and Survivin expression by ASON in the SGC7901 cell line, an antagonistic effect was observed between STAT1 and Survivin. In gastric cancer tissues, STAT1 showed a negative correlation with depth of invasion (p<0.05) in gastric cancer tissues exhibiting a negative Survivin protein expression. Furthermore, in tissues exhibiting a negative STAT1 protein expression, Survivin correlated negatively with N stage (p<0.05). Pathological and molecular markers were used to conduct Cox's multivariate regression analysis, and depth of invasion and N stage were found to be prognostic factors (p<0.05). On the other hand, in tissues exhibiting a negative Survivin protein expression, Cox's multivariate regression analysis revealed that the differentiation type and STAT1 protein expression were prognostic factors (p<0.05). There is an antagonistic effect between STAT1 and Survivin in gastric cancer, and this antagonistic effect is of clinical significance in gastric cancer.
ERIC Educational Resources Information Center
Nelissen, Sara; Van den Bulck, Jan; Beullens, Kathleen
2017-01-01
Introduction: This study aims to (a) construct a typology of how individuals acquire cancer information, and (b) examine whether these types differ regarding socio-demographics and cancer-related knowledge, attitudes and behaviour. Method: A standardized, cross-sectional survey among cancer diagnosed and non-diagnosed individuals in Flanders,…
Diagnosis of Lung Cancer by Fractal Analysis of Damaged DNA
Namazi, Hamidreza; Kiminezhadmalaie, Mona
2015-01-01
Cancer starts when cells in a part of the body start to grow out of control. In fact cells become cancer cells because of DNA damage. A DNA walk of a genome represents how the frequency of each nucleotide of a pairing nucleotide couple changes locally. In this research in order to study the cancer genes, DNA walk plots of genomes of patients with lung cancer were generated using a program written in MATLAB language. The data so obtained was checked for fractal property by computing the fractal dimension using a program written in MATLAB. Also, the correlation of damaged DNA was studied using the Hurst exponent measure. We have found that the damaged DNA sequences are exhibiting higher degree of fractality and less correlation compared with normal DNA sequences. So we confirmed this method can be used for early detection of lung cancer. The method introduced in this research not only is useful for diagnosis of lung cancer but also can be applied for detection and growth analysis of different types of cancers. PMID:26539245
NASA Astrophysics Data System (ADS)
Danala, Gopichandh; Wang, Yunzhi; Thai, Theresa; Gunderson, Camille C.; Moxley, Katherine M.; Moore, Kathleen; Mannel, Robert S.; Cheng, Samuel; Liu, Hong; Zheng, Bin; Qiu, Yuchen
2017-02-01
Accurate tumor segmentation is a critical step in the development of the computer-aided detection (CAD) based quantitative image analysis scheme for early stage prognostic evaluation of ovarian cancer patients. The purpose of this investigation is to assess the efficacy of several different methods to segment the metastatic tumors occurred in different organs of ovarian cancer patients. In this study, we developed a segmentation scheme consisting of eight different algorithms, which can be divided into three groups: 1) Region growth based methods; 2) Canny operator based methods; and 3) Partial differential equation (PDE) based methods. A number of 138 tumors acquired from 30 ovarian cancer patients were used to test the performance of these eight segmentation algorithms. The results demonstrate each of the tested tumors can be successfully segmented by at least one of the eight algorithms without the manual boundary correction. Furthermore, modified region growth, classical Canny detector, and fast marching, and threshold level set algorithms are suggested in the future development of the ovarian cancer related CAD schemes. This study may provide meaningful reference for developing novel quantitative image feature analysis scheme to more accurately predict the response of ovarian cancer patients to the chemotherapy at early stage.
Jouyban, Abolghasem; Djozan, Djavanshir; Mohammadandashti, Parastou; Alizadeh-Nabil, Aliakbar; Ghorbanpour, Hooshangh; Khoubnasabjafari, Maryam; Mohammadzadeh, Mohammad
2017-01-01
Introduction: A simple, rapid and low cost method for enrichment of volatile organic compounds (VOCs) from exhaled breath (EB) is presented. Methods: A 1000 mL home-made extraction device was filled with EB. The VOCs were extracted and condensed in 0.5 mL acetone. Recognition of volatiles in the real studied EB samples was performed by a GC-MS. Results: The method displays an extraction efficiency of >86% with the enrichment factor of 1929 for octanal. Limits of detection and quantification, and linear dynamic range were 0.008, 0.026 and 0.026-400 ng/mL respectively. Analysis of real samples showed the existence of more than 100 compounds in EB of healthy volunteers and patients with lung cancer before and after treatment. Exhaled octanal concentration was significantly higher in lung cancer patient than in healthy volunteers and lung cancer patient after treatment. Conclusion: Having used the proposed approach, high extraction recovery (up to 86%) was attained for the lung cancer marker, octanal, as an important biomarker. Our findings on smaples of EB of healthy controls and patients with lung cancer before and after treatment provide complelling evidence upon the effectiveness of the developed method. PMID:28752074
NASA Astrophysics Data System (ADS)
Li, Shaoxin; Zhang, Yanjiao; Xu, Junfa; Li, Linfang; Zeng, Qiuyao; Lin, Lin; Guo, Zhouyi; Liu, Zhiming; Xiong, Honglian; Liu, Songhao
2014-09-01
This study aims to present a noninvasive prostate cancer screening methods using serum surface-enhanced Raman scattering (SERS) and support vector machine (SVM) techniques through peripheral blood sample. SERS measurements are performed using serum samples from 93 prostate cancer patients and 68 healthy volunteers by silver nanoparticles. Three types of kernel functions including linear, polynomial, and Gaussian radial basis function (RBF) are employed to build SVM diagnostic models for classifying measured SERS spectra. For comparably evaluating the performance of SVM classification models, the standard multivariate statistic analysis method of principal component analysis (PCA) is also applied to classify the same datasets. The study results show that for the RBF kernel SVM diagnostic model, the diagnostic accuracy of 98.1% is acquired, which is superior to the results of 91.3% obtained from PCA methods. The receiver operating characteristic curve of diagnostic models further confirm above research results. This study demonstrates that label-free serum SERS analysis technique combined with SVM diagnostic algorithm has great potential for noninvasive prostate cancer screening.
Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun
2009-12-21
Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment.
Phase II cancer clinical trials for biomarker-guided treatments.
Jung, Sin-Ho
2018-01-01
The design and analysis of cancer clinical trials with biomarker depend on various factors, such as the phase of trials, the type of biomarker, whether the used biomarker is validated or not, and the study objectives. In this article, we demonstrate the design and analysis of two Phase II cancer clinical trials, one with a predictive biomarker and the other with an imaging prognostic biomarker. Statistical testing methods and their sample size calculation methods are presented for each trial. We assume that the primary endpoint of these trials is a time to event variable, but this concept can be used for any type of endpoint.
Nicolau, Monica; Levine, Arnold J; Carlsson, Gunnar
2011-04-26
High-throughput biological data, whether generated as sequencing, transcriptional microarrays, proteomic, or other means, continues to require analytic methods that address its high dimensional aspects. Because the computational part of data analysis ultimately identifies shape characteristics in the organization of data sets, the mathematics of shape recognition in high dimensions continues to be a crucial part of data analysis. This article introduces a method that extracts information from high-throughput microarray data and, by using topology, provides greater depth of information than current analytic techniques. The method, termed Progression Analysis of Disease (PAD), first identifies robust aspects of cluster analysis, then goes deeper to find a multitude of biologically meaningful shape characteristics in these data. Additionally, because PAD incorporates a visualization tool, it provides a simple picture or graph that can be used to further explore these data. Although PAD can be applied to a wide range of high-throughput data types, it is used here as an example to analyze breast cancer transcriptional data. This identified a unique subgroup of Estrogen Receptor-positive (ER(+)) breast cancers that express high levels of c-MYB and low levels of innate inflammatory genes. These patients exhibit 100% survival and no metastasis. No supervised step beyond distinction between tumor and healthy patients was used to identify this subtype. The group has a clear and distinct, statistically significant molecular signature, it highlights coherent biology but is invisible to cluster methods, and does not fit into the accepted classification of Luminal A/B, Normal-like subtypes of ER(+) breast cancers. We denote the group as c-MYB(+) breast cancer.
Trend Analysis of Betel Nut-associated Oral Cancer and Health Burden in China.
Hu, Yan Jia; Chen, Jie; Zhong, Wai Sheng; Ling, Tian You; Jian, Xin Chun; Lu, Ruo Huang; Tang, Zhan Gui; Tao, Lin
To forecast the future trend of betel nut-associated oral cancer and the resulting burden on health based on historical oral cancer patient data in Hunan province, China. Oral cancer patient data in five hospitals in Changsha (the capital city of Hunan province) were collected for the past 12 years. Three methods were used to analyse the data; Microsoft Excel Forecast Sheet, Excel Trendline, and the Logistic growth model. A combination of these three methods was used to forecast the future trend of betel nut-associated oral cancer and the resulting burden on health. Betel nut-associated oral cancer cases have been increasing rapidly in the past 12 years in Changsha. As of 2016, betel nuts had caused 8,222 cases of oral cancer in Changsha and close to 25,000 cases in Hunan, resulting in about ¥5 billion in accumulated financial loss. The combined trend analysis predicts that by 2030, betel nuts will cause more than 100,000 cases of oral cancer in Changsha and more than 300,000 cases in Hunan, and more than ¥64 billion in accumulated financial loss in medical expenses. The trend analysis of oral cancer patient data predicts that the growing betel nut industry in Hunan province will cause a humanitarian catastrophe with massive loss of human life and national resources. To prevent this catastrophe, China should ban betel nuts and provide early oral cancer screening for betel nut consumers as soon as possible.
Gerasimova, Evgeniya; Audit, Benjamin; Roux, Stephane G.; Khalil, André; Gileva, Olga; Argoul, Françoise; Naimark, Oleg; Arneodo, Alain
2014-01-01
Breast cancer is the most common type of cancer among women and despite recent advances in the medical field, there are still some inherent limitations in the currently used screening techniques. The radiological interpretation of screening X-ray mammograms often leads to over-diagnosis and, as a consequence, to unnecessary traumatic and painful biopsies. Here we propose a computer-aided multifractal analysis of dynamic infrared (IR) imaging as an efficient method for identifying women with risk of breast cancer. Using a wavelet-based multi-scale method to analyze the temporal fluctuations of breast skin temperature collected from a panel of patients with diagnosed breast cancer and some female volunteers with healthy breasts, we show that the multifractal complexity of temperature fluctuations observed in healthy breasts is lost in mammary glands with malignant tumor. Besides potential clinical impact, these results open new perspectives in the investigation of physiological changes that may precede anatomical alterations in breast cancer development. PMID:24860510
ERIC Educational Resources Information Center
Hui, Siu-kuen Azor; Engelman, Kimberly; Shireman, Theresa I.; Hunt, Suzanne; Ellerbeck, Edward F.
2012-01-01
Background: The utility of employee wellness programs (EWPs) in cancer prevention and control is not well established. Purpose: This project is to determine the potential value of EWPs in preventing cancer by examining the characteristics of EWP participants and their prevalence of cancer risk factors. Methods: A secondary data analysis of health…
Massage Therapy in Outpatient Cancer Care: A Metropolitan Area Analysis
Miccio, Robin Streit; Parikh, Bijal
2017-01-01
Massage offers cancer patients general quality of life benefits as well as alleviation of cancer-related symptoms/cancer-treatment–related symptoms including pain, anxiety, and fatigue. Little is known about whether massage is accessible to cancer patients who receive treatment in the outpatient setting and how massage is incorporated into the overall cancer treatment plan. Outpatient cancer centers (n = 78) in a single metropolitan area were included this mixed-methods project that included a systematic analysis of website information and a telephone survey. Massage was offered at only 40 centers (51.3% of total). A range of massage modalities were represented, with energy-based therapies (Reiki and Therapeutic Touch) most frequently provided. Although massage therapists are licensed health care providers in the states included in this analysis, massage was also provided by nurses, physical therapists, and other health care professionals. PMID:28845677
Empirical Analysis and Refinement of Expert System Knowledge Bases
1990-03-31
the number of hidden units and the error rates is listed in Figure 6. 3.3. Cancer Data A data qet for eva!ukting th.- Frognosis of breast cancer ...Alternative Rule Induction Methods A data set for evaluating the prognosis of breast cancer recurrence was analyzed by Michalski’s AQI5 rule induction program...AQ15 7 2 32% PVM 2 1 23% Figure 6-3: Comparative Summa-y for AQI5 and PVM on Breast Cancer Data 6.2.2. Alternative Decision Tree Induction Methods
Xu, Haoming; Moni, Mohammad Ali; Liò, Pietro
2015-12-01
In cancer genomics, gene expression levels provide important molecular signatures for all types of cancer, and this could be very useful for predicting the survival of cancer patients. However, the main challenge of gene expression data analysis is high dimensionality, and microarray is characterised by few number of samples with large number of genes. To overcome this problem, a variety of penalised Cox proportional hazard models have been proposed. We introduce a novel network regularised Cox proportional hazard model and a novel multiplex network model to measure the disease comorbidities and to predict survival of the cancer patient. Our methods are applied to analyse seven microarray cancer gene expression datasets: breast cancer, ovarian cancer, lung cancer, liver cancer, renal cancer and osteosarcoma. Firstly, we applied a principal component analysis to reduce the dimensionality of original gene expression data. Secondly, we applied a network regularised Cox regression model on the reduced gene expression datasets. By using normalised mutual information method and multiplex network model, we predict the comorbidities for the liver cancer based on the integration of diverse set of omics and clinical data, and we find the diseasome associations (disease-gene association) among different cancers based on the identified common significant genes. Finally, we evaluated the precision of the approach with respect to the accuracy of survival prediction using ROC curves. We report that colon cancer, liver cancer and renal cancer share the CXCL5 gene, and breast cancer, ovarian cancer and renal cancer share the CCND2 gene. Our methods are useful to predict survival of the patient and disease comorbidities more accurately and helpful for improvement of the care of patients with comorbidity. Software in Matlab and R is available on our GitHub page: https://github.com/ssnhcom/NetworkRegularisedCox.git. Copyright © 2015. Published by Elsevier Ltd.
Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples
Peterson, Thomas A.; Park, Junyong
2017-01-01
The fight against cancer is hindered by its highly heterogeneous nature. Genome-wide sequencing studies have shown that individual malignancies contain many mutations that range from those commonly found in tumor genomes to rare somatic variants present only in a small fraction of lesions. Such rare somatic variants dominate the landscape of genomic mutations in cancer, yet efforts to correlate somatic mutations found in one or few individuals with functional roles have been largely unsuccessful. Traditional methods for identifying somatic variants that drive cancer are ‘gene-centric’ in that they consider only somatic variants within a particular gene and make no comparison to other similar genes in the same family that may play a similar role in cancer. In this work, we present oncodomain hotspots, a new ‘domain-centric’ method for identifying clusters of somatic mutations across entire gene families using protein domain models. Our analysis confirms that our approach creates a framework for leveraging structural and functional information encapsulated by protein domains into the analysis of somatic variants in cancer, enabling the assessment of even rare somatic variants by comparison to similar genes. Our results reveal a vast landscape of somatic variants that act at the level of domain families altering pathways known to be involved with cancer such as protein phosphorylation, signaling, gene regulation, and cell metabolism. Due to oncodomain hotspots’ unique ability to assess rare variants, we expect our method to become an important tool for the analysis of sequenced tumor genomes, complementing existing methods. PMID:28426665
Immunosignature: Serum Antibody Profiling for Cancer Diagnostics.
Chapoval, Andrei I; Legutki, J Bart; Stafford, Philip; Trebukhov, Andrey V; Johnston, Stephen A; Shoikhet, Yakov N; Lazarev, Alexander F
2015-01-01
Biomarkers for preclinical diagnosis of cancer are valuable tools for detection of malignant tumors at early stages in groups at risk and screening healthy people, as well as monitoring disease recurrence after treatment of cancer. However the complexity of the body's response to the pathological processes makes it virtually impossible to evaluate this response to the development of the disease using a single biomarker that is present in the serum at low concentrations. An alternative approach to standard biomarker analysis is called immunosignature. Instead of going after biomarkers themselves this approach rely on the analysis of the humoral immune response to molecular changes associated with the development of pathological processes. It is known that antibodies are produced in response to proteins expressed during cancer development. Accordingly, the changes in antibody repertoire associated with tumor growth can serve as biomarkers of cancer. Immunosignature is a highly sensitive method for antibody repertoire analysis utilizing high density peptide microarrays. In the present review we discuss modern methods for antibody detection, as well as describe the principles and applications of immunosignature in research and clinical practice.
Automated analysis of clonal cancer cells by intravital imaging
Coffey, Sarah Earley; Giedt, Randy J; Weissleder, Ralph
2013-01-01
Longitudinal analyses of single cell lineages over prolonged periods have been challenging particularly in processes characterized by high cell turn-over such as inflammation, proliferation, or cancer. RGB marking has emerged as an elegant approach for enabling such investigations. However, methods for automated image analysis continue to be lacking. Here, to address this, we created a number of different multicolored poly- and monoclonal cancer cell lines for in vitro and in vivo use. To classify these cells in large scale data sets, we subsequently developed and tested an automated algorithm based on hue selection. Our results showed that this method allows accurate analyses at a fraction of the computational time required by more complex color classification methods. Moreover, the methodology should be broadly applicable to both in vitro and in vivo analyses. PMID:24349895
Zhu, Zheng-Ming
2017-01-01
Background Urothelial Carcinoma Associated 1 (UCA1) was an originally identified lncRNA in bladder cancer. Previous studies have reported that UCA1 played a significant role in various types of cancer. This study aimed to clarify the prognostic value of UCA1 in digestive system cancers. Results The meta-analysis of 15 studies were included, comprising 1441 patients with digestive system cancers. The pooled results of 14 studies indicated that high expression of UCA1 was significantly associated with poorer OS in patients with digestive system cancers (HR: 1.89, 95 % CI: 1.52–2.26). In addition, UCA1 could be as an independent prognostic factor for predicting OS of patients (HR: 1.85, 95 % CI: 1.45–2.25). The pooled results of 3 studies indicated a significant association between UCA1 and DFS in patients with digestive system cancers (HR = 2.50; 95 % CI = 1.30–3.69). Statistical significance was also observed in subgroup meta-analysis. Furthermore, the clinicopathological values of UCA1 were discussed in esophageal cancer, colorectal cancer and pancreatic cancer. Materials and methods A comprehensive retrieval was performed to search studies evaluating the prognostic value of UCA1 in digestive system cancers. Many databases were involved, including PubMed, Web of Science, Embase and Chinese National Knowledge Infrastructure and Wanfang database. Quantitative meta-analysis was performed with standard statistical methods and the prognostic significance of UCA1 in digestive system cancers was qualified. Conclusions Elevated level of UCA1 indicated the poor clinical outcome for patients with digestive system cancers. It may serve as a new biomarker related to prognosis in digestive system cancers. PMID:28380443
Quantitative high-resolution genomic analysis of single cancer cells.
Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard
2011-01-01
During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.
DOE Office of Scientific and Technical Information (OSTI.GOV)
James, Veronica J.; O’Malley Ford, Judith M.
Double blind analysis of a batch of thirty skin tissue samples from potential prostate cancer sufferers correctly identified all “control” patients, patients with high and low grade prostate cancers, the presence of benign prostate hyperplasia (BPH), perineural invasions, and the one lymphatic invasion. Identification was by analysis of fibre diffraction patterns interpreted using a schema developed from observations in nine previous studies. The method, schema, and specific experiment results are reported in this paper, with some implications then drawn.
James, Veronica J.; O’Malley Ford, Judith M.
2014-01-01
Double blind analysis of a batch of thirty skin tissue samples from potential prostate cancer sufferers correctly identified all “control” patients, patients with high and low grade prostate cancers, the presence of benign prostate hyperplasia (BPH), perineural invasions, and the one lymphatic invasion. Identification was by analysis of fibre diffraction patterns interpreted using a schema developed from observations in nine previous studies. The method, schema, and specific experiment results are reported in this paper, with some implications then drawn.
NASA Astrophysics Data System (ADS)
Cowherd, Wilson
Breast cancer is one of the most common cancers in women with a very high incident rate, especially for those women who are between 40-60 years old. Most drugs are large or non-polar macromolecules, which cannot get into cancer cells autonomously, so a method that can deliver those drugs is very important. Optoporation method has been facilitated with gold nanoparticles, which are bound to breast cancer cells, and then absorb the optical energy to improve the membrane permeabilization. Long-term dietary consumption of fruits and vegetables high in beta-carotene and other phytochemicals has been shown beneficial in terms of anti-cancer, anti-aging, preventing cardiovascular disease and cataract. However they are large non-polar molecules that are difficult to enter the cancer cells. Here in this study, we applied optoporation method by using beta-carotene, and tetracycline as anti-cancer drugs in various concentrations to optimize highest selective cell death/best potential for T47D breast cancer cell lines.
Li, Qi-Gang; He, Yong-Han; Wu, Huan; Yang, Cui-Ping; Pu, Shao-Yan; Fan, Song-Qing; Jiang, Li-Ping; Shen, Qiu-Shuo; Wang, Xiao-Xiong; Chen, Xiao-Qiong; Yu, Qin; Li, Ying; Sun, Chang; Wang, Xiangting; Zhou, Jumin; Li, Hai-Peng; Chen, Yong-Bin; Kong, Qing-Peng
2017-01-01
Heterogeneity in transcriptional data hampers the identification of differentially expressed genes (DEGs) and understanding of cancer, essentially because current methods rely on cross-sample normalization and/or distribution assumption-both sensitive to heterogeneous values. Here, we developed a new method, Cross-Value Association Analysis (CVAA), which overcomes the limitation and is more robust to heterogeneous data than the other methods. Applying CVAA to a more complex pan-cancer dataset containing 5,540 transcriptomes discovered numerous new DEGs and many previously rarely explored pathways/processes; some of them were validated, both in vitro and in vivo , to be crucial in tumorigenesis, e.g., alcohol metabolism ( ADH1B ), chromosome remodeling ( NCAPH ) and complement system ( Adipsin ). Together, we present a sharper tool to navigate large-scale expression data and gain new mechanistic insights into tumorigenesis.
Woo, Hae Dong; Kim, Jeongseon
2012-01-01
Good biomarkers for early detection of cancer lead to better prognosis. However, harvesting tumor tissue is invasive and cannot be routinely performed. Global DNA methylation of peripheral blood leukocyte DNA was evaluated as a biomarker for cancer risk. We performed a meta-analysis to estimate overall cancer risk according to global DNA hypomethylation levels among studies with various cancer types and analytical methods used to measure DNA methylation. Studies were systemically searched via PubMed with no language limitation up to July 2011. Summary estimates were calculated using a fixed effects model. The subgroup analyses by experimental methods to determine DNA methylation level were performed due to heterogeneity within the selected studies (p<0.001, I(2): 80%). Heterogeneity was not found in the subgroup of %5-mC (p = 0.393, I(2): 0%) and LINE-1 used same target sequence (p = 0.097, I(2): 49%), whereas considerable variance remained in LINE-1 (p<0.001, I(2): 80%) and bladder cancer studies (p = 0.016, I(2): 76%). These results suggest that experimental methods used to quantify global DNA methylation levels are important factors in the association study between hypomethylation levels and cancer risk. Overall, cancer risks of the group with the lowest DNA methylation levels were significantly higher compared to the group with the highest methylation levels [OR (95% CI): 1.48 (1.28-1.70)]. Global DNA hypomethylation in peripheral blood leukocytes may be a suitable biomarker for cancer risk. However, the association between global DNA methylation and cancer risk may be different based on experimental methods, and region of DNA targeted for measuring global hypomethylation levels as well as the cancer type. Therefore, it is important to select a precise and accurate surrogate marker for global DNA methylation levels in the association studies between global DNA methylation levels in peripheral leukocyte and cancer risk.
Mattei, Francesca; Liverani, Silvia; Guida, Florence; Matrat, Mireille; Cenée, Sylvie; Azizi, Lamiae; Menvielle, Gwenn; Sanchez, Marie; Pilorget, Corinne; Lapôtre-Ledoux, Bénédicte; Luce, Danièle; Richardson, Sylvia; Stücker, Isabelle
2016-01-01
Background The association between lung cancer and occupational exposure to organic solvents is discussed. Since different solvents are often used simultaneously, it is difficult to assess the role of individual substances. Objectives The present study is focused on an in-depth investigation of the potential association between lung cancer risk and occupational exposure to a large group of organic solvents, taking into account the well-known risk factors for lung cancer, tobacco smoking and occupational exposure to asbestos. Methods We analysed data from the Investigation of occupational and environmental causes of respiratory cancers (ICARE) study, a large French population-based case–control study, set up between 2001 and 2007. A total of 2276 male cases and 2780 male controls were interviewed, and long-life occupational history was collected. In order to overcome the analytical difficulties created by multiple correlated exposures, we carried out a novel type of analysis based on Bayesian profile regression. Results After analysis with conventional logistic regression methods, none of the 11 solvents examined were associated with lung cancer risk. Through a profile regression approach, we did not observe any significant association between solvent exposure and lung cancer. However, we identified clusters at high risk that are related to occupations known to be at risk of developing lung cancer, such as painters. Conclusions Organic solvents do not appear to be substantial contributors to the occupational risk of lung cancer for the occupations known to be at risk. PMID:26911986
Two-step Raman spectroscopy method for tumor diagnosis
NASA Astrophysics Data System (ADS)
Zakharov, V. P.; Bratchenko, I. A.; Kozlov, S. V.; Moryatov, A. A.; Myakinin, O. O.; Artemyev, D. N.
2014-05-01
Two-step Raman spectroscopy phase method was proposed for differential diagnosis of malignant tumor in skin and lung tissue. It includes detection of malignant tumor in healthy tissue on first step with identification of concrete cancer type on the second step. Proposed phase method analyze spectral intensity alteration in 1300-1340 and 1640-1680 cm-1 Raman bands in relation to the intensity of the 1450 cm-1 band on first step, and relative differences between RS intensities for tumor area and healthy skin closely adjacent to the lesion on the second step. It was tested more than 40 ex vivo samples of lung tissue and more than 50 in vivo skin tumors. Linear Discriminant Analysis, Quadratic Discriminant Analysis and Support Vector Machine were used for tumors type classification on phase planes. It is shown that two-step phase method allows to reach 88.9% sensitivity and 87.8% specificity for malignant melanoma diagnosis (skin cancer); 100% sensitivity and 81.5% specificity for adenocarcinoma diagnosis (lung cancer); 90.9% sensitivity and 77.8% specificity for squamous cell carcinoma diagnosis (lung cancer).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dréan, Gaël; Acosta, Oscar, E-mail: Oscar.Acosta@univ-rennes1.fr; Simon, Antoine
2016-06-15
Purpose: Recent studies revealed a trend toward voxelwise population analysis in order to understand the local dose/toxicity relationships in prostate cancer radiotherapy. Such approaches require, however, an accurate interindividual mapping of the anatomies and 3D dose distributions toward a common coordinate system. This step is challenging due to the high interindividual variability. In this paper, the authors propose a method designed for interindividual nonrigid registration of the rectum and dose mapping for population analysis. Methods: The method is based on the computation of a normalized structural description of the rectum using a Laplacian-based model. This description takes advantage of themore » tubular structure of the rectum and its centerline to be embedded in a nonrigid registration-based scheme. The performances of the method were evaluated on 30 individuals treated for prostate cancer in a leave-one-out cross validation. Results: Performance was measured using classical metrics (Dice score and Hausdorff distance), along with new metrics devised to better assess dose mapping in relation with structural deformation (dose-organ overlap). Considering these scores, the proposed method outperforms intensity-based and distance maps-based registration methods. Conclusions: The proposed method allows for accurately mapping interindividual 3D dose distributions toward a single anatomical template, opening the way for further voxelwise statistical analysis.« less
Trends in incidence of lung cancer in Croatia from 2001 to 2013: gender and regional differences
Siroglavić, Katarina-Josipa; Polić Vižintin, Marina; Tripković, Ingrid; Šekerija, Mario; Kukulj, Suzana
2017-01-01
Aim To provide an overview of the lung cancer incidence trends in the City of Zagreb (Zagreb), Split-Dalmatia County (SDC), and Croatia in the period from 2001 to 2013. Method Incidence data were obtained from the Croatian National Cancer Registry. For calculating incidence rates per 100 000 population, we used population estimates for the period 2001-2013 from the Croatian Bureau of Statistics. Age-standardized rates of lung cancer incidence were calculated by the direct standardization method using the European Standard Population. To describe incidence trends, we used joinpoint regression analysis. Results Joinpoint analysis showed a statistically significant decrease in lung cancer incidence in men in all regions, with an annual percentage change (APC) of -2.2% for Croatia, 1.9% for Zagreb, and -2.0% for SDC. In women, joinpoint analysis showed a statistically significant increase in the incidence for Croatia, with APC of 1.4%, a statistically significant increase of 1.0% for Zagreb, and no significant change in trend for SDC. In both genders, joinpoint analysis showed a significant decrease in age-standardized incidence rates of lung cancer, with APC of -1.3% for Croatia, -1.1% for Zagreb, and -1.6% for SDC. Conclusion There was an increase in female lung cancer incidence rate and a decrease in male lung cancer incidence rate in Croatia in 2001-20013 period, with similar patterns observed in all the investigated regions. These results highlight the importance of smoking prevention and cessation policies, especially among women and young people. PMID:29094814
Pellegrini, Kathryn L.; Patil, Dattatraya; Douglas, Kristen J.S.; Lee, Grace; Wehrmeyer, Kathryn; Torlak, Mersiha; Clark, Jeremy; Cooper, Colin S.; Moreno, Carlos S.; Sanda, Martin G.
2018-01-01
Background The measurement of gene expression in post-digital rectal examination (DRE) urine specimens provides a non-invasive method to determine a patient’s risk of prostate cancer. Many currently available assays use whole urine or cell pellets for the analysis of prostate cancer-associated genes, although the use of extracellular vesicles (EVs) has also recently been of interest. We investigated the expression of prostate-, kidney-, and bladder-specific transcripts and known prostate cancer biomarkers in urine EVs. Methods Cell pellets and EVs were recovered from post-DRE urine specimens, with the total RNA yield and quality determined by Bioanalyzer. The levels of prostate, kidney, and bladder-associated transcripts in EVs were assessed by TaqMan qPCR and targeted sequencing. Results RNA was more consistently recovered from the urine EV specimens, with over 80% of the patients demonstrating higher RNA yields in the EV fraction as compared to urine cell pellets. The median EV RNA yield of 36.4 ng was significantly higher than the median urine cell pellet RNA yield of 4.8 ng. Analysis of the post-DRE urine EVs indicated that prostate-specific transcripts were more abundant than kidney- or bladder-specific transcripts. Additionally, patients with prostate cancer had significantly higher levels of the prostate cancer-associated genes PCA3 and ERG. Conclusions Post-DRE urine EVs are a viable source of prostate-derived RNAs for biomarker discovery and prostate cancer status can be distinguished from analysis of these specimens. Continued analysis of urine EVs offers the potential discovery of novel biomarkers for pre-biopsy prostate cancer detection. PMID:28419548
Oncotripsy: Targeting cancer cells selectively via resonant harmonic excitation
NASA Astrophysics Data System (ADS)
Heyden, S.; Ortiz, M.
2016-07-01
We investigate a method of selectively targeting cancer cells by means of ultrasound harmonic excitation at their resonance frequency, which we refer to as oncotripsy. The geometric model of the cells takes into account the cytoplasm, nucleus and nucleolus, as well as the plasma membrane and nuclear envelope. Material properties are varied within a pathophysiologically-relevant range. A first modal analysis reveals the existence of a spectral gap between the natural frequencies and, most importantly, resonant growth rates of healthy and cancerous cells. The results of the modal analysis are verified by simulating the fully-nonlinear transient response of healthy and cancerous cells at resonance. The fully nonlinear analysis confirms that cancerous cells can be selectively taken to lysis by the application of carefully tuned ultrasound harmonic excitation while simultaneously leaving healthy cells intact.
Methods and Technologies Branch (MTB)
The Methods and Technologies Branch focuses on methods to address epidemiologic data collection, study design and analysis, and to modify technological approaches to better understand cancer susceptibility.
Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma
Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang
2017-01-01
Objective This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Methods Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Results Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification (P=0.009) or deletion (P=0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly (P=1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Conclusion Chromosomal CNVs may contribute to their transcript expression in cervical cancer. PMID:29312578
Surface-enhanced Raman spectra of hemoglobin for esophageal cancer diagnosis
NASA Astrophysics Data System (ADS)
Zhou, Xue; Diao, Zhenqi; Fan, Chunzhen; Guo, Huiqiang; Xiong, Yang; Tang, Weiyue
2014-03-01
Surface-enhanced Raman scattering (SERS) spectra of hemoglobin from 30 esophageal cancer patients and 30 healthy persons have been detected and analyzed. The results indicate that, there are more iron ions in low spin state and less in high for the hemoglobin of esophageal cancer patients than normal persons, which is consistent with the fact that it is easier to hemolyze for the blood of cancer patients. By using principal component analysis (PCA) and discriminate analysis, we can get a three-dimensional scatter plot of PC scores from the SERS spectra of healthy persons and cancer patients, from which the two groups can be discriminated. The total accuracy of this method is 90%, while the diagnostic specificity is 93.3% and sensitivity is 86.7%. Thus SERS spectra of hemoglobin analysis combined with PCA may be a new technique for the early diagnose of esophageal cancer.
Yoshida, Tsuyoshi; Kobayashi, Takumi; Itoda, Masaya; Muto, Taika; Miyaguchi, Ken; Mogushi, Kaoru; Shoji, Satoshi; Shimokawa, Kazuro; Iida, Satoru; Uetake, Hiroyuki; Ishikawa, Toshiaki; Sugihara, Kenichi; Mizushima, Hiroshi; Tanaka, Hiroshi
2010-07-29
Colorectal cancer (CRC) is one of the most frequently occurring cancers in Japan, and thus a wide range of methods have been deployed to study the molecular mechanisms of CRC. In this study, we performed a comprehensive analysis of CRC, incorporating copy number aberration (CRC) and gene expression data. For the last four years, we have been collecting data from CRC cases and organizing the information as an "omics" study by integrating many kinds of analysis into a single comprehensive investigation. In our previous studies, we had experienced difficulty in finding genes related to CRC, as we observed higher noise levels in the expression data than in the data for other cancers. Because chromosomal aberrations are often observed in CRC, here, we have performed a combination of CNA analysis and expression analysis in order to identify some new genes responsible for CRC. This study was performed as part of the Clinical Omics Database Project at Tokyo Medical and Dental University. The purpose of this study was to investigate the mechanism of genetic instability in CRC by this combination of expression analysis and CNA, and to establish a new method for the diagnosis and treatment of CRC. Comprehensive gene expression analysis was performed on 79 CRC cases using an Affymetrix Gene Chip, and comprehensive CNA analysis was performed using an Affymetrix DNA Sty array. To avoid the contamination of cancer tissue with normal cells, laser micro-dissection was performed before DNA/RNA extraction. Data analysis was performed using original software written in the R language. We observed a high percentage of CNA in colorectal cancer, including copy number gains at 7, 8q, 13 and 20q, and copy number losses at 8p, 17p and 18. Gene expression analysis provided many candidates for CRC-related genes, but their association with CRC did not reach the level of statistical significance. The combination of CNA and gene expression analysis, together with the clinical information, suggested UGT2B28, LOC440995, CXCL6, SULT1B1, RALBP1, TYMS, RAB12, RNMT, ARHGDIB, S1000A2, ABHD2, OIT3 and ABHD12 as genes that are possibly associated with CRC. Some of these genes have already been reported as being related to CRC. TYMS has been reported as being associated with resistance to the anti-cancer drug 5-fluorouracil, and we observed a copy number increase for this gene. RALBP1, ARHGDIB and S100A2 have been reported as oncogenes, and we observed copy number increases in each. ARHGDIB has been reported as a metastasis-related gene, and our data also showed copy number increases of this gene in cases with metastasis. The combination of CNA analysis and gene expression analysis was a more effective method for finding genes associated with the clinicopathological classification of CRC than either analysis alone. Using this combination of methods, we were able to detect genes that have already been associated with CRC. We also identified additional candidate genes that may be new markers or targets for this form of cancer.
A novel feature ranking method for prediction of cancer stages using proteomics data
Saghapour, Ehsan; Sehhati, Mohammadreza
2017-01-01
Proteomic analysis of cancers' stages has provided new opportunities for the development of novel, highly sensitive diagnostic tools which helps early detection of cancer. This paper introduces a new feature ranking approach called FRMT. FRMT is based on the Technique for Order of Preference by Similarity to Ideal Solution method (TOPSIS) which select the most discriminative proteins from proteomics data for cancer staging. In this approach, outcomes of 10 feature selection techniques were combined by TOPSIS method, to select the final discriminative proteins from seven different proteomic databases of protein expression profiles. In the proposed workflow, feature selection methods and protein expressions have been considered as criteria and alternatives in TOPSIS, respectively. The proposed method is tested on seven various classifier models in a 10-fold cross validation procedure that repeated 30 times on the seven cancer datasets. The obtained results proved the higher stability and superior classification performance of method in comparison with other methods, and it is less sensitive to the applied classifier. Moreover, the final introduced proteins are informative and have the potential for application in the real medical practice. PMID:28934234
How Have Cancer Clinical Trial Eligibility Criteria Evolved Over Time?
Yaman, Anil; Chakrabarti, Shreya; Sen, Anando; Weng, Chunhua
2016-01-01
Knowledge reuse of cancer trial designs may benefit from a temporal understanding of the evolution of the target populations of cancer studies over time. Therefore, we conducted a retrospective analysis of the trends of cancer trial eligibility criteria between 1999 and 2014. The yearly distributions of eligibility concepts for chemicals and drugs, procedures, observations, and medical conditions extracted from free-text eligibility criteria of 32,000 clinical trials for 89 cancer types were analyzed. We identified the concepts that trend upwards or downwards in all or selected cancer types, and the concepts that show anomalous trends for some cancers. Later, concept trends were studied in a disease-specific manner and illustrated for breast cancer. Criteria trends observed in this study are also validated and interpreted using evidence from the existing medical literature. This study contributes a method for concept trend analysis and original knowledge of the trends in cancer clinical trial eligibility criteria. PMID:27570681
2009-01-01
Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. Conclusions We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment. PMID:20025723
Zahmatkesh, Bibihajar; Keramat, Afsaneh; Alavi, Nasrinossadat; Khosravi, Ahmad; Kousha, Ahmad; Motlagh, Ali Ghanbari; Darman, Mahboobeh; Partovipour, Elham; Chaman, Reza
2016-01-01
Breast cancer is the most common cancer in women worldwide with a rising incidence rate in most countries. Considering the increase in life expectancy and change in lifestyle of Iranian women, this study investigated the age-adjusted trend of breast cancer incidence during 2000-2009 and predicted its incidence to 2020. The 1997 and 2006 census results were used for the projection of female population by age through the cohort-component method over the studied years. Data from the Iranian cancer registration system were used to calculate the annual incidence rate of breast cancer. The age-adjusted incidence rate was then calculated using the WHO standard population distribution. The five-year-age-specific incidence rates were also obtained for each year and future incidence was determined using the trend analysis method. Annual percentage change (APC) was calculated through the joinpoint regression method. The bias adjusted incidence rate of breast cancer increased from 16.7 per 100,000 women in 2000 to 33.6 per 100,000 women in 2009. The incidence of breast cancer had a growing trend in almost all age groups above 30 years over the studied years. In this period, the age groups of 45-65 years had the highest incidence. Investigation into the joinpoint curve showed that the curve had a steep slope with an APC of 23.4% before the first joinpoint, but became milder after this. From 2005 to 2009, the APC was calculated as 2.7%, through which the incidence of breast cancer in 2020 was predicted as 63.0 per 100,000 women. The age-adjusted incidence rate of breast cancer continues to increas in Iranian women. It is predicted that this trend will continue until 2020. Therefore, it seems necessary to prioritize the prevention, control and care for breast cancer in Iran.
Advances in intelligent diagnosis methods for pulmonary ground-glass opacity nodules.
Yang, Jing; Wang, Hailin; Geng, Chen; Dai, Yakang; Ji, Jiansong
2018-02-07
Pulmonary nodule is one of the important lesions of lung cancer, mainly divided into two categories of solid nodules and ground glass nodules. The improvement of diagnosis of lung cancer has significant clinical significance, which could be realized by machine learning techniques. At present, there have been a lot of researches focusing on solid nodules. But the research on ground glass nodules started late, and lacked research results. This paper summarizes the research progress of the method of intelligent diagnosis for pulmonary nodules since 2014. It is described in details from four aspects: nodular signs, data analysis methods, prediction models and system evaluation. This paper aims to provide the research material for researchers of the clinical diagnosis and intelligent analysis of lung cancer, and further improve the precision of pulmonary ground glass nodule diagnosis.
Quantitative High-Resolution Genomic Analysis of Single Cancer Cells
Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A.; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard
2011-01-01
During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics. PMID:22140428
Langholz, Bryan; Thomas, Duncan C.; Stovall, Marilyn; Smith, Susan A.; Boice, John D.; Shore, Roy E.; Bernstein, Leslie; Lynch, Charles F.; Zhang, Xinbo; Bernstein, Jonine L.
2009-01-01
Summary Methods for the analysis of individually matched case-control studies with location-specific radiation dose and tumor location information are described. These include likelihood methods for analyses that just use cases with precise location of tumor information and methods that also include cases with imprecise tumor location information. The theory establishes that each of these likelihood based methods estimates the same radiation rate ratio parameters, within the context of the appropriate model for location and subject level covariate effects. The underlying assumptions are characterized and the potential strengths and limitations of each method are described. The methods are illustrated and compared using the WECARE study of radiation and asynchronous contralateral breast cancer. PMID:18647297
A deep learning-based multi-model ensemble method for cancer prediction.
Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong
2018-01-01
Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.
Engholm, Gerda; Gislum, Mette; Bray, Freddie; Hakulinen, Timo
2010-06-01
Comparable data on cancer incidence and mortality in Denmark, Finland, Iceland, Norway, and Sweden are available for analysis through a collaboration of the national Cancer Registries via the NORDCAN website (http://ancr.nu). In the continued spirit of Nordic collaborative research, a number of studies examining trends in cancer survival are published in this journal. The data were divided into eight 5-year periods by sex in five Nordic countries. Age-standardised 5-year relative survival ratios and excess mortality rates in the short-term (first month and 1-3 months following diagnosis), and the long-term (2-5 years after diagnosis) were calculated, as were age-specific 5-year relative survival using cohort-survival methods. A hybrid method combining the cohort and period methods was used for the period 1999-2003 as not all patients were followed for five years. Age-standardisation used the International Cancer Survival Standard, and calculation of expected deaths used country-specific population mortality rates. The data series constitutes 3 360 397 tumours among 3 160 802 patients followed up for death through 2006 for 39 different cancer sites diagnosed in the years 1964-2003. The paper describes the data, exclusions and imputations, design and analysis, age structure and standardisation procedures, follow-up, and case-mix adjustment methods. The strengths of this study include the overall comparability and quality of the data, the national coverage, and the length of the time series. Collecting and analysing data from the five Nordic countries for 39 different cancer sites over 40 years in a systematised and comparable way is a major undertaking. A thorough description of the analyses, definitions and exclusions in the survival study, supplemented with corresponding information on cancer incidence and mortality is needed for appropriate interpretation and comparison between countries, and between and within cancer sites. This information must be made available to provide appropriate interpretation of the site-specific results.
Dhar, Manjima; Pao, Edward; Renier, Corinne; Go, Derek E; Che, James; Montoya, Rosita; Conrad, Rachel; Matsumoto, Melissa; Heirich, Kyra; Triboulet, Melanie; Rao, Jianyu; Jeffrey, Stefanie S; Garon, Edward B; Goldman, Jonathan; Rao, Nagesh P; Kulkarni, Rajan; Sollier-Christen, Elodie; Di Carlo, Dino
2016-10-14
Circulating tumor cells (CTCs) have a great potential as indicators of metastatic disease that may help physicians improve cancer prognostication, treatment and patient outcomes. Heterogeneous marker expression as well as the complexity of current antibody-based isolation and analysis systems highlights the need for alternative methods. In this work, we use a microfluidic Vortex device that can selectively isolate potential tumor cells from blood independent of cell surface expression. This system was adapted to interface with three protein-marker-free analysis techniques: (i) an in-flow automated image processing system to enumerate cells released, (ii) cytological analysis using Papanicolaou (Pap) staining and (iii) fluorescence in situ hybridization (FISH) targeting the ALK rearrangement. In-flow counting enables a rapid assessment of the cancer-associated large circulating cells in a sample within minutes to determine whether standard downstream assays such as cytological and cytogenetic analyses that are more time consuming and costly are warranted. Using our platform integrated with these workflows, we analyzed 32 non-small cell lung cancer (NSCLC) and 22 breast cancer patient samples, yielding 60 to 100% of the cancer patients with a cell count over the healthy threshold, depending on the detection method used: respectively 77.8% for automated, 60-100% for cytology, and 80% for immunostaining based enumeration.
Dhar, Manjima; Pao, Edward; Renier, Corinne; Go, Derek E.; Che, James; Montoya, Rosita; Conrad, Rachel; Matsumoto, Melissa; Heirich, Kyra; Triboulet, Melanie; Rao, Jianyu; Jeffrey, Stefanie S.; Garon, Edward B.; Goldman, Jonathan; Rao, Nagesh P.; Kulkarni, Rajan; Sollier-Christen, Elodie; Di Carlo, Dino
2016-01-01
Circulating tumor cells (CTCs) have a great potential as indicators of metastatic disease that may help physicians improve cancer prognostication, treatment and patient outcomes. Heterogeneous marker expression as well as the complexity of current antibody-based isolation and analysis systems highlights the need for alternative methods. In this work, we use a microfluidic Vortex device that can selectively isolate potential tumor cells from blood independent of cell surface expression. This system was adapted to interface with three protein-marker-free analysis techniques: (i) an in-flow automated image processing system to enumerate cells released, (ii) cytological analysis using Papanicolaou (Pap) staining and (iii) fluorescence in situ hybridization (FISH) targeting the ALK rearrangement. In-flow counting enables a rapid assessment of the cancer-associated large circulating cells in a sample within minutes to determine whether standard downstream assays such as cytological and cytogenetic analyses that are more time consuming and costly are warranted. Using our platform integrated with these workflows, we analyzed 32 non-small cell lung cancer (NSCLC) and 22 breast cancer patient samples, yielding 60 to 100% of the cancer patients with a cell count over the healthy threshold, depending on the detection method used: respectively 77.8% for automated, 60–100% for cytology, and 80% for immunostaining based enumeration. PMID:27739521
Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana
2011-01-01
Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.
The market trend analysis and prospects of cancer molecular diagnostics kits.
Seo, Ju Hwan; Lee, Joon Woo; Cho, Daemyeong
2018-01-01
The molecular diagnostics market can be broadly divided into PCR (rt-PCR, d-PCR), NGS(Next Generation Sequencing), Microarray, FISH(Fluorescent in situ-hybridization) and other categories, based on the diagnostic technique. Also, depending on the disease being diagnosed, the market can also be divided into cancer, infectious diseases, HIV/STDs (herpes, syphilis), and women's health issues such as breast cancer, cervical cancer, ovarian cancer, HPV(human papillomavirus), and vaginitis.Chromosome analysis (including Fluorescent In-situ Hybridization) is one type of blood cancer diagnostic method, which involves the direct detection of individual cells with chromosomal translocation, but there have been problems of sensitivity when using this method. PCR targeting individual genes or the RT (reverse transcription)-PCR method offers outstanding sensitivity, but one drawback is the risk of false-positive reaction caused by contamination of samples, etc. Blood cancer molecular diagnostics kits allow us to overcome these shortcomings, and related products have been under development, with a focus on improving detection sensitivity, enabling multiple tests, and reducing the cost and diagnostic time. Blood cancer molecular diagnostics is usually performed based on platforms such as PCR. The global market for blood cancer molecular diagnostics kits is $ 335.9 million as of 2016 and is expected to reach $ 6980 million in 2026 with an average annual growth rate of 32.9%. The market in South Korea is anticipated to grow at an average annual rate of 28.9%, from $ 3.75 million as of 2016 to $ 60.89 million in 2026. The Market for blood cancer molecular diagnostics kits is judged to be higher in growth possibility due to the increase in the number of cancer patients.
2013-01-01
Background Colorectal cancer is the third leading cause of cancer deaths in the United States. The initial assessment of colorectal cancer involves clinical staging that takes into account the extent of primary tumor invasion, determining the number of lymph nodes with metastatic cancer and the identification of metastatic sites in other organs. Advanced clinical stage indicates metastatic cancer, either in regional lymph nodes or in distant organs. While the genomic and genetic basis of colorectal cancer has been elucidated to some degree, less is known about the identity of specific cancer genes that are associated with advanced clinical stage and metastasis. Methods We compiled multiple genomic data types (mutations, copy number alterations, gene expression and methylation status) as well as clinical meta-data from The Cancer Genome Atlas (TCGA). We used an elastic-net regularized regression method on the combined genomic data to identify genetic aberrations and their associated cancer genes that are indicators of clinical stage. We ranked candidate genes by their regression coefficient and level of support from multiple assay modalities. Results A fit of the elastic-net regularized regression to 197 samples and integrated analysis of four genomic platforms identified the set of top gene predictors of advanced clinical stage, including: WRN, SYK, DDX5 and ADRA2C. These genetic features were identified robustly in bootstrap resampling analysis. Conclusions We conducted an analysis integrating multiple genomic features including mutations, copy number alterations, gene expression and methylation. This integrated approach in which one considers all of these genomic features performs better than any individual genomic assay. We identified multiple genes that robustly delineate advanced clinical stage, suggesting their possible role in colorectal cancer metastatic progression. PMID:24308539
Strategies for the evaluation of DNA damage and repair mechanisms in cancer.
Figueroa-González, Gabriela; Pérez-Plasencia, Carlos
2017-06-01
DNA lesions and the repair mechanisms that maintain the integrity of genomic DNA are important in preventing carcinogenesis and its progression. Notably, mutations in DNA repair mechanisms are associated with cancer predisposition syndromes. Additionally, these mechanisms maintain the genomic integrity of cancer cells. The majority of therapies established to treat cancer are genotoxic agents that induce DNA damage, promoting cancer cells to undergo apoptotic death. Effective methods currently exist to evaluate the diverse effects of genotoxic agents and the underlying molecular mechanisms that repair DNA lesions. The current study provides an overview of a number of methods that are available for the detection, analysis and quantification of underlying DNA repair mechanisms.
Receipt of Cancer Screening Services: Surprising Results for Some Rural Minorities
ERIC Educational Resources Information Center
Bennett, Kevin J.; Probst, Janice C.; Bellinger, Jessica D.
2012-01-01
Background: Evidence suggests that rural minority populations experience disparities in cancer screening, treatment, and outcomes. It is unknown how race/ethnicity and rurality intersect in these disparities. The purpose of this analysis is to examine the cancer screening rates among minorities in rural areas. Methods: We utilized the 2008…
Rapin, Nicolas; Bagger, Frederik Otzen; Jendholm, Johan; Mora-Jensen, Helena; Krogh, Anders; Kohlmann, Alexander; Thiede, Christian; Borregaard, Niels; Bullinger, Lars; Winther, Ole; Theilgaard-Mönch, Kim; Porse, Bo T
2014-02-06
Gene expression profiling has been used extensively to characterize cancer, identify novel subtypes, and improve patient stratification. However, it has largely failed to identify transcriptional programs that differ between cancer and corresponding normal cells and has not been efficient in identifying expression changes fundamental to disease etiology. Here we present a method that facilitates the comparison of any cancer sample to its nearest normal cellular counterpart, using acute myeloid leukemia (AML) as a model. We first generated a gene expression-based landscape of the normal hematopoietic hierarchy, using expression profiles from normal stem/progenitor cells, and next mapped the AML patient samples to this landscape. This allowed us to identify the closest normal counterpart of individual AML samples and determine gene expression changes between cancer and normal. We find the cancer vs normal method (CvN method) to be superior to conventional methods in stratifying AML patients with aberrant karyotype and in identifying common aberrant transcriptional programs with potential importance for AML etiology. Moreover, the CvN method uncovered a novel poor-outcome subtype of normal-karyotype AML, which allowed for the generation of a highly prognostic survival signature. Collectively, our CvN method holds great potential as a tool for the analysis of gene expression profiles of cancer patients.
Examination of pain experiences of cancer patients in western Turkey: a phenomenological study.
Akin Korhan, Esra; Yildirim, Yasemin; Uyar, Meltem; Eyigör, Can; Uslu, Ruçhan
2013-01-01
This study aims to explore the individual experience of living with cancer pain. This qualitative study was performed by using a phenomenological research design. In-depth and open interviews with participants were conducted to collect the data and a qualitative Colaizzi method of analysis was performed. Following the analysis of the data, the expressions made by the cancer patients during the interviews were grouped under 5 themes. Consistent with the questionnaire format, 5 themes and 19 subthemes of responses were determined describing the pain of the cancer patients. The results of our study have demonstrated that cancer patients go through negative physical, psychological, and social experiences due to the pain they suffered.
Micek, Agnieszka; Marranzano, Marina; Ray, Sumantra
2017-01-01
Background: A meta-analysis was conducted to summarize the evidence from prospective cohort and case-control studies regarding the association between coffee intake and biliary tract cancer (BTC) and liver cancer risk. Methods: Eligible studies were identified by searches of PubMed and EMBASE databases from the earliest available online indexing year to March 2017. The dose–response relationship was assessed by a restricted cubic spline model and multivariate random-effect meta-regression. A stratified and subgroup analysis by smoking status and hepatitis was performed to identify potential confounding factors. Results: We identified five studies on BTC risk and 13 on liver cancer risk eligible for meta-analysis. A linear dose–response meta-analysis did not show a significant association between coffee consumption and BTC risk. However, there was evidence of inverse correlation between coffee consumption and liver cancer risk. The association was consistent throughout the various potential confounding factors explored including smoking status, hepatitis, etc. Increasing coffee consumption by one cup per day was associated with a 15% reduction in liver cancer risk (RR 0.85; 95% CI 0.82 to 0.88). Conclusions: The findings suggest that increased coffee consumption is associated with decreased risk of liver cancer, but not BTC. PMID:28846640
Li, Yongsheng; Sahni, Nidhi; Yi, Song
2016-11-29
Comprehensive understanding of human cancer mechanisms requires the identification of a thorough list of cancer-associated genes, which could serve as biomarkers for diagnoses and therapies in various types of cancer. Although substantial progress has been made in functional studies to uncover genes involved in cancer, these efforts are often time-consuming and costly. Therefore, it remains challenging to comprehensively identify cancer candidate genes. Network-based methods have accelerated this process through the analysis of complex molecular interactions in the cell. However, the extent to which various interactome networks can contribute to prediction of candidate genes responsible for cancer is still enigmatic. In this study, we evaluated different human protein-protein interactome networks and compared their application to cancer gene prioritization. Our results indicate that network analyses can increase the power to identify novel cancer genes. In particular, such predictive power can be enhanced with the use of unbiased systematic protein interaction maps for cancer gene prioritization. Functional analysis reveals that the top ranked genes from network predictions co-occur often with cancer-related terms in literature, and further, these candidate genes are indeed frequently mutated across cancers. Finally, our study suggests that integrating interactome networks with other omics datasets could provide novel insights into cancer-associated genes and underlying molecular mechanisms.
Circulating Tumor Cell Isolation and Analysis
Zhang, J.; Chen, K.; Fan, Z.H.
2016-01-01
Isolation and analysis of cancer cells from body fluids have significant implications in diagnosis and therapeutic treatment of cancers. Circulating tumor cells (CTCs) are cancer cells circulating in the peripheral blood or spreading iatrogenically into blood vessels, which is an early step in the cascade of events leading to cancer metastasis. Therefore, CTCs can be used for diagnosing for therapeutic treatment, prognosing a given anticancer intervention, and estimating the risk of metastatic relapse. However, isolation of CTCs is a significant technological challenge due to their rarity and low recovery rate using traditional purification techniques. Recently microfluidic devices represent a promising platform for isolating cancer cells with high efficiency in processing complex cellular fluids, with simplicity, sensitivity, and throughput. This review summarizes recent methods of CTC isolation and analysis, as well as their applications in clinical studies. PMID:27346614
Circulating Tumor Cell Isolation and Analysis.
Zhang, J; Chen, K; Fan, Z H
Isolation and analysis of cancer cells from body fluids have significant implications in diagnosis and therapeutic treatment of cancers. Circulating tumor cells (CTCs) are cancer cells circulating in the peripheral blood or spreading iatrogenically into blood vessels, which is an early step in the cascade of events leading to cancer metastasis. Therefore, CTCs can be used for diagnosing for therapeutic treatment, prognosing a given anticancer intervention, and estimating the risk of metastatic relapse. However, isolation of CTCs is a significant technological challenge due to their rarity and low recovery rate using traditional purification techniques. Recently microfluidic devices represent a promising platform for isolating cancer cells with high efficiency in processing complex cellular fluids, with simplicity, sensitivity, and throughput. This review summarizes recent methods of CTC isolation and analysis, as well as their applications in clinical studies. © 2016 Elsevier Inc. All rights reserved.
2002-01-01
their expression profile and for classification of cells into tumerous and non- tumerous classes. Then we will present a parallel tree method for... cancerous cells. We will use the same dataset and use tree structured classifiers with multi-resolution analysis for classifying cancerous from non- cancerous ...cells. We have the expressions of 4096 genes from 98 different cell types. Of these 98, 72 are cancerous while 26 are non- cancerous . We are interested
Wen, Yanhua; Wei, Yanjun; Zhang, Shumei; Li, Song; Liu, Hongbo; Wang, Fang; Zhao, Yue; Zhang, Dongwei; Zhang, Yan
2017-05-01
Tumour heterogeneity describes the coexistence of divergent tumour cell clones within tumours, which is often caused by underlying epigenetic changes. DNA methylation is commonly regarded as a significant regulator that differs across cells and tissues. In this study, we comprehensively reviewed research progress on estimating of tumour heterogeneity. Bioinformatics-based analysis of DNA methylation has revealed the evolutionary relationships between breast cancer cell lines and tissues. Further analysis of the DNA methylation profiles in 33 breast cancer-related cell lines identified cell line-specific methylation patterns. Next, we reviewed the computational methods in inferring clonal evolution of tumours from different perspectives and then proposed a deconvolution strategy for modelling cell subclonal populations dynamics in breast cancer tissues based on DNA methylation. Further analysis of simulated cancer tissues and real cell lines revealed that this approach exhibits satisfactory performance and relative stability in estimating the composition and proportions of cellular subpopulations. The application of this strategy to breast cancer individuals of the Cancer Genome Atlas's identified different cellular subpopulations with distinct molecular phenotypes. Moreover, the current and potential future applications of this deconvolution strategy to clinical breast cancer research are discussed, and emphasis was placed on the DNA methylation-based recognition of intra-tumour heterogeneity. The wide use of these methods for estimating heterogeneity to further clinical cohorts will improve our understanding of neoplastic progression and the design of therapeutic interventions for treating breast cancer and other malignancies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
DNA methylation markers for diagnosis and prognosis of common cancers
Hao, Xiaoke; Luo, Huiyan; Krawczyk, Michal; Wei, Wei; Wang, Wenqiu; Wang, Juan; Flagg, Ken; Hou, Jiayi; Zhang, Heng; Yi, Shaohua; Jafari, Maryam; Lin, Danni; Chung, Christopher; Caughey, Bennett A.; Li, Gen; Dhar, Debanjan; Shi, William; Zheng, Lianghong; Hou, Rui; Zhu, Jie; Zhao, Liang; Fu, Xin; Zhang, Edward; Zhang, Charlotte; Zhu, Jian-Kang; Karin, Michael; Xu, Rui-Hua; Zhang, Kang
2017-01-01
The ability to identify a specific cancer using minimally invasive biopsy holds great promise for improving the diagnosis, treatment selection, and prediction of prognosis in cancer. Using whole-genome methylation data from The Cancer Genome Atlas (TCGA) and machine learning methods, we evaluated the utility of DNA methylation for differentiating tumor tissue and normal tissue for four common cancers (breast, colon, liver, and lung). We identified cancer markers in a training cohort of 1,619 tumor samples and 173 matched adjacent normal tissue samples. We replicated our findings in a separate TCGA cohort of 791 tumor samples and 93 matched adjacent normal tissue samples, as well as an independent Chinese cohort of 394 tumor samples and 324 matched adjacent normal tissue samples. The DNA methylation analysis could predict cancer versus normal tissue with more than 95% accuracy in these three cohorts, demonstrating accuracy comparable to typical diagnostic methods. This analysis also correctly identified 29 of 30 colorectal cancer metastases to the liver and 32 of 34 colorectal cancer metastases to the lung. We also found that methylation patterns can predict prognosis and survival. We correlated differential methylation of CpG sites predictive of cancer with expression of associated genes known to be important in cancer biology, showing decreased expression with increased methylation, as expected. We verified gene expression profiles in a mouse model of hepatocellular carcinoma. Taken together, these findings demonstrate the utility of methylation biomarkers for the molecular characterization of cancer, with implications for diagnosis and prognosis. PMID:28652331
¹H NMR-based metabolic profiling of human rectal cancer tissue
2013-01-01
Background Rectal cancer is one of the most prevalent tumor types. Understanding the metabolic profile of rectal cancer is important for developing therapeutic approaches and molecular diagnosis. Methods Here, we report a metabonomics profiling of tissue samples on a large cohort of human rectal cancer subjects (n = 127) and normal controls (n = 43) using 1H nuclear magnetic resonance (1H NMR) based metabonomics assay, which is a highly sensitive and non-destructive method for the biomarker identification in biological systems. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal projection to latent structure with discriminant analysis (OPLS-DA) were applied to analyze the 1H-NMR profiling data to identify the distinguishing metabolites of rectal cancer. Results Excellent separation was obtained and distinguishing metabolites were observed among the different stages of rectal cancer tissues (stage I = 35; stage II = 37; stage III = 37 and stage IV = 18) and normal controls. A total of 38 differential metabolites were identified, 16 of which were closely correlated with the stage of rectal cancer. The up-regulation of 10 metabolites, including lactate, threonine, acetate, glutathione, uracil, succinate, serine, formate, lysine and tyrosine, were detected in the cancer tissues. On the other hand, 6 metabolites, including myo-inositol, taurine, phosphocreatine, creatine, betaine and dimethylglycine were decreased in cancer tissues. These modified metabolites revealed disturbance of energy, amino acids, ketone body and choline metabolism, which may be correlated with the progression of human rectal cancer. Conclusion Our findings firstly identify the distinguishing metabolites in different stages of rectal cancer tissues, indicating possibility of the attribution of metabolites disturbance to the progression of rectal cancer. The altered metabolites may be as potential biomarkers, which would provide a promising molecular diagnostic approach for clinical diagnosis of human rectal cancer. The role and underlying mechanism of metabolites in rectal cancer progression are worth being further investigated. PMID:24138801
Web-TCGA: an online platform for integrated analysis of molecular cancer data sets.
Deng, Mario; Brägelmann, Johannes; Schultze, Joachim L; Perner, Sven
2016-02-06
The Cancer Genome Atlas (TCGA) is a pool of molecular data sets publicly accessible and freely available to cancer researchers anywhere around the world. However, wide spread use is limited since an advanced knowledge of statistics and statistical software is required. In order to improve accessibility we created Web-TCGA, a web based, freely accessible online tool, which can also be run in a private instance, for integrated analysis of molecular cancer data sets provided by TCGA. In contrast to already available tools, Web-TCGA utilizes different methods for analysis and visualization of TCGA data, allowing users to generate global molecular profiles across different cancer entities simultaneously. In addition to global molecular profiles, Web-TCGA offers highly detailed gene and tumor entity centric analysis by providing interactive tables and views. As a supplement to other already available tools, such as cBioPortal (Sci Signal 6:pl1, 2013, Cancer Discov 2:401-4, 2012), Web-TCGA is offering an analysis service, which does not require any installation or configuration, for molecular data sets available at the TCGA. Individual processing requests (queries) are generated by the user for mutation, methylation, expression and copy number variation (CNV) analyses. The user can focus analyses on results from single genes and cancer entities or perform a global analysis (multiple cancer entities and genes simultaneously).
Breitbart, Eckhard; Köberlein-Neu, Juliane
2017-01-01
Introduction Occurring from ultraviolet radiation combined with impairing ozone levels, uncritical sun exposure and use of tanning beds an increasing number of people are affected by different types of skin cancer. But preventive interventions like skin cancer screening are still missing the evidence for effectiveness and therefore are criticised. Fundamental for an appropriate course of action is to approach the defined parameters as measures for effectiveness critically. A prerequisite should be the critical application of used parameter that are defined as measures for effectiveness. This research seeks to establish, through the available literature, the effects and conditions that prove the effectiveness of prevention strategies in skin cancer. Method and analysis A mixed-method approach is employed to combine quantitative to qualitative methods and answer what effects can display effectiveness considering time horizon, perspective and organisational level and what are essential and sufficient conditions to prove effectiveness and cost-effectiveness in skin cancer prevention strategies. A systematic review will be performed to spot studies from any design and assess the data quantitatively and qualitatively. Included studies from each key question will be summarised by characteristics like population, intervention, comparison, outcomes, study design, endpoints, effect estimator and so on. Beside statistical relevancies for a systematic review the qualitative method of qualitative comparative analysis (QCA) will be performed. The estimated outcomes from this review and QCA are the accomplishment and absence of effects that are appropriate for application in effectiveness assessments and further cost-effectiveness assessment. Ethics and dissemination Formal ethical approval is not required as primary data will not be collected. Trial registration number International Prospective Register for Systematic Reviews number CRD42017053859. PMID:28877950
2009-01-01
Background Gastric cancer is the third most common malignancy affecting the general population worldwide. Aberrant activation of KRAS is a key factor in the development of many types of tumor, however, oncogenic mutations of KRAS are infrequent in gastric cancer. We have developed a novel quantitative method of analysis of DNA copy number, termed digital genome scanning (DGS), which is based on the enumeration of short restriction fragments, and does not involve PCR or hybridization. In the current study, we used DGS to survey copy-number alterations in gastric cancer cells. Methods DGS of gastric cancer cell lines was performed using the sequences of 5000 to 15000 restriction fragments. We screened 20 gastric cancer cell lines and 86 primary gastric tumors for KRAS amplification by quantitative PCR, and investigated KRAS amplification at the DNA, mRNA and protein levels by mutational analysis, real-time PCR, immunoblot analysis, GTP-RAS pull-down assay and immunohistochemical analysis. The effect of KRAS knock-down on the activation of p44/42 MAP kinase and AKT and on cell growth were examined by immunoblot and colorimetric assay, respectively. Results DGS analysis of the HSC45 gastric cancer cell line revealed the amplification of a 500-kb region on chromosome 12p12.1, which contains the KRAS gene locus. Amplification of the KRAS locus was detected in 15% (3/20) of gastric cancer cell lines (8–18-fold amplification) and 4.7% (4/86) of primary gastric tumors (8–50-fold amplification). KRAS mutations were identified in two of the three cell lines in which KRAS was amplified, but were not detected in any of the primary tumors. Overexpression of KRAS protein correlated directly with increased KRAS copy number. The level of GTP-bound KRAS was elevated following serum stimulation in cells with amplified wild-type KRAS, but not in cells with amplified mutant KRAS. Knock-down of KRAS in gastric cancer cells that carried amplified wild-type KRAS resulted in the inhibition of cell growth and suppression of p44/42 MAP kinase and AKT activity. Conclusion Our study highlights the utility of DGS for identification of copy-number alterations. Using DGS, we identified KRAS as a gene that is amplified in human gastric cancer. We demonstrated that gene amplification likely forms the molecular basis of overactivation of KRAS in gastric cancer. Additional studies using a larger cohort of gastric cancer specimens are required to determine the diagnostic and therapeutic implications of KRAS amplification and overexpression. PMID:19545448
Value of circulating cell-free DNA analysis as a diagnostic tool for breast cancer: a meta-analysis
Ma, Xuelei; Zhang, Jing; Hu, Xiuying
2017-01-01
Objectives The aim of this study was to systematically evaluate the diagnostic value of cell free DNA (cfDNA) for breast cancer. Results Among 308 candidate articles, 25 with relevant diagnostic screening qualified for final analysis. The mean sensitivity, specificity and area under the curve (AUC) of SROC plots for 24 studies that distinguished breast cancer patients from healthy controls were 0.70, 0.87, and 0.9314, yielding a DOR of 32.31. When analyzed in subgroups, the 14 quantitative studies produced sensitivity, specificity, AUC, and a DOR of 0.78, 0.83, 0.9116, and 24.40. The 10 qualitative studies produced 0.50, 0.98, 0.9919, and 68.45. For 8 studies that distinguished malignant breast cancer from benign diseases, the specificity, sensitivity, AUC and DOR were 0.75, 0.79, 0.8213, and 9.49. No covariate factors had a significant correlation with relative DOR. Deek's funnel plots indicated an absence of publication bias. Materials and Methods Databases were searched for studies involving the use of cfDNA to diagnose breast cancer. The studies were analyzed to determine sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and the summary receiver operating characteristic (SROC). Covariates were evaluated for effect on relative DOR. Deek's Funnel plots were generated to measure publication bias. Conclusions Our analysis suggests a promising diagnostic potential of using cfDNA for breast cancer screening, but this diagnostic method is not yet independently sufficient. Further work refining qualitative cfDNA assays will improve the correct diagnosis of breast cancers. PMID:28460452
Azar, Farbod Ebadifard; Azami-Aghdash, Saber; Pournaghi-Azar, Fatemeh; Mazdaki, Alireza; Rezapour, Aziz; Ebrahimi, Parvin; Yousefzadeh, Negar
2017-06-19
Due to extensive literature in the field of lung cancer and their heterogeneous results, the aim of this study was to systematically review of systematic reviews studies which reviewed the cost-effectiveness of various lung cancer screening and treatment methods. In this systematic review of systematic reviews study, required data were collected searching the following key words which selected from Mesh: "lung cancer", "lung oncology", "lung Carcinoma", "lung neoplasm", "lung tumors", "cost- effectiveness", "systematic review" and "Meta-analysis". The following databases were searched: PubMed, Cochrane Library electronic databases, Google Scholar, and Scopus. Two reviewers (RA and A-AS) evaluated the articles according to the checklist of "assessment of multiple systematic reviews" (AMSTAR) tool. Overall, information of 110 papers was discussed in eight systematic reviews. Authors focused on cost-effectiveness of lung cancer treatments in five systematic reviews. Targeted therapy options (bevacizumab, Erlotinib and Crizotinib) show an acceptable cost-effectiveness. Results of three studies failed to show cost-effectiveness of screening methods. None of the studies had used the meta-analysis method. The Quality of Health Economic Studies (QHES) tool and Drummond checklist were mostly used in assessing the quality of articles. Most perspective was related to the Payer (64 times) and the lowest was related to Social (11times). Most cases referred to Incremental analysis (82%) and also the lowest point of referral was related to Discounting (in 49% of the cases). The average quality score of included studies was calculated 9.2% from 11. Targeted therapy can be an option for the treatment of lung cancer. Evaluation of the cost-effectiveness of computerized tomographic colonography (CTC) in lung cancer screening is recommended. The perspective of the community should be more taken into consideration in studies of cost-effectiveness. Paying more attention to the topic of Discounting will be necessary in the studies.
Trimarchi, Michael P.; Yan, Pearlly; Groden, Joanna; Bundschuh, Ralf; Goodfellow, Paul J.
2017-01-01
Background DNA methylation is a stable epigenetic mark that is frequently altered in tumors. DNA methylation features are attractive biomarkers for disease states given the stability of DNA methylation in living cells and in biologic specimens typically available for analysis. Widespread accumulation of methylation in regulatory elements in some cancers (specifically the CpG island methylator phenotype, CIMP) can play an important role in tumorigenesis. High resolution assessment of CIMP for the entire genome, however, remains cost prohibitive and requires quantities of DNA not available for many tissue samples of interest. Genome-wide scans of methylation have been undertaken for large numbers of tumors, and higher resolution analyses for a limited number of cancer specimens. Methods for analyzing such large datasets and integrating findings from different studies continue to evolve. An approach for comparison of findings from a genome-wide assessment of the methylated component of tumor DNA and more widely applied methylation scans was developed. Methods Methylomes for 76 primary endometrial cancer and 12 normal endometrial samples were generated using methylated fragment capture and second generation sequencing, MethylCap-seq. Publically available Infinium HumanMethylation 450 data from The Cancer Genome Atlas (TCGA) were compared to MethylCap-seq data. Results Analysis of methylation in promoter CpG islands (CGIs) identified a subset of tumors with a methylator phenotype. We used a two-stage approach to develop a 13-region methylation signature associated with a “hypermethylator state.” High level methylation for the 13-region methylation signatures was associated with mismatch repair deficiency, high mutation rate, and low somatic copy number alteration in the TCGA test set. In addition, the signature devised showed good agreement with previously described methylation clusters devised by TCGA. Conclusion We identified a methylation signature for a “hypermethylator phenotype” in endometrial cancer and developed methods that may prove useful for identifying extreme methylation phenotypes in other cancers. PMID:28278225
Enrichment and single-cell analysis of circulating tumor cells
Song, Yanling; Tian, Tian; Shi, Yuanzhi; Liu, Wenli; Zou, Yuan; Khajvand, Tahereh; Wang, Sili; Zhu, Zhi
2017-01-01
Up to 90% of cancer-related deaths are caused by metastatic cancer. Circulating tumor cells (CTCs), a type of cancer cell that spreads through the blood after detaching from a solid tumor, are essential for the establishment of distant metastasis for a given cancer. As a new type of liquid biopsy, analysis of CTCs offers the possibility to avoid invasive tissue biopsy procedures with practical implications for diagnostics. The fundamental challenges of analyzing and profiling CTCs are the extremely low abundances of CTCs in the blood and the intrinsic heterogeneity of CTCs. Various technologies have been proposed for the enrichment and single-cell analysis of CTCs. This review aims to provide in-depth insights into CTC analysis, including various techniques for isolation of CTCs with capture methods based on physical and biochemical principles, and single-cell analysis of CTCs at the genomic, proteomic and phenotypic level, as well as current developmental trends and promising research directions. PMID:28451298
Brenner, Hermann; Jansen, Lina
2016-02-01
Monitoring cancer survival is a key task of cancer registries, but timely disclosure of progress in long-term survival remains a challenge. We introduce and evaluate a novel method, denoted "boomerang method," for deriving more up-to-date estimates of long-term survival. We applied three established methods (cohort, complete, and period analysis) and the boomerang method to derive up-to-date 10-year relative survival of patients diagnosed with common solid cancers and hematological malignancies in the United States. Using the Surveillance, Epidemiology and End Results 9 database, we compared the most up-to-date age-specific estimates that might have been obtained with the database including patients diagnosed up to 2001 with 10-year survival later observed for patients diagnosed in 1997-2001. For cancers with little or no increase in survival over time, the various estimates of 10-year relative survival potentially available by the end of 2001 were generally rather similar. For malignancies with strongly increasing survival over time, including breast and prostate cancer and all hematological malignancies, the boomerang method provided estimates that were closest to later observed 10-year relative survival in 23 of the 34 groups assessed. The boomerang method can substantially improve up-to-dateness of long-term cancer survival estimates in times of ongoing improvement in prognosis. Copyright © 2016 Elsevier Inc. All rights reserved.
Morphological feature extraction for the classification of digital images of cancerous tissues.
Thiran, J P; Macq, B
1996-10-01
This paper presents a new method for automatic recognition of cancerous tissues from an image of a microscopic section. Based on the shape and the size analysis of the observed cells, this method provides the physician with nonsubjective numerical values for four criteria of malignancy. This automatic approach is based on mathematical morphology, and more specifically on the use of Geodesy. This technique is used first to remove the background noise from the image and then to operate a segmentation of the nuclei of the cells and an analysis of their shape, their size, and their texture. From the values of the extracted criteria, an automatic classification of the image (cancerous or not) is finally operated.
Multiview boosting digital pathology analysis of prostate cancer.
Kwak, Jin Tae; Hewitt, Stephen M
2017-04-01
Various digital pathology tools have been developed to aid in analyzing tissues and improving cancer pathology. The multi-resolution nature of cancer pathology, however, has not been fully analyzed and utilized. Here, we develop an automated, cooperative, and multi-resolution method for improving prostate cancer diagnosis. Digitized tissue specimen images are obtained from 5 tissue microarrays (TMAs). The TMAs include 70 benign and 135 cancer samples (TMA1), 74 benign and 89 cancer samples (TMA2), 70 benign and 115 cancer samples (TMA3), 79 benign and 82 cancer samples (TMA4), and 72 benign and 86 cancer samples (TMA5). The tissue specimen images are segmented using intensity- and texture-based features. Using the segmentation results, a number of morphological features from lumens and epithelial nuclei are computed to characterize tissues at different resolutions. Applying a multiview boosting algorithm, tissue characteristics, obtained from differing resolutions, are cooperatively combined to achieve accurate cancer detection. In segmenting prostate tissues, the multiview boosting method achieved≥ 0.97 AUC using TMA1. For detecting cancers, the multiview boosting method achieved an AUC of 0.98 (95% CI: 0.97-0.99) as trained on TMA2 and tested on TMA3, TMA4, and TMA5. The proposed method was superior to single-view approaches, utilizing features from a single resolution or merging features from all the resolutions. Moreover, the performance of the proposed method was insensitive to the choice of the training dataset. Trained on TMA3, TMA4, and TMA5, the proposed method obtained an AUC of 0.97 (95% CI: 0.96-0.98), 0.98 (95% CI: 0.96-0.99), and 0.97 (95% CI: 0.96-0.98), respectively. The multiview boosting method is capable of integrating information from multiple resolutions in an effective and efficient fashion and identifying cancers with high accuracy. The multiview boosting method holds a great potential for improving digital pathology tools and research. Copyright © 2017 Elsevier B.V. All rights reserved.
Tataw, David Besong; Ekúndayò, Olúgbémiga T
2017-01-01
This article reports on the use of sequential and integrated mixed-methods approach in a focused population and small-area analysis. The study framework integrates focus groups, survey research, and community engagement strategies in a search for evidence related to prostate cancer screening services utilization as a component of cancer prevention planning in a marginalized African American community in the United States. Research and data analysis methods are synthesized by aggregation, configuration, and interpretive analysis. The results of synthesis show that qualitative and quantitative data validate and complement each other in advancing our knowledge of population characteristics, variable associations, the complex context in which variables exist, and the best options for prevention and service planning. Synthesis of findings and interpretive analysis provided two important explanations which seemed inexplicable in regression outputs: (a) Focus group data on the limitations of the church as an educational source explain the negative association between preferred educational channels and screening behavior found in quantitative analysis. (b) Focus group data on unwelcoming provider environments explain the inconsistent relationship between knowledge of local sites and screening services utilization found in quantitative analysis. The findings suggest that planners, evaluators, and scientists should grow their planning and evaluation evidence from the community they serve.
Crowdsourcing for translational research: analysis of biomarker expression using cancer microarrays
Lawson, Jonathan; Robinson-Vyas, Rupesh J; McQuillan, Janette P; Paterson, Andy; Christie, Sarah; Kidza-Griffiths, Matthew; McDuffus, Leigh-Anne; Moutasim, Karwan A; Shaw, Emily C; Kiltie, Anne E; Howat, William J; Hanby, Andrew M; Thomas, Gareth J; Smittenaar, Peter
2017-01-01
Background: Academic pathology suffers from an acute and growing lack of workforce resource. This especially impacts on translational elements of clinical trials, which can require detailed analysis of thousands of tissue samples. We tested whether crowdsourcing – enlisting help from the public – is a sufficiently accurate method to score such samples. Methods: We developed a novel online interface to train and test lay participants on cancer detection and immunohistochemistry scoring in tissue microarrays. Lay participants initially performed cancer detection on lung cancer images stained for CD8, and we measured how extending a basic tutorial by annotated example images and feedback-based training affected cancer detection accuracy. We then applied this tutorial to additional cancer types and immunohistochemistry markers – bladder/ki67, lung/EGFR, and oesophageal/CD8 – to establish accuracy compared with experts. Using this optimised tutorial, we then tested lay participants' accuracy on immunohistochemistry scoring of lung/EGFR and bladder/p53 samples. Results: We observed that for cancer detection, annotated example images and feedback-based training both improved accuracy compared with a basic tutorial only. Using this optimised tutorial, we demonstrate highly accurate (>0.90 area under curve) detection of cancer in samples stained with nuclear, cytoplasmic and membrane cell markers. We also observed high Spearman correlations between lay participants and experts for immunohistochemistry scoring (0.91 (0.78, 0.96) and 0.97 (0.91, 0.99) for lung/EGFR and bladder/p53 samples, respectively). Conclusions: These results establish crowdsourcing as a promising method to screen large data sets for biomarkers in cancer pathology research across a range of cancers and immunohistochemical stains. PMID:27959886
Wang, Judy Huei-yu; Adams, Inez F.; Tucker-Seeley, Reginald; Gomez, Scarlett Lin; Allen, Laura; Huang, Ellen; Wang, Yiru; Pasick, Rena J.
2013-01-01
Purpose Cancer-related stress is heavily influenced by culture. This study explored similarities and differences in survivorship care concerns among Chinese American and Non-Hispanic White (NHW) breast cancer survivors. Methods A sequential, mixed-method design (inductive/qualitative research-phase I and deductive/quantitative research-phase II) was employed. Eligible women identified from the Greater Bay Area Cancer Registry were age ≥21, diagnosed with stage 0-IIa breast cancer between 2006–2011, and had no recurrence or other cancers. In phase I, we conducted 4 Chinese (n=19) and 4 NHW (n=22) focus groups, and 31 individual telephone interviews (18 Chinese immigrants, 7 Chinese US-born, and 6 NHW). Content analysis was conducted to examine qualitative data. In phase II, another 296 survivors (148 NHW age-matched to 148 Chinese cases) completed a cross-sectional survey. Descriptive statistics and linear regression analysis were conducted to examine quantitative data. Results Qualitative data revealed “socioeconomic wellbeing” (SWB) as a dominant survivorship concern, which was operationalized as a cancer survivor’s perceived economic and social resources available to access care. Quantitative data showed that low-acculturated Chinese immigrants reported the poorest SWB, controlling for covariates. Highly-acculturated Chinese immigrants and the US-born Chinese/NHW group reported similar SWB. Women who had low income levels or chemotherapy had poorer SWB. Conclusions SWB emerged as an important aspect of breast cancer survivorship. Immigration stress, cancer care costs, and cultural values all contributed to immigrants’ socioeconomic distress. Immigrant and US-born breast cancer survivors experienced different socioeconomic circumstances and well-being following treatment. Our findings warrant further investigation of socioeconomic distress and survivorship outcomes. PMID:23591710
Nam, Seungyoon
2017-04-01
Cancer transcriptome analysis is one of the leading areas of Big Data science, biomarker, and pharmaceutical discovery, not to forget personalized medicine. Yet, cancer transcriptomics and postgenomic medicine require innovation in bioinformatics as well as comparison of the performance of available algorithms. In this data analytics context, the value of network generation and algorithms has been widely underscored for addressing the salient questions in cancer pathogenesis. Analysis of cancer trancriptome often results in complicated networks where identification of network modularity remains critical, for example, in delineating the "druggable" molecular targets. Network clustering is useful, but depends on the network topology in and of itself. Notably, the performance of different network-generating tools for network cluster (NC) identification has been little investigated to date. Hence, using gastric cancer (GC) transcriptomic datasets, we compared two algorithms for generating pathway versus gene regulatory network-based NCs, showing that the pathway-based approach better agrees with a reference set of cancer-functional contexts. Finally, by applying pathway-based NC identification to GC transcriptome datasets, we describe cancer NCs that associate with candidate therapeutic targets and biomarkers in GC. These observations collectively inform future research on cancer transcriptomics, drug discovery, and rational development of new analysis tools for optimal harnessing of omics data.
The lived experience of men diagnosed with prostate cancer.
Krumwiede, Kelly A; Krumwiede, Norma
2012-09-01
To investigate the lived experience of prostate cancer from a patient perspective. Descriptive, qualitative. Community setting. 10 men with prostate cancer aged 62-70 years. A hermeneutic phenomenologic method using semistructured, open-ended questions addressing the lived experience. Phenomenology of praxis proposed by van Manen guided the data analysis and transformed personal experiences into disciplinary understanding. The use of van Manen's method of inquiry and analysis has contributed to the findings of the study by providing a way to explore the meaning of the lived experiences in an attempt to understand living with prostate cancer. Several themes were identified: living in the unknown, yearning to understand and know, struggling with unreliability of body, bearing the diagnosis of cancer, shifting priorities in the gap, and feeling comfort in the presence of others. Oncology nurses can use van Manen's four fundamental existentials-lived space (spatiality), lived body (corporeality), lived time (temporality), and lived other (relationality)-to understand the lived experience of prostate cancer. Nurses have many opportunities to impact the lives of men diagnosed with prostate cancer, including diagnosis, management of physical integrity, management of psychosocial integrity, and providing education. Nurses may encourage men to describe their diagnosis story and illness experience to better understand the meaning of the prostate cancer experience and to provide appropriate nursing care.
Yamamoto, Tetsushi; Kudo, Mitsuhiro; Peng, Wei-Xia; Takata, Hideyuki; Takakura, Hideki; Teduka, Kiyoshi; Fujii, Takenori; Mitamura, Kuniko; Taga, Atsushi; Uchida, Eiji; Naito, Zenya
2016-10-01
Colorectal cancer (CRC) is one of the most common cancers worldwide, and many patients are already at an advanced stage when they are diagnosed. Therefore, novel biomarkers for early detection of colorectal cancer are required. In this study, we performed a global shotgun proteomic analysis using formalin-fixed and paraffin-embedded (FFPE) CRC tissue. We identified 84 candidate proteins whose expression levels were differentially expressed in cancer and non-cancer regions. A label-free semiquantitative method based on spectral counting and gene ontology (GO) analysis led to a total of 21 candidate proteins that could potentially be detected in blood. Validation studies revealed cyclophilin A, annexin A2, and aldolase A mRNA and protein expression levels were significantly higher in cancer regions than in non-cancer regions. Moreover, an in vitro study showed that secretion of aldolase A into the culture medium was clearly suppressed in CRC cells compared to normal colon epithelium. These findings suggest that decreased aldolase A in blood may be a novel biomarker for the early detection of CRC.
Amemiya, Kenji; Hirotsu, Yosuke; Goto, Taichiro; Nakagomi, Hiroshi; Mochizuki, Hitoshi; Oyama, Toshio; Omata, Masao
2016-12-01
Identifying genetic alterations in tumors is critical for molecular targeting of therapy. In the clinical setting, formalin-fixed paraffin-embedded (FFPE) tissue is usually employed for genetic analysis. However, DNA extracted from FFPE tissue is often not suitable for analysis because of its low levels and poor quality. Additionally, FFPE sample preparation is time-consuming. To provide early treatment for cancer patients, a more rapid and robust method is required for precision medicine. We present a simple method for genetic analysis, called touch imprint cytology combined with massively paralleled sequencing (touch imprint cytology [TIC]-seq), to detect somatic mutations in tumors. We prepared FFPE tissues and TIC specimens from tumors in nine lung cancer patients and one patient with breast cancer. We found that the quality and quantity of TIC DNA was higher than that of FFPE DNA, which requires microdissection to enrich DNA from target tissues. Targeted sequencing using a next-generation sequencer obtained sufficient sequence data using TIC DNA. Most (92%) somatic mutations in lung primary tumors were found to be consistent between TIC and FFPE DNA. We also applied TIC DNA to primary and metastatic tumor tissues to analyze tumor heterogeneity in a breast cancer patient, and showed that common and distinct mutations among primary and metastatic sites could be classified into two distinct histological subtypes. TIC-seq is an alternative and feasible method to analyze genomic alterations in tumors by simply touching the cut surface of specimens to slides. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gao, M; Fan, T; Duan, J
2015-06-15
Purpose: Prospectively assess the potential utility of texture analysis for differentiation of central cancer from atelectasis. Methods: 0 consecutive central lung cancer patients who were referred for CT imaging and PET-CT were enrolled. Radiotherapy doctor delineate the tumor and atelectasis according to the fusion imaging based on CT image and PET-CT image. The texture parameters (such as energy, correlation, sum average, difference average, difference entropy), were obtained respectively to quantitatively discriminate tumor and atelectasis based on gray level co-occurrence matrix (GLCM) Results: The texture analysis results showed that the parameters of correlation and sum average had an obviously statistical significance(P<0.05).more » Conclusion: the results of this study indicate that texture analysis may be useful for the differentiation of central lung cancer and atelectasis.« less
NASA Astrophysics Data System (ADS)
Chen, Xiwen; Huang, Zufang; Xi, Gangqin; Chen, Yongjian; Lin, Duo; Wang, Jing; Li, Zuanfang; Sun, Liqing; Chen, Jianxin; Chen, Rong
2012-03-01
Second-harmonic generation (SHG) is proved to be a high spatial resolution, large penetration depth and non-photobleaching method. In our study, SHG method was used to investigate the normal and cancerous thyroid tissue. For SHG imaging performance, system parameters were adjusted for high-contrast images acquisition. Each x-y image was recorded in pseudo-color, which matches the wavelength range in the visible spectrum. The acquisition time for a 512×512-pixels image was 1.57 sec; each acquired image was averaged four frames to improve the signal-to-noise ratio. Our results indicated that collagen presence as determined by counting the ratio of the SHG pixels over the whole pixels for normal and cancerous thyroid tissues were 0.48+/-0.05, 0.33+/-0.06 respectively. In addition, to quantitatively assess collagen-related changes, we employed GLCM texture analysis to the SHG images. Corresponding results showed that the correlation both fell off with distance in normal and cancerous group. Calculated value of Corr50 (the distance where the correlation crossed 50% of the initial correlation) indicated significant difference. This study demonstrates that SHG method can be used as a complementary tool in thyroid histopathology.
[Possibilities of the TruScreen for screening of precancer and cancer of the uterine cervix].
Zlatkov, V
2009-01-01
The classic approach of detection of pre-cancer and cancer of uterine cervix includes cytological examination, followed by colposcopy assessment of the detected cytological abnormalities. Real-time devices use in-vivo techniques for the measurement, computerized analysis and classifying of different types of cervical tissues. The aim of the present review is to present the technical characteristics and to discus the diagnostic possibilities of TruScreen-automated optical-electron system for cervical screening. The analysis of the presented in the literature diagnostic value of the method at different grades intraepithelial lesions shows that it has higher sensitivity (67-70%) and lower specificity (81%) in comparison to the Pap test with the following results (45-69% sensitivity and 95% specificity). This makes the method suitable for independent primary screening, as well as for adding the diagnostic assurance of the cytological method.
2005-01-01
Quantitative Analysis of Cancer Cell Migration in Gradients of EGF, HGF, and SDF-alpha Using a Microfluidic Chemotaxis Device The University of California...allowing for parallel analysis . Additionally, simple methods of localizing gels into microdevices are demonstrated. The device was characterized by...To overcome some of these drawbacks, several approaches have utilized free diffusion to produce gradients in static environ - ments.5-9 However
Kacen, Lea; Bakshy, Iris
2005-09-01
In this study, the authors examine a discourse between members of a cancer patients' self-help organization (CP-SHO) and oncological social workers (OSWs) on support groups for cancer patients. Eight OSWs and 8 CP-SHO volunteers served as the key research population. Using the interpretive-narrative approach to research, the authors apply a variety of data collection methods and a combination of data analysis methods: narrative analysis and discourse analysis. The findings point to the simultaneous existence of two institutional narratives for each organization, one internal and the other external. Discourse between the organizations takes place mainly at the external institutional narrative level, with each body maintaining the mistaken impression that the other's perception of reality is similar to its own (false consensus). In the meantime, the internal narratives that attest to the latent meaning of the discourse govern the interaction and prevent effective dialogue between the respective organizations.
Network-based machine learning and graph theory algorithms for precision oncology.
Zhang, Wei; Chien, Jeremy; Yong, Jeongsik; Kuang, Rui
2017-01-01
Network-based analytics plays an increasingly important role in precision oncology. Growing evidence in recent studies suggests that cancer can be better understood through mutated or dysregulated pathways or networks rather than individual mutations and that the efficacy of repositioned drugs can be inferred from disease modules in molecular networks. This article reviews network-based machine learning and graph theory algorithms for integrative analysis of personal genomic data and biomedical knowledge bases to identify tumor-specific molecular mechanisms, candidate targets and repositioned drugs for personalized treatment. The review focuses on the algorithmic design and mathematical formulation of these methods to facilitate applications and implementations of network-based analysis in the practice of precision oncology. We review the methods applied in three scenarios to integrate genomic data and network models in different analysis pipelines, and we examine three categories of network-based approaches for repositioning drugs in drug-disease-gene networks. In addition, we perform a comprehensive subnetwork/pathway analysis of mutations in 31 cancer genome projects in the Cancer Genome Atlas and present a detailed case study on ovarian cancer. Finally, we discuss interesting observations, potential pitfalls and future directions in network-based precision oncology.
Terahertz spectral unmixing based method for identifying gastric cancer
NASA Astrophysics Data System (ADS)
Cao, Yuqi; Huang, Pingjie; Li, Xian; Ge, Weiting; Hou, Dibo; Zhang, Guangxin
2018-02-01
At present, many researchers are exploring biological tissue inspection using terahertz time-domain spectroscopy (THz-TDS) techniques. In this study, based on a modified hard modeling factor analysis method, terahertz spectral unmixing was applied to investigate the relationships between the absorption spectra in THz-TDS and certain biomarkers of gastric cancer in order to systematically identify gastric cancer. A probability distribution and box plot were used to extract the distinctive peaks that indicate carcinogenesis, and the corresponding weight distributions were used to discriminate the tissue types. The results of this work indicate that terahertz techniques have the potential to detect different levels of cancer, including benign tumors and polyps.
The cancer transcriptome is shaped by genetic changes, variation in gene transcription, mRNA processing, editing and stability, and the cancer microbiome. Deciphering this variation and understanding its implications on tumorigenesis requires sophisticated computational analyses. Most RNA-Seq analyses rely on methods that first map short reads to a reference genome, and then compare them to annotated transcripts or assemble them. However, this strategy can be limited when the cancer genome is substantially different than the reference or for detecting sequences from the cancer microbiome.
[LAPAROSCOPIC NERVE-SPARING RADICAL HYSTERECTOMY IN CERVICAL CANCER].
Berlev, I V; Ulrikh, E A; Korolkova, E N; Ibragimov, Z N; Kashina, N O; Mikhailyuk, G I; Khadzhimba, A V; Urmancheeva, A F
2015-01-01
Cervical cancer is the most common cancer of the female reproductive system up to 20% of malignant tumors of the female genital organs. Surgery is the main method in treatment for local cervical cancer but postoperative complications often are associated with dysfunction of the pelvic organs. Some researchers focus their attention on the preservation of the pelvic innervation without loss of surgery's radicalism, which is represented in this survey. The paper presents the results of comparative analysis of 54 cases of surgical treatment for invasive cervical cancer.
Takahashi, Hiro; Aoyagi, Kazuhiko; Nakanishi, Yukihiro; Sasaki, Hiroki; Yoshida, Teruhiko; Honda, Hiroyuki
2006-07-01
Esophageal cancer is a well-known cancer with poorer prognosis than other cancers. An optimal and individualized treatment protocol based on accurate diagnosis is urgently needed to improve the treatment of cancer patients. For this purpose, it is important to develop a sophisticated algorithm that can manage a large amount of data, such as gene expression data from DNA microarrays, for optimal and individualized diagnosis. Marker gene selection is essential in the analysis of gene expression data. We have already developed a combination method of the use of the projective adaptive resonance theory and that of a boosted fuzzy classifier with the SWEEP operator denoted PART-BFCS. This method is superior to other methods, and has four features, namely fast calculation, accurate prediction, reliable prediction, and rule extraction. In this study, we applied this method to analyze microarray data obtained from esophageal cancer patients. A combination method of PART-BFCS and the U-test was also investigated. It was necessary to use a specific type of BFCS, namely, BFCS-1,2, because the esophageal cancer data were very complexity. PART-BFCS and PART-BFCS with the U-test models showed higher performances than two conventional methods, namely, k-nearest neighbor (kNN) and weighted voting (WV). The genes including CDK6 could be found by our methods and excellent IF-THEN rules could be extracted. The genes selected in this study have a high potential as new diagnosis markers for esophageal cancer. These results indicate that the new methods can be used in marker gene selection for the diagnosis of cancer patients.
Ellis, Matthew J; Gillette, Michael; Carr, Steven A; Paulovich, Amanda G; Smith, Richard D; Rodland, Karin K; Townsend, R Reid; Kinsinger, Christopher; Mesri, Mehdi; Rodriguez, Henry; Liebler, Daniel C
2013-10-01
The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium is applying the latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and the National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA, and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biologic insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods. ©2013 AACR.
Silva, C L; Passos, M; Câmara, J S
2011-01-01
Background: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. Methods: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxen-polydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 50°C for 60 min using samples with high ionic strengths (17% sodium chloride, w v−1) and under agitation. Results: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (P<0.05). A significant increase in the peak area of 2-methyl-3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. Conclusions: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved. PMID:22085842
A qualitative exploration of Malaysian cancer patients’ perceptions of cancer screening
2013-01-01
Background Despite the existence of different screening methods, the response to cancer screening is poor among Malaysians. The current study aims to examine cancer patients’ perceptions of cancer screening and early diagnosis. Methods A qualitative methodology was used to collect in-depth information from cancer patients. After obtaining institutional ethical approval, patients with different types and stages of cancer from the three major ethnic groups (Malay, Chinese and Indian) were approached. Twenty semi-structured interviews were conducted. All interviews were audiotaped, transcribed verbatim, and translated into English for thematic content analysis. Results Thematic content analysis yielded four major themes: awareness of cancer screening, perceived benefits of cancer screening, perceived barriers to cancer screening, and cues to action. The majority of respondents had never heard of cancer screening before their diagnosis. Some participants reported hearing about mammogram and Pap smear tests but did not undergo screening due to a lack of belief in personal susceptibility. Those who had negative results from screening prior to diagnosis perceived such tests as untrustworthy. Lack of knowledge and financial constraints were reported as barriers to cancer screening. Finally, numerous suggestions were given to improve screening behaviour among healthy individuals, including the role of mass media in disseminating the message ‘prevention is better than cure’. Conclusions Patients’ narratives revealed some significant issues that were in line with the Health Belief Model which could explain negative health behaviour. The description of the personal experiences of people with cancer could provide many cues to action for those who have never encountered this potentially deadly disease, if incorporated into health promotion activities. PMID:23331785
Lemlem, Semarya Berhe; Sinishaw, Worknish; Hailu, Mignote; Abebe, Mesfin; Aregay, Alemseged
2013-01-01
Background. According to the American Cancer Society, about 1.3 million women will be diagnosed with breast cancer annually worldwide and about 465,000 will die from the disease. In Ethiopia breast cancer is the second most often occurring cancer among women. Early diagnosis is especially important for breast cancer because the disease responds best to treatment before it has spread. Objective. To assess knowledge of breast cancer and screening methods among nurses in university hospitals. Method. This cross-sectional descriptive study used simple random sampling on sample of 281 nurses. Structured questionnaires draw out responses about knowledge and screening method of nurses in regard to breast cancer. Bivariate analysis was used principally and variables were then entered to multiple logistic regressions model for controlling the possible effect of confounders and the variables which have significant association were identified on the basis of OR, with 95% CI and P value. Results. The findings of this study revealed that only 156 (57.8%) of them were knowledgeable about breast cancer and its screening and 114 (42.2%) were not. Knowledge of breast cancer was found to be significantly associated with regular course in nursing, family history of respondents, and unit of work. Conclusion and Recommendation. The results of this study indicate that the knowledge of nurses is not satisfying and highlight the need to improve the content in the nursing curriculum and to undergo more workplace training in the area of breast cancer and screening methods. PMID:23986873
Zhang, Xiaojing; Zhu, Haixia; Wu, Xiaomin; Wang, Meilin; Gu, Dongying; Gong, Weida; Xu, Zhi; Tan, Yongfei; Gong, Yongling; Zhou, Jianwei; Tang, Cuiju; Tong, Na; Chen, Jinfei; Zhang, Zhengdong
2013-01-01
Recently, genetic polymorphism (rs3803662C>T) in TOX3 was reported to induce the risk of breast cancer. In this study, we hypothesized that rs3803662 could influence gastric cancer survival outcomes. With multiplex SNaPshot method, we genotyped TOX3 rs3803662 in 880 gastric patients with surgical resection. The association between genotype and survival outcomes was performed by the Kaplan-Meier method, Cox regression analysis models and the log-rank test. There was no association in the analyses of rs3803662 and survival of gastric cancer. However, the stratified analysis by histology showed that rs3803662 CT/TT genotype was associated with a significantly better survival for diffuse-type gastric cancer (log-rank p = 0.030, hazard ratio [HR] = 0.67, 95% confidence interval [CI] = 0.46-0.96), than the CC genotype. In addition, this favorable effect was especially obvious among gastric cancer patients with tumor size >5 cm, T3 and T4 depth of invasion, lymph node metastasis, no drinking, no distant metastasis, no chemotherapy and gastric cardia cancer. TOX3 rs3803662 might play an important role in the prognostic outcome and treatment of gastric cancer, especially perhaps further help in explaining the reduced risk of death associated with diffuse-type gastric cancer.
Ellrott, Kyle; Bailey, Matthew H; Saksena, Gordon; Covington, Kyle R; Kandoth, Cyriac; Stewart, Chip; Hess, Julian; Ma, Singer; Chiotti, Kami E; McLellan, Michael; Sofia, Heidi J; Hutter, Carolyn; Getz, Gad; Wheeler, David; Ding, Li
2018-03-28
The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
CASTIN: a system for comprehensive analysis of cancer-stromal interactome.
Komura, Daisuke; Isagawa, Takayuki; Kishi, Kazuki; Suzuki, Ryohei; Sato, Reiko; Tanaka, Mariko; Katoh, Hiroto; Yamamoto, Shogo; Tatsuno, Kenji; Fukayama, Masashi; Aburatani, Hiroyuki; Ishikawa, Shumpei
2016-11-09
Cancer microenvironment plays a vital role in cancer development and progression, and cancer-stromal interactions have been recognized as important targets for cancer therapy. However, identifying relevant and druggable cancer-stromal interactions is challenging due to the lack of quantitative methods to analyze whole cancer-stromal interactome. We present CASTIN (CAncer-STromal INteractome analysis), a novel framework for the evaluation of cancer-stromal interactome from RNA-Seq data using cancer xenograft models. For each ligand-receptor interaction which is derived from curated protein-protein interaction database, CASTIN summarizes gene expression profiles of cancer and stroma into three evaluation indices. These indices provide quantitative evaluation and comprehensive visualization of interactome, and thus enable to identify critical cancer-microenvironment interactions, which would be potential drug targets. We applied CASTIN to the dataset of pancreas ductal adenocarcinoma, and successfully characterized the individual cancer in terms of cancer-stromal relationships, and identified both well-known and less-characterized druggable interactions. CASTIN provides comprehensive view of cancer-stromal interactome and is useful to identify critical interactions which may serve as potential drug targets in cancer-microenvironment. CASTIN is available at: http://github.com/tmd-gpat/CASTIN .
NASA Astrophysics Data System (ADS)
Aytaç Korkmaz, Sevcan; Binol, Hamidullah
2018-03-01
Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.
Cancer Survivorship in the Age of YouTube and Social Media: A Narrative Analysis
Hunt, Yvonne; Folkers, Anna
2011-01-01
Background As evidenced by the increasing popularity of YouTube (www.youtube.com), personal narratives shared through social media are an area of rapid development in communication among cancer survivors. Identifying the thematic and linguistic characteristics of YouTube cancer stories can provide a better understanding of this naturally occurring communication channel and inform social media communication efforts aiming to use personal stories to reach individuals with serious illnesses. Objective The objective of our study was to provide an in-depth description of authentic personal cancer stories. Through a linguistically based narrative analysis of YouTube stories, the analysis explicates the common attributes of these narratives. Methods Informed by narrative theories, we conducted an iterative, bottom-up analysis of 35 YouTube videos identified by the search terms “cancer survivor” and “cancer stories”. A list of shared thematic and linguistic characteristics was identified and analyzed. Results A subnarrative on the cancer diagnosis was present in 86% (30/35) of the stories under analysis. These diagnostic narratives were characterized by dramatic tension, emotional engagement, markers of the loss of agency or control, depersonalized reference to the medical personnel, and the unexpectedness of a cancer diagnosis. The analysis highlights the themes of story authenticity and emotional engagement in this online communication medium. Conclusions Internet advances have enabled new and efficient exchange of personal stories, including the sharing of personal cancer experience among cancer survivors and their caregivers. The analytic results of this descriptive study point to the common characteristics of authentic cancer survivorship stories online. Furthermore, the results of this descriptive study may inform development of narrative-based communication, particularly in maintaining authenticity and emotional engagement. PMID:21247864
Spectral fiber sensors for cancer diagnostics in vitro
NASA Astrophysics Data System (ADS)
Artyushenko, V.; Schulte, F.; Zabarylo, U.; Berlien, H.-P.; Usenov, I.; Saeb Gilani, T.; Eichler, H.; Pieszczek, Ł.; Bogomolov, A.; Krause, H.; Minet, O.
2015-07-01
Cancer is one of the leading causes for morbidity and mortality worldwide. Therefore, efforts are concentrated on cancer detection in an early stage to enhance survival rates for cancer patients. A certain intraoperative navigation in the tumor border zone is also an essential task to lower the mortality rate after surgical treatment. Molecular spectroscopy methods proved to be powerful tools to differentiate cancerous and healthy tissue. Within our project comparison of different vibration spectroscopy methods were tested to select the better one or to reach synergy from their combination. One key aspect was in special fiber probe development for each technique. Using fiber optic probes in Raman, MIR and NIR spectroscopy is a very powerful method for non-invasive in vivo applications. Miniaturization of Raman probes was achieved by deposition of dielectric filters directly onto the silica fiber end surfaces. Raman, NIR and MIR spectroscopy were used to analyze samples from kidney tumors. The differentiation between cancer and healthy samples was successfully obtained by multivariate data analysis.
Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi
2015-01-01
Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy. PMID:26630674
Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi; Åkerfelt, Malin; Nees, Matthias
2015-01-01
Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.
A Bibliometric Analysis on Cancer Population Science with Topic Modeling.
Li, Ding-Cheng; Rastegar-Mojarad, Majid; Okamoto, Janet; Liu, Hongfang; Leichow, Scott
2015-01-01
Bibliometric analysis is a research method used in library and information science to evaluate research performance. It applies quantitative and statistical analyses to describe patterns observed in a set of publications and can help identify previous, current, and future research trends or focus. To better guide our institutional strategic plan in cancer population science, we conducted bibliometric analysis on publications of investigators currently funded by either Division of Cancer Preventions (DCP) or Division of Cancer Control and Population Science (DCCPS) at National Cancer Institute. We applied two topic modeling techniques: author topic modeling (AT) and dynamic topic modeling (DTM). Our initial results show that AT can address reasonably the issues related to investigators' research interests, research topic distributions and popularities. In compensation, DTM can address the evolving trend of each topic by displaying the proportion changes of key words, which is consistent with the changes of MeSH headings.
Eyal-Altman, Noah; Last, Mark; Rubin, Eitan
2017-01-17
Numerous publications attempt to predict cancer survival outcome from gene expression data using machine-learning methods. A direct comparison of these works is challenging for the following reasons: (1) inconsistent measures used to evaluate the performance of different models, and (2) incomplete specification of critical stages in the process of knowledge discovery. There is a need for a platform that would allow researchers to replicate previous works and to test the impact of changes in the knowledge discovery process on the accuracy of the induced models. We developed the PCM-SABRE platform, which supports the entire knowledge discovery process for cancer outcome analysis. PCM-SABRE was developed using KNIME. By using PCM-SABRE to reproduce the results of previously published works on breast cancer survival, we define a baseline for evaluating future attempts to predict cancer outcome with machine learning. We used PCM-SABRE to replicate previous work that describe predictive models of breast cancer recurrence, and tested the performance of all possible combinations of feature selection methods and data mining algorithms that was used in either of the works. We reconstructed the work of Chou et al. observing similar trends - superior performance of Probabilistic Neural Network (PNN) and logistic regression (LR) algorithms and inconclusive impact of feature pre-selection with the decision tree algorithm on subsequent analysis. PCM-SABRE is a software tool that provides an intuitive environment for rapid development of predictive models in cancer precision medicine.
Fuzzy method for pre-diagnosis of breast cancer from the Fine Needle Aspirate analysis
2012-01-01
Background Across the globe, breast cancer is one of the leading causes of death among women and, currently, Fine Needle Aspirate (FNA) with visual interpretation is the easiest and fastest biopsy technique for the diagnosis of this deadly disease. Unfortunately, the ability of this method to diagnose cancer correctly when the disease is present varies greatly, from 65% to 98%. This article introduces a method to assist in the diagnosis and second opinion of breast cancer from the analysis of descriptors extracted from smears of breast mass obtained by FNA, with the use of computational intelligence resources - in this case, fuzzy logic. Methods For data acquisition of FNA, the Wisconsin Diagnostic Breast Cancer Data (WDBC), from the University of California at Irvine (UCI) Machine Learning Repository, available on the internet through the UCI domain was used. The knowledge acquisition process was carried out by the extraction and analysis of numerical data of the WDBC and by interviews and discussions with medical experts. The PDM-FNA-Fuzzy was developed in four steps: 1) Fuzzification Stage; 2) Rules Base; 3) Inference Stage; and 4) Defuzzification Stage. Performance cross-validation was used in the tests, with three databases with gold pattern clinical cases randomly extracted from the WDBC. The final validation was held by medical specialists in pathology, mastology and general practice, and with gold pattern clinical cases, i.e. with known and clinically confirmed diagnosis. Results The Fuzzy Method developed provides breast cancer pre-diagnosis with 98.59% sensitivity (correct pre-diagnosis of malignancies); and 85.43% specificity (correct pre-diagnosis of benign cases). Due to the high sensitivity presented, these results are considered satisfactory, both by the opinion of medical specialists in the aforementioned areas and by comparison with other studies involving breast cancer diagnosis using FNA. Conclusions This paper presents an intelligent method to assist in the diagnosis and second opinion of breast cancer, using a fuzzy method capable of processing and sorting data extracted from smears of breast mass obtained by FNA, with satisfactory levels of sensitivity and specificity. The main contribution of the proposed method is the reduction of the variation hit of malignant cases when compared to visual interpretation currently applied in the diagnosis by FNA. While the MPD-FNA-Fuzzy features stable sensitivity at 98.59%, visual interpretation diagnosis provides a sensitivity variation from 65% to 98% (this track showing sensitivity levels below those considered satisfactory by medical specialists). Note that this method will be used in an Intelligent Virtual Environment to assist the decision-making (IVEMI), which amplifies its contribution. PMID:23122391
Zhou, Fangbin; Zhou, Yaying; Yang, Ming; Wen, Jinli; Dong, Jun; Tan, Wenyong
2018-01-01
Circulating endothelial cells (CECs) and their subpopulations could be potential novel biomarkers for various malignancies. However, reliable enumerable methods are warranted to further improve their clinical utility. This study aimed to optimize a flow cytometric method (FCM) assay for CECs and subpopulations in peripheral blood for patients with solid cancers. An FCM assay was used to detect and identify CECs. A panel of 60 blood samples, including 44 metastatic cancer patients and 16 healthy controls, were used in this study. Some key issues of CEC enumeration, including sample material and anticoagulant selection, optimal titration of antibodies, lysis/wash procedures of blood sample preparation, conditions of sample storage, sufficient cell events to enhance the signal, fluorescence-minus-one controls instead of isotype controls to reduce background noise, optimal selection of cell surface markers, and evaluating the reproducibility of our method, were integrated and investigated. Wilcoxon and Mann-Whitney U tests were used to determine statistically significant differences. In this validation study, we refined a five-color FCM method to detect CECs and their subpopulations in peripheral blood of patients with solid tumors. Several key technical issues regarding preanalytical elements, FCM data acquisition, and analysis were addressed. Furthermore, we clinically validated the utility of our method. The baseline levels of mature CECs, endothelial progenitor cells, and activated CECs were higher in cancer patients than healthy subjects ( P <0.01). However, there was no significant difference in resting CEC levels between healthy subjects and cancer patients ( P =0.193). We integrated and comprehensively addressed significant technical issues found in previously published assays and validated the reproducibility and sensitivity of our proposed method. Future work is required to explore the potential of our optimized method in clinical oncologic applications.
NASA Astrophysics Data System (ADS)
Rocha-Osornio, L. N.; Pichardo-Molina, J. L.; Barbosa-Garcia, O.; Frausto-Reyes, C.; Araujo-Andrade, C.; Huerta-Franco, R.; Gutiérrez-Juárez, G.
2008-02-01
Raman spectroscopy and Multivariate methods were used to study serum blood samples of control and breast cancer patients. Blood samples were obtained from 11 patients and 12 controls from the central region of Mexico. Our results show that principal component analysis is able to discriminate serum sample of breast cancer patients from those of control group, also the loading vectors of PCA plotted as a function of Raman shift shown which bands permitted to make the maximum discrimination between both groups of samples.
Rasul, V H; Cheraghi, M A; Behboodi Moqadam, Z
2015-01-01
Aim: This study was aimed to explore and describe the Kurdish women's perception of cervical cancer screening. Methods: A qualitative design based on a conventional content analysis approach. Purposive sampling was applied to 19 women chosen, who had a Pap smear or refused to have one. The study was performed in the Kurdistan Region, Iraq. Semi-structure din-depth individual interviews were carried out to collect data. Results: Four main themes including conflict, belief, and awareness about cervical cancer screening and socio-cultural factors emerged during data analysis Conclusions: Cervical cancer has a high mortality rate in the developing countries. However, only a few Kurdish women participated in the cervical cancer screening in the Kurdistan Region, Iraq. Understanding the factors associated with the women's perception of cervical cancer could guide future educational planning and clinical interventions improve the cervical cancer screening.
Rasul, VH; Cheraghi, MA; Behboodi Moqadam, Z
2015-01-01
Aim:This study was aimed to explore and describe the Kurdish women’s perception of cervical cancer screening. Methods: A qualitative design based on a conventional content analysis approach. Purposive sampling was applied to 19 women chosen, who had a Pap smear or refused to have one. The study was performed in the Kurdistan Region, Iraq. Semi-structure din-depth individual interviews were carried out to collect data. Results: Four main themes including conflict, belief, and awareness about cervical cancer screening and socio-cultural factors emerged during data analysis Conclusions: Cervical cancer has a high mortality rate in the developing countries. However, only a few Kurdish women participated in the cervical cancer screening in the Kurdistan Region, Iraq. Understanding the factors associated with the women’s perception of cervical cancer could guide future educational planning and clinical interventions improve the cervical cancer screening. PMID:28255397
Heritable DNA methylation marks associated with susceptibility to breast cancer.
Joo, Jihoon E; Dowty, James G; Milne, Roger L; Wong, Ee Ming; Dugué, Pierre-Antoine; English, Dallas; Hopper, John L; Goldgar, David E; Giles, Graham G; Southey, Melissa C
2018-02-28
Mendelian-like inheritance of germline DNA methylation in cancer susceptibility genes has been previously reported. We aimed to scan the genome for heritable methylation marks associated with breast cancer susceptibility by studying 25 Australian multiple-case breast cancer families. Here we report genome-wide DNA methylation measured in 210 peripheral blood DNA samples provided by family members using the Infinium HumanMethylation450. We develop and apply a new statistical method to identify heritable methylation marks based on complex segregation analysis. We estimate carrier probabilities for the 1000 most heritable methylation marks based on family structure, and we use Cox proportional hazards survival analysis to identify 24 methylation marks with corresponding carrier probabilities significantly associated with breast cancer. We replicate an association with breast cancer risk for four of the 24 marks using an independent nested case-control study. Here, we report a novel approach for identifying heritable DNA methylation marks associated with breast cancer risk.
Rapid Detection Method for the Four Most Common CHEK2 Mutations Based on Melting Profile Analysis.
Borun, Pawel; Salanowski, Kacper; Godlewski, Dariusz; Walkowiak, Jaroslaw; Plawski, Andrzej
2015-12-01
CHEK2 is a tumor suppressor gene, and the mutations affecting the functionality of the protein product increase cancer risk in various organs. The elevated risk, in a significant percentage of cases, is determined by the occurrence of one of the four most common mutations in the CHEK2 gene, including c.470T>C (p.I157T), c.444+1G>A (IVS2+1G>A), c.1100delC, and c.1037+1538_1224+328del5395 (del5395). We have developed and validated a rapid and effective method for their detection based on high-resolution melting analysis and comparative-high-resolution melting, a novel approach enabling simultaneous detection of copy number variations. The analysis is performed in two polymerase chain reactions followed by melting analysis, without any additional reagents or handling other than that used in standard high-resolution melting. Validation of the method was conducted in a group of 103 patients with diagnosed breast cancer, a group of 240 unrelated patients with familial history of cancer associated with the CHEK2 gene mutations, and a 100-person control group. The results of the analyses for all three groups were fully consistent with the results from other methods. The method we have developed improves the identification of the CHEK2 mutation carriers, reduces the cost of such analyses, as well as facilitates their implementation. Along with the increased efficiency, the method maintains accuracy and reliability comparable to other more labor-consuming techniques.
The BioMedical Evidence Graph (BMEG) | Informatics Technology for Cancer Research (ITCR)
The BMEG is a Cancer Data integration Platform that utilizes methods collected from DREAM challenges and applied to large datasets, such as the TCGA, and makes them avalible for analysis using a high performance graph database
2011-01-01
Background Recent evidence has suggested that the capability of cancer to grow, propagate and relapse after therapy is dependent on a small subset of the cell population within the tumor, called cancer stem cells. Therefore, this subpopulation of cells needs to be targeted with different approaches by identification of unique stem-cell specific target antigens. One of the well known tumor antigens is the epithelial cell mucin MUC4, which is aberrantly expressed in ovarian cancer as compared to the normal ovary and plays a pivotal role in the aggressiveness and metastasis of ovarian cancer cells. In the present study, we aimed to analyze the cancer stem cell population in MUC4 overexpressed ovarian cancer cells. Methods MUC4 was ectopically overexpressed in SKOV3 ovarian cancer cells. Western blot analysis was performed for MUC4, HER2, CD133, ALDH1 and Shh expression in MUC4 overexpressed cells. Confocal analysis of MUC4, HER2 and CD133 was also done in the MUC4 overexpressed cells. CD133 and Hoechst33342 dye staining was used to analyze the cancer stem cell population via FACS method in SKOV3-MUC4 cells. Results MUC4 overexpressed SKOV3 cells showed an increased expression of HER2 compared to control cells. MUC4 overexpression leads to increased (0.1%) side population (SP) and CD133-positive cancer stem cells compared to the control cells. Interestingly, the tumor sphere type circular colony formation was observed only in the MUC4 overexpressed ovarian cancer cells. Furthermore, the cancer stem cell marker CD133 was expressed along with MUC4 in the isolated circular colonies as analyzed by both confocal and western blot analysis. HER2 and cancer stem cell specific marker ALDH1 along with Shh, a self-renewal marker, showed increased expression in the isolated circular colonies compared to MUC4-transfected cells. Conclusion These studies demonstrate that MUC4 overexpression leads to an enriched ovarian cancer stem cell population either directly or indirectly through HER2. In future, this study would be helpful for MUC4-directed therapy for the ovarian cancer stem cell population. PMID:21521521
Cooperberg, Matthew R; Ramakrishna, Naren R; Duff, Steven B; Hughes, Kathleen E; Sadownik, Sara; Smith, Joseph A; Tewari, Ashutosh K
2013-03-01
WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: Multiple treatment alternatives exist for localised prostate cancer, with few high-quality studies directly comparing their comparative effectiveness and costs. The present study is the most comprehensive cost-effectiveness analysis to date for localised prostate cancer, conducted with a lifetime horizon and accounting for survival, health-related quality-of-life, and cost impact of secondary treatments and other downstream events, as well as primary treatment choices. The analysis found minor differences, generally slightly favouring surgical methods, in quality-adjusted life years across treatment options. However, radiation therapy (RT) was consistently more expensive than surgery, and some alternatives, e.g. intensity-modulated RT for low-risk disease, were dominated - that is, both more expensive and less effective than competing alternatives. To characterise the costs and outcomes associated with radical prostatectomy (open, laparoscopic, or robot-assisted) and radiation therapy (RT: dose-escalated three-dimensional conformal RT, intensity-modulated RT, brachytherapy, or combination), using a comprehensive, lifetime decision analytical model. A Markov model was constructed to follow hypothetical men with low-, intermediate-, and high-risk prostate cancer over their lifetimes after primary treatment; probabilities of outcomes were based on an exhaustive literature search yielding 232 unique publications. In each Markov cycle, patients could have remission, recurrence, salvage treatment, metastasis, death from prostate cancer, and death from other causes. Utilities for each health state were determined, and disutilities were applied for complications and toxicities of treatment. Costs were determined from the USA payer perspective, with incorporation of patient costs in a sensitivity analysis. Differences across treatments in quality-adjusted life years across methods were modest, ranging from 10.3 to 11.3 for low-risk patients, 9.6-10.5 for intermediate-risk patients and 7.8-9.3 for high-risk patients. There were no statistically significant differences among surgical methods, which tended to be more effective than RT methods, with the exception of combined external beam + brachytherapy for high-risk disease. RT methods were consistently more expensive than surgical methods; costs ranged from $19 901 (robot-assisted prostatectomy for low-risk disease) to $50 276 (combined RT for high-risk disease). These findings were robust to an extensive set of sensitivity analyses. Our analysis found small differences in outcomes and substantial differences in payer and patient costs across treatment alternatives. These findings may inform future policy discussions about strategies to improve efficiency of treatment selection for localised prostate cancer. © 2012 BJU International.
A meta-analysis of interleukin-10-1082 promoter polymorphism associated with gastric cancer risk.
Ni, Peihua; Xu, Hong; Xue, Huiping; Lin, Bing; Lu, Yang
2012-04-01
We aimed to explore the role of allele A/G single nucleotide polymorphism (SNP) of gene Interleukin 10 (IL-10) promoter-1082 in the susceptibility to gastric cancer through a systematic review and meta-analysis. Each initially included article was scored for quality appraisal. Desirable data were extracted and registered into databases. Twenty studies were ultimately eligible for the meta-analysis of IL-10-1082 A/G SNP. We adopted the most probably appropriate genetic model (dominant model), with the combined group of GG-plus-GA genotypes compared with the AA genotype. Potential sources of heterogeneity were sought out via subgroup analyses and sensitivity analyses, and publication biases were estimated. Between IL-10-1082 GG-plus-GA genotypes with the risk of developing gastric cancer, statistically significant association could be noted with overall gastric cancer, being mainly in Asian subgroup, large sample subgroup, high quality subgroup, intestinal-type subgroup, cardia-type subgroup, and some genotyping method subgroups. Our meta-analysis indicates that IL-10-1082 GG-plus-GA genotypes are associated with the overall risk of developing gastric cancer and seem to be more susceptible to overall gastric cancer in Asian populations. IL-10-1082 GG-plus-GA genotypes are more associated with the pathologically intestinal-type gastric cancer or anatomically cardia-type gastric cancer.
A Meta-Analysis of Interleukin-10-1082 Promoter Polymorphism Associated with Gastric Cancer Risk
Ni, Peihua; Xu, Hong; Xue, Huiping; Lin, Bing
2012-01-01
We aimed to explore the role of allele A/G single nucleotide polymorphism (SNP) of gene Interleukin 10 (IL-10) promoter-1082 in the susceptibility to gastric cancer through a systematic review and meta-analysis. Each initially included article was scored for quality appraisal. Desirable data were extracted and registered into databases. Twenty studies were ultimately eligible for the meta-analysis of IL-10-1082 A/G SNP. We adopted the most probably appropriate genetic model (dominant model), with the combined group of GG-plus-GA genotypes compared with the AA genotype. Potential sources of heterogeneity were sought out via subgroup analyses and sensitivity analyses, and publication biases were estimated. Between IL-10-1082 GG-plus-GA genotypes with the risk of developing gastric cancer, statistically significant association could be noted with overall gastric cancer, being mainly in Asian subgroup, large sample subgroup, high quality subgroup, intestinal-type subgroup, cardia-type subgroup, and some genotyping method subgroups. Our meta-analysis indicates that IL-10-1082 GG-plus-GA genotypes are associated with the overall risk of developing gastric cancer and seem to be more susceptible to overall gastric cancer in Asian populations. IL-10-1082 GG-plus-GA genotypes are more associated with the pathologically intestinal-type gastric cancer or anatomically cardia-type gastric cancer. PMID:22335769
Zou, Xue; Zhou, Wenzhao; Lu, Yan; Shen, Chengyin; Hu, Zongtao; Wang, Hongzhi; Jiang, Haihe; Chu, Yannan
2016-11-01
Esophageal cancer is a prevalent malignancy. There is a considerable demand for developing a fast and noninvasive method to screen out the suspect esophageal cancer patients who may undergo further clinical diagnosis. The exhaled breathes from 29 esophageal cancer patients and 57 healthy people were directly measured using our home-made proton transfer reaction mass spectrometer (PTR-MS). Mann-Whitney U test and stepwise discriminant analysis were applied to identify the ions in the breath mass spectral data which can distinguish cancer cohort from healthy group. Receiver operating characteristics (ROC) analysis was also performed. Seven kinds of ions in the breath mass spectrum, viz., m/z 136, m/z 34, m/z 63, m/z 27, m/z 95, m/z 107 and m/z 45, have been found to distinguish between the esophageal cancer patients and healthy people with a sensitivity of 86.2% and a specificity of 89.5%, respectively. Compared with that from the healthy people, the breath mass spectra from esophageal cancer patients show that the mediant intensities of five kinds of ions were decrease and the rest two kinds of ions were increase. ROC analysis gave the area under the curve (AUC) of 0.943. This pilot study shows that the ionic characteristics of exhaled VOCs detected by PTR-MS may be used to differentiate between the esophageal cancer patients and the healthy people. Although the breath tests for more patients are needed to confirm such results, the present work indicates that the PTR-MS may be a promising method in the esophageal cancer screening. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.
Coyle, Kathryn; Carrier, Marc; Lazo-Langner, Alejandro; Shivakumar, Sudeep; Zarychanski, Ryan; Tagalakis, Vicky; Solymoss, Susan; Routhier, Nathalie; Douketis, James; Coyle, Douglas
2017-03-01
Unprovoked venous thromboembolism (VTE) can be the first manifestation of cancer. It is unclear if extensive screening for occult cancer including a comprehensive computed tomography (CT) scan of the abdomen/pelvis is cost-effective in this patient population. To assess the health care related costs, number of missed cancer cases and health related utility values of a limited screening strategy with and without the addition of a comprehensive CT scan of the abdomen/pelvis and to identify to what extent testing should be done in these circumstances to allow early detection of occult cancers. Cost effectiveness analysis using data that was collected alongside the SOME randomized controlled trial which compared an extensive occult cancer screening including a CT of the abdomen/pelvis to a more limited screening strategy in patients with a first unprovoked VTE, was used for the current analyses. Analyses were conducted with a one-year time horizon from a Canadian health care perspective. Primary analysis was based on complete cases, with sensitivity analysis using appropriate multiple imputation methods to account for missing data. Data from a total of 854 patients with a first unprovoked VTE were included in these analyses. The addition of a comprehensive CT scan was associated with higher costs ($551 CDN) with no improvement in utility values or number of missed cancers. Results were consistent when adopting multiple imputation methods. The addition of a comprehensive CT scan of the abdomen/pelvis for the screening of occult cancer in patients with unprovoked VTE is not cost effective, as it is both more costly and not more effective in detecting occult cancer. Copyright © 2017 Elsevier Ltd. All rights reserved.
Diagnostic performance and safety of a three-dimensional 14-core systematic biopsy method.
Takeshita, Hideki; Kawakami, Satoru; Numao, Noboru; Sakura, Mizuaki; Tatokoro, Manabu; Yamamoto, Shinya; Kijima, Toshiki; Komai, Yoshinobu; Saito, Kazutaka; Koga, Fumitaka; Fujii, Yasuhisa; Fukui, Iwao; Kihara, Kazunori
2015-03-01
To investigate the diagnostic performance and safety of a three-dimensional 14-core biopsy (3D14PBx) method, which is a combination of the transrectal six-core and transperineal eight-core biopsy methods. Between December 2005 and August 2010, 1103 men underwent 3D14PBx at our institutions and were analysed prospectively. Biopsy criteria included a PSA level of 2.5-20 ng/mL or abnormal digital rectal examination (DRE) findings, or both. The primary endpoint of the study was diagnostic performance and the secondary endpoint was safety. We applied recursive partitioning to the entire study cohort to delineate the unique contribution of each sampling site to overall and clinically significant cancer detection. Prostate cancer was detected in 503 of the 1103 patients (45.6%). Age, family history of prostate cancer, DRE, PSA, percentage of free PSA and prostate volume were associated with the positive biopsy results significantly and independently. Of the 503 cancers detected, 39 (7.8%) were clinically locally advanced (≥cT3a), 348 (69%) had a biopsy Gleason score (GS) of ≥7, and 463 (92%) met the definition of biopsy-based significant cancer. Recursive partitioning analysis showed that each sampling site contributed uniquely to both the overall and the biopsy-based significant cancer detection rate of the 3D14PBx method. The overall cancer-positive rate of each sampling site ranged from 14.5% in the transrectal far lateral base to 22.8% in the transrectal far lateral apex. As of August 2010, 210 patients (42%) had undergone radical prostatectomy, of whom 55 (26%) were found to have pathologically non-organ-confined disease, 174 (83%) had prostatectomy GS ≥7 and 185 (88%) met the definition of prostatectomy-based significant cancer. This is the first prospective analysis of the diagnostic performance of an extended biopsy method, which is a simplified version of the somewhat redundant super-extended three-dimensional 26-core biopsy. As expected, each sampling site uniquely contributed not only to overall cancer detection, but also to significant cancer detection. 3D14PBx is a feasible systematic biopsy method in men with PSA <20 ng/mL. © 2014 The Authors. BJU International © 2014 BJU International.
Feng, Wen; Li, Hong-Chang; Xu, Ke; Chen, Ya-Feng; Pan, Li-Yun; Mei, Yi; Cai, Han; Jiang, Yi-Ming; Chen, Teng; Feng, Dian-Xu
2016-08-01
SHC SH2-binding protein 1, a member of Src homolog and collagen homolog (Shc) family, has been recently identified in different contexts in unbiased screening assays. It has been reported to be over-expressed in several malignant cancers. Immunohistochemistry of SHCBP1 on 128 breast cancer tissues and adjacent normal tissues were used to evaluate the prognostic significance of SHCBP1. Survival analyses were performed by Kaplan-Meier method. CRISPR/CAS9 method was used to knockout SHCBP1 expression. CRISPR/CAS9 technology was used to knockout SHCBP1 in 2 breast cancer cell lines. MTT assay, BrdU assay, colony formation assay, cell cycle assay and apoptosis analysis in MCF-7 and MDA-MB-231 cell lines were carried out to evaluate the effects of SHCBP1 on breast cancer in vitro. Immunohistochemical analysis revealed SHCBP1 was significantly up-regulated in breast cancer tissues compared with adjacent normal tissues (82 of 128, 64%). Over-expressed SHCBP1 was correlated with advanced clinical stage and poorer survival. Ablation of SHCBP1 inhibited the proliferation in vitro. SHCBP1 knockout increased cyclin-dependent kinase inhibitor p21, and decreased the Cyclin B1 and CDK1. Our study suggests SHCBP1 is dysregulated expressed in breast cancer and plays a critical role in cancer progression, which can be a potential prognosis predictor of breast cancer. Copyright © 2016. Published by Elsevier B.V.
Visualization techniques for tongue analysis in traditional Chinese medicine
NASA Astrophysics Data System (ADS)
Pham, Binh L.; Cai, Yang
2004-05-01
Visual inspection of the tongue has been an important diagnostic method of Traditional Chinese Medicine (TCM). Clinic data have shown significant connections between various viscera cancers and abnormalities in the tongue and the tongue coating. Visual inspection of the tongue is simple and inexpensive, but the current practice in TCM is mainly experience-based and the quality of the visual inspection varies between individuals. The computerized inspection method provides quantitative models to evaluate color, texture and surface features on the tongue. In this paper, we investigate visualization techniques and processes to allow interactive data analysis with the aim to merge computerized measurements with human expert's diagnostic variables based on five-scale diagnostic conditions: Healthy (H), History Cancers (HC), History of Polyps (HP), Polyps (P) and Colon Cancer (C).
Pediatric Cancer Survivorship Research: Experience of the Childhood Cancer Survivor Study
Leisenring, Wendy M.; Mertens, Ann C.; Armstrong, Gregory T.; Stovall, Marilyn A.; Neglia, Joseph P.; Lanctot, Jennifer Q.; Boice, John D.; Whitton, John A.; Yasui, Yutaka
2009-01-01
The Childhood Cancer Survivor Study (CCSS) is a comprehensive multicenter study designed to quantify and better understand the effects of pediatric cancer and its treatment on later health, including behavioral and sociodemographic outcomes. The CCSS investigators have published more than 100 articles in the scientific literature related to the study. As with any large cohort study, high standards for methodologic approaches are imperative for valid and generalizable results. In this article we describe methodological issues of study design, exposure assessment, outcome validation, and statistical analysis. Methods for handling missing data, intrafamily correlation, and competing risks analysis are addressed; each with particular relevance to pediatric cancer survivorship research. Our goal in this article is to provide a resource and reference for other researchers working in the area of long-term cancer survivorship. PMID:19364957
Microarray Data Mining for Potential Selenium Targets in Chemoprevention of Prostate Cancer
ZHANG, HAITAO; DONG, YAN; ZHAO, HONGJUAN; BROOKS, JAMES D.; HAWTHORN, LESLEYANN; NOWAK, NORMA; MARSHALL, JAMES R.; GAO, ALLEN C.; IP, CLEMENT
2008-01-01
Background A previous clinical trial showed that selenium supplementation significantly reduced the incidence of prostate cancer. We report here a bioinformatics approach to gain new insights into selenium molecular targets that might be relevant to prostate cancer chemoprevention. Materials and Methods We first performed data mining analysis to identify genes which are consistently dysregulated in prostate cancer using published datasets from gene expression profiling of clinical prostate specimens. We then devised a method to systematically analyze three selenium microarray datasets from the LNCaP human prostate cancer cells, and to match the analysis to the cohort of genes implicated in prostate carcinogenesis. Moreover, we compared the selenium datasets with two datasets obtained from expression profiling of androgen-stimulated LNCaP cells. Results We found that selenium reverses the expression of genes implicated in prostate carcinogenesis. In addition, we found that selenium could counteract the effect of androgen on the expression of a subset obtained from androgen-regulated genes. Conclusions The above information provides us with a treasure of new clues to investigate the mechanism of selenium chemoprevention of prostate cancer. Furthermore, these selenium target genes could also serve as biomarkers in future clinical trials to gauge the efficacy of selenium intervention. PMID:18548127
Seale, Clive; Ziebland, Sue; Charteris-Black, Jonathan
2006-05-01
A new method, comparative keyword analysis, is used to compare the language of men and women with cancer in 97 research interviews and two popular internet based support groups for people with cancer. The method is suited to the conjoint qualitative and quantitative analysis of differences between large bodies of text, an alternative to the 'code and retrieval' approach used in much thematic analysis of qualitative materials. Web forums are a rich source of data about illness experience and gender differences. Marked differences in the performance of gender are evident. These differences follow linguistic and other behavioural patterns (such as social network differences) established in other contexts. Men with prostate cancer indicate in research interviews that they are more likely to seek information on the internet; women with breast cancer that they are more likely to seek social and emotional support. Men's concerns cluster around treatment information, medical personnel and procedures. Their experience of disease is more localised on particular areas of the body, while women's experience is more holistic. Women's forum postings orientate much more towards the exchange of emotional support, including concern with the impact of illness on a wide range of other people. Women's use of superlatives as well as words referring to feelings indicate their enactment of greater emotional expressivity. Web forums are platforms for an intensification of men's knowledge gathering activities. Web forums, though actually quite publicly visible, appear to be subjectively experienced by both sexes as relatively private places for the exchange of intimate personal information. The 'privacy' of the breast cancer forum facilitated interactions found in other studies to be characteristic of women's friendship groups.
Rajput, Ashish B; Turbin, Dmitry A; Cheang, Maggie Cu; Voduc, David K; Leung, Sam; Gelmon, Karen A; Gilks, C Blake; Huntsman, David G
2008-01-01
We have previously demonstrated in a pilot study of 348 invasive breast cancers that mast cell (MC) infiltrates within primary breast cancers are associated with a good prognosis. Our aim was to verify this finding in a larger cohort of invasive breast cancer patients and examine the relationship between the presence of MCs and other clinical and pathological features. Clinically annotated tissue microarrays (TMAs) containing 4,444 cases were constructed and stained with c-Kit (CD-117) using standard immunoperoxidase techniques to identify and quantify MCs. For statistical analysis, we applied a split-sample validation technique. Breast cancer specific survival was analyzed by Kaplan-Meier [KM] method and log rank test was used to compare survival curves. Survival analysis by KM method showed that the presence of stromal MCs was a favourable prognostic factor in the training set (P = 0.001), and the validation set group (P = 0.006). X-tile plot generated to define the optimal number of MCs showed that the presence of any number of stromal MCs predicted good prognosis. Multivariate analysis showed that the MC effect in the training set (Hazard ratio [HR] = 0.804, 95% Confidence interval [CI], 0.653-0.991, P = 0.041) and validation set analysis (HR = 0.846, 95% CI, 0.683-1.049, P = 0.128) was independent of age, tumor grade, tumor size, lymph node, ER and Her2 status. This study concludes that stromal MC infiltration in invasive breast cancer is an independent good prognostic marker and reiterates the critical role of local inflammatory responses in breast cancer progression.
Rajput, Ashish B.; Turbin, Dmitry A.; Cheang, Maggie CU; Voduc, David K.; Leung, Sam; Gelmon, Karen A.; Gilks, C. Blake
2007-01-01
Purpose We have previously demonstrated in a pilot study of 348 invasive breast cancers that mast cell (MC) infiltrates within primary breast cancers are associated with a good prognosis. Our aim was to verify this finding in a larger cohort of invasive breast cancer patients and examine the relationship between the presence of MCs and other clinical and pathological features. Experimental design Clinically annotated tissue microarrays (TMAs) containing 4,444 cases were constructed and stained with c-Kit (CD-117) using standard immunoperoxidase techniques to identify and quantify MCs. For statistical analysis, we applied a split-sample validation technique. Breast cancer specific survival was analyzed by Kaplan–Meier [KM] method and log rank test was used to compare survival curves. Results Survival analysis by KM method showed that the presence of stromal MCs was a favourable prognostic factor in the training set (P = 0.001), and the validation set group (P = 0.006). X-tile plot generated to define the optimal number of MCs showed that the presence of any number of stromal MCs predicted good prognosis. Multivariate analysis showed that the MC effect in the training set (Hazard ratio [HR] = 0.804, 95% Confidence interval [CI], 0.653–0.991, P = 0.041) and validation set analysis (HR = 0.846, 95% CI, 0.683–1.049, P = 0.128) was independent of age, tumor grade, tumor size, lymph node, ER and Her2 status. Conclusions This study concludes that stromal MC infiltration in invasive breast cancer is an independent good prognostic marker and reiterates the critical role of local inflammatory responses in breast cancer progression. PMID:17431762
Cook, Michael B.; Guénel, Pascal; Gapstur, Susan M.; van den Brandt, Piet A.; Michels, Karin B.; Casagrande, John T.; Cooke, Rosie; Van Den Eeden, Stephen K.; Ewertz, Marianne; Falk, Roni T.; Gaudet, Mia M.; Gkiokas, George; Habel, Laurel A.; Hsing, Ann W.; Johnson, Kenneth; Kolonel, Laurence N.; La Vecchia, Carlo; Lynge, Elsebeth; Lubin, Jay H.; McCormack, Valerie A.; Negri, Eva; Olsson, Håkan; Parisi, Dominick; Petridou, Eleni Th.; Riboli, Elio; Sesso, Howard D.; Swerdlow, Anthony; Thomas, David B.; Willett, Walter C.; Brinton, Louise A.
2015-01-01
Background The etiology of male breast cancer is poorly understood, partly due to its relative rarity. Although tobacco and alcohol exposures are known carcinogens, their association with male breast cancer risk remains ill-defined. Methods The Male Breast Cancer Pooling Project consortium provided 2,378 cases and 51,959 controls for analysis from 10 case-control and 10 cohort studies. Individual participant data were harmonized and pooled. Unconditional logistic regression was used to estimate study design-specific (case-control/cohort) odds ratios (OR) and 95% confidence intervals (CI), which were then combined using fixed effects meta-analysis. Results Cigarette smoking status, smoking pack-years, duration, intensity, and age at initiation were not associated with male breast cancer risk. Relations with cigar and pipe smoking, tobacco chewing, and snuff use were also null. Recent alcohol consumption and average grams of alcohol consumed per day were also not associated with risk; only one sub-analysis of very high recent alcohol consumption (>60 grams/day) was tentatively associated with male breast cancer (ORunexposed referent=1.29, 95%CI:0.97–1.71; OR>0–<7 g/day referent=1.36, 95%CI:1.04–1.77). Specific alcoholic beverage types were not associated with male breast cancer. Relations were not altered when stratified by age or body mass index. Conclusions In this analysis of the Male Breast Cancer Pooling Project we found little evidence that tobacco and alcohol exposures were associated with risk of male breast cancer. Impact Tobacco and alcohol do not appear to be carcinogenic for male breast cancer. Future studies should aim to assess these exposures in relation to subtypes of male breast cancer. PMID:25515550
Kurok, Marlene; Goldis, Alon; Dreier, Maren; Kaltenborn, Alexander; Gwinner, Wilfried; Barthold, Marc; Liebeneiner, Jan; Winny, Markus; Klempnauer, Jürgen; Kleine, Moritz
2016-01-01
Background The aim of this study is to identify independent pre-transplant cancer risk factors after kidney transplantation and to assess the utility of G-chart analysis for clinical process control. This may contribute to the improvement of cancer surveillance processes in individual transplant centers. Patients and Methods 1655 patients after kidney transplantation at our institution with a total of 9,425 person-years of follow-up were compared retrospectively to the general German population using site-specific standardized-incidence-ratios (SIRs) of observed malignancies. Risk-adjusted multivariable Cox regression was used to identify independent pre-transplant cancer risk factors. G-chart analysis was applied to determine relevant differences in the frequency of cancer occurrences. Results Cancer incidence rates were almost three times higher as compared to the matched general population (SIR = 2.75; 95%-CI: 2.33–3.21). Significantly increased SIRs were observed for renal cell carcinoma (SIR = 22.46), post-transplant lymphoproliferative disorder (SIR = 8.36), prostate cancer (SIR = 2.22), bladder cancer (SIR = 3.24), thyroid cancer (SIR = 10.13) and melanoma (SIR = 3.08). Independent pre-transplant risk factors for cancer-free survival were age <52.3 years (p = 0.007, Hazard ratio (HR): 0.82), age >62.6 years (p = 0.001, HR: 1.29), polycystic kidney disease other than autosomal dominant polycystic kidney disease (ADPKD) (p = 0.001, HR: 0.68), high body mass index in kg/m2 (p<0.001, HR: 1.04), ADPKD (p = 0.008, HR: 1.26) and diabetic nephropathy (p = 0.004, HR = 1.51). G-chart analysis identified relevant changes in the detection rates of cancer during aftercare with no significant relation to identified risk factors for cancer-free survival (p<0.05). Conclusions Risk-adapted cancer surveillance combined with prospective G-chart analysis likely improves cancer surveillance schemes by adapting processes to identified risk factors and by using G-chart alarm signals to trigger Kaizen events and audits for root-cause analysis of relevant detection rate changes. Further, comparative G-chart analysis would enable benchmarking of cancer surveillance processes between centers. PMID:27398803
Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex
2016-11-16
Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.
Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex
2016-01-01
Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968
Dutta, Sudhir K.; Girotra, Mohit; Singla, Montish; Dutta, Anand; Stephen, F. Otis; Nair, Padmanabhan P.; Merchant, Nipun B.
2014-01-01
Objectives Heat shock protein 70 (HSP70) is overexpressed in human pancreatic cancer cell lines. To determine if serum HSP70 levels are elevated in patients with pancreatic cancer and can function as a biomarker for early detection of pancreatic cancer. Methods Study subjects were divided into 3 groups: histologically proven pancreatic cancer (PC; n = 23), chronic pancreatitis (CP; n = 12), and matched normal control subjects (C; n = 10). Serum HSP70 levels were determined using a novel immunoelectrophoresis method developed and validated by the authors. Significance of difference between the groups was analyzed with analysis of variance (ANOVA). Receiver operating characteristic (ROC) curve analysis was performed to discriminate patients with pancreatic cancer from normal controls. Results The mean ± SE serum HSP70 levels in the PC, CP, and C groups were 1.68 ± 0.083 ng/mL, 0.40 ± 0.057 ng/mL, and 0.04 ng/mL, respectively. Serum HSP70 levels in the PC group were significantly higher compared with either the CP or C groups (P < 0.01). The sensitivity and specificity of elevated serum HSP70 in the PC group was 74% and 90%, respectively. Conclusions Serum HSP70 levels are significantly increased in patients with pancreatic cancer and may be useful as an additional biomarker for the detection of pancreatic cancer. PMID:22158074
Innovative Diagnostic Methods for Early Prostate Cancer Detection through Urine Analysis: A Review.
Bax, Carmen; Taverna, Gianluigi; Eusebio, Lidia; Sironi, Selena; Grizzi, Fabio; Guazzoni, Giorgio; Capelli, Laura
2018-04-18
Prostate cancer is the second most common cause of cancer death among men. It is an asymptomatic and slow growing tumour, which starts occurring in young men, but can be detected only around the age of 40–50. Although its long latency period and potential curability make prostate cancer a perfect candidate for screening programs, the current procedure lacks in specificity. Researchers are rising to the challenge of developing innovative tools able of detecting the disease during its early stage that is the most curable. In recent years, the interest in characterisation of biological fluids aimed at the identification of tumour-specific compounds has increased significantly, since cell neoplastic transformation causes metabolic alterations leading to volatile organic compounds release. In the scientific literature, different approaches have been proposed. Many studies focus on the identification of a cancer-characteristic “odour fingerprint” emanated from biological samples through the application of sensorial or senso-instrumental analyses, others suggest a chemical characterisation of biological fluids with the aim of identifying prostate cancer (PCa)-specific biomarkers. This paper focuses on the review of literary studies in the field of prostate cancer diagnosis, in order to provide an overview of innovative methods based on the analysis of urine, thereby comparing them with the traditional diagnostic procedures.
Use of the Analysis of the Volatile Faecal Metabolome in Screening for Colorectal Cancer
2015-01-01
Diagnosis of colorectal cancer is an invasive and expensive colonoscopy, which is usually carried out after a positive screening test. Unfortunately, existing screening tests lack specificity and sensitivity, hence many unnecessary colonoscopies are performed. Here we report on a potential new screening test for colorectal cancer based on the analysis of volatile organic compounds (VOCs) in the headspace of faecal samples. Faecal samples were obtained from subjects who had a positive faecal occult blood sample (FOBT). Subjects subsequently had colonoscopies performed to classify them into low risk (non-cancer) and high risk (colorectal cancer) groups. Volatile organic compounds were analysed by selected ion flow tube mass spectrometry (SIFT-MS) and then data were analysed using both univariate and multivariate statistical methods. Ions most likely from hydrogen sulphide, dimethyl sulphide and dimethyl disulphide are statistically significantly higher in samples from high risk rather than low risk subjects. Results using multivariate methods show that the test gives a correct classification of 75% with 78% specificity and 72% sensitivity on FOBT positive samples, offering a potentially effective alternative to FOBT. PMID:26086914
Isolation of circulating tumor cells from pancreatic cancer by automated filtration
Brychta, Nora; Drosch, Michael; Driemel, Christiane; Fischer, Johannes C.; Neves, Rui P.; Esposito, Irene; Knoefel, Wolfram; Möhlendick, Birte; Hille, Claudia; Stresemann, Antje; Krahn, Thomas; Kassack, Matthias U.; Stoecklein, Nikolas H.; von Ahsen, Oliver
2017-01-01
It is now widely recognized that the isolation of circulating tumor cells based on cell surface markers might be hindered by variability in their protein expression. Especially in pancreatic cancer, isolation based only on EpCAM expression has produced very diverse results. Methods that are independent of surface markers and therefore independent of phenotypical changes in the circulating cells might increase CTC recovery also in pancreatic cancer. We compared an EpCAM-dependent (IsoFlux) and a size-dependent (automated Siemens Healthineers filtration device) isolation method for the enrichment of pancreatic cancer CTCs. The recovery rate of the filtration based approach is dramatically superior to the EpCAM-dependent approach especially for cells with low EpCAM-expression (filtration: 52%, EpCAM-dependent: 1%). As storage and shipment of clinical samples is important for centralized analyses, we also evaluated the use of frozen diagnostic leukapheresis (DLA) as source for isolating CTCs and subsequent genetic analysis such as KRAS mutation detection analysis. Using frozen DLA samples of pancreatic cancer patients we detected CTCs in 42% of the samples by automated filtration. PMID:29156783
Isolation of circulating tumor cells from pancreatic cancer by automated filtration.
Brychta, Nora; Drosch, Michael; Driemel, Christiane; Fischer, Johannes C; Neves, Rui P; Esposito, Irene; Knoefel, Wolfram; Möhlendick, Birte; Hille, Claudia; Stresemann, Antje; Krahn, Thomas; Kassack, Matthias U; Stoecklein, Nikolas H; von Ahsen, Oliver
2017-10-17
It is now widely recognized that the isolation of circulating tumor cells based on cell surface markers might be hindered by variability in their protein expression. Especially in pancreatic cancer, isolation based only on EpCAM expression has produced very diverse results. Methods that are independent of surface markers and therefore independent of phenotypical changes in the circulating cells might increase CTC recovery also in pancreatic cancer. We compared an EpCAM-dependent (IsoFlux) and a size-dependent (automated Siemens Healthineers filtration device) isolation method for the enrichment of pancreatic cancer CTCs. The recovery rate of the filtration based approach is dramatically superior to the EpCAM-dependent approach especially for cells with low EpCAM-expression (filtration: 52%, EpCAM-dependent: 1%). As storage and shipment of clinical samples is important for centralized analyses, we also evaluated the use of frozen diagnostic leukapheresis (DLA) as source for isolating CTCs and subsequent genetic analysis such as KRAS mutation detection analysis. Using frozen DLA samples of pancreatic cancer patients we detected CTCs in 42% of the samples by automated filtration.
Nuclear magnetic resonance (NMR)-based metabolomics for cancer research.
Ranjan, Renuka; Sinha, Neeraj
2018-05-07
Nuclear magnetic resonance (NMR) has emerged as an effective tool in various spheres of biomedical research, amongst which metabolomics is an important method for the study of various types of disease. Metabolomics has proved its stronghold in cancer research by the development of different NMR methods over time for the study of metabolites, thus identifying key players in the aetiology of cancer. A plethora of one-dimensional and two-dimensional NMR experiments (in solids, semi-solids and solution phases) are utilized to obtain metabolic profiles of biofluids, cell extracts and tissue biopsy samples, which can further be subjected to statistical analysis. Any alteration in the assigned metabolite peaks gives an indication of changes in metabolic pathways. These defined changes demonstrate the utility of NMR in the early diagnosis of cancer and provide further measures to combat malignancy and its progression. This review provides a snapshot of the trending NMR techniques and the statistical analysis involved in the metabolomics of diseases, with emphasis on advances in NMR methodology developed for cancer research. Copyright © 2018 John Wiley & Sons, Ltd.
Lyles, Courtney Rees; Godbehere, Andrew; Le, Gem; El Ghaoui, Laurent; Sarkar, Urmimala
2016-06-10
It is difficult to synthesize the vast amount of textual data available from social media websites. Capturing real-world discussions via social media could provide insights into individuals' opinions and the decision-making process. We conducted a sequential mixed methods study to determine the utility of sparse machine learning techniques in summarizing Twitter dialogues. We chose a narrowly defined topic for this approach: cervical cancer discussions over a 6-month time period surrounding a change in Pap smear screening guidelines. We applied statistical methodologies, known as sparse machine learning algorithms, to summarize Twitter messages about cervical cancer before and after the 2012 change in Pap smear screening guidelines by the US Preventive Services Task Force (USPSTF). All messages containing the search terms "cervical cancer," "Pap smear," and "Pap test" were analyzed during: (1) January 1-March 13, 2012, and (2) March 14-June 30, 2012. Topic modeling was used to discern the most common topics from each time period, and determine the singular value criterion for each topic. The results were then qualitatively coded from top 10 relevant topics to determine the efficiency of clustering method in grouping distinct ideas, and how the discussion differed before vs. after the change in guidelines . This machine learning method was effective in grouping the relevant discussion topics about cervical cancer during the respective time periods (~20% overall irrelevant content in both time periods). Qualitative analysis determined that a significant portion of the top discussion topics in the second time period directly reflected the USPSTF guideline change (eg, "New Screening Guidelines for Cervical Cancer"), and many topics in both time periods were addressing basic screening promotion and education (eg, "It is Cervical Cancer Awareness Month! Click the link to see where you can receive a free or low cost Pap test.") It was demonstrated that machine learning tools can be useful in cervical cancer prevention and screening discussions on Twitter. This method allowed us to prove that there is publicly available significant information about cervical cancer screening on social media sites. Moreover, we observed a direct impact of the guideline change within the Twitter messages.
Yu, Qingzhao; Medeiros, Kaelen L; Wu, Xiaocheng; Jensen, Roxanne E
2018-04-02
Mediation analysis allows the examination of effects of a third variable (mediator/confounder) in the causal pathway between an exposure and an outcome. The general multiple mediation analysis method (MMA), proposed by Yu et al., improves traditional methods (e.g., estimation of natural and controlled direct effects) to enable consideration of multiple mediators/confounders simultaneously and the use of linear and nonlinear predictive models for estimating mediation/confounding effects. Previous studies find that compared with non-Hispanic cancer survivors, Hispanic survivors are more likely to endure anxiety and depression after cancer diagnoses. In this paper, we applied MMA on MY-Health study to identify mediators/confounders and quantify the indirect effect of each identified mediator/confounder in explaining ethnic disparities in anxiety and depression among cancer survivors who enrolled in the study. We considered a number of socio-demographic variables, tumor characteristics, and treatment factors as potential mediators/confounders and found that most of the ethnic differences in anxiety or depression between Hispanic and non-Hispanic white cancer survivors were explained by younger diagnosis age, lower education level, lower proportions of employment, less likely of being born in the USA, less insurance, and less social support among Hispanic patients.
Alcohol Intake and Risk of Thyroid Cancer: A Meta-Analysis of Observational Studies
Hong, Seung-Hee; Myung, Seung-Kwon; Kim, Hyeon Suk
2017-01-01
Purpose The purpose of this study was to assess whether alcohol intake is associated with the risk of thyroid cancer by a meta-analysis of observational studies. Materials and Methods We searched PubMed and EMBASE in June of 2015 to locate eligible studies. We included observational studies such as cross-sectional studies, case-control studies, and cohort studies reporting odd ratios (ORs) or relative risk (RRs) with 95% confidence intervals (CIs). Results We included 33 observational studies with two cross-sectional studies, 20 case-controls studies, and 11 cohort studies, which involved a total of 7,725 thyroid cancer patients and 3,113,679 participants without thyroid cancer in the final analysis. In the fixed-effect model meta-analysis of all 33 studies, we found that alcohol intake was consistently associated with a decreased risk of thyroid cancer (OR or RR, 0.74; 95% CI, 0.67 to 0.83; I2=38.6%). In the subgroup meta-analysis by type of study, alcohol intake also decreased the risk of thyroid cancer in both case-control studies (OR, 0.77; 95% CI, 0.65 to 0.92; I2=29.5%; n=20) and cohort studies (RR, 0.70; 95% CI, 0.60 to 0.82; I2=0%; n=11). Moreover, subgroup meta-analyses by type of thyroid cancer, gender, amount of alcohol consumed, and methodological quality of study showed that alcohol intake was significantly associated with a decreased risk of thyroid cancer. Conclusion The current meta-analysis of observational studies found that, unlike most of other types of cancer, alcohol intake decreased the risk of thyroid cancer. PMID:27456949
Peterson, Thomas A; Nehrt, Nathan L; Park, DoHwan
2012-01-01
Background and objective With recent breakthroughs in high-throughput sequencing, identifying deleterious mutations is one of the key challenges for personalized medicine. At the gene and protein level, it has proven difficult to determine the impact of previously unknown variants. A statistical method has been developed to assess the significance of disease mutation clusters on protein domains by incorporating domain functional annotations to assist in the functional characterization of novel variants. Methods Disease mutations aggregated from multiple databases were mapped to domains, and were classified as either cancer- or non-cancer-related. The statistical method for identifying significantly disease-associated domain positions was applied to both sets of mutations and to randomly generated mutation sets for comparison. To leverage the known function of protein domain regions, the method optionally distributes significant scores to associated functional feature positions. Results Most disease mutations are localized within protein domains and display a tendency to cluster at individual domain positions. The method identified significant disease mutation hotspots in both the cancer and non-cancer datasets. The domain significance scores (DS-scores) for cancer form a bimodal distribution with hotspots in oncogenes forming a second peak at higher DS-scores than non-cancer, and hotspots in tumor suppressors have scores more similar to non-cancers. In addition, on an independent mutation benchmarking set, the DS-score method identified mutations known to alter protein function with very high precision. Conclusion By aggregating mutations with known disease association at the domain level, the method was able to discover domain positions enriched with multiple occurrences of deleterious mutations while incorporating relevant functional annotations. The method can be incorporated into translational bioinformatics tools to characterize rare and novel variants within large-scale sequencing studies. PMID:22319177
Engelberg, Jesse A.; Giberson, Richard T.; Young, Lawrence J.T.; Hubbard, Neil E.
2014-01-01
Microwave methods of fixation can dramatically shorten fixation times while preserving tissue structure; however, it remains unclear if adequate tissue antigenicity is preserved. To assess and validate antigenicity, robust quantitative methods and animal disease models are needed. We used two mouse mammary models of human breast cancer to evaluate microwave-assisted and standard 24-hr formalin fixation. The mouse models expressed four antigens prognostic for breast cancer outcome: estrogen receptor, progesterone receptor, Ki67, and human epidermal growth factor receptor 2. Using pathologist evaluation and novel methods of quantitative image analysis, we measured and compared the quality of antigen preservation, percentage of positive cells, and line plots of cell intensity. Visual evaluations by pathologists established that the amounts and patterns of staining were similar in tissues fixed by the different methods. The results of the quantitative image analysis provided a fine-grained evaluation, demonstrating that tissue antigenicity is preserved in tissues fixed using microwave methods. Evaluation of the results demonstrated that a 1-hr, 150-W fixation is better than a 45-min, 150-W fixation followed by a 15-min, 650-W fixation. The results demonstrated that microwave-assisted formalin fixation can standardize fixation times to 1 hr and produce immunohistochemistry that is in every way commensurate with longer conventional fixation methods. PMID:24682322
Hoseini, Mina; Bahrampour, Abbas; Mirzaee, Moghaddameh
2017-02-16
Breast cancer is the most common cancer after lung cancer and the second cause of death. In this study we compared Weibull and Lognormal Cure Models with Cox regression on the survival of breast cancer. A cohort study. The current study retrospective cohort study was conducted on 140 patients referred to Ali Ibn Abitaleb Hospital, Rafsanjan southeastern Iran from 2001 to 2015 suffering from breast cancer. We determined and analyzed the effective survival causes by different models using STATA14. According to AIC, log-normal model was more consistent than Weibull. In the multivariable Lognormal model, the effective factors like smoking, second -hand smoking, drinking herbal tea and the last breast-feeding period were included. In addition, using Cox regression factors of significant were the disease grade, size of tumor and its metastasis (p-value<0.05). As Rafsanjan is surrounded by pistachio orchards and pesticides applied by farmers, people of this city are exposed to agricultural pesticides and its harmful consequences. The effect of the pesticide on breast cancer was studied and the results showed that the effect of pesticides on breast cancer was not in agreement with the models used in this study. Based on different methods for survival analysis, researchers can decide how they can reach a better conclusion. This comparison indicates the result of semi-parametric Cox method is closer to clinical experiences evidences.
Miyagi, Yohei; Higashiyama, Masahiko; Gochi, Akira; Akaike, Makoto; Ishikawa, Takashi; Miura, Takeshi; Saruki, Nobuhiro; Bando, Etsuro; Kimura, Hideki; Imamura, Fumio; Moriyama, Masatoshi; Ikeda, Ichiro; Chiba, Akihiko; Oshita, Fumihiro; Imaizumi, Akira; Yamamoto, Hiroshi; Miyano, Hiroshi; Horimoto, Katsuhisa; Tochikubo, Osamu; Mitsushima, Toru; Yamakado, Minoru; Okamoto, Naoyuki
2011-01-01
Background Recently, rapid advances have been made in metabolomics-based, easy-to-use early cancer detection methods using blood samples. Among metabolites, profiling of plasma free amino acids (PFAAs) is a promising approach because PFAAs link all organ systems and have important roles in metabolism. Furthermore, PFAA profiles are known to be influenced by specific diseases, including cancers. Therefore, the purpose of the present study was to determine the characteristics of the PFAA profiles in cancer patients and the possibility of using this information for early detection. Methods and Findings Plasma samples were collected from approximately 200 patients from multiple institutes, each diagnosed with one of the following five types of cancer: lung, gastric, colorectal, breast, or prostate cancer. Patients were compared to gender- and age- matched controls also used in this study. The PFAA levels were measured using high-performance liquid chromatography (HPLC)–electrospray ionization (ESI)–mass spectrometry (MS). Univariate analysis revealed significant differences in the PFAA profiles between the controls and the patients with any of the five types of cancer listed above, even those with asymptomatic early-stage disease. Furthermore, multivariate analysis clearly discriminated the cancer patients from the controls in terms of the area under the receiver-operator characteristics curve (AUC of ROC >0.75 for each cancer), regardless of cancer stage. Because this study was designed as case-control study, further investigations, including model construction and validation using cohorts with larger sample sizes, are necessary to determine the usefulness of PFAA profiling. Conclusions These findings suggest that PFAA profiling has great potential for improving cancer screening and diagnosis and understanding disease pathogenesis. PFAA profiles can also be used to determine various disease diagnoses from a single blood sample, which involves a relatively simple plasma assay and imposes a lower physical burden on subjects when compared to existing screening methods. PMID:21915291
Locating relationship and communication issues among stressors associated with breast cancer.
Weber, Kirsten M; Solomon, Denise Haunani
2008-11-01
This article clarifies how the social contexts in which breast cancer survivors live can contribute to the stress they experience because of the disease. Guided by Solomon and Knobloch's (2004) relational turbulence model and Petronio's (2002) communication privacy management theory, this study explores personal relationship and communication boundary issues within stressors that are associated with the diagnosis, treatment, and early survivorship of breast cancer. A qualitative analysis of discourse posted on breast cancer discussion boards and weblogs using the constant comparative method and open-coding techniques revealed 12 sources of stress. Using axial coding methods and probing these topics for underlying relationship and communication issues yielded 5 themes. The discussion highlights the implications of the findings for the theories that guided this investigation and for breast cancer survivorship more generally.
The study of esophageal cancer in an early stage by using Raman spectroscopy
NASA Astrophysics Data System (ADS)
Ishigaki, Mika; Taketani, Akinori; Maeda, Yasuhiro; Andriana, Bibin B.; Ishihara, Ryu; Sato, Hidetoshi
2013-02-01
The esophageal cancer is a disease with a high mortality. In order to lead a higher survival rate five years after the cancer's treatment, we inevitably need a method to diagnose the cancer in an early stage and support the therapy. Raman spectroscopy is one of the most powerful techniques for the purpose. In the present study, we apply Raman spectroscopy to obtain ex vivo spectra of normal and early tumor human esophageal sample. The result of principal component analysis indicates that the tumor tissue is associated with a decrease in tryptophan concentration. Furthermore, we can predict the tissue type with 80% accuracy by linear discriminant analysis which model is made by tryptophan bands.
NASA Astrophysics Data System (ADS)
Liu, Quan; Grant, Gerald; Li, Jianjun; Zhang, Yan; Hu, Fangyao; Li, Shuqin; Wilson, Christy; Chen, Kui; Bigner, Darell; Vo-Dinh, Tuan
2011-03-01
We report the development of a compact point-detection fluorescence spectroscopy system and two data analysis methods to quantify the intrinsic fluorescence redox ratio and diagnose brain cancer in an orthotopic brain tumor rat model. Our system employs one compact cw diode laser (407 nm) to excite two primary endogenous fluorophores, reduced nicotinamide adenine dinucleotide, and flavin adenine dinucleotide. The spectra were first analyzed using a spectral filtering modulation method developed previously to derive the intrinsic fluorescence redox ratio, which has the advantages of insensitivty to optical coupling and rapid data acquisition and analysis. This method represents a convenient and rapid alternative for achieving intrinsic fluorescence-based redox measurements as compared to those complicated model-based methods. It is worth noting that the method can also extract total hemoglobin concentration at the same time but only if the emission path length of fluorescence light, which depends on the illumination and collection geometry of the optical probe, is long enough so that the effect of absorption on fluorescence intensity due to hemoglobin is significant. Then a multivariate method was used to statistically classify normal tissues and tumors. Although the first method offers quantitative tissue metabolism information, the second method provides high overall classification accuracy. The two methods provide complementary capabilities for understanding cancer development and noninvasively diagnosing brain cancer. The results of our study suggest that this portable system can be potentially used to demarcate the elusive boundary between a brain tumor and the surrounding normal tissue during surgical resection.
Lu, Jing; Chen, Lei; Yin, Jun; Huang, Tao; Bi, Yi; Kong, Xiangyin; Zheng, Mingyue; Cai, Yu-Dong
2016-01-01
Lung cancer, characterized by uncontrolled cell growth in the lung tissue, is the leading cause of global cancer deaths. Until now, effective treatment of this disease is limited. Many synthetic compounds have emerged with the advancement of combinatorial chemistry. Identification of effective lung cancer candidate drug compounds among them is a great challenge. Thus, it is necessary to build effective computational methods that can assist us in selecting for potential lung cancer drug compounds. In this study, a computational method was proposed to tackle this problem. The chemical-chemical interactions and chemical-protein interactions were utilized to select candidate drug compounds that have close associations with approved lung cancer drugs and lung cancer-related genes. A permutation test and K-means clustering algorithm were employed to exclude candidate drugs with low possibilities to treat lung cancer. The final analysis suggests that the remaining drug compounds have potential anti-lung cancer activities and most of them have structural dissimilarity with approved drugs for lung cancer.
He, J X; Jiang, Y F
2017-08-06
Hereditary cancer is caused by specific pathogenic gene mutations. Early detection and early intervention are the most effective ways to prevent and control hereditary cancer. High-throughput sequencing based genetic testing technology (NGS) breaks through the restrictions of pedigree analysis, provide a convenient and efficient method to detect and diagnose hereditary cancer. Here, we introduce the mechanism of hereditary cancer, summarize, discuss and prospect the application of NGS and other genetic tests in the diagnosis of hereditary retinoblastoma, hereditary breast and ovarian cancer syndrome, hereditary colorectal cancer and other complex and rare hereditary tumors.
Yang, Qian; Wang, Shuyuan; Dai, Enyu; Zhou, Shunheng; Liu, Dianming; Liu, Haizhou; Meng, Qianqian; Jiang, Bin; Jiang, Wei
2017-08-16
Pathway enrichment analysis has been widely used to identify cancer risk pathways, and contributes to elucidating the mechanism of tumorigenesis. However, most of the existing approaches use the outdated pathway information and neglect the complex gene interactions in pathway. Here, we first reviewed the existing widely used pathway enrichment analysis approaches briefly, and then, we proposed a novel topology-based pathway enrichment analysis (TPEA) method, which integrated topological properties and global upstream/downstream positions of genes in pathways. We compared TPEA with four widely used pathway enrichment analysis tools, including database for annotation, visualization and integrated discovery (DAVID), gene set enrichment analysis (GSEA), centrality-based pathway enrichment (CePa) and signaling pathway impact analysis (SPIA), through analyzing six gene expression profiles of three tumor types (colorectal cancer, thyroid cancer and endometrial cancer). As a result, we identified several well-known cancer risk pathways that could not be obtained by the existing tools, and the results of TPEA were more stable than that of the other tools in analyzing different data sets of the same cancer. Ultimately, we developed an R package to implement TPEA, which could online update KEGG pathway information and is available at the Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/TPEA/. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Radiopharmaceutical stannic Sn-117m chelate compositions and methods of use
Srivastava, Suresh C.; Meinken, George E.
2001-01-01
Radiopharmaceutical compositions including .sup.117m Sn labeled stannic (Sn.sup.4+) chelates are provided. The chelates are preferably polyhydroxycarboxylate, such as oxalates, tartrates, citrates, malonates, gluconates, glucoheptonates and the like. Methods of making .sup.117m Sn-labeled (Sn.sup.4+) polyhydroxycarboxylic chelates are also provided. The foregoing pharmaceutical compositions can be used in methods of preparing bone for scintigraphical analysis, for radiopharmaceutical skeletal imaging, treatment of pain resulting from metastatic bone involvement, treatment of primary bone cancer, treatment of cancer resulting from metastatic spread to bone from other primary cancers, treatment of pain resulting from rheumatoid arthritis, treatment of bone/joint disorders and to monitor radioactively the skeletal system.
Software for the Integration of Multiomics Experiments in Bioconductor.
Ramos, Marcel; Schiffer, Lucas; Re, Angela; Azhar, Rimsha; Basunia, Azfar; Rodriguez, Carmen; Chan, Tiffany; Chapman, Phil; Davis, Sean R; Gomez-Cabrero, David; Culhane, Aedin C; Haibe-Kains, Benjamin; Hansen, Kasper D; Kodali, Hanish; Louis, Marie S; Mer, Arvind S; Riester, Markus; Morgan, Martin; Carey, Vince; Waldron, Levi
2017-11-01
Multiomics experiments are increasingly commonplace in biomedical research and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multiomics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide the unrestricted multiple 'omics data for each cancer tissue in The Cancer Genome Atlas as ready-to-analyze MultiAssayExperiment objects and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable, and reproducible statistical analysis of multiomics data and enhances data science applications of multiple omics datasets. Cancer Res; 77(21); e39-42. ©2017 AACR . ©2017 American Association for Cancer Research.
Hamatani, Kiyohiro; Eguchi, Hidetaka; Mukai, Mayumi; Koyama, Kazuaki; Taga, Masataka; Ito, Reiko; Hayashi, Yuzo; Nakachi, Kei
2010-01-01
Since many thyroid cancer tissue samples from atomic bomb (A-bomb) survivors have been preserved for several decades as unbuffered formalin-fixed, paraffin-embedded specimens, molecular oncological analysis of such archival specimens is indispensable for clarifying the mechanisms of thyroid carcinogenesis in A-bomb survivors. Although RET gene rearrangements are the most important targets, it is a difficult task to examine all of the 13 known types of RET gene rearrangements with the use of the limited quantity of RNA that has been extracted from invaluable paraffin-embedded tissue specimens of A-bomb survivors. In this study, we established an improved 5' rapid amplification of cDNA ends (RACE) method using a small amount of RNA extracted from archival thyroid cancer tissue specimens. Three archival thyroid cancer tissue specimens from three different patients were used as in-house controls to determine the conditions for an improved switching mechanism at 5' end of RNA transcript (SMART) RACE method; one tissue specimen with RET/PTC1 rearrangement and one with RET/PTC3 rearrangement were used as positive samples. One other specimen, used as a negative sample, revealed no detectable expression of the RET gene tyrosine kinase domain. We established a 5' RACE method using an amount of RNA as small as 10 ng extracted from long-term preserved, unbuffered formalin-fixed, paraffin-embedded thyroid cancer tissue by application of SMART technology. This improved SMART RACE method not only identified common RET gene rearrangements, but also isolated a clone containing a 93-bp insert of rare RTE/PTC8 in RNA extracted from formalin-fixed, paraffin-embedded thyroid cancer specimens from one A-bomb survivor who had been exposed to a high radiation dose. In addition, in the papillary thyroid cancer of another high-dose A-bomb survivor, this method detected one novel type of RET gene rearrangement whose partner gene is acyl coenzyme A binding domain 5, located on chromosome 10p. We conclude that our improved SMART RACE method is expected to prove useful in molecular analyses using archival formalin-fixed, paraffin-embedded tissue samples of limited quantity.
Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath
Machado, Roberto F.; Laskowski, Daniel; Deffenderfer, Olivia; Burch, Timothy; Zheng, Shuo; Mazzone, Peter J.; Mekhail, Tarek; Jennings, Constance; Stoller, James K.; Pyle, Jacqueline; Duncan, Jennifer; Dweik, Raed A.; Erzurum, Serpil C.
2005-01-01
Rationale: Electronic noses are successfully used in commercial applications, including detection and analysis of volatile organic compounds in the food industry. Objectives: We hypothesized that the electronic nose could identify and discriminate between lung diseases, especially bronchogenic carcinoma. Methods: In a discovery and training phase, exhaled breath of 14 individuals with bronchogenic carcinoma and 45 healthy control subjects or control subjects without cancer was analyzed. Principal components and canonic discriminant analysis of the sensor data was used to determine whether exhaled gases could discriminate between cancer and noncancer. Discrimination between classes was performed using Mahalanobis distance. Support vector machine analysis was used to create and apply a cancer prediction model prospectively in a separate group of 76 individuals, 14 with and 62 without cancer. Main Results: Principal components and canonic discriminant analysis demonstrated discrimination between samples from patients with lung cancer and those from other groups. In the validation study, the electronic nose had 71.4% sensitivity and 91.9% specificity for detecting lung cancer; positive and negative predictive values were 66.6 and 93.4%, respectively. In this population with a lung cancer prevalence of 18%, positive and negative predictive values were 66.6 and 94.5%, respectively. Conclusion: The exhaled breath of patients with lung cancer has distinct characteristics that can be identified with an electronic nose. The results provide feasibility to the concept of using the electronic nose for managing and detecting lung cancer. PMID:15750044
Barriers to Breast and Cervical Cancer Screening in Singapore: a Mixed Methods Analysis.
Malhotra, Chetna; Bilger, Marcel; Liu, Joy; Finkelstein, Eric
2016-01-01
In order to increase breast and cervical cancer screening uptake in Singapore, women's perceived barriers to screening need to be identified and overcome. Using data from both focus groups and surveys, we aimed to assess perceived barriers and motivations for breast and cervical cancer screening. We conducted 8 focus groups with 64 women, using thematic analysis to identify overarching themes related to women's attitudes towards screening. Based on recurring themes from focus groups, several hypotheses regarding potential barriers and motivations to screen were generated and tested through a national survey of 801 women aged 25-64. Focus group participants had misconceptions related to screening, believing that the procedures were painful. Cost was an issue, as well as efficacy and fatalism. By identifying barriers to and motivators for screening through a mixed-method design that has both nuance and external validity, this study offers valuable suggestions to policymakers to improve breast and cervical cancer screening uptake in Singapore.
Parameters analysis of a porous medium model for treatment with hyperthermia using OpenMP
NASA Astrophysics Data System (ADS)
Freitas Reis, Ruy; dos Santos Loureiro, Felipe; Lobosco, Marcelo
2015-09-01
Cancer is the second cause of death in the world so treatments have been developed trying to work around this world health problem. Hyperthermia is not a new technique, but its use in cancer treatment is still at early stage of development. This treatment is based on overheat the target area to a threshold temperature that causes cancerous cell necrosis and apoptosis. To simulate this phenomenon using magnetic nanoparticles in an under skin cancer treatment, a three-dimensional porous medium model was adopted. This study presents a sensibility analysis of the model parameters such as the porosity and blood velocity. To ensure a second-order solution approach, a 7-points centered finite difference method was used for space discretization while a predictor-corrector method was used to time evolution. Due to the massive computations required to find the solution of a three-dimensional model, this paper also presents a first attempt to improve performance using OpenMP, a parallel programming API.
Randomization in cancer clinical trials: permutation test and development of a computer program.
Ohashi, Y
1990-01-01
When analyzing cancer clinical trial data where the treatment allocation is done using dynamic balancing methods such as the minimization method for balancing the distribution of important prognostic factors in each arm, conservativeness occurs if such a randomization scheme is ignored and a simple unstratified analysis is carried out. In this paper, the above conservativeness is demonstrated by computer simulation, and the development of a computer program that carries out permutation tests of the log-rank statistics for clinical trial data where the allocation is done by the minimization method or a stratified permuted block design is introduced. We are planning to use this program in practice to supplement a usual stratified analysis and model-based methods such as the Cox regression. The most serious problem in cancer clinical trials in Japan is how to carry out the quality control or data management in trials that are initiated and conducted by researchers without support from pharmaceutical companies. In the final section of this paper, one international collaborative work for developing international guidelines on data management in clinical trials of bladder cancer is briefly introduced, and the differences between the system adopted in US/European statistical centers and the Japanese system is described. PMID:2269216
Akuoko, Cynthia Pomaa; Armah, Ernestina; Sarpong, Theresa; Quansah, Dan Yedu; Amankwaa, Isaac
2017-01-01
Background Breast cancer (BC) has been described as the leading cause of cancer deaths among women especially in the developing world including sub Saharan Africa (SSA). Delayed presentation and late diagnosis at health facilities are parts of the contributing factors of high BC mortality in Africa. This review aimed to appraise the contributing factors to delayed breast cancer presentation and diagnosis among SSA women. Methods Five databases encompassing medical and social sciences were systematically searched using predefined search terms linked with breast cancer presentation and diagnosis and sub Saharan Africa. Reference lists of relevant papers were also hand searched. Quality of quantitative and qualitative articles were assessed using the National Institute of Health (NIH) Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies and the Critical Appraisal Skills Programme (CASP) quality appraisal checklist. Thematic analysis was used to synthesize the qualitative studies to integrate findings. Results Fourteen (14) quantitative studies, two (2) qualitative studies and one (1) mixed method study merited inclusion for analysis. This review identified low knowledge of breast cancer among SSA women. This review also found lack of awareness of early detection treatment, poor perception of BC, socio-cultural factors such as belief, traditions and fear as factors impacting African women’s health seeking behavior in relation to breast cancer. Conclusion Improving African women’s knowledge and understanding will improve behaviors related to breast cancer and facilitate early presentation and detection and enhance proper management and treatment of breast cancer. PMID:28192444
Katanoda, Kota; Kamo, Ken-Ichi; Tsugane, Shoichiro
2016-01-01
A thyroid ultrasound examination programme has been conducted in Fukushima Prefecture, Japan, after the nuclear disaster in 2011. Although remarkably high prevalence of thyroid cancer was observed, no relevant quantitative evaluation was conducted. We calculated the observed/expected (O/E) ratio of thyroid cancer prevalence for the residents aged ≤20 years. Observed prevalence was the number of thyroid cancer cases detected by the programme through the end of April 2015. Expected prevalence was calculated as cumulative incidence by a life-table method using the national estimates of thyroid cancer incidence rate in 2001–10 (prior to the disaster) and the population of Fukushima Prefecture. The underlying assumption was that there was neither nuclear accident nor screening intervention. The observed and estimated prevalence of thyroid cancer among residents aged ≤20 years was 160.1 and 5.2, respectively, giving an O/E ratio of 30.8 [95% confidence interval (CI): 26.2, 35.9]. When the recent increasing trend in thyroid cancer was considered, the overall O/E ratio was 22.2 (95% CI: 18.9, 25.9). The cumulative number of thyroid cancer deaths in Fukushima Prefecture, estimated with the same method (annual average in 2009–13), was 0.6 under age 40. Combined with the existing knowledge about radiation effect on thyroid cancer, our descriptive analysis suggests the possibility of overdiagnosis. Evaluation including individual-level analysis is required to further clarify the contribution of underlying factors. PMID:26755830
Breast Cancer Status in Iran: Statistical Analysis of 3010 Cases between 1998 and 2014
Akbari, Mohammad Esmaeil; Sayad, Saed; Khayamzadeh, Maryam; Shojaee, Leila; Shormeji, Zeynab; Amiri, Mojtaba
2017-01-01
Background Breast cancer is the 5th leading cause of cancer death in Iranian women. This study analyzed 3010 women with breast cancer that had been referred to a cancer research center in Tehran between 1998 and 2014. Methods In this retrospective study, we analyzed 3010 breast cancer cases with 32 clinical and paraclinical attributes. We checked the data quality rigorously and removed any invalid values or records. The method was data mining (problem definition, data preparation, data exploration, modeling, evaluation, and deployment). However, only the descriptive analyses' results of the variables are presented in this article. To our knowledge, this is the most comprehensive study on breast cancer status in Iran. Results A typical Iranian breast cancer patient has been a 40–50-year-old married woman with two children, who has a high school diploma and no history of abortion, smoking, or diabetes. Most patients were estrogen and progesterone receptor positive, human epidermal growth factor (HER) negative, and P53 negative. Most cases were detected in stage 2 with intermediate grade. Conclusion This study revealed original findings which can be used in national policymaking to find the best early detection method and improve the care quality and breast cancer prevention in Iran. PMID:29201466
El Mhamdi, Sana; Bouanene, Ines; Mhirsi, Amel; Sriha, Asma; Ben Salem, Kamel; Soltani, Mohamed Soussi
2013-01-01
Breast cancer remains a worldwide public health problem. In Tunisia, it is considered to be the primary women's cancer and causes high morbidity and mortality. This study aimed to investigate female knowledge, attitudes and practice of breast cancer screening in the region of Monastir (Tunisia). We conducted a descriptive cross-sectional design exploring knowledge, attitudes and practices of women in the region of Monastir on breast cancer screening. The study was conducted in health centres of this region from 1 March 2009 to 30 June 2009. Data were collected via a structured questionnaire containing 15 items on demographic status, knowledge of risk factors and screening methods and attitudes towards the relevance and effectiveness of breast cancer screening. A scoring scheme was used to score women's responses. A total of 900 women agreed to take part in the study. Their mean age was 41.6±12.4 years and 64% did not exceed the primary level of education. According to the constructed scores, 92% of participants had poor knowledge of the specific risk factors for breast cancer and 63.2% had poor knowledge of the screening methods. Proper practice of breast cancer screening was observed in 14.3% of cases. Multiple logistic regression analysis showed that good knowledge of risk factors and screening methods, higher level of education and positive family history of breast cancer were independently correlated with breast cancer screening practice. This study revealed poor knowledge of breast cancer and the screening methods as well as low levels of practice of breast cancer screening among women in the region of Monastir. Results justify educational programs to raise women's adherence to breast cancer screening programs in Tunisia.
Park, Ji Hyun; Kim, Hyeon-Young; Lee, Hanna; Yun, Eun Kyoung
2015-12-01
This study compares the performance of the logistic regression and decision tree analysis methods for assessing the risk factors for infection in cancer patients undergoing chemotherapy. The subjects were 732 cancer patients who were receiving chemotherapy at K university hospital in Seoul, Korea. The data were collected between March 2011 and February 2013 and were processed for descriptive analysis, logistic regression and decision tree analysis using the IBM SPSS Statistics 19 and Modeler 15.1 programs. The most common risk factors for infection in cancer patients receiving chemotherapy were identified as alkylating agents, vinca alkaloid and underlying diabetes mellitus. The logistic regression explained 66.7% of the variation in the data in terms of sensitivity and 88.9% in terms of specificity. The decision tree analysis accounted for 55.0% of the variation in the data in terms of sensitivity and 89.0% in terms of specificity. As for the overall classification accuracy, the logistic regression explained 88.0% and the decision tree analysis explained 87.2%. The logistic regression analysis showed a higher degree of sensitivity and classification accuracy. Therefore, logistic regression analysis is concluded to be the more effective and useful method for establishing an infection prediction model for patients undergoing chemotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.
The relationship between selenium levels and breast cancer: a systematic review and meta-analysis.
Babaknejad, Nasim; Sayehmiri, Fatemeh; Sayehmiri, Kourosh; Rahimifar, Parya; Bahrami, Somaye; Delpesheh, Ali; Hemati, Farhad; Alizadeh, Sajjad
2014-06-01
Breast cancer is the most common cancer type. In several studies, hints have been provided that there is a correlation between selenium deficiency and the incidence of breast cancer. Findings of these published reports are, however, inconsistent. This study serves as a pioneering study aiming at combining the results of studies using a meta-analytic method. A total of 16 articles published between 1980 and 2012 worldwide were selected through searching PubMed, Scopus, and Google scholar databases, and the information were analyzed using a meta-analytic method [random effects model]. I (2) statistics were used to examine heterogeneity. The information was then analyzed by STATA version 12. In this study, due to the non-uniform methods used to measure selenium concentrations, selenium levels were measured in the various subgroups in both case and control groups. There were significant correlations between selenium concentration and breast cancer [P<0.05]. Hence, the mean risk differentiating criteria were estimated to be 0.63 [95% confidence interval [95% CI] 0.93 to 0.32] in serum and toenails. Subgroup analysis showed that the value in toenails was -0.07 [95% CI -0.16 to 0.03] and in serum -1.04 [95% CI 1.71 to -0.38]. In studies in which selenium concentrations were measured in serum, a significant correlation was observed between selenium concentration and breast cancer. In contrast, in studies in which selenium concentration was measured in toenails, the correlation was not significant. Therefore, the selenium concentration can be used as one predictor for breast cancer.
Gripsrud, Birgitta Haga; Brassil, Kelly J; Summers, Barbara; Søiland, Håvard; Kronowitz, Steven; Lode, Kirsten
2015-01-01
Background Expressive writing has been shown to improve quality of life, fatigue, and post-traumatic stress among breast cancer patients across cultures. Understanding how and why the method may be beneficial to patients can increase awareness of the psychosocial impact of breast cancer and enhance interventional work within this population. Qualitative research on experiential aspects of interventions may inform the theoretical understanding, and generate hypotheses for future studies. Aim To explore and describe the experience and feasibility of expressive writing among women with breast cancer following mastectomy and immediate or delayed reconstructive surgery. Methods Seven participants enrolled to undertake 4 episodes of expressive writing at home, with semi-structured interviews conducted afterwards and analyzed using experiential thematic analysis. Results Three themes emerged through analysis: writing as process, writing as therapeutic, and writing as a means to help others. Implications for practice This study augments existing evidence to support the appropriateness of expressive writing as an intervention after a breast cancer diagnosis. Further studies should evaluate its feasibility at different time points in survivorship. Conclusions Findings illuminate experiential variations in expressive writing and how storytelling encourages a release of cognitive and emotional strains, surrendering these to reside in the text. The method was said to process feelings and capture experiences tied to a new and overwhelming illness situation, as impressions became expressions through writing. Expressive writing, therefore, is a valuable tool for health care providers to introduce into the plan of care for patients with breast cancer, and potentially other cancer patient groups. PMID:26390074
2011-01-01
Background Copy number aberrations (CNAs) are an important molecular signature in cancer initiation, development, and progression. However, these aberrations span a wide range of chromosomes, making it hard to distinguish cancer related genes from other genes that are not closely related to cancer but are located in broadly aberrant regions. With the current availability of high-resolution data sets such as single nucleotide polymorphism (SNP) microarrays, it has become an important issue to develop a computational method to detect driving genes related to cancer development located in the focal regions of CNAs. Results In this study, we introduce a novel method referred to as the wavelet-based identification of focal genomic aberrations (WIFA). The use of the wavelet analysis, because it is a multi-resolution approach, makes it possible to effectively identify focal genomic aberrations in broadly aberrant regions. The proposed method integrates multiple cancer samples so that it enables the detection of the consistent aberrations across multiple samples. We then apply this method to glioblastoma multiforme and lung cancer data sets from the SNP microarray platform. Through this process, we confirm the ability to detect previously known cancer related genes from both cancer types with high accuracy. Also, the application of this approach to a lung cancer data set identifies focal amplification regions that contain known oncogenes, though these regions are not reported using a recent CNAs detecting algorithm GISTIC: SMAD7 (chr18q21.1) and FGF10 (chr5p12). Conclusions Our results suggest that WIFA can be used to reveal cancer related genes in various cancer data sets. PMID:21569311
Fingerprinting Breast Cancer vs. Normal Mammary Cells by Mass Spectrometric Analysis of Volatiles
NASA Astrophysics Data System (ADS)
He, Jingjing; Sinues, Pablo Martinez-Lozano; Hollmén, Maija; Li, Xue; Detmar, Michael; Zenobi, Renato
2014-06-01
There is increasing interest in the development of noninvasive diagnostic methods for early cancer detection, to improve the survival rate and quality of life of cancer patients. Identification of volatile metabolic compounds may provide an approach for noninvasive early diagnosis of malignant diseases. Here we analyzed the volatile metabolic signature of human breast cancer cell lines versus normal human mammary cells. Volatile compounds in the headspace of conditioned culture medium were directly fingerprinted by secondary electrospray ionization-mass spectrometry. The mass spectra were subsequently treated statistically to identify discriminating features between normal vs. cancerous cell types. We were able to classify different samples by using feature selection followed by principal component analysis (PCA). Additionally, high-resolution mass spectrometry allowed us to propose their chemical structures for some of the most discriminating molecules. We conclude that cancerous cells can release a characteristic odor whose constituents may be used as disease markers.
Coquet, Julia Becaria; Tumas, Natalia; Osella, Alberto Ruben; Tanzi, Matteo; Franco, Isabella; Diaz, Maria Del Pilar
2016-01-01
A number of studies have evidenced the effect of modifiable lifestyle factors such as diet, breastfeeding and nutritional status on breast cancer risk. However, none have addressed the missing data problem in nutritional epidemiologic research in South America. Missing data is a frequent problem in breast cancer studies and epidemiological settings in general. Estimates of effect obtained from these studies may be biased, if no appropriate method for handling missing data is applied. We performed Multiple Imputation for missing values on covariates in a breast cancer case-control study of Córdoba (Argentina) to optimize risk estimates. Data was obtained from a breast cancer case control study from 2008 to 2015 (318 cases, 526 controls). Complete case analysis and multiple imputation using chained equations were the methods applied to estimate the effects of a Traditional dietary pattern and other recognized factors associated with breast cancer. Physical activity and socioeconomic status were imputed. Logistic regression models were performed. When complete case analysis was performed only 31% of women were considered. Although a positive association of Traditional dietary pattern and breast cancer was observed from both approaches (complete case analysis OR=1.3, 95%CI=1.0-1.7; multiple imputation OR=1.4, 95%CI=1.2-1.7), effects of other covariates, like BMI and breastfeeding, were only identified when multiple imputation was considered. A Traditional dietary pattern, BMI and breastfeeding are associated with the occurrence of breast cancer in this Argentinean population when multiple imputation is appropriately performed. Multiple Imputation is suggested in Latin America’s epidemiologic studies to optimize effect estimates in the future. PMID:27892664
The Effect of XPD Polymorphisms on Digestive Tract Cancers Risk: A Meta-Analysis
Zhang, Qian; Chen, Zhipeng; Lu, Kai; Shu, Yongqian; Chen, Tao; Zhu, Lingjun
2014-01-01
Background The Xeroderma pigmento-sum group D gene (XPD) plays a key role in nucleotide excision repair. Single nucleotide polymorphisms (SNP) located in its functional region may alter DNA repair capacity phenotype and cancer risk. Many studies have demonstrated that XPD polymorphisms are significantly associated with digestive tract cancers risk, but the results are inconsistent. We conducted a comprehensive meta-analysis to assess the association between XPD Lys751Gln polymorphism and digestive tract cancers risk. The digestive tract cancers that our study referred to, includes oral cancer, esophageal cancer, gastric cancer and colorectal cancer. Methods We searched PubMed and EmBase up to December 31, 2012 to identify eligible studies. A total of 37 case-control studies including 9027 cases and 16072 controls were involved in this meta-analysis. Statistical analyses were performed with Stata software (version 11.0, USA). Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of the association. Results The results showed that XPD Lys751Gln polymorphism was associated with the increased risk of digestive tract cancers (homozygote comparison (GlnGln vs. LysLys): OR = 1.12, 95% CI = 1.01–1.24, P = 0.029, P heterogeneity = 0.133). We found no statistical evidence for a significantly increased digestive tract cancers risk in the other genetic models. In the subgroup analysis, we also found the homozygote comparison increased the susceptibility of Asian population (OR = 1.28, 95% CI = 1.01–1.63, P = 0.045, P heterogeneity = 0.287). Stratified by cancer type and source of control, no significantly increased cancer risk was found in these subgroups. Additionally, risk estimates from hospital-based studies and esophageal studies were heterogeneous. Conclusions Our meta-analysis suggested that the XPD 751Gln/Gln genotype was a low-penetrate risk factor for developing digestive tract cancers, especially in Asian populations. PMID:24787743
Health Behaviors and Quality of Life Among Colorectal Cancer Survivors
Rohan, Elizabeth A.; Townsend, Julie S.; Fairley, Temeika L.; Stewart, Sherri L.
2015-01-01
Purpose To examine, at the population level, health behaviors, comorbidities, and health-related quality of life among colorectal cancer (CRC) survivors compared with other cancer survivors and persons without cancer. Methods We used data from the 2009 and 2010 Behavioral Risk Factor Surveillance System cancer survivor modules. We calculated descriptive statistics, conducted chi-square tests for comparisons, and used multivariable logistic regression analysis to compare CRC survivors with other cancer survivors and persons without cancer. Results Of the 52,788 cancer survivors included in this analysis, 4001 reported being CRC survivors. When compared with other cancer survivors, CRC survivors reported higher percentages of obesity and lack of physical activity; however, they had lower levels of current smoking. Adjusted results show that CRC survivors were significantly more likely to report lack of physical activity, fair/poor health, and other chronic health conditions compared with persons without a cancer diagnosis. Conversely, CRC survivors reported lower levels of current smoking than persons without cancer. Conclusions CRC survivors have a higher proportion of heath conditions and behaviors that may significantly increase their risks for recurrence or development of a second cancer. Targeted interventions to address these health issues should be considered. PMID:25736006
The Clinicopathological Significance of MicroRNA-155 in Breast Cancer: A Meta-Analysis
Zeng, Hui; Fang, Cheng; Nam, Seungyoon; Cai, Qing; Long, Xinghua
2014-01-01
Objective. Previous studies demonstrated that the associations between expression level of microRNA-155 (miR-155) and clinicopathological significance of breast cancer remained inconsistent. Therefore, we performed a meta-analysis based on eligible studies to summarize the possible associations. Methods. We identified eligible studies published up to May 2014 by a comprehensive search of PubMed, EMBASE, CNKI, and VIP databases. The analysis was performed with RevMan. 5.0 software. Results. A total of 15 studies were included. The results of meta-analysis showed that miR-155 was positively correlated with breast cancer with standardized mean difference (SMD) = 1.22. Elevated miR-155 was found in Her-2 positive or lymph node metastasis positive, or p53 mutant type breast cancer. But the result showed to be insignificant in TNM comparison. With respect to estrogen receptor alpha (ER) and progesterone receptor (PR) status, both of them showed significant associations with SMD = −1.2 and −1.85, respectively. Conclusion. MiR-155 detection might have a diagnostic value in breast cancer patients. It might be used as an auxiliary biomarker for different clinicopathological breast cancer. PMID:25157366
Selective isolation and noninvasive analysis of circulating cancer stem cells through Raman imaging.
Cho, Hyeon-Yeol; Hossain, Md Khaled; Lee, Jin-Ho; Han, Jiyou; Lee, Hun Joo; Kim, Kyeong-Jun; Kim, Jong-Hoon; Lee, Ki-Bum; Choi, Jeong-Woo
2018-04-15
Circulating cancer stem cells (CCSCs), a rare circulating tumor cell (CTC) type, recently arose as a useful resource for monitoring and characterizing both cancers and their metastatic derivatives. However, due to the scarcity of CCSCs among hematologic cells in the blood and the complexity of the phenotype confirmation process, CCSC research can be extremely challenging. Hence, we report a nanoparticle-mediated Raman imaging method for CCSC characterization which profiles CCSCs based on their surface marker expression phenotypes. We have developed an integrated combinatorial Raman-Active Nanoprobe (RAN) system combined with a microfluidic chip to successfully process complete blood samples. CCSCs and CTCs were detected (90% efficiency) and classified in accordance with their respective surface marker expression via completely distinct Raman signals of RANs. Selectively isolated CCSCs (93% accuracy) were employed for both in vitro and in vivo tumor phenotyping to identify the tumorigenicity of the CCSCs. We utilized our new method to predict metastasis by screening blood samples from xenograft models, showing that upon CCSC detection, all subjects exhibited liver metastasis. Having highly efficient detection and noninvasive isolation capabilities, we have demonstrated that our RAN-based Raman imaging method will be valuable for predicting cancer metastasis and relapse via CCSC detection. Moreover, the exclusion of peak overlapping in CCSC analysis with our Raman imaging method will allow to expand the RAN families for various cancer types, therefore, increasing therapeutic efficacy by providing detailed molecular features of tumor subtypes. Copyright © 2017 Elsevier B.V. All rights reserved.
Parents’ Perceptions of Skin Cancer Threat and Children’s Physical Activity
Tran, Alexander D.; Aalborg, Jenny; Asdigian, Nancy L.; Morelli, Joseph G.; Mokrohisky, Stefan T.; Dellavalle, Robert P.; Berwick, Marianne; Box, Neil F.
2012-01-01
Introduction Sun exposure is a major risk factor for skin cancer, but without physical activity, children are at risk of childhood obesity. The objective of this study was to explore relationships between parental perceptions of skin cancer threat, sun protection behaviors, physical activity, and body mass index (BMI) in children. Methods This is a cross-sectional analysis nested within the Colorado Kids Sun Care Program sun safety intervention trial. In summer 2007, parent telephone interviews provided data on demographics, perceptions of skin cancer threat, sun protection behaviors, and physical activity. Physical examinations provided data on phenotype, freckling, and BMI. Data from 999 Colorado children born in 1998 were included in analysis. We used analysis of variance, Spearman’s rho (ρ) correlation, and multivariable linear regression analysis to evaluate relationships with total amount of outdoor physical activity. Results After controlling for sex, race/ethnicity, skin color, and sun protection, regression analysis showed that each unit increase in perceived severity of nonmelanoma skin cancer was associated with a 30% increase in hours of outdoor physical activity (P = .005). Hours of outdoor physical activity were not related to perceived severity of melanoma or perceived susceptibility to skin cancer. BMI-for-age was not significantly correlated with perceptions of skin cancer threat, use of sun protection, or level of physical activity. Conclusion The promotion of sun safety is not likely to inhibit physical activity. Skin cancer prevention programs should continue to promote midday sun avoidance and sun protection during outdoor activities. PMID:22935145
Tumor Content Chart-Assisted HER2/CEP17 Digital PCR Analysis of Gastric Cancer Biopsy Specimens.
Matsusaka, Keisuke; Ishikawa, Shumpei; Nakayama, Atsuhito; Ushiku, Tetsuo; Nishimoto, Aiko; Urabe, Masayuki; Kaneko, Nobuyuki; Kunita, Akiko; Kaneda, Atsushi; Aburatani, Hiroyuki; Fujishiro, Mitsuhiro; Seto, Yasuyuki; Fukayama, Masashi
2016-01-01
Evaluating HER2 gene amplification is an essential component of therapeutic decision-making for advanced or metastatic gastric cancer. A simple method that is applicable to small, formalin-fixed, paraffin-embedded biopsy specimens is desirable as an adjunct to or as a substitute for currently used HER2 immunohistochemistry and in situ hybridization protocols. In this study, we developed a microfluidics-based digital PCR method for determining HER2 and chromosome 17 centromere (CEP17) copy numbers and estimating tumor content ratio (TCR). The HER2/CEP17 ratio is determined by three variables-TCR and absolute copy numbers of HER2 and CEP17-by examining tumor cells; only the ratio of the latter two can be obtained by digital PCR using the whole specimen without purifying tumor cells. TCR was determined by semi-automatic image analysis. We developed a Tumor Content chart, which is a plane of rectangular coordinates consisting of HER2/CEP17 digital PCR data and TCR that delineates amplified, non-amplified, and equivocal areas. By applying this method, 44 clinical gastric cancer biopsy samples were classified as amplified (n = 13), non-amplified (n = 25), or equivocal (n = 6). By comparison, 11 samples were positive, 11 were negative, and 22 were equivocally immunohistochemistry. Thus, our novel method reduced the number of equivocal samples from 22 to 6, thereby obviating the need for confirmation by fluorescence or dual-probe in situ hybridization to < 30% of cases. Tumor content chart-assisted digital PCR analysis is also applicable to multiple sites in surgically resected tissues. These results indicate that this analysis is a useful alternative to HER2 immunohistochemistry in gastric cancers that can serve as a basis for the automated evaluation of HER2 status.
Tumor Content Chart-Assisted HER2/CEP17 Digital PCR Analysis of Gastric Cancer Biopsy Specimens
Matsusaka, Keisuke; Ishikawa, Shumpei; Nakayama, Atsuhito; Ushiku, Tetsuo; Nishimoto, Aiko; Urabe, Masayuki; Kaneko, Nobuyuki; Kunita, Akiko; Kaneda, Atsushi; Aburatani, Hiroyuki; Fujishiro, Mitsuhiro; Seto, Yasuyuki; Fukayama, Masashi
2016-01-01
Evaluating HER2 gene amplification is an essential component of therapeutic decision-making for advanced or metastatic gastric cancer. A simple method that is applicable to small, formalin-fixed, paraffin-embedded biopsy specimens is desirable as an adjunct to or as a substitute for currently used HER2 immunohistochemistry and in situ hybridization protocols. In this study, we developed a microfluidics-based digital PCR method for determining HER2 and chromosome 17 centromere (CEP17) copy numbers and estimating tumor content ratio (TCR). The HER2/CEP17 ratio is determined by three variables—TCR and absolute copy numbers of HER2 and CEP17—by examining tumor cells; only the ratio of the latter two can be obtained by digital PCR using the whole specimen without purifying tumor cells. TCR was determined by semi-automatic image analysis. We developed a Tumor Content chart, which is a plane of rectangular coordinates consisting of HER2/CEP17 digital PCR data and TCR that delineates amplified, non-amplified, and equivocal areas. By applying this method, 44 clinical gastric cancer biopsy samples were classified as amplified (n = 13), non-amplified (n = 25), or equivocal (n = 6). By comparison, 11 samples were positive, 11 were negative, and 22 were equivocally immunohistochemistry. Thus, our novel method reduced the number of equivocal samples from 22 to 6, thereby obviating the need for confirmation by fluorescence or dual-probe in situ hybridization to < 30% of cases. Tumor content chart-assisted digital PCR analysis is also applicable to multiple sites in surgically resected tissues. These results indicate that this analysis is a useful alternative to HER2 immunohistochemistry in gastric cancers that can serve as a basis for the automated evaluation of HER2 status. PMID:27119558
Omics Profiling in Precision Oncology*
Yu, Kun-Hsing; Snyder, Michael
2016-01-01
Cancer causes significant morbidity and mortality worldwide, and is the area most targeted in precision medicine. Recent development of high-throughput methods enables detailed omics analysis of the molecular mechanisms underpinning tumor biology. These studies have identified clinically actionable mutations, gene and protein expression patterns associated with prognosis, and provided further insights into the molecular mechanisms indicative of cancer biology and new therapeutics strategies such as immunotherapy. In this review, we summarize the techniques used for tumor omics analysis, recapitulate the key findings in cancer omics studies, and point to areas requiring further research on precision oncology. PMID:27099341
Proteomics analysis of human breast milk to assess breast cancer risk.
Aslebagh, Roshanak; Channaveerappa, Devika; Arcaro, Kathleen F; Darie, Costel C
2018-02-01
Detection of breast cancer (BC) in young women is challenging because mammography, the most common tool for detecting BC, is not effective on the dense breast tissue characteristic of young women. In addition to the limited means for detecting their BC, young women face a transient increased risk of pregnancy-associated BC. As a consequence, reproductively active women could benefit significantly from a tool that provides them with accurate risk assessment and early detection of BC. One potential method for detection of BC is biochemical monitoring of proteins and other molecules in bodily fluids such as serum, nipple aspirate, ductal lavage, tear, urine, saliva and breast milk. Of all these fluids, only breast milk provides access to a large volume of breast tissue, in the form of exfoliated epithelial cells, and to the local breast environment, in the form of molecules in the milk. Thus, analysis of breast milk is a non-invasive method with significant potential for assessing BC risk. Here we analyzed human breast milk by mass spectrometry (MS)-based proteomics to build a biomarker signature for early detection of BC. Ten milk samples from eight women provided five paired-groups (cancer versus control) for analysis of dysregulatedproteins: two within woman comparisons (milk from a diseased breast versus a healthy breast of the same woman) and three across women comparisons (milk from a woman with cancer versus a woman without cancer). Despite a wide range in the time between milk donation and cancer diagnosis (cancer diagnosis occurred from 1 month before to 24 months after milk donation), the levels of some proteins differed significantly between cancer and control in several of the five comparison groups. These pilot data are supportive of the idea that molecular analysis of breast milk will identify proteins informative for early detection and accurate assessment of BC risk, and warrant further research. Data are available via ProteomeXchange with identifier PXD007066. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Integration of multimodal RNA-seq data for prediction of kidney cancer survival
Schwartzi, Matt; Parkl, Martin; Phanl, John H.; Wang., May D.
2016-01-01
Kidney cancer is of prominent concern in modern medicine. Predicting patient survival is critical to patient awareness and developing a proper treatment regimens. Previous prediction models built upon molecular feature analysis are limited to just gene expression data. In this study we investigate the difference in predicting five year survival between unimodal and multimodal analysis of RNA-seq data from gene, exon, junction, and isoform modalities. Our preliminary findings report higher predictive accuracy-as measured by area under the ROC curve (AUC)-for multimodal learning when compared to unimodal learning with both support vector machine (SVM) and k-nearest neighbor (KNN) methods. The results of this study justify further research on the use of multimodal RNA-seq data to predict survival for other cancer types using a larger sample size and additional machine learning methods. PMID:27532026
Tumor purity and differential methylation in cancer epigenomics.
Wang, Fayou; Zhang, Naiqian; Wang, Jun; Wu, Hao; Zheng, Xiaoqi
2016-11-01
DNA methylation is an epigenetic modification of DNA molecule that plays a vital role in gene expression regulation. It is not only involved in many basic biological processes, but also considered an important factor for tumorigenesis and other human diseases. Study of DNA methylation has been an active field in cancer epigenomics research. With the advances of high-throughput technologies and the accumulation of enormous amount of data, method development for analyzing these data has gained tremendous interests in the fields of computational biology and bioinformatics. In this review, we systematically summarize the recent developments of computational methods and software tools in high-throughput methylation data analysis with focus on two aspects: differential methylation analysis and tumor purity estimation in cancer studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset.
Detection and characterization of translational research in cancer and cardiovascular medicine
2011-01-01
Background Scientists and experts in science policy have become increasingly interested in strengthening translational research. Efforts to understand the nature of translational research and monitor policy interventions face an obstacle: how can translational research be defined in order to facilitate analysis of it? We describe methods of scientometric analysis that can do this. Methods We downloaded bibliographic and citation data from all articles published in 2009 in the 75 leading journals in cancer and in cardiovascular medicine (roughly 15,000 articles for each field). We calculated citation relationships between journals and between articles and we extracted the most prevalent natural language concepts. Results Network analysis and mapping revealed polarization between basic and clinical research, but with translational links between these poles. The structure of the translational research in cancer and cardiac medicine is, however, quite different. In the cancer literature the translational interface is composed of different techniques (e.g., gene expression analysis) that are used across the various subspecialties (e.g., specific tumor types) within cancer research and medicine. In the cardiac literature, the clinical problems are more disparate (i.e., from congenital anomalies to coronary artery disease); although no distinctive translational interface links these fields, translational research does occur in certain subdomains, especially in research on atherosclerosis and hypertension. Conclusions These techniques can be used to monitor the continuing evolution of translational research in medicine and the impact of interventions designed to enhance it. PMID:21569299
Song, Ehwang; Gao, Yuqian; Wu, Chaochao; ...
2017-07-19
Here, mass spectrometry (MS) based targeted proteomic methods such as selected reaction monitoring (SRM) are becoming the method of choice for preclinical verification of candidate protein biomarkers. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute has investigated the standardization and analytical validation of the SRM assays and demonstrated robust analytical performance on different instruments across different laboratories. An Assay Portal has also been established by CPTAC to provide the research community a resource consisting of large set of targeted MS-based assays, and a depository to share assays publicly, providing that assays meet the guidelines proposed bymore » CPTAC. Herein, we report 98 SRM assays covering 70 candidate protein biomarkers previously reported as associated with ovarian cancer that have been thoroughly characterized according to the CPTAC Assay Characterization Guidance Document. The experiments, methods and results for characterizing these SRM assays for their MS response, repeatability, selectivity, stability, and reproducible detection of endogenous analytes are described in detail.« less
Cancer cell profiling by barcoding allows multiplexed protein analysis in fine-needle aspirates.
Ullal, Adeeti V; Peterson, Vanessa; Agasti, Sarit S; Tuang, Suan; Juric, Dejan; Castro, Cesar M; Weissleder, Ralph
2014-01-15
Immunohistochemistry-based clinical diagnoses require invasive core biopsies and use a limited number of protein stains to identify and classify cancers. We introduce a technology that allows analysis of hundreds of proteins from minimally invasive fine-needle aspirates (FNAs), which contain much smaller numbers of cells than core biopsies. The method capitalizes on DNA-barcoded antibody sensing, where barcodes can be photocleaved and digitally detected without any amplification steps. After extensive benchmarking in cell lines, this method showed high reproducibility and achieved single-cell sensitivity. We used this approach to profile ~90 proteins in cells from FNAs and subsequently map patient heterogeneity at the protein level. Additionally, we demonstrate how the method could be used as a clinical tool to identify pathway responses to molecularly targeted drugs and to predict drug response in patient samples. This technique combines specificity with ease of use to offer a new tool for understanding human cancers and designing future clinical trials.
Cancer cell profiling by barcoding allows multiplexed protein analysis in fine needle aspirates
Ullal, Adeeti V.; Peterson, Vanessa; Agasti, Sarit S.; Tuang, Suan; Juric, Dejan; Castro, Cesar M.; Weissleder, Ralph
2014-01-01
Immunohistochemistry-based clinical diagnoses require invasive core biopsies and use a limited number of protein stains to identify and classify cancers. Here, we introduce a technology that allows analysis of hundreds of proteins from minimally invasive fine needle aspirates (FNA), which contain much smaller numbers of cells than core biopsies. The method capitalizes on DNA-barcoded antibody sensing where barcodes can be photo-cleaved and digitally detected without any amplification steps. Following extensive benchmarking in cell lines, this method showed high reproducibility and achieved single cell sensitivity. We used this approach to profile ~90 proteins in cells from FNAs and subsequently map patient heterogeneity at the protein level. Additionally, we demonstrate how the method could be used as a clinical tool to identify pathway responses to molecularly targeted drugs and to predict drug response in patient samples. This technique combines specificity with ease of use to offer a new tool for understanding human cancers and designing future clinical trials. PMID:24431113
Ultrasound-contrast-agent dispersion and velocity imaging for prostate cancer localization.
van Sloun, Ruud Jg; Demi, Libertario; Postema, Arnoud W; de la Rosette, Jean Jmch; Wijkstra, Hessel; Mischi, Massimo
2017-01-01
Prostate cancer (PCa) is the second-leading cause of cancer death in men; however, reliable tools for detection and localization are still lacking. Dynamic Contrast Enhanced UltraSound (DCE-US) is a diagnostic tool that is suitable for analysis of vascularization, by imaging an intravenously injected microbubble bolus. The localization of angiogenic vascularization associated with the development of tumors is of particular interest. Recently, methods for the analysis of the bolus convective dispersion process have shown promise to localize angiogenesis. However, independent estimation of dispersion was not possible due to the ambiguity between convection and dispersion. Therefore, in this study we propose a new method that considers the vascular network as a dynamic linear system, whose impulse response can be locally identified. To this end, model-based parameter estimation is employed, that permits extraction of the apparent dispersion coefficient (D), velocity (v), and Péclet number (Pe) of the system. Clinical evaluation using data recorded from 25 patients shows that the proposed method can be applied effectively to DCE-US, and is able to locally characterize the hemodynamics, yielding promising results (receiver-operating-characteristic curve area of 0.84) for prostate cancer localization. Copyright © 2016 Elsevier B.V. All rights reserved.
Kim, Dohyun; Lee, Mi Hee; Koo, Min-Ah; Kwon, Byeong-Ju; Kim, Min Sung; Seon, Gyeung Mi; Hong, Seung Hee; Park, Jong-Chul
2018-06-13
Systemic injection of a photosensitizer is a general method in photodynamic therapy, but it has complications due to the unintended systemic distribution and remnants of photosensitizers. This study focused on the possibility of suppressing luminal proliferative cells by excessive reactive oxygen species from locally delivered photosensitizer with biocompatible polyurethane, instead of the systemic injection method. We used human bladder cancer cells, hematoporphyrin as the photosensitizer, and polyurethane film as the photosensitizer-delivering container. The light source was a self-made LED (510 nm, 5 mW cm-2) system. The cancer cells were cultured on different doses of hematoporphyrin-containing polyurethane film and irradiated with LED for 15 minutes and 30 minutes each. After irradiating with LED and incubating for 24 hours, cell viability analysis, cell cycle analysis, apoptosis assay, intracellular and extracellular ROS generation study and western blot were performed. The cancer cell suppression effects of different concentrations of the locally delivered hematoporphyrin with PDT were compared. Apoptosis dominant cancer cell suppressions were shown to be hematoporphyrin dose-dependent. However, after irradiation, intracellular ROS amounts were similar in all the groups having different doses of hematoporphyrin, but these values were definitely higher than those in the control group. Excessive extracellular ROS from the intended, locally delivered photosensitizer for photodynamic treatment application had an inhibitory effect on luminal proliferative cancer cells. This method can be another possibility for PDT application on contactable or attachable lesions.
Chen, Jeon-Hor; Liao, Fuyi; Zhang, Yang; Li, Yifan; Chang, Chia-Ju; Chou, Chen-Pin; Yang, Tsung-Lung; Su, Min-Ying
2017-07-01
Breast cancer occurs more frequently in the upper outer (UO) quadrant, but whether this higher cancer incidence is related to the greater amount of dense tissue is not known. Magnetic resonance imaging acquires three-dimensional volumetric images and is the most suitable among all breast imaging modalities for regional quantification of density. This study applied a magnetic resonance imaging-based method to measure quadrant percent density (QPD), and evaluated its association with the quadrant location of the developed breast cancer. A total of 126 cases with pathologically confirmed breast cancer were reviewed. Only women who had unilateral breast cancer located in a clear quadrant were selected for analysis. A total of 84 women, including 47 Asian women and 37 western women, were included. An established computer-aided method was used to segment the diseased breast and the contralateral normal breast, and to separate the dense and fatty tissues. Then, a breast was further separated into four quadrants using the nipple and the centroid as anatomic landmarks. The tumor was segmented using a computer-aided method to determine its quadrant location. The distribution of cancer quadrant location, the quadrant with the highest QPD, and the proportion of cancers occurring in the highest QPD were analyzed. The highest incidence of cancer occurred in the UO quadrant (36 out of 84, 42.9%). The highest QPD was also noted most frequently in the UO quadrant (31 out of 84, 36.9%). When correlating the highest QPD with the quadrant location of breast cancer, only 17 women out of 84 (20.2%) had breast cancer occurring in the quadrant with the highest QPD. The results showed that the development of breast cancer in a specific quadrant could not be explained by the density in that quadrant, and further studies are needed to find the biological reasons accounting for the higher breast cancer incidence in the UO quadrant. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
Analysis of Invasive Activity of CAF Spheroids into Three Dimensional (3D) Collagen Matrices.
Villaronga, María Ángeles; Teijeiro, Saúl Álvarez; Hermida-Prado, Francisco; Garzón-Arango, Marta; Sanz-Moreno, Victoria; García-Pedrero, Juana María
2018-01-01
Tumor growth and progression is the result of a complex process controlled not only by malignant cancer cells but also by the surrounding tumor microenvironment (TME). Cancer associated fibroblasts (CAFs), the most abundant cellular component of TME, play an active role in tumor invasion and metastasis by promoting cancer cell invasion through cell-cell interactions and secretion of pro-invasive factors such as extracellular matrix (ECM)-degrading proteases. Due to their tumor-promoting activities, there is an emerging interest in investigating CAFs biology and its potential as drug targets for cancer therapies. Here we describe an easy and highly reproducible quantitative method to analyze CAF invasive activity by forming multicellular spheroids embedded into a three-dimensional (3D) matrix that mimics in vivo ECM. Subsequently, invasion is monitored over time using a time-lapse microscope. We also provide an automated image analysis system that enables the rapid quantification of the spheroid area increase (invasive area) over time. The use of a 96-well plate format with one CAF spheroid per well and the automated analysis provides a method suitable for drug screening test, such as protease inhibitors.
Support vector machine and principal component analysis for microarray data classification
NASA Astrophysics Data System (ADS)
Astuti, Widi; Adiwijaya
2018-03-01
Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.
NASA Astrophysics Data System (ADS)
Depciuch, J.; Kaznowska, E.; Szmuc, K.; Zawlik, I.; Cholewa, M.; Heraud, P.; Cebulski, J.
2016-05-01
Breast cancer makes up a quarter of all cancer in women, which is why research into new diagnostic methods and sample preparations need to be developed at an accelerated pace. Researchers are looking for diagnostic tools to detect when an individual has cancer cells and use that information to see what measurements and approaches can be used to take further diagnostic steps. The most common method of sample preparation is the imbibing of tumor tissue in paraffin, which can produce a background for spectroscopic measurements in the range of 500-3500 cm-1. In this study we demonstrated that proper preparation of paraffin-embedded specimens and the measurement methodology can eliminate paraffin vibration, as was done in the work Depciuch et al. 2015. Thanks to this spectroscopic technique there may become a reliable and accurate method of diagnosing breast cancer based on the evidence found from the prepared samples. The study compared the results obtained through Raman spectroscopy and FTIR (Fourier Transform Infrared) measurements of healthy and cancerous breast tissues that were either embedded in paraffin or deparaffinized. The resulting spectrum and accurate analysis led to the conclusion that the appropriate measurement of the background and the elimination of peaks from the paraffin had the greatest impact on the reliability of results. Furthermore, after the accurate, detailed studies FTIR and Raman spectroscopy on samples of breast tissue that were deparaffinized or embedded in paraffin, including a complete analysis of the peak after transformation Kramers-Kröning (KK), it was found that sample preparation did not affect the result obtained by measuring the reflectance in the mid-infrared range, and that this only had a minimal effect relating to the intensity obtained by the measurement of the Raman peak. Only in special cases, when Raman spectroscopic methods are used for research to find the peculiarities of the spectra, are deparaffinization recommended, in order to attain more detailed results that could be crucial in understanding the process of carcinogenesis.
Jagannathan, A; Juvva, S
2016-01-01
Background and Rationale: Patients suffering with head and neck cancers are observed to have a relatively high risk of developing emotional disturbances after diagnosis and treatment. These emotional concerns can be best understood and explored through the method of content analysis or qualitative data. Though a number of qualitative studies have been conducted in the last few years in the field of psychosocial oncology, none have looked at the emotions experienced and the coping by head and neck cancer patients. Materials and Methods: Seventy-five new cases of postsurgery patients of head and neck cancers were qualitatively interviewed regarding the emotions experienced and coping strategies after diagnosis. Results: Qualitative content analysis of the in-depth interviews brought out that patients experienced varied emotions on realizing that they were suffering from cancer, the cause of which could be mainly attributed to three themes: 1) knowledge of their illness; 2) duration of untreated illness; and 3) object of blame. They coped with their emotions by either: 1) inculcating a positive attitude and faith in the doctor/treatment, 2) ventilating their emotions with family and friends, or 3) indulging in activities to divert attention. Conclusion: The results brought out a conceptual framework, which showed that an in-depth understanding of the emotions — Their root cause, coping strategies, and spiritual and cultural orientations of the cancer survivor — Is essential to develop any effective intervention program in India. PMID:27320951
Tay, Timothy Kwang Yong; Thike, Aye Aye; Pathmanathan, Nirmala; Jara-Lazaro, Ana Richelia; Iqbal, Jabed; Sng, Adeline Shi Hui; Ye, Heng Seow; Lim, Jeffrey Chun Tatt; Koh, Valerie Cui Yun; Tan, Jane Sie Yong; Yeong, Joe Poh Sheng; Chow, Zi Long; Li, Hui Hua; Cheng, Chee Leong; Tan, Puay Hoon
2018-01-01
Background Ki67 positivity in invasive breast cancers has an inverse correlation with survival outcomes and serves as an immunohistochemical surrogate for molecular subtyping of breast cancer, particularly ER positive breast cancer. The optimal threshold of Ki67 in both settings, however, remains elusive. We use computer assisted image analysis (CAIA) to determine the optimal threshold for Ki67 in predicting survival outcomes and differentiating luminal B from luminal A breast cancers. Methods Quantitative scoring of Ki67 on tissue microarray (TMA) sections of 440 invasive breast cancers was performed using Aperio ePathology ImmunoHistochemistry Nuclear Image Analysis algorithm, with TMA slides digitally scanned via Aperio ScanScope XT System. Results On multivariate analysis, tumours with Ki67 ≥14% had an increased likelihood of recurrence (HR 1.941, p=0.021) and shorter overall survival (HR 2.201, p=0.016). Similar findings were observed in the subset of 343 ER positive breast cancers (HR 2.409, p=0.012 and HR 2.787, p=0.012 respectively). The value of Ki67 associated with ER+HER2-PR<20% tumours (Luminal B subtype) was found to be <17%. Conclusion Using CAIA, we found optimal thresholds for Ki67 that predict a poorer prognosis and an association with the Luminal B subtype of breast cancer. Further investigation and validation of these thresholds are recommended. PMID:29545924
Assertions of Japanese Websites for and Against Cancer Screening: a Text Mining Analysis
Okuhara, Tsuyoshi; Ishikawa, Hirono; Okada, Masahumi; Kato, Mio; Kiuchi, Takahiro
2017-04-01
Background: Cancer screening rates are lower in Japan than in Western countries such as the United States and the United Kingdom. While health professionals publish pro-cancer-screening messages online to encourage proactive seeking for screening, anti-screening activists use the same medium to warn readers against following guidelines. Contents of pro- and anti-cancer-screening sites may contribute to readers’ acceptance of one or the other position. We aimed to use a text-mining method to examine frequently appearing contents on sites for and against cancer screening. Methods: We conducted online searches in December 2016 using two major search engines in Japan (Google Japan and Yahoo! Japan). Targeted websites were classified as “pro”, “anti”, or “neutral” depending on their claims, with the author(s) classified as “health professional”, “mass media”, or “layperson”. Text-mining analyses were conducted, and statistical analysis was performed using the chi-square test. Results: Of the 169 websites analyzed, the top-three most frequently appearing content topics in pro sites were reducing mortality via cancer screening, benefits of early detection, and recommendations for obtaining detailed examination. The top three most frequent in anti-sites were harm from radiation exposure, non-efficacy of cancer screening, and lack of necessity of early detection. Anti-sites also frequently referred to a well-known Japanese radiologist, Makoto Kondo, who rejects the standard forms of cancer care. Conclusion: Our findings should enable authors of pro-cancer-screening sites to write to counter misleading anti-cancer-screening messages and facilitate dissemination of accurate information. Creative Commons Attribution License
Thierry, Alain R
2016-01-01
Circulating cell-free DNA (cfDNA) is a valuable source of tumor material available with a simple blood sampling enabling a noninvasive quantitative and qualitative analysis of the tumor genome. cfDNA is released by tumor cells and exhibits the genetic and epigenetic alterations of the tumor of origin. Circulating cell-free DNA (cfDNA) analysis constitutes a hopeful approach to provide a noninvasive tumor molecular test for cancer patients. Based upon basic research on the origin and structure of cfDNA, new information on circulating cell-free DNA (cfDNA) structure, and specific determination of cfDNA fragmentation and size, we revisited Q-PCR-based method and recently developed a the allele-specific-Q-PCR-based method with blocker (termed as Intplex) which is the first multiplexed test for cfDNA. This technique, named Intplex(®) and based on a refined Q-PCR method, derived from critical observations made on the specific structure and size of cfDNA. It enables the simultaneous determination of five parameters: the cfDNA total concentration, the presence of a previously known point mutation, the mutant (tumor) cfDNA concentration (ctDNA), the proportion of mutant cfDNA, and the cfDNA fragmentation index. Intplex(®) has enabled the first clinical validation of ctDNA analysis in oncology by detecting KRAS and BRAF point mutations in mCRC patients and has demonstrated that a blood test could replace tumor section analysis for the detection of KRAS and BRAF mutations. The Intplex(®) test can be adapted to all mutations, genes, or cancers and enables rapid, highly sensitive, cost-effective, and repetitive analysis. As regards to the determination of mutations on cfDNA Intplex(®) is limited to the mutational status of known hotspot mutation; it is a "targeted approach." However, it offers the opportunity in detecting quantitatively and dynamically mutation and could constitute a noninvasive attractive tool potentially allowing diagnosis, prognosis, theranostics, therapeutic monitoring, and follow-up of cancer patients expanding the scope of personalized cancer medicine.
Radiomic analysis in prediction of Human Papilloma Virus status.
Yu, Kaixian; Zhang, Youyi; Yu, Yang; Huang, Chao; Liu, Rongjie; Li, Tengfei; Yang, Liuqing; Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Zhu, Hongtu
2017-12-01
Human Papilloma Virus (HPV) has been associated with oropharyngeal cancer prognosis. Traditionally the HPV status is tested through invasive lab test. Recently, the rapid development of statistical image analysis techniques has enabled precise quantitative analysis of medical images. The quantitative analysis of Computed Tomography (CT) provides a non-invasive way to assess HPV status for oropharynx cancer patients. We designed a statistical radiomics approach analyzing CT images to predict HPV status. Various radiomics features were extracted from CT scans, and analyzed using statistical feature selection and prediction methods. Our approach ranked the highest in the 2016 Medical Image Computing and Computer Assisted Intervention (MICCAI) grand challenge: Oropharynx Cancer (OPC) Radiomics Challenge, Human Papilloma Virus (HPV) Status Prediction. Further analysis on the most relevant radiomic features distinguishing HPV positive and negative subjects suggested that HPV positive patients usually have smaller and simpler tumors.
Liu, Xiang; Peng, Yingwei; Tu, Dongsheng; Liang, Hua
2012-10-30
Survival data with a sizable cure fraction are commonly encountered in cancer research. The semiparametric proportional hazards cure model has been recently used to analyze such data. As seen in the analysis of data from a breast cancer study, a variable selection approach is needed to identify important factors in predicting the cure status and risk of breast cancer recurrence. However, no specific variable selection method for the cure model is available. In this paper, we present a variable selection approach with penalized likelihood for the cure model. The estimation can be implemented easily by combining the computational methods for penalized logistic regression and the penalized Cox proportional hazards models with the expectation-maximization algorithm. We illustrate the proposed approach on data from a breast cancer study. We conducted Monte Carlo simulations to evaluate the performance of the proposed method. We used and compared different penalty functions in the simulation studies. Copyright © 2012 John Wiley & Sons, Ltd.
Spectroscopic analysis of bladder cancer tissues using Fourier transform infrared spectroscopy
NASA Astrophysics Data System (ADS)
Al-Muslet, Nafie A.; Ali, Essam E.
2012-03-01
Bladder cancer is one of the most common cancers in Africa. It takes several days to reach a diagnosis using histological examinations of specimens obtained by endoscope, which increases the medical expense. Recently, spectroscopic analysis of bladder cancer tissues has received considerable attention as a diagnosis technique due to its sensitivity to biochemical variations in the samples. This study investigated the use of Fourier transform infrared (FTIR) spectroscopy to analyze a number of bladder cancer tissues. Twenty-two samples were collected from 11 patients diagnosed with bladder cancer from different hospitals without any pretreatment. From each patient two samples were collected, one normal and another cancerous. FTIR spectrometer was used to differentiate between normal and cancerous bladder tissues via changes in spectra of these samples. The investigations detected obvious changes in the bands of proteins (1650, 1550 cm-1), lipids (2925, 2850 cm-1), and nucleic acid (1080, 1236 cm-1). The results show that FTIR spectroscopy is promising as a rapid, accurate, nondestructive, and easy to use alternative method for identification and diagnosis of bladder cancer tissues.
Valkonen, Mira; Ruusuvuori, Pekka; Kartasalo, Kimmo; Nykter, Matti; Visakorpi, Tapio; Latonen, Leena
2017-01-01
Cancer involves histological changes in tissue, which is of primary importance in pathological diagnosis and research. Automated histological analysis requires ability to computationally separate pathological alterations from normal tissue with all its variables. On the other hand, understanding connections between genetic alterations and histological attributes requires development of enhanced analysis methods suitable also for small sample sizes. Here, we set out to develop computational methods for early detection and distinction of prostate cancer-related pathological alterations. We use analysis of features from HE stained histological images of normal mouse prostate epithelium, distinguishing the descriptors for variability between ventral, lateral, and dorsal lobes. In addition, we use two common prostate cancer models, Hi-Myc and Pten+/− mice, to build a feature-based machine learning model separating the early pathological lesions provoked by these genetic alterations. This work offers a set of computational methods for separation of early neoplastic lesions in the prostates of model mice, and provides proof-of-principle for linking specific tumor genotypes to quantitative histological characteristics. The results obtained show that separation between different spatial locations within the organ, as well as classification between histologies linked to different genetic backgrounds, can be performed with very high specificity and sensitivity. PMID:28317907
Association among Dietary Flavonoids, Flavonoid Subclasses and Ovarian Cancer Risk: A Meta-Analysis
You, Ruxu; Yang, Yu; Liao, Jing; Chen, Dongsheng; Yu, Lixiu
2016-01-01
Background Previous studies have indicated that intake of dietary flavonoids or flavonoid subclasses is associated with the ovarian cancer risk, but presented controversial results. Therefore, we conducted a meta-analysis to derive a more precise estimation of these associations. Methods We performed a search in PubMed, Google Scholar and ISI Web of Science from their inception to April 25, 2015 to select studies on the association among dietary flavonoids, flavonoid subclasses and ovarian cancer risk. The information was extracted by two independent authors. We assessed the heterogeneity, sensitivity, publication bias and quality of the articles. A random-effects model was used to calculate the pooled risk estimates. Results Five cohort studies and seven case-control studies were included in the final meta-analysis. We observed that intake of dietary flavonoids can decrease ovarian cancer risk, which was demonstrated by pooled RR (RR = 0.82, 95% CI = 0.68–0.98). In a subgroup analysis by flavonoid subtypes, the ovarian cancer risk was also decreased for isoflavones (RR = 0.67, 95% CI = 0.50–0.92) and flavonols (RR = 0.68, 95% CI = 0.58–0.80). While there was no compelling evidence that consumption of flavones (RR = 0.86, 95% CI = 0.71–1.03) could decrease ovarian cancer risk, which revealed part sources of heterogeneity. The sensitivity analysis indicated stable results, and no publication bias was observed based on the results of Funnel plot analysis and Egger’s test (p = 0.26). Conclusions This meta-analysis suggested that consumption of dietary flavonoids and subtypes (isoflavones, flavonols) has a protective effect against ovarian cancer with a reduced risk of ovarian cancer except for flavones consumption. Nevertheless, further investigations on a larger population covering more flavonoid subclasses are warranted. PMID:26960146
The association between physical activity and renal cancer: systematic review and meta-analysis
Behrens, G; Leitzmann, M F
2013-01-01
Background: Physical activity may decrease renal cancer risk by reducing obesity, blood pressure, insulin resistance, and lipid peroxidation. Despite plausible biologic mechanisms linking increased physical activity to decreased risk for renal cancer, few epidemiologic studies have been able to report a clear inverse association between physical activity and renal cancer, and no meta-analysis is available on the topic. Methods: We searched the literature using PubMed and Web of Knowledge to identify published non-ecologic epidemiologic studies quantifying the relationship between physical activity and renal cancer risk in individuals without a cancer history. Following the PRISMA guidelines, we conducted a systematic review and meta-analysis, including information from 19 studies based on a total of 2 327 322 subjects and 10 756 cases. The methodologic quality of the studies was examined using a comprehensive scoring system. Results: Comparing high vs low levels of physical activity, we observed an inverse association between physical activity and renal cancer risk (summary relative risk (RR) from random-effects meta-analysis=0.88; 95% confidence interval (CI)=0.79–0.97). Summarising risk estimates from high-quality studies strengthened the inverse association between physical activity and renal cancer risk (RR=0.78; 95% CI=0.66–0.92). Effect modification by adiposity, hypertension, type 2 diabetes, smoking, gender, or geographic region was not observed. Conclusion: Our comprehensive meta-analysis provides strong support for an inverse relation of physical activity to renal cancer risk. Future high-quality studies are required to discern which specific types, intensities, frequencies, and durations of physical activity are needed for renal cancer risk reduction. PMID:23412105
Choi, Mi-Ri; Jeon, Sang-Wan; Yi, Eun-Surk
2018-04-01
The purpose of this study is to analyze the differences among the hospitalized cancer patients on their perception of exercise and physical activity constraints based on their medical history. The study used questionnaire survey as measurement tool for 194 cancer patients (male or female, aged 20 or older) living in Seoul metropolitan area (Seoul, Gyeonggi, Incheon). The collected data were analyzed using frequency analysis, exploratory factor analysis, reliability analysis t -test, and one-way distribution using statistical program SPSS 18.0. The following results were obtained. First, there was no statistically significant difference between cancer stage and exercise recognition/physical activity constraint. Second, there was a significant difference between cancer stage and sociocultural constraint/facility constraint/program constraint. Third, there was a significant difference between cancer operation history and physical/socio-cultural/facility/program constraint. Fourth, there was a significant difference between cancer operation history and negative perception/facility/program constraint. Fifth, there was a significant difference between ancillary cancer treatment method and negative perception/facility/program constraint. Sixth, there was a significant difference between hospitalization period and positive perception/negative perception/physical constraint/cognitive constraint. In conclusion, this study will provide information necessary to create patient-centered healthcare service system by analyzing exercise recognition of hospitalized cancer patients based on their medical history and to investigate the constraint factors that prevents patients from actually making efforts to exercise.
Circulating Tumor Cell and Cell-free Circulating Tumor DNA in Lung Cancer.
Nurwidya, Fariz; Zaini, Jamal; Putra, Andika Chandra; Andarini, Sita; Hudoyo, Achmad; Syahruddin, Elisna; Yunus, Faisal
2016-09-01
Circulating tumor cells (CTCs) are tumor cells that are separated from the primary site or metastatic lesion and disseminate in blood circulation. CTCs are considered to be part of the long process of cancer metastasis. As a 'liquid biopsy', CTC molecular examination and investigation of single cancer cells create an important opportunity for providing an understanding of cancer biology and the process of metastasis. In the last decade, we have seen dramatic development in defining the role of CTCs in lung cancer in terms of diagnosis, genomic alteration determination, treatment response and, finally, prognosis prediction. The aims of this review are to understand the basic biology and to review methods of detection of CTCs that apply to the various types of solid tumor. Furthermore, we explored clinical applications, including treatment monitoring to anticipate therapy resistance as well as biomarker analysis, in the context of lung cancer. We also explored the potential use of cell-free circulating tumor DNA (ctDNA) in the genomic alteration analysis of lung cancer.
van Roozendaal, Lori M.; Strobbe, Luc J. A.; Aebi, Stefan; Cameron, David A.; Dixon, J. Michael; Giuliano, Armando E.; Haffty, Bruce G.; Hickey, Brigid E.; Hudis, Clifford A.; Klimberg, V. Suzanne; Koczwara, Bogda; Kühn, Thorsten; Lippman, Marc E.; Lucci, Anthony; Piccart, Martine; Smith, Benjamin D.; Tjan-Heijnen, Vivianne C. G.; van de Velde, Cornelis J. H.; Van Zee, Kimberly J.; Vermorken, Jan B.; Viale, Giuseppe; Voogd, Adri C.; Wapnir, Irene L.; White, Julia R.; Smidt, Marjolein L.
2014-01-01
Background In breast cancer studies, many different endpoints are used. Definitions are often not provided or vary between studies. For instance, “local recurrence” may include different components in similar studies. This limits transparency and comparability of results. This project aimed to reach consensus on the definitions of local event, second primary breast cancer, regional and distant event for breast cancer studies. Methods The RAND-UCLA Appropriateness method (modified Delphi method) was used. A Consensus Group of international breast cancer experts was formed, including representatives of all involved clinical disciplines. Consensus was reached in two rounds of online questionnaires and one meeting. Results Twenty-four international breast cancer experts participated. Consensus was reached on 134 items in four categories. Local event is defined as any epithelial breast cancer or ductal carcinoma in situ (DCIS) in the ipsilateral breast, or skin and subcutaneous tissue on the ipsilateral thoracic wall. Second primary breast cancer is defined as epithelial breast cancer in the contralateral breast. Regional events are breast cancer in ipsilateral lymph nodes. A distant event is breast cancer in any other location. Therefore, this includes metastasis in contralateral lymph nodes and breast cancer involving the sternal bone. If feasible, tissue sampling of a first, solitary, lesion suspected for metastasis is highly recommended. Conclusion This project resulted in consensus-based event definitions for classification of recurrence in breast cancer research. Future breast cancer research projects should adopt these definitions to increase transparency. This should facilitate comparison of results and conducting reviews as well as meta-analysis. PMID:25381395
Lin, Chung-Ying; Hwang, Jing-Shiang; Wang, Wen-Chung; Lai, Wu-Wei; Su, Wu-Chou; Wu, Tzu-Yi; Yao, Grace; Wang, Jung-Der
2018-04-13
Quality of life (QoL) is important for clinicians to evaluate how cancer survivors judge their sense of well-being, and WHOQOL-BREF may be a good tool for clinical use. However, at least three issues remain unresolved: (1) the psychometric properties of the WHOQOL-BREF for cancer patients are insufficient; (2) the scoring method used for WHOQOL-BREF needs to be clarify; (3) whether different types of cancer patients interpret the WHOQOL-BREF similarly. We recruited 1000 outpatients with head/neck cancer, 1000 with colorectal cancer, 965 with liver cancer, 1438 with lung cancer and 1299 with gynecologic cancers in a medical center. Data analyses included Rasch models, confirmatory factor analysis (CFA), and Pearson correlations. The mean WHOQOL-BREF domain scores were between 13.34 and 14.77 among all participants. CFA supported construct validity; Rasch models revealed that almost all items were embedded in their expected domains and were interpreted similarly across five types of cancer patients; all correlation coefficients between Rasch scores and original domain scores were above 0.9. The linear relationship between Rasch scores and domain scores suggested that the current calculations for domain scores were applicable and without serious bias. Clinical practitioners may regularly collect and record the WHOQOL-BREF domain scores into electronic health records. Copyright © 2018. Published by Elsevier B.V.
Ohigashi, An; Ahmed, Salim; Afzal, Arfan R; Shigeta, Naoko; Tam-Tham, Helen; Kanda, Hideyuki; Ishikawa, Yoshihiro; Turin, Tanvir C
2017-06-01
INTRODUCTION Japan is a developed country with high use of Internet and online platforms for health information. 'Yahoo! Answer Japan' is the most commonly used question-and-answer service in Japan. AIM To explore the information users seek regarding breast cancer from the 'Yahoo! Answer Japan' web portal. METHODS The 'Yahoo! Answer Japan' portal was searched for the key word 'breast cancer' and all questions searched for the period of 1 January to 31 December 2014 were obtained. The selected questions related to human breast cancer and were not advertisements or promotional material. The questions were categorized using a coding schema. High and low access of the questions were defined by the number of view-counts. RESULTS Among the 2392 selected questions, six major categories were identified; (1) suspected breast cancer, (2) breast cancer screening, (3) treatment of breast cancer, (4) life with breast cancer, (5) prevention of breast cancer and (6) others. The highest number of questions were treatment related (28.8%) followed by suspected breast cancer-related questions (23.4%) and screening-related questions (20%). Statistical analysis revealed that the treatment-related questions were more likely to be highly accessed. CONCLUSION Content analysis of Internet question-answer communities is important, as questions posted on these sites would serve as a rich source of direct reflection regarding the health-related information needs of the general population.
Occult Blood Testing for Early Detection of Colorectal Cancer: Diagnostic Outcomes
Hislop, T. Gregory; Morrison, Brenda J.; Hoogewerf, Peter E.; Burns, Sheilagh D.; Sizto, Ronald
1987-01-01
Three thousand five hundred and fifty-four asymptomatic persons from 32 family practices returned hemoccult II tests for colorectal cancer; 2.2% of these returned tests were positive. The diagnoses for the 47 persons with positive tests which were done while on meat restriction included six cancers (1.7/1000) and five polyps (1.4/1000); 18 were diagnosed with other known sources, and 18 were undiagnosed. All polyps and four of six cancers were diagnosed by combined barium enema with sigmoidoscopy or by colonoscopy. Five of six cancers were diagnosed at early stages. Meat restriction, the method of returning the test for analysis, the number of holes completed in the test, and the delay time from completing the test to analysis did not influence the likelihood of a positive test. PMID:20469468
Smith, Selina A.; Whitehead, Mary S.; Sheats, Joyce Q.; Fontenot, Brittney; Alema-Mensah, Ernest; Ansa, Benjamin
2016-01-01
Background There is a proliferation of lifestyle-oriented mobile technologies; however, few have targeted users. Through intervention mapping, investigators and community partners completed Steps 1–3 (needs assessment, formulation of change objectives, and selection of theory-based methods) of a process to develop a mobile cancer prevention application (app) for cancer prevention. The aim of this qualitative study was to complete Step 4 (intervention development) by eliciting input from African American (AA) breast cancer survivors (BCSs) to guide app development. Methods Four focus group discussions (n=60) and three individual semi-structured interviews (n=36) were conducted with AA BCSs (40–72 years of age) to assess barriers and strategies for lifestyle change. All focus groups and interviews were recorded and transcribed verbatim. Data were analyzed with NVivo qualitative data analysis software version 10, allowing categories, themes, and patterns to emerge. Results Three categories and related themes emerged from the analysis: 1) perceptions about modifiable risk factors; 2) strategies related to adherence to cancer prevention guidelines; and 3) app components to address barriers to adherence. Participant perceptions, strategies, and recommended components guided development of the app. Conclusions For development of a mobile cancer prevention app, these findings will assist investigators in targeting features that are usable, acceptable, and accessible for AA BCSs. PMID:27583307
Bourdel, Nicolas; Chauvet, Pauline; Tognazza, Enrica; Pereira, Bruno; Botchorishvili, Revaz; Canis, Michel
2016-01-01
Our objective was to identify the most accurate method of endometrial sampling for the diagnosis of complex atypical hyperplasia (CAH), and the related risk of underestimation of endometrial cancer. We conducted a systematic literature search in PubMed and EMBASE (January 1999-September 2013) to identify all registered articles on this subject. Studies were selected with a 2-step method. First, titles and abstracts were analyzed by 2 reviewers, and 69 relevant articles were selected for full reading. Then, the full articles were evaluated to determine whether full inclusion criteria were met. We selected 27 studies, taking into consideration the comparison between histology of endometrial hyperplasia obtained by diagnostic tests of interest (uterine curettage, hysteroscopically guided biopsy, or hysteroscopic endometrial resection) and subsequent results of hysterectomy. Analysis of the studies reviewed focused on 1106 patients with a preoperative diagnosis of atypical endometrial hyperplasia. The mean risk of finding endometrial cancer at hysterectomy after atypical endometrial hyperplasia diagnosed by uterine curettage was 32.7% (95% confidence interval [CI], 26.2-39.9), with a risk of 45.3% (95% CI, 32.8-58.5) after hysteroscopically guided biopsy and 5.8% (95% CI, 0.8-31.7) after hysteroscopic resection. In total, the risk of underestimation of endometrial cancer reaches a very high rate in patients with CAH using the classic method of evaluation (i.e., uterine curettage or hysteroscopically guided biopsy). This rate of underdiagnosed endometrial cancer leads to the risk of inappropriate surgical procedures (31.7% of tubal conservation in the data available and no abdominal exploration in 24.6% of the cases). Hysteroscopic resection seems to reduce the risk of underdiagnosed endometrial cancer. Copyright © 2016 AAGL. Published by Elsevier Inc. All rights reserved.
Brozek-Pluska, Beata; Kopec, Monika; Niedzwiecka, Izabela; Morawiec-Sztandera, Alina
2015-04-07
The applications of optical spectroscopic methods in cancer detection open new possibilities in oncological diagnostics. Raman spectroscopy and Raman imaging represent noninvasive, label-free, and rapidly developing tools in cancer diagnosis. In the study described in this paper Raman microspectroscopy has been employed to examine noncancerous and cancerous human salivary gland tissues of the same patient. The most significant differences between noncancerous and cancerous tissues were found in regions typical for the vibrations of lipids and proteins. The detailed analysis of secondary structures of proteins contained in the cancerous and the noncancerous tissues is also presented.
ERIC Educational Resources Information Center
Taylor, Kathryn M.; And Others
1983-01-01
A program is described that relates behavioral science research to cancer care, encourages frank discussion and objective analysis of oncology practice, and attempts to dispell the myth that cancer patients are not medically manageable. A wide range of teaching methods are used. (MSE)
Sun Protection Motivational Stages and Behavior: Skin Cancer Risk Profiles
ERIC Educational Resources Information Center
Pagoto, Sherry L.; McChargue, Dennis E.; Schneider, Kristin; Cook, Jessica Werth
2004-01-01
Objective: To create skin cancer risk profiles that could be used to predict sun protection among Midwest beachgoers. Method: Cluster analysis was used with study participants (N=239), who provided information about sun protection motivation and behavior, perceived risk, burn potential, and tan importance. Participants were clustered according to…
Social Support, a Mediator in Collaborative Depression Care for Cancer Patients
ERIC Educational Resources Information Center
Oh, Hyunsung; Ell, Kathleen
2015-01-01
Objective: This study assessed whether perceived social support (PSS) is a factor in improving physical and functional well-being observed among cancer patients receiving collaborative depression care. Methods: A secondary analysis was conducted of data collected in a randomized clinical trial testing the effectiveness of collaborative depression…
Sawicka-Żukowska, Malgorzata; Krawczuk-Rybak, Maryna; Muszynska-Roslan, Katarzyna; Panasiuk, Anna; Latoch, Eryk; Konstantynowicz, Jerzy
2013-01-01
Childhood cancer survivors are in augmented risk for developing obesity. For many factors leptin and leptin receptor gene polymorphism play an important role in the development and metabolism not only of fat, but also, bone tissue. The aim of the analysis was to find the relationships between Q223R, leptin levels, and anthropometric parameters. Patients and Methods. In the study 74 cancer survivors participated (ALL n = 64, lymphomas n = 10), and the control group consisted of 51 healthy peers. Leptin blood concentration was determined by ELISA method. To estimate leptin receptor gene polymorphism, RFLP method was used. Bone mineral density (BMD) and content (BMC), fat, and lean tissue measurements were obtained by DXA. Results. We found no correlations between serum leptin concentrations and anthropometric parameters nor BMD. Serum leptin concentrations were significantly lower in the group of cancer survivors compared to controls; however, in those overweight from examined group we found leptin levels higher than those in nonoverweight. Genotype Q223R was not associated with higher leptin levels, BMI, BMD, body fat or lean tissue. Conclusion. To our knowledge, this is the first report describing the relationship between BMD and Q223R polymorphism in childhood cancer survivors. Further analysis, based on a larger group of patients, is needed to confirm these findings. PMID:24319457
The economic burden of cancer care in Canada: a population-based cost study
de Oliveira, Claire; Weir, Sharada; Rangrej, Jagadish; Krahn, Murray D.; Mittmann, Nicole; Hoch, Jeffrey S.; Chan, Kelvin K.W.; Peacock, Stuart
2018-01-01
Background: Resource and cost issues are a growing concern in health care. Thus, it is important to have an accurate estimate of the economic burden of care. Previous work has estimated the economic burden of cancer care for Canada; however, there is some concern this estimate is too low. The objective of this analysis was to provide a comprehensive revised estimate of this burden. Methods: We used a case-control prevalence-based approach to estimate direct annual cancer costs from 2005 to 2012. We used patient-level administrative health care data from Ontario to correctly attribute health care costs to cancer. We employed the net cost method (cost difference between patients with cancer and control subjects without cancer) to account for costs directly and indirectly related to cancer and its sequelae. Using average patient-level cost estimates from Ontario, we applied proportions from national health expenditures data to obtain the economic burden of cancer care for Canada. All costs were adjusted to 2015 Canadian dollars. Results: Costs of cancer care rose steadily over our analysis period, from $2.9 billion in 2005 to $7.5 billion in 2012, mostly owing to the increase in costs of hospital-based care. Most expenditures for health care services increased over time, with chemotherapy and radiation therapy expenditures accounting for the largest increases over the study period. Our cost estimates were larger than those in the Economic Burden of Illness in Canada 2005-2008 report for every year except 2005 and 2006. Interpretation: The economic burden of cancer care in Canada is substantial. Further research is needed to understand how the economic burden of cancer compares to that of other diseases. PMID:29301745
Photo diagnosis of early pre cancer (LSIL) in genital tissue
NASA Astrophysics Data System (ADS)
Vaitkuviene, A.; Andersen-Engels, S.; Auksorius, E.; Bendsoe, N.; Gavriushin, V.; Gustafsson, U.; Oyama, J.; Palsson, S.; Soto Thompson, M.; Stenram, U.; Svanberg, K.; Viliunas, V.; De Weert, M. J.
2005-11-01
Permanent infections recognized as oncogenic factor. STD is common concomitant diseases in early precancerous genital tract lesions. Simple optical detection of early regressive pre cancer in cervix is the aim of this study. Hereditary immunosupression most likely is risk factor for cervical cancer development. Light induced fluorescence point monitoring fitted to live cervical tissue diagnostics in 42 patients. Human papilloma virus DNR in cervix tested by means of Hybrid Capture II method. Ultraviolet (337 nm) laser excited fluorescence spectra in the live cervical tissue analyzed by Principal Component (PrC) regression method and spectra decomposition method. PCr method best discriminated pathology group "CIN I and inflammation"(AUC=75%) related to fluorescence emission in short wave region. Spectra decomposition method suggested a few possible fluorophores in a long wave region. Ultraviolet (398 nm) light excitation of live cervix proved sharp selective spectra intensity enhancement in region above 600nm for High-grade cervical lesion. Conclusion: PC analysis of UV (337 nm) light excitation fluorescence spectra gives opportunity to obtain local immunity and Low-grade cervical lesion related information. Addition of shorter and longer wavelengths is promising for multi wave LIF point monitoring method progress in cervical pre-cancer diagnostics and utility for cancer prevention especially in developing countries.
A Combined Negative and Positive Enrichment Assay for Cancer Cells Isolation and Purification.
Cheng, Boran; Wang, Shuyi; Chen, Yuanyuan; Fang, Yuan; Chen, Fangfang; Wang, Zhenmeng; Xiong, Bin
2016-02-01
Cancer cells that detach from solid tumor and circulate in the peripheral blood (CTCs) have been considered as a new "biomarker" for the detection and characterization of cancers. However, isolating and detecting cancer cells from the cancer patient peripheral blood have been technically challenging, owing to the small sub-population of CTCs (a few to hundreds per milliliter). Here we demonstrate a simple and efficient cancer cells isolation and purification method. A biocompatible and surface roughness controllable TiO2 nanofilm was deposited onto a glass slide to achieve enhanced topographic interactions with nanoscale cellular surface components, again, anti-CD45 (a leukocyte common antigen) and anti-EpCAM (epithelial cell adhesion molecule) were then coated onto the surface of the nanofilm for advance depletion of white blood cells (WBCs) and specific isolation of CTCs, respectively. Comparing to the conventional positive enrichment technology, this method exhibited excellent biocompatibility and equally high capture efficiency. Moreover, the maximum number of background cells (WBCs) was removed, and viable and functional cancer cells were isolated with high purity. Utilizing the horizontally packed TiO2 nanofilm improved pure CTC-capture through combining cell-capture-agent and cancer cell-preferred nanoscale topography, which represented a new method capable of obtaining biologically functional CTCs for subsequent molecular analysis. © The Author(s) 2014.
Improving breast cancer services for African-American women living in St. Louis.
Noel, Lailea; Connors, Shahnjayla K; Goodman, Melody S; Gehlert, Sarah
2015-11-01
A mixed methods, community-based research study was conducted to understand how provider-level factors contribute to the African-American and white disparity in breast cancer mortality in a lower socioeconomic status area of North St. Louis. This study used mixed methods including: (1) secondary analysis of Missouri Cancer Registry data on all 885 African-American women diagnosed with breast cancer from 2000 to 2008 while living in the geographic area of focus; (2) qualitative interviews with a subset of these women; (3) analysis of data from electronic medical records of the women interviewed; and (4) focus group interviews with community residents, patient navigators, and other health care professionals. 565 women diagnosed with breast cancer from 2000 to 2008 in the geographic area were alive at the time of secondary data analysis; we interviewed (n = 96; 17 %) of these women. Provider-level obstacles to completion of prescribed treatment included fragmented navigation (separate navigators at Federally Qualified Health Centers, surgical oncology, and medical oncology, and no navigation services in surgical oncology). Perhaps related to the latter, women described radiation as optional, often in the same words as they described breast reconstruction. Discontinuous and fragmented patient navigation leads to failure to associate radiation therapy with vital treatment recommendations. Better integrated navigation that continues throughout treatment will increase treatment completion with the potential to improve outcomes in African Americans and decrease the disparity in mortality.
Exact tests using two correlated binomial variables in contemporary cancer clinical trials.
Yu, Jihnhee; Kepner, James L; Iyer, Renuka
2009-12-01
New therapy strategies for the treatment of cancer are rapidly emerging because of recent technology advances in genetics and molecular biology. Although newer targeted therapies can improve survival without measurable changes in tumor size, clinical trial conduct has remained nearly unchanged. When potentially efficacious therapies are tested, current clinical trial design and analysis methods may not be suitable for detecting therapeutic effects. We propose an exact method with respect to testing cytostatic cancer treatment using correlated bivariate binomial random variables to simultaneously assess two primary outcomes. The method is easy to implement. It does not increase the sample size over that of the univariate exact test and in most cases reduces the sample size required. Sample size calculations are provided for selected designs.
Champion, Claudine; Berry, Tanya R; Kingsley, Bethan; Spence, John C
2016-10-01
This research examined media coverage of breast cancer (n = 145) and heart disease and stroke (n = 39) news articles, videos, advertisements, and images in a local Canadian context through quantitative and thematic content analyses. Quantitative analysis revealed significant differences between coverage of the diseases in placement, survivors as a source of information, health agency, human interest stories, citation of a research study, the inclusion of risk statistics, discussion of preventative behaviors, and tone used. The thematic analysis revealed themes that characterized a "typical" breast cancer survivor and indicated that "good" citizens and businesses should help the cause of breast cancer. Themes for heart disease and stroke articulated individual responsibility and the ways fundraising reinforced femininity and privilege. Findings provide insight on how these diseases are framed in local Canadian media, which might impact an individual's understanding of the disease.
Development of a scale to assess cancer stigma in the non-patient population
2014-01-01
Background Illness-related stigma has attracted considerable research interest, but few studies have specifically examined stigmatisation of cancer in the non-patient population. The present study developed and validated a Cancer Stigma Scale (CASS) for use in the general population. Methods An item pool was developed on the basis of previous research into illness-related stigma in the general population and patients with cancer. Two studies were carried out. The first study used Exploratory factor analysis to explore the structure of items in a sample of 462 postgraduate students recruited through a London university. The second study used Confirmatory factor analysis to confirm the structure among 238 adults recruited through an online market research panel. Internal reliability, test-retest reliability and construct validity were also assessed. Results Exploratory factor analysis suggested six subscales, representing: Awkwardness, Severity, Avoidance, Policy Opposition, Personal Responsibility and Financial Discrimination. Confirmatory factor analysis confirmed this structure with a 25-item scale. All subscales showed adequate to good internal and test-retest reliability in both samples. Construct validity was also good, with mean scores for each subscale varying in the expected directions by age, gender, experience of cancer, awareness of lifestyle risk factors for cancer, and social desirability. Means for the subscales were consistent across the two samples. Conclusions These findings highlight the complexity of cancer stigma and provide the Cancer Stigma Scale (CASS) which can be used to compare populations, types of cancer and evaluate the effects of interventions designed to reduce cancer stigma in non-patient populations. PMID:24758482
NASA Astrophysics Data System (ADS)
Bukreeva, Ekaterina B.; Bulanova, Anna A.; Kistenev, Yury V.; Kuzmin, Dmitry A.; Nikiforova, Olga Yu.; Ponomarev, Yurii N.; Tuzikov, Sergei A.; Yumov, Evgeny L.
2014-11-01
The results of application of the joint use of laser photoacoustic spectroscopy and chemometrics methods in gas analysis of exhaled air of patients with chronic respiratory diseases (chronic obstructive pulmonary disease and lung cancer) are presented. The absorption spectra of exhaled breath of representatives of the target groups and healthy volunteers were measured; the selection by chemometrics methods of the most informative absorption coefficients in scan spectra in terms of the separation investigated nosology was implemented.
Khanmohammadi, Mohammadreza; Bagheri Garmarudi, Amir; Samani, Simin; Ghasemi, Keyvan; Ashuri, Ahmad
2011-06-01
Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) microspectroscopy was applied for detection of colon cancer according to the spectral features of colon tissues. Supervised classification models can be trained to identify the tissue type based on the spectroscopic fingerprint. A total of 78 colon tissues were used in spectroscopy studies. Major spectral differences were observed in 1,740-900 cm(-1) spectral region. Several chemometric methods such as analysis of variance (ANOVA), cluster analysis (CA) and linear discriminate analysis (LDA) were applied for classification of IR spectra. Utilizing the chemometric techniques, clear and reproducible differences were observed between the spectra of normal and cancer cases, suggesting that infrared microspectroscopy in conjunction with spectral data processing would be useful for diagnostic classification. Using LDA technique, the spectra were classified into cancer and normal tissue classes with an accuracy of 95.8%. The sensitivity and specificity was 100 and 93.1%, respectively.
2014-01-01
Background We conducted a dose–response meta-analysis of prospective studies to summarize evidence of the association between tea consumption and the risk of breast, colorectal, liver, prostate, and stomach cancer. Methods We searched PubMed and two other databases. Prospective studies that reported risk ratios (RRs) with 95% confidence intervals (CIs) of cancer risk for ≥3 categories of tea consumption were included. We estimated an overall RR with 95% CI for an increase of three cups/day of tea consumption, and, usingrestricted cubic splines, we examined a nonlinear association between tea consumption and cancer risk. Results Forty-one prospective studies, with a total of 3,027,702 participants and 49,103 cancer cases, were included. From the pooled overall RRs, no inverse association between tea consumption and risk of five major cancers was observed. However, subgroup analysis showed that increase in consumption of three cups of black tea per day was a significant risk factor for breast cancer (RR, 1.18; 95% CI, 1.05-1.32). Conclusion Ourresults did not show a protective role of tea in five major cancers. Additional large prospective cohort studies are needed to make a convincing case for associations. PMID:24636229
2015-01-01
Background microRNA (miRNA) expression plays an influential role in cancer classification and malignancy, and miRNAs are feasible as alternative diagnostic markers for pancreatic cancer, a highly aggressive neoplasm with silent early symptoms, high metastatic potential, and resistance to conventional therapies. Methods In this study, we evaluated the benefits of multi-omics data analysis by integrating miRNA and mRNA expression data in pancreatic cancer. Using support vector machine (SVM) modelling and leave-one-out cross validation (LOOCV), we evaluated the diagnostic performance of single- or multi-markers based on miRNA and mRNA expression profiles from 104 PDAC tissues and 17 benign pancreatic tissues. For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) data depositories. For validation, miRNA activity was estimated by miRNA-target gene interaction and mRNA expression datasets in pancreatic cancer. Results Using a comprehensive identification approach, we successfully identified 705 multi-markers having powerful diagnostic performance for PDAC. In addition, these marker candidates annotated with cancer pathways using gene ontology analysis. Conclusions Our prediction models have strong potential for the diagnosis of pancreatic cancer. PMID:26328610
Masoudi-Nejad, Ali; Asgari, Yazdan
2015-02-01
The cancer cell metabolism or the Warburg effect discovery goes back to 1924 when, for the first time Otto Warburg observed, in contrast to the normal cells, cancer cells have different metabolism. With the initiation of high throughput technologies and computational systems biology, cancer cell metabolism renaissances and many attempts were performed to revise the Warburg effect. The development of experimental and analytical tools which generate high-throughput biological data including lots of information could lead to application of computational models in biological discovery and clinical medicine especially for cancer. Due to the recent availability of tissue-specific reconstructed models, new opportunities in studying metabolic alteration in various kinds of cancers open up. Structural approaches at genome-scale levels seem to be suitable for developing diagnostic and prognostic molecular signatures, as well as in identifying new drug targets. In this review, we have considered these recent advances in structural-based analysis of cancer as a metabolic disease view. Two different structural approaches have been described here: topological and constraint-based methods. The ultimate goal of this type of systems analysis is not only the discovery of novel drug targets but also the development of new systems-based therapy strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.
SBCDDB: Sleeping Beauty Cancer Driver Database for gene discovery in mouse models of human cancers
Mann, Michael B
2018-01-01
Abstract Large-scale oncogenomic studies have identified few frequently mutated cancer drivers and hundreds of infrequently mutated drivers. Defining the biological context for rare driving events is fundamentally important to increasing our understanding of the druggable pathways in cancer. Sleeping Beauty (SB) insertional mutagenesis is a powerful gene discovery tool used to model human cancers in mice. Our lab and others have published a number of studies that identify cancer drivers from these models using various statistical and computational approaches. Here, we have integrated SB data from primary tumor models into an analysis and reporting framework, the Sleeping Beauty Cancer Driver DataBase (SBCDDB, http://sbcddb.moffitt.org), which identifies drivers in individual tumors or tumor populations. Unique to this effort, the SBCDDB utilizes a single, scalable, statistical analysis method that enables data to be grouped by different biological properties. This allows for SB drivers to be evaluated (and re-evaluated) under different contexts. The SBCDDB provides visual representations highlighting the spatial attributes of transposon mutagenesis and couples this functionality with analysis of gene sets, enabling users to interrogate relationships between drivers. The SBCDDB is a powerful resource for comparative oncogenomic analyses with human cancer genomics datasets for driver prioritization. PMID:29059366
Secretome Identifies Tenascin-X as a Potent Marker of Ovarian Cancer
Kramer, Marianne; Pierredon, Sandra; Ribaux, Pascale; Tille, Jean-Christophe; Cohen, Marie
2015-01-01
CA-125 has been a valuable marker for the follow-up of ovarian cancer patients but it is not sensitive enough to be used as diagnostic marker. We had already used secretomic methods to identify proteins differentially secreted by serous ovarian cancer cells compared to healthy ovarian cells. Here, we evaluated the secretion of these proteins by ovarian cancer cells during the follow-up of one patient. Proteins that correlated with CA-125 levels were screened using serum samples from ovarian cancer patients as well as benign and healthy controls. Tenascin-X secretion was shown to correlate with CA-125 value in the initial case study. The immunohistochemical detection of increased amount of tenascin-X in ovarian cancer tissues compared to healthy tissues confirms the potent interest in tenascin-X as marker. We then quantified the tenascin-X level in serum of patients and identified tenascin-X as potent marker for ovarian cancer, showing that secretomic analysis is suitable for the identification of protein biomarkers when combined with protein immunoassay. Using this method, we determined tenascin-X as a new potent marker for serous ovarian cancer. PMID:26090390
OVCAR-3 Spheroid-Derived Cells Display Distinct Metabolic Profiles
Vermeersch, Kathleen A.; Wang, Lijuan; Mezencev, Roman; McDonald, John F.; Styczynski, Mark P.
2015-01-01
Introduction Recently, multicellular spheroids were isolated from a well-established epithelial ovarian cancer cell line, OVCAR-3, and were propagated in vitro. These spheroid-derived cells displayed numerous hallmarks of cancer stem cells, which are chemo- and radioresistant cells thought to be a significant cause of cancer recurrence and resultant mortality. Gene set enrichment analysis of expression data from the OVCAR-3 cells and the spheroid-derived putative cancer stem cells identified several metabolic pathways enriched in differentially expressed genes. Before this, there had been little previous knowledge or investigation of systems-scale metabolic differences between cancer cells and cancer stem cells, and no knowledge of such differences in ovarian cancer stem cells. Methods To determine if there were substantial metabolic changes corresponding with these transcriptional differences, we used two-dimensional gas chromatography coupled to mass spectrometry to measure the metabolite profiles of the two cell lines. Results These two cell lines exhibited significant metabolic differences in both intracellular and extracellular metabolite measurements. Principal components analysis, an unsupervised dimensional reduction technique, showed complete separation between the two cell types based on their metabolite profiles. Pathway analysis of intracellular metabolomics data revealed close overlap with metabolic pathways identified from gene expression data, with four out of six pathways found enriched in gene-level analysis also enriched in metabolite-level analysis. Some of those pathways contained multiple metabolites that were individually statistically significantly different between the two cell lines, with one of the most broadly and consistently different pathways, arginine and proline metabolism, suggesting an interesting hypothesis about cancerous and stem-like metabolic phenotypes in this pair of cell lines. Conclusions Overall, we demonstrate for the first time that metabolism in an ovarian cancer stem cell line is distinct from that of more differentiated isogenic cancer cells, supporting the potential importance of metabolism in the differences between cancer cells and cancer stem cells. PMID:25688563
Liu, Li; Dinu, Valentin
2018-01-01
Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway’s topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher’s exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov–Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level. PMID:29666752
Li, Chaoxing; Liu, Li; Dinu, Valentin
2018-01-01
Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level.
Thermographic image analysis as a pre-screening tool for the detection of canine bone cancer
NASA Astrophysics Data System (ADS)
Subedi, Samrat; Umbaugh, Scott E.; Fu, Jiyuan; Marino, Dominic J.; Loughin, Catherine A.; Sackman, Joseph
2014-09-01
Canine bone cancer is a common type of cancer that grows fast and may be fatal. It usually appears in the limbs which is called "appendicular bone cancer." Diagnostic imaging methods such as X-rays, computed tomography (CT scan), and magnetic resonance imaging (MRI) are more common methods in bone cancer detection than invasive physical examination such as biopsy. These imaging methods have some disadvantages; including high expense, high dose of radiation, and keeping the patient (canine) motionless during the imaging procedures. This project study identifies the possibility of using thermographic images as a pre-screening tool for diagnosis of bone cancer in dogs. Experiments were performed with thermographic images from 40 dogs exhibiting the disease bone cancer. Experiments were performed with color normalization using temperature data provided by the Long Island Veterinary Specialists. The images were first divided into four groups according to body parts (Elbow/Knee, Full Limb, Shoulder/Hip and Wrist). Each of the groups was then further divided into three sub-groups according to views (Anterior, Lateral and Posterior). Thermographic pattern of normal and abnormal dogs were analyzed using feature extraction and pattern classification tools. Texture features, spectral feature and histogram features were extracted from the thermograms and were used for pattern classification. The best classification success rate in canine bone cancer detection is 90% with sensitivity of 100% and specificity of 80% produced by anterior view of full-limb region with nearest neighbor classification method and normRGB-lum color normalization method. Our results show that it is possible to use thermographic imaging as a pre-screening tool for detection of canine bone cancer.
Dashtban, M; Balafar, Mohammadali
2017-03-01
Gene selection is a demanding task for microarray data analysis. The diverse complexity of different cancers makes this issue still challenging. In this study, a novel evolutionary method based on genetic algorithms and artificial intelligence is proposed to identify predictive genes for cancer classification. A filter method was first applied to reduce the dimensionality of feature space followed by employing an integer-coded genetic algorithm with dynamic-length genotype, intelligent parameter settings, and modified operators. The algorithmic behaviors including convergence trends, mutation and crossover rate changes, and running time were studied, conceptually discussed, and shown to be coherent with literature findings. Two well-known filter methods, Laplacian and Fisher score, were examined considering similarities, the quality of selected genes, and their influences on the evolutionary approach. Several statistical tests concerning choice of classifier, choice of dataset, and choice of filter method were performed, and they revealed some significant differences between the performance of different classifiers and filter methods over datasets. The proposed method was benchmarked upon five popular high-dimensional cancer datasets; for each, top explored genes were reported. Comparing the experimental results with several state-of-the-art methods revealed that the proposed method outperforms previous methods in DLBCL dataset. Copyright © 2017 Elsevier Inc. All rights reserved.
Katanoda, Kota; Kamo, Ken-Ichi; Tsugane, Shoichiro
2016-03-01
A thyroid ultrasound examination programme has been conducted in Fukushima Prefecture, Japan, after the nuclear disaster in 2011. Although remarkably high prevalence of thyroid cancer was observed, no relevant quantitative evaluation was conducted. We calculated the observed/expected (O/E) ratio of thyroid cancer prevalence for the residents aged ≤20 years. Observed prevalence was the number of thyroid cancer cases detected by the programme through the end of April 2015. Expected prevalence was calculated as cumulative incidence by a life-table method using the national estimates of thyroid cancer incidence rate in 2001-10 (prior to the disaster) and the population of Fukushima Prefecture. The underlying assumption was that there was neither nuclear accident nor screening intervention. The observed and estimated prevalence of thyroid cancer among residents aged ≤20 years was 160.1 and 5.2, respectively, giving an O/E ratio of 30.8 [95% confidence interval (CI): 26.2, 35.9]. When the recent increasing trend in thyroid cancer was considered, the overall O/E ratio was 22.2 (95% CI: 18.9, 25.9). The cumulative number of thyroid cancer deaths in Fukushima Prefecture, estimated with the same method (annual average in 2009-13), was 0.6 under age 40. Combined with the existing knowledge about radiation effect on thyroid cancer, our descriptive analysis suggests the possibility of overdiagnosis. Evaluation including individual-level analysis is required to further clarify the contribution of underlying factors. © The Author 2016. Published by Oxford University Press.
Lalitwongsa, Somkiat; Pongnikorn, Donsuk; Daoprasert, Karnchana; Sriplung, Hutcha; Bilheem, Surichai
2015-01-01
The recent epidemiologic transition in Thailand, with decreasing incidence of infectious diseases along with increasing rates of chronic conditions, including cancer, is a serious problem for the country. Breast cancer has the highest incidence rates among females throughout Thailand. Lampang is a province in the upper part of Northern Thailand. A study was needed to identify the current burden, and the future trends of breast cancer in upper Northern Thai women. Here we used cancer incidence data from the Lampang Cancer Registry to characterize and analyze the local incidence of breast cancer. Joinpoint analysis, age period cohort model and Nordpred package were used to investigate the incidences of breast cancer in the province from 1993 to 2012 and to project future trends from 2013 to 2030. Age-standardized incidence rates (world) of breast cancer in the upper parts of Northern Thailand increased from 16.7 to 26.3 cases per 100,000 female population which is equivalent to an annual percentage change of 2.0-2.8%, according to the method used. Linear drift effects played a role in shaping the increase of incidence. The three projection method suggested that incidence rates would continue to increase in the future with incidence for women aged 50 and above, increasing at a higher rate than for women below the age of 50. The current early detection measures increase detection rates of early disease. Preparation of a budget for treatment facilities and human resources, both in surgical and medical oncology, is essential.
Cervical Cancer Worry and Screening Among Appalachian Women
Schoenberg, Nancy; Wilson, Tomorrow D.; Atkins, Elvonna; Dickinson, Stephanie; Paskett, Electra
2015-01-01
Although many have sought to understand cervical cancer screening (CCS) behavior, little research has examined worry about cervical cancer and its relationship to CCS, particularly in the underserved, predominantly rural Appalachian region. Our mixed method investigation aimed to obtain a more complete and theoretically-informed understanding of the role of cancer worry in CCS among Appalachian women, using the Self-Regulation Model (SRM). Our quantitative analysis indicated that the perception of being at higher risk of cervical cancer and having greater distress about cancer were both associated with greater worry about cancer. In our qualitative analysis, we found that, consistent with the SRM, negative affect had a largely concrete-experiential component, with many women having first-hand experience of the physical consequences of cervical cancer. Based on the results of this manuscript, we describe a number of approaches to lessen the fear associated with CCS. Intervention in this elevated risk community is merited and may focus on decreasing feelings of worry about cervical cancer and increasing communication of objective risk and need for screening. From a policy perspective, increasing the quantity and quality of care may also improve CCS rates and decrease the burden of cancer in Appalachia. PMID:25416153
Virani, Shama; Sriplung, Hutcha; Rozek, Laura S; Meza, Rafael
2014-06-01
Thailand is undergoing an epidemiologic transition, with decreasing incidence of infectious diseases and increasing rates of chronic conditions, including cancer. Breast cancer has the highest incidence rates among females both in the southern region Thailand and throughout Thailand. However, there is a lack of research on the epidemiology of this and other cancers. Here we use cancer incidence data from the Songkhla Cancer Registry to characterize and analyze the incidence of breast cancer in Southern Thailand. We use joinpoint analysis, age-period-cohort models and nordpred analysis to investigate the incidence of breast cancer in Southern Thailand from 1990 to 2010 and project future trends from 2010 to 2029. We found that age-adjusted breast cancer incidence rates in Southern Thailand increased by almost 300% from 1990 to 2010 going from 10.0 to 27.8 cases per 100,000 person-years. Both period and cohort effects played a role in shaping the increase in incidence. Three distinct incidence projection methods consistently suggested that incidence rates will continue to increase in the future with incidence for women age 50 and above increasing at a higher rate than for women below 50. To date, this is the first study to examine Thai breast cancer incidence from a regional registry. This study provides a basis for future planning strategies in breast cancer prevention and to guide hypotheses for population-based epidemiologic research in Thailand. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Irshad, Humayun; Oh, Eun-Yeong; Schmolze, Daniel; Quintana, Liza M.; Collins, Laura; Tamimi, Rulla M.; Beck, Andrew H.
2017-02-01
The assessment of protein expression in immunohistochemistry (IHC) images provides important diagnostic, prognostic and predictive information for guiding cancer diagnosis and therapy. Manual scoring of IHC images represents a logistical challenge, as the process is labor intensive and time consuming. Since the last decade, computational methods have been developed to enable the application of quantitative methods for the analysis and interpretation of protein expression in IHC images. These methods have not yet replaced manual scoring for the assessment of IHC in the majority of diagnostic laboratories and in many large-scale research studies. An alternative approach is crowdsourcing the quantification of IHC images to an undefined crowd. The aim of this study is to quantify IHC images for labeling of ER status with two different crowdsourcing approaches, image-labeling and nuclei-labeling, and compare their performance with automated methods. Crowdsourcing- derived scores obtained greater concordance with the pathologist interpretations for both image-labeling and nuclei-labeling tasks (83% and 87%), as compared to the pathologist concordance achieved by the automated method (81%) on 5,338 TMA images from 1,853 breast cancer patients. This analysis shows that crowdsourcing the scoring of protein expression in IHC images is a promising new approach for large scale cancer molecular pathology studies.
Li, Yongsheng; Chen, Juan; Zhang, Jinwen; Wang, Zishan; Shao, Tingting; Jiang, Chunjie; Xu, Juan; Li, Xia
2015-09-22
Long non-coding RNAs (lncRNAs) play key roles in diverse biological processes. Moreover, the development and progression of cancer often involves the combined actions of several lncRNAs. Here we propose a multi-step method for constructing lncRNA-lncRNA functional synergistic networks (LFSNs) through co-regulation of functional modules having three features: common coexpressed genes of lncRNA pairs, enrichment in the same functional category and close proximity within protein interaction networks. Applied to three cancers, we constructed cancer-specific LFSNs and found that they exhibit a scale free and modular architecture. In addition, cancer-associated lncRNAs tend to be hubs and are enriched within modules. Although there is little synergistic pairing of lncRNAs across cancers, lncRNA pairs involved in the same cancer hallmarks by regulating same or different biological processes. Finally, we identify prognostic biomarkers within cancer lncRNA expression datasets using modules derived from LFSNs. In summary, this proof-of-principle study indicates synergistic lncRNA pairs can be identified through integrative analysis of genome-wide expression data sets and functional information.
[Therapeutic strategies targeting brain tumor stem cells].
Toda, Masahiro
2009-07-01
Progress in stem cell research reveals cancer stem cells to be present in a variety of malignant tumors. Since they exhibit resistance to anticancer drugs and radiotherapy, analysis of their properties has been rapidly carried forward as an important target for the treatment of intractable malignancies, including brain tumors. In fact, brain cancer stem cells (BCSCs) have been isolated from brain tumor tissue and brain tumor cell lines by using neural stem cell culture methods and isolation methods for side population (SP) cells, which have high drug-efflux capacity. Although the analysis of the properties of BCSCs is the most important to developing methods in treating BCSCs, the absence of BCSC purification methods should be remedied by taking it up as an important research task in the immediate future. Thus far, there are no effective treatment methods for BCSCs, and several treatment methods have been proposed based on the cell biology characteristics of BCSCs. In this article, I outline potential treatment methods damaging treatment-resistant BCSCs, including immunotherapy which is currently a topic of our research.
Fringe projection application for surface variation analysis on helical shaped silicon breast
NASA Astrophysics Data System (ADS)
Vairavan, R.; Ong, N. R.; Sauli, Z.; Shahimin, M. M.; Kirtsaeng, S.; Sakuntasathien, S.; Alcain, J. B.; Paitong, P.; Retnasamy, V.
2017-09-01
Breast carcinoma is rated as a second collective cause of cancer associated death among adult females. Detection of the disease at an early stage would enhance the chance for survival. Established detection methods such as mammography, ultrasound and MRI are classified as non invasive breast cancer detection modality, but however they are not entire non-invasive as physical contact still occurs to the breast. Thus requirement for a complete non invasive and non contact is evident. Therefore, in this work, a novel application of digital fringe projection for early detection of breast cancer based on breast surface analysis is reported. Phase shift fringe projection technique and pixel tracing method was utilized to analyze the breast surface change due to the incidence of breast lump. Results have shown that the digital fringe projection is capable in detecting the existence of 1 cm sized lump within the breast sample.
Osera, Shozo; Yano, Tomonori; Odagaki, Tomoyuki; Oono, Yasuhiro; Ikematsu, Hiroaki; Ohtsu, Atsushi; Kaneko, Kazuhiro
2015-10-01
Percutaneous endoscopic gastrostomy (PEG) using the direct method is generally indicated for cancer patients. However, there are little available data about peritonitis related to this method. The aim of this retrospective analysis was to assess peritonitis related to PEG using the direct method in patients with cancer. We assessed the prevalence of peritonitis and the relationship between peritonitis and patients' backgrounds, as well as the clinical course after peritonitis. Between December 2008 and December 2011, peritonitis was found in 9 (2.1 %) of 421 patients. Of the 9 patients with peritonitis, 4 had received PEG prior to chemoradiotherapy. Emergency surgical drainage was required in 1 patient, and the remaining 8 recovered with conservative treatment. Peritonitis occurred within 8 days of PEG for 8 of the 9 patients and occurred within 2 days of suture removal for 4 of the 9 patients. Peritonitis related to PEG using the direct method was less frequent for cancer patients. Peritonitis tended to occur within a few days after removal of securing suture and in patients with palliative stage.
Study of risk factors for gastric cancer by populational databases analysis
Ferrari, Fangio; Reis, Marco Antonio Moura
2013-01-01
AIM: To study the association between the incidence of gastric cancer and populational exposure to risk/protective factors through an analysis of international databases. METHODS: Open-access global databases concerning the incidence of gastric cancer and its risk/protective factors were identified through an extensive search on the Web. As its distribution was neither normal nor symmetric, the cancer incidence of each country was categorized according to ranges of percentile distribution. The association of each risk/protective factor with exposure was measured between the extreme ranges of the incidence of gastric cancer (under the 25th percentile and above the 75th percentile) by the use of the Mann-Whitney test, considering a significance level of 0.05. RESULTS: A variable amount of data omission was observed among all of the factors under study. A weak or nonexistent correlation between the incidence of gastric cancer and the study variables was shown by a visual analysis of scatterplot dispersion. In contrast, an analysis of categorized incidence revealed that the countries with the highest human development index (HDI) values had the highest rates of obesity in males and the highest consumption of alcohol, tobacco, fruits, vegetables and meat, which were associated with higher incidences of gastric cancer. There was no significant difference for the risk factors of obesity in females and fish consumption. CONCLUSION: Higher HDI values, coupled with a higher prevalence of male obesity and a higher per capita consumption of alcohol, tobacco, fruits, vegetables and meat, are associated with a higher incidence of gastric cancer based on an analysis of populational global data. PMID:24409066
Yerrell, Paul Henry; Roder, David; Cargo, Margaret; Reilly, Rachel; Banham, David; Micklem, Jasmine May; Morey, Kim; Stewart, Harold Bundamurra; Stajic, Janet; Norris, Michael; Brown, Alex
2016-01-01
Introduction In Australia, Aboriginal and Torres Strait Islander People carry a greater burden of cancer-related mortality than non-Aboriginal Australians. The Cancer Data and Aboriginal Disparities Project aims to develop and test an integrated, comprehensive cancer monitoring and surveillance system capable of incorporating epidemiological and narrative data to address disparities and advocate for clinical system change. Methods and analysis The Advanced Cancer Data System will integrate routinely collected unit record data from the South Australian Population Cancer Registry and a range of other data sources for a retrospective cohort of indigenous people with cancers diagnosed from 1990 to 2010. A randomly drawn non-Aboriginal cohort will be matched by primary cancer site, sex, age and year at diagnosis. Cross-tabulations and regression analyses will examine the extent to which demographic attributes, cancer stage and survival vary between the cohorts. Narratives from Aboriginal people with cancer, their families, carers and service providers will be collected and analysed using patient pathway mapping and thematic analysis. Statements from the narratives will structure both a concept mapping process of rating, sorting and prioritising issues, focusing on issues of importance and feasibility, and the development of a real-time Aboriginal Cancer Measure of Experience for ongoing linkage with epidemiological data in the Advanced Cancer Data System. Aboriginal Community engagement underpins this Project. Ethics and dissemination The research has been approved by relevant local and national ethics committees. Findings will be disseminated in local and international peer-reviewed journals and conference presentations. In addition, the research will provide data for knowledge translation activities across the partner organisations and feed directly into the Statewide Cancer Control Plan. It will provide a mechanism for monitoring and evaluating the implementation of the recommendations in these documents. PMID:28011808
NASA Astrophysics Data System (ADS)
Chung, Hyunkoo; Lu, Guolan; Tian, Zhiqiang; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei
2016-03-01
Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications. HSI acquires two dimensional images at various wavelengths. The combination of both spectral and spatial information provides quantitative information for cancer detection and diagnosis. This paper proposes using superpixels, principal component analysis (PCA), and support vector machine (SVM) to distinguish regions of tumor from healthy tissue. The classification method uses 2 principal components decomposed from hyperspectral images and obtains an average sensitivity of 93% and an average specificity of 85% for 11 mice. The hyperspectral imaging technology and classification method can have various applications in cancer research and management.
Karataş, Tuğba; Özen, Şükrü; Kutlutürkan, Sevinç
2017-01-01
Objective: The main aim of this study was to investigate the factor structure and psychometric properties of the Brief Illness Perception Questionnaire (BIPQ) in Turkish cancer patients. Methods: This methodological study involved 135 cancer patients. Statistical methods included confirmatory or exploratory factor analysis and Cronbach alpha coefficients for internal consistency. Results: The values of fit indices are within the acceptable range. The alpha coefficients for emotional illness representations, cognitive illness representations, and total scale are 0.83, 0.80, and 0.85, respectively. Conclusions: The results confirm the two-factor structure of the Turkish BIPQ and demonstrate its reliability and validity. PMID:28217734
Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data.
Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X
2018-01-05
Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value <0.05) that cannot be discovered by other machine learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.
Marko, Nicholas F.; Weil, Robert J.
2012-01-01
Introduction Gene expression data is often assumed to be normally-distributed, but this assumption has not been tested rigorously. We investigate the distribution of expression data in human cancer genomes and study the implications of deviations from the normal distribution for translational molecular oncology research. Methods We conducted a central moments analysis of five cancer genomes and performed empiric distribution fitting to examine the true distribution of expression data both on the complete-experiment and on the individual-gene levels. We used a variety of parametric and nonparametric methods to test the effects of deviations from normality on gene calling, functional annotation, and prospective molecular classification using a sixth cancer genome. Results Central moments analyses reveal statistically-significant deviations from normality in all of the analyzed cancer genomes. We observe as much as 37% variability in gene calling, 39% variability in functional annotation, and 30% variability in prospective, molecular tumor subclassification associated with this effect. Conclusions Cancer gene expression profiles are not normally-distributed, either on the complete-experiment or on the individual-gene level. Instead, they exhibit complex, heavy-tailed distributions characterized by statistically-significant skewness and kurtosis. The non-Gaussian distribution of this data affects identification of differentially-expressed genes, functional annotation, and prospective molecular classification. These effects may be reduced in some circumstances, although not completely eliminated, by using nonparametric analytics. This analysis highlights two unreliable assumptions of translational cancer gene expression analysis: that “small” departures from normality in the expression data distributions are analytically-insignificant and that “robust” gene-calling algorithms can fully compensate for these effects. PMID:23118863
BCC skin cancer diagnosis based on texture analysis techniques
NASA Astrophysics Data System (ADS)
Chuang, Shao-Hui; Sun, Xiaoyan; Chang, Wen-Yu; Chen, Gwo-Shing; Huang, Adam; Li, Jiang; McKenzie, Frederic D.
2011-03-01
In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% and 95%, respectively.
TGF-Beta Antibody for Prostate Cancer: Role of ERK
2012-07-01
medicine has been used either as a major medication or as a supplement either for cancer prevention or for cancer treatment. These herbal products...Blot Analysis ell lysates were prepared by using cell lysis buffer (Cell Sig- aling, Danvers, MA) supplemented with 1 mM PMSF and 1% rotease inhibitor...of target protein was used. Negative controls were identical array sections stained in the absence of primary antibody. (TIF) Method S1 Supplemental
Magnetic resonance elastography (MRE) in cancer: Technique, analysis, and applications
Pepin, Kay M.; Ehman, Richard L.; McGee, Kiaran P.
2015-01-01
Tissue mechanical properties are significantly altered with the development of cancer. Magnetic resonance elastography (MRE) is a noninvasive technique capable of quantifying tissue mechanical properties in vivo. This review describes the basic principles of MRE and introduces some of the many promising MRE methods that have been developed for the detection and characterization of cancer, evaluation of response to therapy, and investigation of the underlying mechanical mechanisms associated with malignancy. PMID:26592944
Forensic evaluation of STR typing reliability in lung cancer.
Zhang, Peng; Zhu, Ying; Li, Yongguo; Zhu, Shisheng; Ma, Ruoxiang; Zhao, Minzhu; Li, Jianbo
2018-01-01
Short tandem repeats (STR) analysis is the gold standard method in the forensics field for personal identification and paternity testing. In cancerous tissues, STR markers are gaining attention, with some studies showing increased instability. Lung cancer, which is one of the most commonmalignancies, has become the most lethal among all cancers. In certain situations, lung cancer tissues may be the only resource available for forensic analysis. Therefore, evaluating the reliability of STR markers in lung cancer tissues is required to avoid false exclusions. In this study, 75 lung cancer tissue samples were examined to evaluate the reliability of various STR markers. Out of the 75 examined samples, 24 of the cancerous samples (32%) showed genetic alterations on at least one STR loci, totaling 55 times. The most common type of STR variation was a partial loss of heterozygosity, with the D5S818 loci having the highest variation frequency and no alterations detected on the D2S441 and Penta E loci. Moreover, STR variation frequencies were shown to increase with an increased patient age and increased clinical and pathological characteristics, thus an older patient with an advanced stage of progression exhibited a higher variation frequency. Overall, this study provides forensic scientists with further insight into STR analysis relating to lung cancer tissue. Copyright © 2017 Elsevier B.V. All rights reserved.
Cost-effectiveness analysis of colorectal cancer screening methods in Iran.
Allameh, Zahra; Davari, Majid; Emami, Mohammad Hasan
2011-03-01
Screening can prevent colorectal cancer from becoming advanced by early detection of precancerous lesions. Cost-effectiveness analysis of colorectal cancer screening methods is highly necessary due to increased prevalence, decreased age at onset and the limited budget in Iran. Methods of screening currently available in Iran were selected. A systematic search revealed the sensitivity and specificity of each method. For this study, a model for a 20 year screening period of a population of 100,000 apparently healthy persons of ages 45-65 years in Isfahan Province was used. The cost-effectiveness of each method and the ratio of cost-effectiveness were calculated based on this model. The most and the least effective methods were CT colonography and fecal occult blood test, respectively. The highest and lowest expenditures in the governmental sector were related to fecal occult blood test and flexible sigmoidoscopy and in the private sector, to CT colonography and fecal occult blood test, respectively. The cost per cancer detected in 20 years of screening in the governmental sector was 0.28, 0.22 and 0.42 billion Rials, respectively for screening by colonoscopy, flexible sigmoidoscopy and fecal occult blood test. In the private sector, these were 1.54 (colonoscopy), 1.68 (flexible sigmoidoscopy), and 1.60 (fecal occult blood test) billion and 2.58 billion Rials for CT colonography, respectively. Although CT colonography is the most effective method, it needs a budget of 2.58 billion Rials for each screened patient. If costs in the governmental sector are considered, flexible sigmoidoscopy would be the most cost-effective method for screening the 45 - 65-year-old population in Iran.
Application of FT-IR spectroscopy on breast cancer serum analysis
NASA Astrophysics Data System (ADS)
Elmi, Fatemeh; Movaghar, Afshin Fayyaz; Elmi, Maryam Mitra; Alinezhad, Heshmatollah; Nikbakhsh, Novin
2017-12-01
Breast cancer is regarded as the most malignant tumor among women throughout the world. Therefore, early detection and proper diagnostic methods have been known to help save women's lives. Fourier Transform Infrared (FT-IR) spectroscopy, coupled with PCA-LDA analysis, is a new technique to investigate the characteristics of serum in breast cancer. In this study, 43 breast cancer and 43 healthy serum samples were collected, and the FT-IR spectra were recorded for each one. Then, PCA analysis and linear discriminant analysis (LDA) were used to analyze the spectral data. The results showed that there were differences between the spectra of the two groups. Discriminating wavenumbers were associated with several spectral differences over the 950-1200 cm- 1(sugar), 1190-1350 cm- 1 (collagen), 1475-1710 cm- 1 (protein), 1710-1760 cm- 1 (ester), 2800-3000 cm- 1 (stretching motions of -CH2 & -CH3), and 3090-3700 cm- 1 (NH stretching) regions. PCA-LDA performance on serum IR could recognize changes between the control and the breast cancer cases. The diagnostic accuracy, sensitivity, and specificity of PCA-LDA analysis for 3000-3600 cm- 1 (NH stretching) were found to be 83%, 84%, 74% for the control and 80%, 76%, 72% for the breast cancer cases, respectively. The results showed that the major spectral differences between the two groups were related to the differences in protein conformation in serum samples. It can be concluded that FT-IR spectroscopy, together with multivariate data analysis, is able to discriminate between breast cancer and healthy serum samples.
Xu, Zicheng; Li, Xiao; Qin, Zhiqiang; Xue, Jianxin; Wang, Jingyuan; Liu, Zhentao; Cai, Hongzhou; Yu, Bin; Xu, Ting; Zou, Qin
2017-07-24
Individual studies of the association between N-acetyltransferase 1 (NAT1)*10 allele and bladder cancer susceptibility have shown inconclusive results. To derive a more precise estimation of any such relationship, we performed this systemic review and updated meta-analysis based on 17 publications. A total of 17 studies were investigated with 4,322 bladder cancer cases and 4,944 controls. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of the association. Subgroup analyses were conducted based on ethnicity, sex, source of controls and detecting methods. Then trial sequential analysis was performed to evaluate whether the evidence of the results was sufficient and reduce the risk of type I error. There was no association between NAT1*10 allele and bladder cancer risk in a random-effects model (OR = 0.96, 95% CI, 0.84-1.10) or in a fixed-effects model (OR = 0.95, 95% CI, 0.87-1.03). In addition, no significantly increased risk of bladder cancer was found in any other subgroup analysis. Then, trial sequential analyses demonstrated that the results of our study need to be further verified. Despite its limitations, the results of the present meta-analysis suggested that there was no association between NAT1*10 allele and bladder cancer risk. More importantly, our findings need to be further validated regarding whether being without the NAT1*10 allele could in the future be shown to be a potential marker for the risk of bladder cancer.
Li, Xiaofang; Tian, Run; Gao, Hugh; Yan, Feng; Ying, Le; Yang, Yongkang; Yang, Pei
2018-01-01
Cervical cancer is the leading cause of death with gynecological malignancies. We aimed to explore the molecular mechanism of carcinogenesis and biomarkers for cervical cancer by integrated bioinformatic analysis. We employed RNA-sequencing details of 254 cervical squamous cell carcinomas and 3 normal samples from The Cancer Genome Atlas. To explore the distinct pathways, messenger RNA expression was submitted to a Gene Set Enrichment Analysis. Kyoto Encyclopedia of Genes and Genomes and protein–protein interaction network analysis of differentially expressed genes were performed. Then, we conducted pathway enrichment analysis for modules acquired in protein–protein interaction analysis and obtained a list of pathways in every module. After intersecting the results from the 3 approaches, we evaluated the survival rates of both mutual pathways and genes in the pathway, and 5 survival-related genes were obtained. Finally, Cox hazards ratio analysis of these 5 genes was performed. DNA replication pathway (P < .001; 12 genes included) was suggested to have the strongest association with the prognosis of cervical squamous cancer. In total, 5 of the 12 genes, namely, minichromosome maintenance 2, minichromosome maintenance 4, minichromosome maintenance 5, proliferating cell nuclear antigen, and ribonuclease H2 subunit A were significantly correlated with survival. Minichromosome maintenance 5 was shown as an independent prognostic biomarker for patients with cervical cancer. This study identified a distinct pathway (DNA replication). Five genes which may be prognostic biomarkers and minichromosome maintenance 5 were identified as independent prognostic biomarkers for patients with cervical cancer. PMID:29642758
Ge, Long; Tian, Jin-hui; Li, Xiu-xia; Song, Fujian; Li, Lun; Zhang, Jun; Li, Ge; Pei, Gai-qin; Qiu, Xia; Yang, Ke-hu
2016-01-01
Because of the methodological complexity of network meta-analyses (NMAs), NMAs may be more vulnerable to methodological risks than conventional pair-wise meta-analysis. Our study aims to investigate epidemiology characteristics, conduction of literature search, methodological quality and reporting of statistical analysis process in the field of cancer based on PRISMA extension statement and modified AMSTAR checklist. We identified and included 102 NMAs in the field of cancer. 61 NMAs were conducted using a Bayesian framework. Of them, more than half of NMAs did not report assessment of convergence (60.66%). Inconsistency was assessed in 27.87% of NMAs. Assessment of heterogeneity in traditional meta-analyses was more common (42.62%) than in NMAs (6.56%). Most of NMAs did not report assessment of similarity (86.89%) and did not used GRADE tool to assess quality of evidence (95.08%). 43 NMAs were adjusted indirect comparisons, the methods used were described in 53.49% NMAs. Only 4.65% NMAs described the details of handling of multi group trials and 6.98% described the methods of similarity assessment. The median total AMSTAR-score was 8.00 (IQR: 6.00–8.25). Methodological quality and reporting of statistical analysis did not substantially differ by selected general characteristics. Overall, the quality of NMAs in the field of cancer was generally acceptable. PMID:27848997
Automatic segmentation and supervised learning-based selection of nuclei in cancer tissue images.
Nandy, Kaustav; Gudla, Prabhakar R; Amundsen, Ryan; Meaburn, Karen J; Misteli, Tom; Lockett, Stephen J
2012-09-01
Analysis of preferential localization of certain genes within the cell nuclei is emerging as a new technique for the diagnosis of breast cancer. Quantitation requires accurate segmentation of 100-200 cell nuclei in each tissue section to draw a statistically significant result. Thus, for large-scale analysis, manual processing is too time consuming and subjective. Fortuitously, acquired images generally contain many more nuclei than are needed for analysis. Therefore, we developed an integrated workflow that selects, following automatic segmentation, a subpopulation of accurately delineated nuclei for positioning of fluorescence in situ hybridization-labeled genes of interest. Segmentation was performed by a multistage watershed-based algorithm and screening by an artificial neural network-based pattern recognition engine. The performance of the workflow was quantified in terms of the fraction of automatically selected nuclei that were visually confirmed as well segmented and by the boundary accuracy of the well-segmented nuclei relative to a 2D dynamic programming-based reference segmentation method. Application of the method was demonstrated for discriminating normal and cancerous breast tissue sections based on the differential positioning of the HES5 gene. Automatic results agreed with manual analysis in 11 out of 14 cancers, all four normal cases, and all five noncancerous breast disease cases, thus showing the accuracy and robustness of the proposed approach. Published 2012 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Lee, Hyeon-Guck; Hong, Seong-Jong; Cho, Jae-Hwan; Han, Man-Seok; Kim, Tae-Hyung; Lee, Ik-Han
2013-02-01
The purpose of this study was to assess and compare the changes in the SUV (standardized uptake value), the 18F-FDG (18F-fluorodeoxyglucose) uptake pattern, and the radioactivity level for the diagnosis of thyroid cancer via dual-time-point 18F-FDG PET/CT (positron emission tomographycomputed tomography) imaging. Moreover, the study aimed to verify the usefulness and significance of SUV values and radioactivity levels to discriminate tumor malignancy. A retrospective analysis was performed on 40 patients who received 18F-FDG PET/CT for thyroid cancer as a primary tumor. To set the background, we compared changes in values by calculating the dispersion of scattered rays in the neck area and the lung apex, and by comparing the mean and SD (standard deviation) values of the maxSUV and the radioactivity levels. According to the statistical analysis of the changes in 18F-FDG uptake for the diagnosis of thyroid cancer, a high similarity was observed with the coefficient of determination being R2 = 0.939, in the SUVs and the radioactivity levels. Moreover, similar results were observed in the assessment of tumor malignancy using dual-time-point. The quantitative analysis method for assessing tumor malignancy using radioactivity levels was neither specific nor discriminative compared to the semi-quantitative analysis method.
Mooney-Somers, Julie; Lewis, Peter; Kerridge, Ian
2016-06-01
As part of work to understand the experiences of young people who had cancer, we were keen to examine the perspectives of peers who share their social worlds. Our study aimed to examine how cancer in young people, young people with cancer and young cancer survivors are represented through language, metaphor and performance. We generated data using creative activities and focus group discussions with three high school drama classes and used Foucauldian discourse analysis to identify the discursive constructions of youth cancer. Our analysis identified two prevailing discursive constructions: youth cancer as an inevitable decline towards death and as overwhelming personhood by reducing the young person with cancer to 'cancer victim'. If we are to understand life after cancer treatment and how to support young people who have been treated for cancer, we need a sophisticated understanding of the social contexts they return to. Discourses shape the way young people talk and think about youth cancer; cancer as an inevitable decline towards death and as overwhelming personhood is a key discursive construction that young people draw on when a friend discloses cancer. The way cancer is constructed shapes how friends react to and relate to a young person with cancer. These constructions are likely to shape challenging social dynamics, such as bullying, that many young cancer survivors experience. Awareness of these discursive constructions can better equip young cancer survivors, their family and health professionals negotiate life after cancer.
El-Najjar, Nahed; Jantsch, Jonathan; Gessner, André
2017-08-28
Cancer remains a leading cause of mortality and morbidity worldwide. In addition to organ failure, the most frequent reasons for admission of cancer patients to intensive care units (ICU) are: infections and sepsis. As critically ill, the complexity of the health situation of cancer patients renders the standard antimicrobial regimen more complex and even inadequate which results in increased mortality rates. This is due to pathophysiological changes in the volume of distribution, increased clearance, as well as to organ dysfunction. While in the former cases a decrease in drug efficacy is observed, the hallmark of the latter one is overdosing leading to increased toxicity at the expense of efficacy. Furthermore, an additional risk factor is the potential drug-drug interaction between antibiotics and antineoplastic agents. Therefore, therapeutic drug monitoring (TDM) is a necessity to improve the clinical outcome of antimicrobial therapy in cancer patients. To be applied in routine analysis the method used for TDM should be cheap, fast and highly accurate/sensitive. Furthermore, as ICU patients are treated with a cocktail of antibiotics the method has to cover the simultaneous analysis of antibiotics used as a first/second line of treatment. The aim of the current review is to briefly survey the pitfalls in the current antimicrobial therapy and the central role of TDM in dose adjustment and drug-drug interaction's evaluation. A major section is dedicated to summarize the currently published analytical methods and to shed light on the difficulties and potential problems that can be encountered during method development.
Chen, Tung-Sheng; Chang, Mu-Hsin; Kuo, Wei-Wen; Lin, Yueh-Min; Yeh, Yu-Lan; Day, Cecilia Hsuan; Lin, Chien-Chung; Tsai, Fuu-Jen; Tsai, Chang-Hai; Huang, Chih-Yang
2013-04-01
Statistical and clinical reports indicate that betel nut chewing is strongly associated with progression of oral cancer because some ingredients in betel nuts are potential cancer promoters, especially arecoline. Early diagnosis for cancer biomarkers is the best strategy for prevention of cancer progression. Several methods are suggested for investigating cancer biomarkers. Among these methods, gel-based proteomics approach is the most powerful and recommended tool for investigating biomarkers due to its high-throughput. However, this proteomics approach is not suitable for screening biomarkers with molecular weight under 10 KDa because of the characteristics of gel electrophoresis. This study investigated biomarkers with molecular weight under 10 KDa in rats with arecoline challenge. The centrifuging vials with membrane (10 KDa molecular weight cut-off) played a crucial role in this study. After centrifuging, the filtrate (containing compounds with molecular weight under 10 KDa) was collected and spotted on a sample plate for MALDI-TOF mass spectrometry analysis. Compared to control, three extra peaks (m/z values were 1553.1611, 1668.2097 and 1740.1832, respectively) were found in sera and two extra peaks were found in heart tissue samples (408.9719 and 524.9961, respectively). These small compounds should play important roles and may be potential biomarker candidates in rats with arecoline. This study successfully reports a mass-based method for investigating biomarker candidates with small molecular weight in different types of sample (including serum and tissue). In addition, this reported method is more time-efficient (1 working day) than gel-based proteomics approach (5~7 working days).
Karaçalı, Bilge; Vamvakidou, Alexandra P; Tözeren, Aydın
2007-01-01
Background Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images. Methods Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system. Results Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images. Conclusion Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development. PMID:17822559
Goovaerts, Pierre
2006-01-01
Boundary analysis of cancer maps may highlight areas where causative exposures change through geographic space, the presence of local populations with distinct cancer incidences, or the impact of different cancer control methods. Too often, such analysis ignores the spatial pattern of incidence or mortality rates and overlooks the fact that rates computed from sparsely populated geographic entities can be very unreliable. This paper proposes a new methodology that accounts for the uncertainty and spatial correlation of rate data in the detection of significant edges between adjacent entities or polygons. Poisson kriging is first used to estimate the risk value and the associated standard error within each polygon, accounting for the population size and the risk semivariogram computed from raw rates. The boundary statistic is then defined as half the absolute difference between kriged risks. Its reference distribution, under the null hypothesis of no boundary, is derived through the generation of multiple realizations of the spatial distribution of cancer risk values. This paper presents three types of neutral models generated using methods of increasing complexity: the common random shuffle of estimated risk values, a spatial re-ordering of these risks, or p-field simulation that accounts for the population size within each polygon. The approach is illustrated using age-adjusted pancreatic cancer mortality rates for white females in 295 US counties of the Northeast (1970–1994). Simulation studies demonstrate that Poisson kriging yields more accurate estimates of the cancer risk and how its value changes between polygons (i.e. boundary statistic), relatively to the use of raw rates or local empirical Bayes smoother. When used in conjunction with spatial neutral models generated by p-field simulation, the boundary analysis based on Poisson kriging estimates minimizes the proportion of type I errors (i.e. edges wrongly declared significant) while the frequency of these errors is predicted well by the p-value of the statistical test. PMID:19023455
Duell, Eric J.; Yu, Kai; Risch, Harvey A.; Olson, Sara H.; Kooperberg, Charles; Wolpin, Brian M.; Jiao, Li; Dong, Xiaoqun; Wheeler, Bill; Arslan, Alan A.; Bueno-de-Mesquita, H. Bas; Fuchs, Charles S.; Gallinger, Steven; Gross, Myron; Hartge, Patricia; Hoover, Robert N.; Holly, Elizabeth A.; Jacobs, Eric J.; Klein, Alison P.; LaCroix, Andrea; Mandelson, Margaret T.; Petersen, Gloria; Zheng, Wei; Agalliu, Ilir; Albanes, Demetrius; Boutron-Ruault, Marie-Christine; Bracci, Paige M.; Buring, Julie E.; Canzian, Federico; Chang, Kenneth; Chanock, Stephen J.; Cotterchio, Michelle; Gaziano, J.Michael; Giovannucci, Edward L.; Goggins, Michael; Hallmans, Göran; Hankinson, Susan E.; Hoffman Bolton, Judith A.; Hunter, David J.; Hutchinson, Amy; Jacobs, Kevin B.; Jenab, Mazda; Khaw, Kay-Tee; Kraft, Peter; Krogh, Vittorio; Kurtz, Robert C.; McWilliams, Robert R.; Mendelsohn, Julie B.; Patel, Alpa V.; Rabe, Kari G.; Riboli, Elio; Shu, Xiao-Ou; Tjønneland, Anne; Tobias, Geoffrey S.; Trichopoulos, Dimitrios; Virtamo, Jarmo; Visvanathan, Kala; Watters, Joanne; Yu, Herbert; Zeleniuch-Jacquotte, Anne; Stolzenberg-Solomon, Rachael Z.
2012-01-01
Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case–control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10−6, 1.6 × 10−5, 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10−5), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H. pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer. PMID:22523087
Improved numerical solutions for chaotic-cancer-model
NASA Astrophysics Data System (ADS)
Yasir, Muhammad; Ahmad, Salman; Ahmed, Faizan; Aqeel, Muhammad; Akbar, Muhammad Zubair
2017-01-01
In biological sciences, dynamical system of cancer model is well known due to its sensitivity and chaoticity. Present work provides detailed computational study of cancer model by counterbalancing its sensitive dependency on initial conditions and parameter values. Cancer chaotic model is discretized into a system of nonlinear equations that are solved using the well-known Successive-Over-Relaxation (SOR) method with a proven convergence. This technique enables to solve large systems and provides more accurate approximation which is illustrated through tables, time history maps and phase portraits with detailed analysis.
Wang, Judy Huei-yu; Adams, Inez F; Tucker-Seeley, Reginald; Gomez, Scarlett Lin; Allen, Laura; Huang, Ellen; Wang, Yiru; Pasick, Rena J
2013-12-01
Cancer-related stress is heavily influenced by culture. This study explored similarities and differences in survivorship care concerns among Chinese American and non-Hispanic White (NHW) breast cancer survivors. A sequential, mixed-method design (inductive/qualitative research-phase I and deductive/quantitative research-phase II) was employed. Eligible women identified from the Greater Bay Area Cancer Registry were age ≥21, diagnosed with stage 0-IIa breast cancer between 2006 and 2011, and had no recurrence or other cancers. In phase I, we conducted 4 Chinese (n = 19) and 4 NHW (n = 22) focus groups, and 31 individual telephone interviews (18 Chinese immigrants, 7 Chinese US-born, and 6 NHW). Content analysis was conducted to examine qualitative data. In phase II, another 296 survivors (148 NHW age-matched to 148 Chinese cases) completed a cross-sectional survey. Descriptive statistics and linear regression analysis were conducted to examine quantitative data. Qualitative data revealed "socioeconomic well-being" (SWB) as a dominant survivorship concern, which was operationalized as a cancer survivor's perceived economic and social resources available to access care. Quantitative data showed that low-acculturated Chinese immigrants reported the poorest SWB, controlling for covariates. Highly acculturated Chinese immigrants and the US-born Chinese/NHW group reported similar SWB. Women who had low-income levels or chemotherapy had poorer SWB. SWB emerged as an important aspect of breast cancer survivorship. Immigration stress, cancer care costs, and cultural values all contributed to immigrants' socioeconomic distress. Immigrant and US-born breast cancer survivors experienced different socioeconomic circumstances and well-being following treatment. Our findings warrant further investigation of socioeconomic distress and survivorship outcomes.
Enhanced expression of G-protein coupled estrogen receptor (GPER/GPR30) in lung cancer
2012-01-01
Background G-protein-coupled estrogen receptor (GPER/GPR30) was reported to bind 17β-estradiol (E2), tamoxifen, and ICI 182,780 (fulvestrant) and promotes activation of epidermal growth factor receptor (EGFR)-mediated signaling in breast, endometrial and thyroid cancer cells. Although lung adenocarcinomas express estrogen receptors α and β (ERα and ERβ), the expression of GPER in lung cancer has not been investigated. The purpose of this study was to examine the expression of GPER in lung cancer. Methods The expression patterns of GPER in various lung cancer lines and lung tumors were investigated using standard quantitative real time PCR (at mRNA levels), Western blot and immunohistochemistry (IHC) methods (at protein levels). The expression of GPER was scored and the pairwise comparisons (cancer vs adjacent tissues as well as cancer vs normal lung tissues) were performed. Results Analysis by real-time PCR and Western blotting revealed a significantly higher expression of GPER at both mRNA and protein levels in human non small cell lung cancer cell (NSCLC) lines relative to immortalized normal lung bronchial epithelial cells (HBECs). The virally immortalized human small airway epithelial cell line HPL1D showed higher expression than HBECs and similar expression to NSCLC cells. Immunohistochemical analysis of tissue sections of murine lung adenomas as well as human lung adenocarcinomas, squamous cell carcinomas and non-small cell lung carcinomas showed consistently higher expression of GPER in the tumor relative to the surrounding non-tumor tissue. Conclusion The results from this study demonstrate increased GPER expression in lung cancer cells and tumors compared to normal lung. Further evaluation of the function and regulation of GPER will be necessary to determine if GPER is a marker of lung cancer progression. PMID:23273253
Jitaree, Sirinapa; Phinyomark, Angkoon; Boonyaphiphat, Pleumjit; Phukpattaranont, Pornchai
2015-01-01
Having a classifier of cell types in a breast cancer microscopic image (BCMI), obtained with immunohistochemical staining, is required as part of a computer-aided system that counts the cancer cells in such BCMI. Such quantitation by cell counting is very useful in supporting decisions and planning of the medical treatment of breast cancer. This study proposes and evaluates features based on texture analysis by fractal dimension (FD), for the classification of histological structures in a BCMI into either cancer cells or non-cancer cells. The cancer cells include positive cells (PC) and negative cells (NC), while the normal cells comprise stromal cells (SC) and lymphocyte cells (LC). The FD feature values were calculated with the box-counting method from binarized images, obtained by automatic thresholding with Otsu's method of the grayscale images for various color channels. A total of 12 color channels from four color spaces (RGB, CIE-L*a*b*, HSV, and YCbCr) were investigated, and the FD feature values from them were used with decision tree classifiers. The BCMI data consisted of 1,400, 1,200, and 800 images with pixel resolutions 128 × 128, 192 × 192, and 256 × 256, respectively. The best cross-validated classification accuracy was 93.87%, for distinguishing between cancer and non-cancer cells, obtained using the Cr color channel with window size 256. The results indicate that the proposed algorithm, based on fractal dimension features extracted from a color channel, performs well in the automatic classification of the histology in a BCMI. This might support accurate automatic cell counting in a computer-assisted system for breast cancer diagnosis. © Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Potcoava, Mariana C.; Futia, Gregory L.; Aughenbaugh, Jessica; Schlaepfer, Isabel R.; Gibson, Emily A.
2014-11-01
Increasing interest in the role of lipids in cancer cell proliferation and resistance to drug therapies has motivated the need to develop better tools for cellular lipid analysis. Quantification of lipids in cells is typically done by destructive chromatography protocols that do not provide spatial information on lipid distribution and prevent dynamic live cell studies. Methods that allow the analysis of lipid content in live cells are therefore of great importance. Using micro-Raman spectroscopy and coherent anti-Stokes Raman scattering (CARS) microscopy, we generated a lipid profile for breast (T47D, MDA-MB-231) and prostate (LNCaP, PC3) cancer cells upon exposure to medroxyprogesterone acetate (MPA) and synthetic androgen R1881. Combining Raman spectra with CARS imaging, we can study the process of hormone-mediated lipogenesis. Our results show that hormone-treated cancer cells T47D and LNCaP have an increased number and size of intracellular lipid droplets and higher degree of saturation than untreated cells. MDA-MB-231 and PC3 cancer cells showed no significant changes upon treatment. Principal component analysis with linear discriminant analysis of the Raman spectra was able to differentiate between cancer cells that were treated with MPA, R1881, and untreated.
Zhang, Xiangwei; Wang, Yang; Zhao, Linping; Sang, Shaowei; Zhang, Lin
2018-04-01
The platelet-to-lymphocyte ratio (PLR) is a useful prognostic factor in several cancers. However, the prognostic role of PLR in esophageal cancer remains controversial. The aim of this study is to evaluate the association between PLR and the oncologic outcome of esophageal cancer patients through a meta-analysis. Relevant articles were researched from Embase, PubMed, and Web of Science databases. The meta-analysis was performed using hazard ratio (HR) and 95% confidence intervals (CIs) as effect measures. Finally, 19 articles with 6134 patients were included in our study. The summary results indicated that the elevated PLR was negatively related to overall survival (HR= 1.263; 95% CI 1.094, 1.458). The subgroup analysis revealed that increased PLR was associated with poor overall survival in esophageal cancer patients for Asians (HR=1.252; 95% CI 1.141, 1.373) but not for Caucasians (HR=1.463; 95% CI 0.611, 3.502). When the patients were segregated by pathological type, sample size, and HR estimate method, high PLR was also significantly correlated with poor overall survival. In contrast, elevated PLR was not statistically associated with disease-free survival or cancer-specific survival. High PLR is associated with poor overall survival in patients with esophageal cancer. PLR may be a significant predictive biomarker in patients with esophageal cancer. Further large-cohort studies are needed to confirm these findings.
Bo, Yacong; Lu, Yan; Zhao, Yan; Zhao, Erjiang; Yuan, Ling; Lu, Weiquan; Cui, Lingling; Lu, Quanjun
2016-04-15
While several epidemiological studies have investigated the association between vitamin C and risk of esophageal cancer, the results remain inconsistent. In the present study, a meta-analysis was conducted to assess the impact of dietary vitamin C intake on esophageal cancer risk. Online databases were searched up to March 29, 2015, for studies on the association between dietary vitamin C intake and esophageal cancer risk. Pooled risk ratios (RRs) or odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a random-effects model. Dose-response analyses were performed using the method of restricted cubic splines with four knots at percentiles of 5, 35, 65 and 95% of the distribution. Publication bias was estimated using Egger's tests and funnel plots. In all, 15 articles were included in this meta-analysis, including 20 studies, containing 7063 controls and 3955 cases of esophageal cancer. By comparing the highest vs. the lowest categories of vitamin C intake, we found that vitamin C was inversely associated with the risk of esophageal cancer [overall OR = 0.58, 95% CI = 0.49-0.68, I(2) = 56%]. A linear dose-response relationship was found. With an increase in dietary vitamin C intake of 50 mg/day, the risk of esophageal cancer statistically decreased by 13% (OR = 0.87, 95% CI = 0.80-0.93, p(linearity) = 0.0002). In conclusion, our analysis suggested that the higher intake of dietary vitamin C might have a protective effect against esophageal cancer. © 2015 UICC.
Evaluation of algorithm methods for fluorescence spectra of cancerous and normal human tissues
NASA Astrophysics Data System (ADS)
Pu, Yang; Wang, Wubao; Alfano, Robert R.
2016-03-01
The paper focus on the various algorithms on to unravel the fluorescence spectra by unmixing methods to identify cancerous and normal human tissues from the measured fluorescence spectroscopy. The biochemical or morphologic changes that cause fluorescence spectra variations would appear earlier than the histological approach; therefore, fluorescence spectroscopy holds a great promise as clinical tool for diagnosing early stage of carcinomas and other deceases for in vivo use. The method can further identify tissue biomarkers by decomposing the spectral contributions of different fluorescent molecules of interest. In this work, we investigate the performance of blind source un-mixing methods (backward model) and spectral fitting approaches (forward model) in decomposing the contributions of key fluorescent molecules from the tissue mixture background when certain selected excitation wavelength is applied. Pairs of adenocarcinoma as well as normal tissues confirmed by pathologist were excited by selective wavelength of 340 nm. The emission spectra of resected fresh tissue were used to evaluate the relative changes of collagen, reduced nicotinamide adenine dinucleotide (NADH), and Flavin by various spectral un-mixing methods. Two categories of algorithms: forward methods and Blind Source Separation [such as Principal Component Analysis (PCA) and Independent Component Analysis (ICA), and Nonnegative Matrix Factorization (NMF)] will be introduced and evaluated. The purpose of the spectral analysis is to discard the redundant information which conceals the difference between these two types of tissues, but keep their diagnostically significance. The facts predicted by different methods were compared to the gold standard of histopathology. The results indicate that these key fluorophores within tissue, e.g. tryptophan, collagen, and NADH, and flavin, show differences of relative contents of fluorophores among different types of human cancer and normal tissues. The sensitivity, specificity, and receiver operating characteristic (ROC) are finally employed as the criteria to evaluate the efficacy of these methods in cancer detection. The underlying physical and biological basis for these optical approaches will be discussed with examples. This ex vivo preliminary trial demonstrates that these different criteria from different methods can distinguish carcinoma from normal tissues with good sensitivity and specificity while among them, we found that ICA appears to be the superior method in predication accuracy.
Statistical analysis and machine learning algorithms for optical biopsy
NASA Astrophysics Data System (ADS)
Wu, Binlin; Liu, Cheng-hui; Boydston-White, Susie; Beckman, Hugh; Sriramoju, Vidyasagar; Sordillo, Laura; Zhang, Chunyuan; Zhang, Lin; Shi, Lingyan; Smith, Jason; Bailin, Jacob; Alfano, Robert R.
2018-02-01
Analyzing spectral or imaging data collected with various optical biopsy methods is often times difficult due to the complexity of the biological basis. Robust methods that can utilize the spectral or imaging data and detect the characteristic spectral or spatial signatures for different types of tissue is challenging but highly desired. In this study, we used various machine learning algorithms to analyze a spectral dataset acquired from human skin normal and cancerous tissue samples using resonance Raman spectroscopy with 532nm excitation. The algorithms including principal component analysis, nonnegative matrix factorization, and autoencoder artificial neural network are used to reduce dimension of the dataset and detect features. A support vector machine with a linear kernel is used to classify the normal tissue and cancerous tissue samples. The efficacies of the methods are compared.
Mullins, C Daniel; Wang, Junling; Cooke, Jesse L; Blatt, Lisa; Baquet, Claudia R
2004-01-01
Projecting future breast cancer treatment expenditure is critical for budgeting purposes, medical decision making and the allocation of resources in order to maximise the overall impact on health-related outcomes of care. Currently, both longitudinal and cross-sectional methodologies are used to project the economic burden of cancer. This pilot study examined the differences in estimates that were obtained using these two methods, focusing on Maryland, US Medicaid reimbursement data for chemotherapy and prescription drugs for the years 1999-2000. Two different methodologies for projecting life cycles of cancer expenditure were considered. The first examined expenditure according to chronological time (calendar quarter) for all cancer patients in the database in a given quarter. The second examined only the most recent quarter and constructed a hypothetical expenditure life cycle by taking into consideration the number of quarters since the respective patient had her first claim. We found different average expenditures using the same data and over the same time period. The longitudinal measurement had less extreme peaks and troughs, and yielded average expenditure in the final period that was 60% higher than that produced using the cross-sectional analysis; however, the longitudinal analysis had intermediate periods with significantly lower estimated expenditure than the cross-sectional data. These disparate results signify that each of the methods has merit. The longitudinal method tracks changes over time while the cross-sectional approach reflects more recent data, e.g. current practice patterns. Thus, this study reiterates the importance of considering the methodology when projecting future cancer expenditure.
Marateb, Hamid Reza; Mansourian, Marjan; Adibi, Peyman; Farina, Dario
2014-01-01
Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal–variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD). Ordinal-to-Interval scale conversion example: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinal-scale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests. Results: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable. Conclusion: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables. PMID:24672565
Mass Spectrometry Imaging for the Investigation of Intratumor Heterogeneity.
Balluff, B; Hanselmann, M; Heeren, R M A
2017-01-01
One of the big clinical challenges in the treatment of cancer is the different behavior of cancer patients under guideline therapy. An important determinant for this phenomenon has been identified as inter- and intratumor heterogeneity. While intertumor heterogeneity refers to the differences in cancer characteristics between patients, intratumor heterogeneity refers to the clonal and nongenetic molecular diversity within a patient. The deciphering of intratumor heterogeneity is recognized as key to the development of novel therapeutics or treatment regimens. The investigation of intratumor heterogeneity is challenging since it requires an untargeted molecular analysis technique that accounts for the spatial and temporal dynamics of the tumor. So far, next-generation sequencing has contributed most to the understanding of clonal evolution within a cancer patient. However, it falls short in accounting for the spatial dimension. Mass spectrometry imaging (MSI) is a powerful tool for the untargeted but spatially resolved molecular analysis of biological tissues such as solid tumors. As it provides multidimensional datasets by the parallel acquisition of hundreds of mass channels, multivariate data analysis methods can be applied for the automated annotation of tissues. Moreover, it integrates the histology of the sample, which enables studying the molecular information in a histopathological context. This chapter will illustrate how MSI in combination with statistical methods and histology has been used for the description and discovery of intratumor heterogeneity in different cancers. This will give evidence that MSI constitutes a unique tool for the investigation of intratumor heterogeneity, and could hence become a key technology in cancer research. © 2017 Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
Fong, Carlton J.; Murphy, Kathleen M.; Westbrook, John D.; Markle, Minda M.
2018-01-01
Purpose: The objective was to examine experimental and quasi-experimental studies about interventions that (i) included behavioral, psychological, educational, or vocational components; (ii) involved cancer survivors aged 18 years or older; and (iii) assessed employment outcomes. Methods: The aims were both to describe the variety of interventions…
ERIC Educational Resources Information Center
Bantum, Erin O'Carroll; Owen, Jason E.
2009-01-01
Psychological interventions provide linguistic data that are particularly useful for testing mechanisms of action and improving intervention methodologies. For this study, emotional expression in an Internet-based intervention for women with breast cancer (n = 63) was analyzed via rater coding and 2 computerized coding methods (Linguistic Inquiry…
NASA Astrophysics Data System (ADS)
Luo, Shuwen; Chen, Changshui; Mao, Hua; Jin, Shaoqin
2013-06-01
The feasibility of early detection of gastric cancer using near-infrared (NIR) Raman spectroscopy (RS) by distinguishing premalignant lesions (adenomatous polyp, n=27) and cancer tissues (adenocarcinoma, n=33) from normal gastric tissues (n=45) is evaluated. Significant differences in Raman spectra are observed among the normal, adenomatous polyp, and adenocarcinoma gastric tissues at 936, 1003, 1032, 1174, 1208, 1323, 1335, 1450, and 1655 cm-1. Diverse statistical methods are employed to develop effective diagnostic algorithms for classifying the Raman spectra of different types of ex vivo gastric tissues, including principal component analysis (PCA), linear discriminant analysis (LDA), and naive Bayesian classifier (NBC) techniques. Compared with PCA-LDA algorithms, PCA-NBC techniques together with leave-one-out, cross-validation method provide better discriminative results of normal, adenomatous polyp, and adenocarcinoma gastric tissues, resulting in superior sensitivities of 96.3%, 96.9%, and 96.9%, and specificities of 93%, 100%, and 95.2%, respectively. Therefore, NIR RS associated with multivariate statistical algorithms has the potential for early diagnosis of gastric premalignant lesions and cancer tissues in molecular level.
Physical break-down of the classical view on cancer cell invasion and metastasis.
Mierke, Claudia T
2013-03-01
Eight classical hallmarks of cancer have been proposed and are well-defined by using biochemical or molecular genetic methods, but are not yet precisely defined by cellular biophysical processes. To define the malignant transformation of neoplasms and finally reveal the functional pathway, which enables cancer cells to promote cancer progression, these classical hallmarks of cancer require the inclusion of specific biomechanical properties of cancer cells and their microenvironment such as the extracellular matrix and embedded cells such as fibroblasts, macrophages or endothelial cells. Nonetheless a main novel ninth hallmark of cancer is still elusive in classical tumor biological reviews, which is the aspect of physics in cancer disease by the natural selection of an aggressive (highly invasive) subtype of cancer cells. The physical aspects can be analyzed by using state-of-the-art biophysical methods. Thus, this review will present current cancer research in a different light and will focus on novel physical methods to investigate the aggressiveness of cancer cells from a biophysicist's point of view. This may lead to novel insights into cancer disease and will overcome classical views on cancer. In addition, this review will discuss how physics of cancer can help to reveal whether cancer cells will invade connective tissue and metastasize. In particular, this review will point out how physics can improve, break-down or support classical approaches to examine tumor growth even across primary tumor boundaries, the invasion of single or collective cancer cells, transendothelial migration of cancer cells and metastasis in targeted organs. Finally, this review will show how physical measurements can be integrated into classical tumor biological analysis approaches. The insights into physical interactions between cancer cells, the primary tumor and the microenvironment may help to solve some "old" questions in cancer disease progression and may finally lead to novel approaches for development and improvement of cancer diagnostics and therapies. Copyright © 2013 Elsevier GmbH. All rights reserved.
Nanolock-Nanopore Facilitated Digital Diagnostics of Cancer Driver Mutation in Tumor Tissue.
Wang, Yong; Tian, Kai; Shi, Ruicheng; Gu, Amy; Pennella, Michael; Alberts, Lindsey; Gates, Kent S; Li, Guangfu; Fan, Hongxin; Wang, Michael X; Gu, Li-Qun
2017-07-28
Cancer driver mutations are clinically significant biomarkers. In precision medicine, accurate detection of these oncogenic changes in patients would enable early diagnostics of cancer, individually tailored targeted therapy, and precise monitoring of treatment response. Here we investigated a novel nanolock-nanopore method for single-molecule detection of a serine/threonine protein kinase gene BRAF V600E mutation in tumor tissues of thyroid cancer patients. The method lies in a noncovalent, mutation sequence-specific nanolock. We found that the nanolock formed on the mutant allele/probe duplex can separate the duplex dehybridization procedure into two sequential steps in the nanopore. Remarkably, this stepwise unzipping kinetics can produce a unique nanopore electric marker, with which a single DNA molecule of the cancer mutant allele can be unmistakably identified in various backgrounds of the normal wild-type allele. The single-molecule sensitivity for mutant allele enables both binary diagnostics and quantitative analysis of mutation occurrence. In the current configuration, the method can detect the BRAF V600E mutant DNA lower than 1% in the tumor tissues. The nanolock-nanopore method can be adapted to detect a broad spectrum of both transversion and transition DNA mutations, with applications from diagnostics to targeted therapy.
Turetta, Matteo; Ben, Fabio Del; Brisotto, Giulia; Biscontin, Eva; Bulfoni, Michela; Cesselli, Daniela; Colombatti, Alfonso; Scoles, Giacinto; Gigli, Giuseppe; Del Mercato, Loretta L
2018-06-05
In the present review, we describe three hot topics in cancer research such as circulating tumor cells, exosomes, and 3D environment models. The first section is dedicated to microfluidic platforms for detecting circulating tumor cells, including both affinity-based methods that take advantage of antibodies and aptamers, and "label-free" approaches, exploiting cancer cells physical features and, more recently, abnormal cancer metabolism. In the second section, we briefly describe biology of exosomes and their role in cancer, as well as conventional techniques for their isolation and innovative microfluidic platforms. In the third section, the importance of tumor microenvironment is highlighted, along with techniques for modeling it in vitro. Finally, we discuss limitations of two-dimensional monolayer methods and describe advantages and disadvantages of different three-dimensional tumor systems for cell-cell interaction analysis and their potential applications in cancer management. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Dehghani, Fateme; Omidi, Fariborz; Heravizadeh, Omidreza; Barati Chamgordani, Saied; Gharibi, Vahid; Sotoudeh Manesh, Akbar
2018-03-27
In this study, cancer and non-cancer risks of exposure to volatile organic compounds in the coke production unit of a steel plant were evaluated. To determine individual exposure to benzene, toluene, xylene and ethylbenzene, personal samples were taken from the breathing zone of workers according to National Institute for Occupational Safety and Health (NIOSH) method 1501. Cancer and non-cancer risk assessment was performed, using US Environmental Protection Agency (US EPA) methods. Samples analysis showed that the concentration of benzene in the energy and biochemistry and the benzol refinement sections was higher than occupational exposure limits. The cancer risk for benzene in all sections was significantly higher than allowable limit; the non-cancer risk for benzene in all sections and toluene in the benzol refinement section was also higher than 1.0. In conclusion, the current control measures are not sufficient and should be improved for efficient control of occupational exposures.
Wang, Hsiang-Chen; Nguyen, Ngoc-Viet; Lin, Rui-Yi; Jen, Chun-Ping
2017-05-06
Analysis of cancerous cells allows us to provide useful information for the early diagnosis of cancer and to monitor treatment progress. An approach based on electrical principles has recently become an attractive technique. This study presents a microdevice that utilizes a dielectrophoretic impedance measurement method for the identification of cancerous cells. The proposed biochip consists of circle-on-line microelectrodes that are patterned using a standard microfabrication processes. A sample of various cell concentrations was introduced in an open-top microchamber. The target cells were collectively concentrated between the microelectrodes using dielectrophoresis manipulation, and their electrical impedance properties were also measured. Different stages of human esophageal squamous cell carcinoma lines could be distinguished. This result is consistent with findings using hyperspectral imaging technology. Moreover, it was observed that the distinguishing characteristics change in response to the progression of cancer cell invasiveness by Raman spectroscopy. The device enables highly efficient cell collection and provides rapid, sensitive, and label-free electrical measurements of cancerous cells.
Godbehere, Andrew; Le, Gem; El Ghaoui, Laurent; Sarkar, Urmimala
2016-01-01
Background It is difficult to synthesize the vast amount of textual data available from social media websites. Capturing real-world discussions via social media could provide insights into individuals’ opinions and the decision-making process. Objective We conducted a sequential mixed methods study to determine the utility of sparse machine learning techniques in summarizing Twitter dialogues. We chose a narrowly defined topic for this approach: cervical cancer discussions over a 6-month time period surrounding a change in Pap smear screening guidelines. Methods We applied statistical methodologies, known as sparse machine learning algorithms, to summarize Twitter messages about cervical cancer before and after the 2012 change in Pap smear screening guidelines by the US Preventive Services Task Force (USPSTF). All messages containing the search terms “cervical cancer,” “Pap smear,” and “Pap test” were analyzed during: (1) January 1–March 13, 2012, and (2) March 14–June 30, 2012. Topic modeling was used to discern the most common topics from each time period, and determine the singular value criterion for each topic. The results were then qualitatively coded from top 10 relevant topics to determine the efficiency of clustering method in grouping distinct ideas, and how the discussion differed before vs. after the change in guidelines . Results This machine learning method was effective in grouping the relevant discussion topics about cervical cancer during the respective time periods (~20% overall irrelevant content in both time periods). Qualitative analysis determined that a significant portion of the top discussion topics in the second time period directly reflected the USPSTF guideline change (eg, “New Screening Guidelines for Cervical Cancer”), and many topics in both time periods were addressing basic screening promotion and education (eg, “It is Cervical Cancer Awareness Month! Click the link to see where you can receive a free or low cost Pap test.”) Conclusions It was demonstrated that machine learning tools can be useful in cervical cancer prevention and screening discussions on Twitter. This method allowed us to prove that there is publicly available significant information about cervical cancer screening on social media sites. Moreover, we observed a direct impact of the guideline change within the Twitter messages. PMID:27288093
Association of choline and betaine levels with cancer incidence and survival: A meta-analysis.
Youn, Jiyoung; Cho, Eunyoung; Lee, Jung Eun
2018-03-22
Evidences suggest possible link between betaine and choline, methyl group donors, and cancer progression. We examined the association between choline and betaine levels and cancer incidence and survival in a meta-analysis of observational studies. We identified observational studies examining the association between choline and/or betaine levels from diet or blood and cancer incidence and survival by searching the PubMed and Web of Science databases for studies published up to Jan, 2018. After applying the selection criteria, 28 observational studies (9 case-control, 1 cross-sectional, and 18 cohort studies) were included. Relative risks (RRs) and 95% confidence intervals (CIs) were extracted, and combined RRs were calculated using random-effects models. Choline levels were not associated with cancer incidence in a meta-analysis of cohort studies. Betaine levels reduced the risk of cancer incidence in a meta-analysis of cohort studies; combined relative risks (RRs) (95% CIs) comparing the top with the bottom categories were 0.93 (0.87-0.99). When we analyzed separately according to exposure assessment method, combined RRs (95% CIs) comparing the top with the bottom categories of betaine levels were 0.87 (95% CI: 0.78-0.95) for dietary betaine and 0.88 (95% CI: 0.77-0.99) for blood levels of betaine. There were no significant associations with cancer survivorship of choline or betaine levels. We concluded that high betaine levels were associated with lower risk of the cancer incidence, especially for colorectal cancer. Copyright © 2018 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
NASA Astrophysics Data System (ADS)
Lee, Juhun; Nishikawa, Robert M.; Rohde, Gustavo K.
2018-02-01
We propose using novel imaging biomarkers for detecting mammographically-occult (MO) cancer in women with dense breast tissue. MO cancer indicates visually occluded, or very subtle, cancer that radiologists fail to recognize as a sign of cancer. We used the Radon Cumulative Distribution Transform (RCDT) as a novel image transformation to project the difference between left and right mammograms into a space, increasing the detectability of occult cancer. We used a dataset of 617 screening full-field digital mammograms (FFDMs) of 238 women with dense breast tissue. Among 238 women, 173 were normal with 2 - 4 consecutive screening mammograms, 552 normal mammograms in total, and the remaining 65 women had an MO cancer with a negative screening mammogram. We used Principal Component Analysis (PCA) to find representative patterns in normal mammograms in the RCDT space. We projected all mammograms to the space constructed by the first 30 eigenvectors of the RCDT of normal cases. Under 10-fold crossvalidation, we conducted quantitative feature analysis to classify normal mammograms and mammograms with MO cancer. We used receiver operating characteristic (ROC) analysis to evaluate the classifier's output using the area under the ROC curve (AUC) as the figure of merit. Four eigenvectors were selected via a feature selection method. The mean and standard deviation of the AUC of the trained classifier on the test set were 0.74 and 0.08, respectively. In conclusion, we utilized imaging biomarkers to highlight differences between left and right mammograms to detect MO cancer using novel imaging transformation.
Yiu, Andrew; Van Hemelrijck, Mieke; Garmo, Hans; Holmberg, Lars; Malmström, Håkan; Lambe, Mats; Hammar, Niklas; Walldius, Göran; Jungner, Ingmar; Wulaningsih, Wahyu
2017-01-01
Objectives Serum uric acid has been suggested to be associated with cancer risk. We aimed to study the association between serum uric acid and cancer incidence in a large Swedish cohort. Results A positive association was found between uric acid levels and overall cancer risk, and results were similar with adjustment for glucose, triglycerides and BMI. Hazard ratio (HR) for overall cancer for the 4th quartile of uric acid compared to the 1st was 1.08 (95% CI: 1.05–1.11) in men and 1.12 (1.09 – 1.16) in women. Site-specific analysis showed a positive association between uric acid and risk of colorectal, hepatobiliary, kidney, non-melanoma skin, and other cancers in men and of head and neck and other cancers in women. An inverse association was observed for pulmonary and central nervous system (CNS) cancers in men and breast, lymphatic and haematological, and CNS malignancies in women. Materials and Methods We included 493,281 persons aged 20 years and older who had a measurement of serum uric acid and were cancer-free at baseline in the AMORIS study. Multivariable Cox proportional hazards regression was used to investigate sex-specific quartiles of serum uric acid in relation to cancer risk in men and women. Analysis was further adjusted for serum glucose, triglycerides and, where available, BMI. Site-specific analysis was performed for major cancers. Conclusions Altered uric acid levels were associated with risk of overall and some specific cancers, further indicating the potential role of uric acid metabolism in carcinogenesis. PMID:28418841
Rousseau, Sally J.; Humiston, Sharon G.; Yosha, Amy; Winters, Paul C.; Loader, Starlene; Luong, Vi; Schwartzbauer, Bonnie; Fiscella, Kevin
2014-01-01
Purpose Patient navigation is increasingly employed to guide patients through cancer treatment. We assessed the elements of navigation that promoted patients’ involvement in treatment among patients with breast and colorectal cancer that participated in a navigation study. Methods We conducted qualitative analysis of 28 audiotaped and transcribed semi-structured interviews of navigated and un-navigated cancer patients. Results Themes included feeling emotionally and cognitively overwhelmed and desire for a strong patient-navigator partnership. Both participants who were navigated and those who were not felt that navigation did or could help address their emotional, informational, and communicational needs. The benefits of logistical support were cited less often. Conclusions Findings underscore the salience of personal relationships between patients and navigators in meeting patients’ emotional and informational needs. PMID:24890503
Zhou, Zhan; Zou, Yangyun; Liu, Gangbiao; Zhou, Jingqi; Wu, Jingcheng; Zhao, Shimin; Su, Zhixi; Gu, Xun
2017-08-29
Human genes exhibit different effects on fitness in cancer and normal cells. Here, we present an evolutionary approach to measure the selection pressure on human genes, using the well-known ratio of the nonsynonymous to synonymous substitution rate in both cancer genomes ( C N / C S ) and normal populations ( p N / p S ). A new mutation-profile-based method that adopts sample-specific mutation rate profiles instead of conventional substitution models was developed. We found that cancer-specific selection pressure is quite different from the selection pressure at the species and population levels. Both the relaxation of purifying selection on passenger mutations and the positive selection of driver mutations may contribute to the increased C N / C S values of human genes in cancer genomes compared with the p N / p S values in human populations. The C N / C S values also contribute to the improved classification of cancer genes and a better understanding of the onco-functionalization of cancer genes during oncogenesis. The use of our computational pipeline to identify cancer-specific positively and negatively selected genes may provide useful information for understanding the evolution of cancers and identifying possible targets for therapeutic intervention.
Body image disturbance in adults treated for cancer - a concept analysis.
Rhoten, Bethany A
2016-05-01
To report an analysis of the concept of body image disturbance in adults who have been treated for cancer as a phenomenon of interest to nurses. Although the concept of body image disturbance has been clearly defined in adolescents and adults with eating disorders, adults who have been treated for cancer may also experience body image disturbance. In this context, the concept of body image disturbance has not been clearly defined. Concept analysis. PubMed, Psychological Information Database and Cumulative Index of Nursing and Allied Health Literature were searched for publications from 1937 - 2015. Search terms included body image, cancer, body image disturbance, adult and concept analysis. Walker and Avant's 8-step method of concept analysis was used. The defining attributes of body image disturbance in adults who have been treated for cancer are: (1) self-perception of a change in appearance and displeasure with the change or perceived change in appearance; (2) decline in an area of function; and (3) psychological distress regarding changes in appearance and/or function. This concept analysis provides a foundation for the development of multidimensional assessment tools and interventions to alleviate body image disturbance in this population. A better understanding of body image disturbance in adults treated for cancer will assist nurses and other clinicians in identifying this phenomenon and nurse scientists in developing instruments that accurately measure this condition, along with interventions that will promote a better quality of life for survivors. © 2016 John Wiley & Sons Ltd.
Yin, Chengqiang; Zhou, Xiaoying; Dang, Yini; Yan, Jin; Zhang, Guoxin
2015-12-01
Recent evidences indicate that circulating microRNAs (miRNAs) exhibit aberrant expression in the plasma of patients suffering from cancer compared to normal individuals, suggesting that it may be a useful noninvasion diagnostic method. MiR-21 plays crucial roles in carcinogenesis and can be served as a biomarker for the detection of various cancers. Therefore, the aim of this meta-analysis is to assess the potential role of miR-21 for digestive system cancer. By searching the PubMed, Embase, and Web of Science for publications concerning the diagnostic value of miR-21 for digestive system cancer, total of 23 publications were included in this meta-analysis. Receiver operating characteristic curves (ROC) were used to check the overall test performance. For prognostic meta-analysis, pooled hazard ratios (HRs) of circulating miR-21 for survival were calculated. Totally 23 eligible publications were included in this meta-analysis (15 articles for diagnosis and 8 articles for prognosis). For diagnostic meta-analysis, the summary estimates revealed that the pooled sensitivity and specificity were 0.76 (95% CI = 0.70-0.82) and 0.84 (95% CI = 0.78-0.89). Besides, the area under the summary ROC curve (AUC) is 0.87. For prognostic meta-analysis, the pooled HR of higher miR-21 expression in circulation was 1.94 (95% CI = 0.99-3.82, P = 0.055), which indicated higher miR-21 expression could be likely to predict poorer survival in digestive system cancer. The subgroup analysis implied the higher expression of miR-21 was correlated with worse overall survival in the Asian population in digestive system cancer (HR = 2.41, 95% CI = 1.21-4.77, P = 0.012). The current evidence suggests circulating miR-21 may be suitable to be a diagnostic and prognostic biomarker for digestive system cancer in the Asians.
Rama, Ranganathan; Shanta, Viswanathan
2008-01-01
Abstract Objective To measure the bias in absolute cancer survival estimates in the absence of active follow-up of cancer patients in developing countries. Methods Included in the study were all incident cases of the 10 most common cancers and corresponding subtypes plus all tobacco-related cancers not ranked among the top 10 that were registered in the population-based cancer registry in Chennai, India, during 1990–1999 and followed through 2001. Registered incident cases were first matched with those in the all-cause mortality database from the vital statistics division of the Corporation of Chennai. Unmatched incident cancer cases were then actively followed up to determine their survival status. Absolute survival was estimated by using an actuarial method and applying different assumptions regarding the survival status (alive/dead) of cases under passive and active follow-up. Findings Before active follow-up, matches between cases ranged from 20% to 66%, depending on the site of the primary tumour. Active follow-up of unmatched incident cases revealed that 15% to 43% had died by the end of the follow-up period, while the survival status of 4% to 38% remained unknown. Before active follow-up of cancer patients, 5-year absolute survival was estimated to be between 22% and 47% higher, than when conventional actuarial assumption methods were applied to cases that were lost to follow-up. The smallest survival estimates were obtained when cases lost to follow-up were excluded from the analysis. Conclusion Under the conditions that prevail in India and other developing countries, active follow-up of cancer patients yields the most reliable estimates of cancer survival rates. Passive case follow-up alone or applying standard methods to estimate survival is likely to result in an upward bias. PMID:18670662
Advances in the Molecular Analysis of Breast Cancer: Pathway Toward Personalized Medicine.
Rosa, Marilin
2015-04-01
Breast cancer is a heterogeneous disease that encompasses a wide range of clinical behaviors and histological and molecular variants. It is the most common type of cancer affecting women worldwide and is the second leading cause of cancer death. A comprehensive literature search was performed to explore the advances in molecular medicine related to the diagnosis and treatment of breast cancer. During the last few decades, advances in molecular medicine have changed the landscape of cancer treatment as new molecular tests complement and, in many instances, exceed traditional methods for determining patient prognosis and response to treatment options. Personalized medicine is becoming the standard of care around the world. Developments in molecular profiling, genomic analysis, and the discovery of targeted drug therapies have significantly improved patient survival rates and quality of life. This review highlights what pathologists need to know about current molecular tests for classification and prognostic/ predictive assessment of breast carcinoma as well as their role as part of the medical team.
The Efficacy of Exercise in Reducing Depressive Symptoms among Cancer Survivors: A Meta-Analysis
Brown, Justin C.; Huedo-Medina, Tania B.; Pescatello, Linda S.; Ryan, Stacey M.; Pescatello, Shannon M.; Moker, Emily; LaCroix, Jessica M.; Ferrer, Rebecca A.; Johnson, Blair T.
2012-01-01
Introduction The purpose of this meta-analysis was to examine the efficacy of exercise to reduce depressive symptoms among cancer survivors. In addition, we examined the extent to which exercise dose and clinical characteristics of cancer survivors influence the relationship between exercise and reductions in depressive symptoms. Methods We conducted a systematic search identifying randomized controlled trials of exercise interventions among adult cancer survivors, examining depressive symptoms as an outcome. We calculated effect sizes for each study and performed weighted multiple regression moderator analysis. Results We identified 40 exercise interventions including 2,929 cancer survivors. Diverse groups of cancer survivors were examined in seven exercise interventions; breast cancer survivors were examined in 26; prostate cancer, leukemia, and lymphoma were examined in two; and colorectal cancer in one. Cancer survivors who completed an exercise intervention reduced depression more than controls, d + = −0.13 (95% CI: −0.26, −0.01). Increases in weekly volume of aerobic exercise reduced depressive symptoms in dose-response fashion (β = −0.24, p = 0.03), a pattern evident only in higher quality trials. Exercise reduced depressive symptoms most when exercise sessions were supervised (β = −0.26, p = 0.01) and when cancer survivors were between 47–62 yr (β = 0.27, p = 0.01). Conclusion Exercise training provides a small overall reduction in depressive symptoms among cancer survivors but one that increased in dose-response fashion with weekly volume of aerobic exercise in high quality trials. Depressive symptoms were reduced to the greatest degree among breast cancer survivors, among cancer survivors aged between 47–62 yr, or when exercise sessions were supervised. PMID:22303474
Teerlink, Craig C.; Thibodeau, Stephen N.; McDonnell, Shannon K.; Schaid, Daniel J.; Rinckleb, Antje; Maier, Christiane; Vogel, Walther; Cancel-Tassin, Geraldine; Egrot, Christophe; Cussenot, Olivier; Foulkes, William D.; Giles, Graham G.; Hopper, John L.; Severi, Gianluca; Eeles, Ros; Easton, Douglas; Kote-Jarai, Zsofia; Guy, Michelle; Cooney, Kathleen A.; Ray, Anna M.; Zuhlke, Kimberly A.; Lange, Ethan M.; FitzGerald, Liesel M.; Stanford, Janet L.; Ostrander, Elaine A.; Wiley, Kathleen E.; Isaacs, Sarah D.; Walsh, Patrick C.; Isaacs, William B.; Wahlfors, Tiina; Tammela, Teuvo; Schleutker, Johanna; Wiklund, Fredrik; Grönberg, Henrik; Emanuelsson, Monica; Carpten, John; Bailey-Wilson, Joan; Whittemore, Alice S.; Oakley-Girvan, Ingrid; Hsieh, Chih-Lin; Catalona, William J.; Zheng, S. Lilly; Jin, Guangfu; Lu, Lingyi; Xu, Jianfeng; Camp, Nicola J.; Cannon-Albright, Lisa A.
2013-01-01
Previous GWAS studies have reported significant associations between various common SNPs and prostate cancer risk using cases unselected for family history. How these variants influence risk in familial prostate cancer is not well studied. Here, we analyzed 25 previously reported SNPs across 14 loci from prior prostate cancer GWAS. The International Consortium for Prostate Cancer Genetics (ICPCG) previously validated some of these using a family-based association method (FBAT). However, this approach suffered reduced power due to the conditional statistics implemented in FBAT. Here, we use a case-control design with an empirical analysis strategy to analyze the ICPCG resource for association between these 25 SNPs and familial prostate cancer risk. Fourteen sites contributed 12,506 samples (9,560 prostate cancer cases, 3,368 with aggressive disease, and 2,946 controls from 2,283 pedigrees). We performed association analysis with Genie software which accounts for relationships. We analyzed all familial prostate cancer cases and the subset of aggressive cases. For the familial prostate cancer phenotype, 20 of the 25 SNPs were at least nominally associated with prostate cancer and 16 remained significant after multiple testing correction (p≤1E−3) occurring on chromosomal bands 6q25, 7p15, 8q24, 10q11, 11q13, 17q12, 17q24, and Xp11. For aggressive disease, 16 of the SNPs had at least nominal evidence and 8 were statistically significant including 2p15. The results indicate that the majority of common, low-risk alleles identified in GWAS studies for all prostate cancer also contribute risk for familial prostate cancer, and that some may be contribute risk to aggressive disease. PMID:24162621
NASA Astrophysics Data System (ADS)
Nallala, Jayakrupakar; Gobinet, Cyril; Diebold, Marie-Danièle; Untereiner, Valérie; Bouché, Olivier; Manfait, Michel; Sockalingum, Ganesh Dhruvananda; Piot, Olivier
2012-11-01
Innovative diagnostic methods are the need of the hour that could complement conventional histopathology for cancer diagnosis. In this perspective, we propose a new concept based on spectral histopathology, using IR spectral micro-imaging, directly applied to paraffinized colon tissue array stabilized in an agarose matrix without any chemical pre-treatment. In order to correct spectral interferences from paraffin and agarose, a mathematical procedure is implemented. The corrected spectral images are then processed by a multivariate clustering method to automatically recover, on the basis of their intrinsic molecular composition, the main histological classes of the normal and the tumoral colon tissue. The spectral signatures from different histological classes of the colonic tissues are analyzed using statistical methods (Kruskal-Wallis test and principal component analysis) to identify the most discriminant IR features. These features allow characterizing some of the biomolecular alterations associated with malignancy. Thus, via a single analysis, in a label-free and nondestructive manner, main changes associated with nucleotide, carbohydrates, and collagen features can be identified simultaneously between the compared normal and the cancerous tissues. The present study demonstrates the potential of IR spectral imaging as a complementary modern tool, to conventional histopathology, for an objective cancer diagnosis directly from paraffin-embedded tissue arrays.
Beliefs Underlying Messages of Anti-Cancer-Screening Websites in Japan: A Qualitative Analysis
Okuhara, Tsuyoshi; Ishikawa, Hirono; Okada, Masahumi; Kato, Mio; Kiuchi, Takahiro
2018-01-01
Background: Cancer screening rates are lower in Japan than in Western countries. Meanwhile, anti-cancer-screening activists take to the internet to spread their messages that cancer screening has little or no efficacy, poses substantial health risks such as side effects from radiation exposure, and that people should forgo cancer screening. We applied a qualitative approach to explore the beliefs underlying the messages of anti-cancer-screening websites, by focusing on perceived value the beliefs provided to those who held them. Methods: We conducted online searches using Google Japan and Yahoo! Japan, targeting websites we classified as “pro,” “anti,” or “neutral” depending on their claims. We applied a dual analytic approach- inductive thematic analysis and deductive interpretative analysis- to the textual data of the anti websites. Results: Of the 88 websites analyzed, five themes that correspond to beliefs were identified: destruction of common knowledge, denial of standard cancer control, education about right cancer control, education about hidden truths, and sense of superiority that only I know the truth. Authors of anti websites ascribed two values (“safety of people” and “self-esteem”) to their beliefs. Conclusion: The beliefs of authors of anti-cancer-screening websites were supposed to be strong. It would be better to target in cancer screening promotion not outright screening refusers but screening hesitant people who are more amenable to changing their attitudes toward screening. The possible means to persuade them were discussed. PMID:29479993
Respiratory cancer population-based survival in Mumbai, India.
Yeole, Balkrishna B
2005-01-01
Survival experience of patients with cancer of the larynx (ICD-32) or lung (ICD-34) registered by the Mumbai (Bombay) population based cancer registry, India, during the years 1992-94 was determined. The vital statistics of the patients were established by matching with death certificates from the Mumbai Municipal death register and by active methods such as telephone enquiry, reply-paid postal enquiry, house visits and scrutiny of case records. Of the 1905 (675 larynx and 1230 lung) eligible cases for analysis, 1480 were dead (450 larynx and 1030 lung) and 425 were alive (225 larynx and 200 lung). The overall 5-year observed and relative survival rates for laryngeal cancers were 29.1% and 36.4%, and for lung cancers were 12.5% and 15.9% respectively. On multivariate analysis, age, treatment and clinical extent of disease emerged as independent predictors of survival with both cancers. People aged 55 years and above had a relative risk of four or more for laryngeal cancer and 2.3 times and more for lung cancer death as compared to those aged less than 35 years. Early detection and prompt treatment should improve overall survival from lung as well as laryngeal cancer.
Hsiao, Tzu-Hung; Chiu, Yu-Chiao; Hsu, Pei-Yin; Lu, Tzu-Pin; Lai, Liang-Chuan; Tsai, Mong-Hsun; Huang, Tim H.-M.; Chuang, Eric Y.; Chen, Yidong
2016-01-01
Several mutual information (MI)-based algorithms have been developed to identify dynamic gene-gene and function-function interactions governed by key modulators (genes, proteins, etc.). Due to intensive computation, however, these methods rely heavily on prior knowledge and are limited in genome-wide analysis. We present the modulated gene/gene set interaction (MAGIC) analysis to systematically identify genome-wide modulation of interaction networks. Based on a novel statistical test employing conjugate Fisher transformations of correlation coefficients, MAGIC features fast computation and adaption to variations of clinical cohorts. In simulated datasets MAGIC achieved greatly improved computation efficiency and overall superior performance than the MI-based method. We applied MAGIC to construct the estrogen receptor (ER) modulated gene and gene set (representing biological function) interaction networks in breast cancer. Several novel interaction hubs and functional interactions were discovered. ER+ dependent interaction between TGFβ and NFκB was further shown to be associated with patient survival. The findings were verified in independent datasets. Using MAGIC, we also assessed the essential roles of ER modulation in another hormonal cancer, ovarian cancer. Overall, MAGIC is a systematic framework for comprehensively identifying and constructing the modulated interaction networks in a whole-genome landscape. MATLAB implementation of MAGIC is available for academic uses at https://github.com/chiuyc/MAGIC. PMID:26972162
contamDE: differential expression analysis of RNA-seq data for contaminated tumor samples.
Shen, Qi; Hu, Jiyuan; Jiang, Ning; Hu, Xiaohua; Luo, Zewei; Zhang, Hong
2016-03-01
Accurate detection of differentially expressed genes between tumor and normal samples is a primary approach of cancer-related biomarker identification. Due to the infiltration of tumor surrounding normal cells, the expression data derived from tumor samples would always be contaminated with normal cells. Ignoring such cellular contamination would deflate the power of detecting DE genes and further confound the biological interpretation of the analysis results. For the time being, there does not exists any differential expression analysis approach for RNA-seq data in literature that can properly account for the contamination of tumor samples. Without appealing to any extra information, we develop a new method 'contamDE' based on a novel statistical model that associates RNA-seq expression levels with cell types. It is demonstrated through simulation studies that contamDE could be much more powerful than the existing methods that ignore the contamination. In the application to two cancer studies, contamDE uniquely found several potential therapy and prognostic biomarkers of prostate cancer and non-small cell lung cancer. An R package contamDE is freely available at http://homepage.fudan.edu.cn/zhangh/softwares/ zhanghfd@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
2014-01-01
Background Osteopontin (Eta, secreted sialoprotein 1, opn) is secreted from different cell types including cancer cells. Three splice variant forms namely osteopontin-a, osteopontin-b and osteopontin-c have been identified. The main astonishing feature is that osteopontin-c is found to be elevated in almost all types of cancer cells. This was the vital point to consider it for sequence analysis and structure predictions which provide ample chances for prognostic, therapeutic and preventive cancer research. Methods Osteopontin-c gene sequence was determined from Breast Cancer sample and was translated to protein sequence. It was then analyzed using various software and web tools for binding pockets, docking and druggability analysis. Due to the lack of homological templates, tertiary structure was predicted using ab-initio method server – I-TASSER and was evaluated after refinement using web tools. Refined structure was compared with known bone sialoprotein electron microscopic structure and docked with CD44 for binding analysis and binding pockets were identified for drug designing. Results Signal sequence of about sixteen amino acid residues was identified using signal sequence prediction servers. Due to the absence of known structures of similar proteins, three dimensional structure of osteopontin-c was predicted using I-TASSER server. The predicted structure was refined with the help of SUMMA server and was validated using SAVES server. Molecular dynamic analysis was carried out using GROMACS software. The final model was built and was used for docking with CD44. Druggable pockets were identified using pocket energies. Conclusions The tertiary structure of osteopontin-c was predicted successfully using the ab-initio method and the predictions showed that osteopontin-c is of fibrous nature comparable to firbronectin. Docking studies showed the significant similarities of QSAET motif in the interaction of CD44 and osteopontins between the normal and splice variant forms of osteopontins and binding pockets analyses revealed several pockets which paved the way to the identification of a druggable pocket. PMID:24401206
Smith, Benjamin R; Ashton, Katherine M; Brodbelt, Andrew; Dawson, Timothy; Jenkinson, Michael D; Hunt, Neil T; Palmer, David S; Baker, Matthew J
2016-06-07
Fourier transform infrared (FTIR) spectroscopy has long been established as an analytical technique for the measurement of vibrational modes of molecular systems. More recently, FTIR has been used for the analysis of biofluids with the aim of becoming a tool to aid diagnosis. For the clinician, this represents a convenient, fast, non-subjective option for the study of biofluids and the diagnosis of disease states. The patient also benefits from this method, as the procedure for the collection of serum is much less invasive and stressful than traditional biopsy. This is especially true of patients in whom brain cancer is suspected. A brain biopsy is very unpleasant for the patient, potentially dangerous and can occasionally be inconclusive. We therefore present a method for the diagnosis of brain cancer from serum samples using FTIR and machine learning techniques. The scope of the study involved 433 patients from whom were collected 9 spectra each in the range 600-4000 cm(-1). To begin the development of the novel method, various pre-processing steps were investigated and ranked in terms of final accuracy of the diagnosis. Random forest machine learning was utilised as a classifier to separate patients into cancer or non-cancer categories based upon the intensities of wavenumbers present in their spectra. Generalised 2D correlational analysis was then employed to further augment the machine learning, and also to establish spectral features important for the distinction between cancer and non-cancer serum samples. Using these methods, sensitivities of up to 92.8% and specificities of up to 91.5% were possible. Furthermore, ratiometrics were also investigated in order to establish any correlations present in the dataset. We show a rapid, computationally light, accurate, statistically robust methodology for the identification of spectral features present in differing disease states. With current advances in IR technology, such as the development of rapid discrete frequency collection, this approach is of importance to enable future clinical translation and enables IR to achieve its potential.
Lung cancer detection by proton transfer reaction mass-spectrometric analysis of human breath gas
NASA Astrophysics Data System (ADS)
Wehinger, Andreas; Schmid, Alex; Mechtcheriakov, Sergei; Ledochowski, Maximilian; Grabmer, Christoph; Gastl, Guenther A.; Amann, Anton
2007-08-01
Background Determination of the diagnostic usefulness of proton transfer reaction mass spectrometry (PTR-MS) for detecting primary lung cancer through analysis of volatile organic compounds (VOCs) in exhaled human breath was demonstrated in this investigation. Unlike, for example, gas-chromatographic analyses, PTR-MS can be used without time-consuming preconcentration of the gas samples.Methods By means of PTR-MS, exhaled breath samples from primary lung cancer patients (n = 17) were analyzed and compared with both an overall control collective (controls total, n = 170) and three sub-collectives: hospital personnel (controls hospital, n = 35), age-matched persons (controls age, n = 25), and smokers (controls s, n = 60), respectively.Results Among the VOCs present at reasonably high concentrations, the ones leading to the product ion at m/z = 31 (VOC-31, tentatively protonated formaldehyde) and m/z = 43 (VOC-43, tentatively a fragment of protonated iso-propanol), were found at significantly higher concentrations in the breath gas of the primary lung cancer patients as compared to the healthy controls at the following median concentrations (with interquartile distance, iqr): For VOC-31 the median concentrations were 7.0 ppb (iqr, 15.5 ppb) versus 3.0 ppb (iqr, 1.9 ppb) with P < 10-4. For VOC-43 the median concentrations were 244.1 ppb (iqr, 236.2 ppb) versus 94.1 ppb (iqr, 55.2 ppb) with P < 10-6. The discriminative power between the two collectives was further assessed by ROC-curves obtained upon variation of the chosen threshold concentration and by Fisher's Quadratic Discriminant Method.Conclusions Within the limits of pilot study, VOC-31 and -43 were found to best discriminate between exhaled breath of primary lung cancer cases and healthy controls. Simple and time-saving breath gas analysis by PTR-MS makes this method attractive for a larger clinical evaluation. It may become a new valuable tool for diagnosing primary lung cancer.
2009-01-01
Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical. Conclusion Feature variability can have a strong impact on breast cancer signature composition, as well as the classification of individual patient samples. We therefore strongly recommend that feature variability is considered in analyzing data from microarray breast cancer expression profiling experiments. PMID:19941644
Fully automated screening of immunocytochemically stained specimens for early cancer detection
NASA Astrophysics Data System (ADS)
Bell, André A.; Schneider, Timna E.; Müller-Frank, Dirk A. C.; Meyer-Ebrecht, Dietrich; Böcking, Alfred; Aach, Til
2007-03-01
Cytopathological cancer diagnoses can be obtained less invasive than histopathological investigations. Cells containing specimens can be obtained without pain or discomfort, bloody biopsies are avoided, and the diagnosis can, in some cases, even be made earlier. Since no tissue biopsies are necessary these methods can also be used in screening applications, e.g., for cervical cancer. Among the cytopathological methods a diagnosis based on the analysis of the amount of DNA in individual cells achieves high sensitivity and specificity. Yet this analysis is time consuming, which is prohibitive for a screening application. Hence, it will be advantageous to retain, by a preceding selection step, only a subset of suspicious specimens. This can be achieved using highly sensitive immunocytochemical markers like p16 ink4a for preselection of suspicious cells and specimens. We present a method to fully automatically acquire images at distinct positions at cytological specimens using a conventional computer controlled microscope and an autofocus algorithm. Based on the thus obtained images we automatically detect p16 ink4a-positive objects. This detection in turn is based on an analysis of the color distribution of the p16 ink4a marker in the Lab-colorspace. A Gaussian-mixture-model is used to describe this distribution and the method described in this paper so far achieves a sensitivity of up to 90%.
Height and Breast Cancer Risk: Evidence From Prospective Studies and Mendelian Randomization
Zhang, Ben; Shu, Xiao-Ou; Delahanty, Ryan J.; Zeng, Chenjie; Michailidou, Kyriaki; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Wen, Wanqing; Long, Jirong; Li, Chun; Dunning, Alison M.; Chang-Claude, Jenny; Shah, Mitul; Perkins, Barbara J.; Czene, Kamila; Darabi, Hatef; Eriksson, Mikael; Bojesen, Stig E.; Nordestgaard, Børge G.; Nielsen, Sune F.; Flyger, Henrik; Lambrechts, Diether; Neven, Patrick; Wildiers, Hans; Floris, Giuseppe; Schmidt, Marjanka K.; Rookus, Matti A.; van den Hurk, Katja; de Kort, Wim L. A. M.; Couch, Fergus J.; Olson, Janet E.; Hallberg, Emily; Vachon, Celine; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Peto, Julian; dos-Santos-Silva, Isabel; Fletcher, Olivia; Johnson, Nichola; Nevanlinna, Heli; Muranen, Taru A.; Aittomäki, Kristiina; Blomqvist, Carl; Li, Jingmei; Humphreys, Keith; Brand, Judith; Guénel, Pascal; Truong, Thérèse; Cordina-Duverger, Emilie; Menegaux, Florence; Burwinkel, Barbara; Marme, Frederik; Yang, Rongxi; Surowy, Harald; Benitez, Javier; Zamora, M. Pilar; Perez, Jose I. A.; Cox, Angela; Cross, Simon S.; Reed, Malcolm W. R.; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Tchatchou, Sandrine; Sawyer, Elinor J.; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Chenevix-Trench, Georgia; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Marchand, Loic Le; Lindblom, Annika; Margolin, Sara; Hooning, Maartje J.; Martens, John W. M.; Tilanus-Linthorst, Madeleine M. A.; Collée, J. Margriet; Hopper, John L.; Southey, Melissa C.; Tsimiklis, Helen; Apicella, Carmel; Slager, Susan; Toland, Amanda E.; Ambrosone, Christine B.; Yannoukakos, Drakoulis; Giles, Graham G.; Milne, Roger L.; McLean, Catriona; Fasching, Peter A.; Haeberle, Lothar; Ekici, Arif B.; Beckmann, Matthias W.; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Swerdlow, Anthony J.; Ashworth, Alan; Orr, Nick; Jones, Michael; Figueroa, Jonine; Garcia-Closas, Montserrat; Brinton, Louise; Lissowska, Jolanta; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Brüning, Thomas; Ko, Yon-Dschun; Peterlongo, Paolo; Manoukian, Siranoush; Bonanni, Bernardo; Radice, Paolo; Bogdanova, Natalia; Antonenkova, Natalia; Dörk, Thilo; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Devilee, Peter; Seynaeve, Caroline; Van Asperen, Christi J.; Jakubowska, Anna; Lubiński, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katarzyna; Hamann, Ute; Torres, Diana; Schmutzler, Rita K.; Neuhausen, Susan L.; Anton-Culver, Hoda; Kristensen, Vessela N.; Grenaker Alnæs, Grethe I.; Pierce, Brandon L.; Kraft, Peter; Peters, Ulrike; Lindstrom, Sara; Seminara, Daniela; Burgess, Stephen; Ahsan, Habibul; Whittemore, Alice S.; John, Esther M.; Gammon, Marilie D.; Malone, Kathleen E.; Tessier, Daniel C.; Vincent, Daniel; Bacot, Francois; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Maranian, Mel; Healey, Catherine S.; González-Neira, Anna; Pita, Guillermo; Alonso, M. Rosario; Álvarez, Nuria; Herrero, Daniel; Pharoah, Paul D. P.; Simard, Jacques; Hall, Per; Hunter, David J.; Easton, Douglas F.
2015-01-01
Background: Epidemiological studies have linked adult height with breast cancer risk in women. However, the magnitude of the association, particularly by subtypes of breast cancer, has not been established. Furthermore, the mechanisms of the association remain unclear. Methods: We performed a meta-analysis to investigate associations between height and breast cancer risk using data from 159 prospective cohorts totaling 5216302 women, including 113178 events. In a consortium with individual-level data from 46325 case patients and 42482 control subjects, we conducted a Mendelian randomization analysis using a genetic score that comprised 168 height-associated variants as an instrument. This association was further evaluated in a second consortium using summary statistics data from 16003 case patients and 41335 control subjects. Results: The pooled relative risk of breast cancer was 1.17 (95% confidence interval [CI] = 1.15 to 1.19) per 10cm increase in height in the meta-analysis of prospective studies. In Mendelian randomization analysis, the odds ratio of breast cancer per 10cm increase in genetically predicted height was 1.22 (95% CI = 1.13 to 1.32) in the first consortium and 1.21 (95% CI = 1.05 to 1.39) in the second consortium. The association was found in both premenopausal and postmenopausal women but restricted to hormone receptor–positive breast cancer. Analyses of height-associated variants identified eight new loci associated with breast cancer risk after adjusting for multiple comparisons, including three loci at 1q21.2, DNAJC27, and CCDC91 at genome-wide significance level P < 5×10–8. Conclusions: Our study provides strong evidence that adult height is a risk factor for breast cancer in women and certain genetic factors and biological pathways affecting adult height have an important role in the etiology of breast cancer. PMID:26296642
Guo, L W; Zhang, S K; Liu, S Z; Chen, Q; Zhang, M; Quan, P L; Lu, J B; Sun, X B
2016-02-01
Globally, the prevalence of oesophageal cancer cases is particularly high in China. Since 1982, oncogenic human papillomavirus (HPV) has been hypothesized as a risk factor for oesophageal cancer, but no firm evidence of HPV infection in oesophageal cancer has been established to date. We aimed to conduct a meta-analysis to estimate the high-risk HPV-18 prevalence of oesophageal cancer in the Chinese population. Eligible studies published from 1 January 2005 to 12 July 2014 were retrieved via computer searches of English and Chinese literature databases (including Medline, EMBASE, Chinese National Knowledge Infrastructure and Wanfang Data Knowledge Service Platform). A random-effects model was used to calculate pooled prevalence and corresponding 95% confidence intervals (CIs). A total of 2556 oesophageal cancer cases from 19 studies were included in this meta-analysis. Overall, the pooled HPV-18 prevalence in oesophageal cancer cases was 4·1% (95% CI 2·7-5·5) in China, 6·1% (95% CI 2·9-9·3) in fresh or frozen biopsies and 4·0% (95% CI 2·3-5·8) in paraffin-embedded fixed biopsies, 8·2% (95% CI 4·6-11·7) by the E6/E7 region and 2·2% (95% CI 0·9-3·6) by the L1 region of the HPV gene. This meta-analysis indicated that China has a moderate HPV-18 prevalence of oesophageal cancer compared to cervical cancer, although there is variation between different variables. Further studies are needed to elucidate the role of HPV in oesophagus carcinogenesis with careful consideration of study design and laboratory detection method, providing more accurate assessment of HPV status in oesophageal cancer.
Circulating tumor DNA: a promising biomarker in the liquid biopsy of cancer.
Cheng, Feifei; Su, Li; Qian, Cheng
2016-07-26
Tissue biopsy is the standard diagnostic procedure for cancers and also provides a material for genotyping, which can assist in the targeted therapies of cancers. However, tissue biopsy-based cancer diagnostic procedures have limitations in their assessment of cancer development, prognosis and genotyping, due to tumor heterogeneity and evolution. Circulating tumor DNA (ctDNA) is single- or double-stranded DNA released by the tumor cells into the blood and it thus harbors the mutations of the original tumor. In recent years, liquid biopsy based on ctDNA analysis has shed a new light on the molecular diagnosis and monitoring of cancer. Studies found that the screening of genetic mutations using ctDNA is highly sensitive and specific, suggesting that ctDNA analysis may significantly improve current systems of tumor diagnosis, even facilitating early-stage detection. Moreover, ctDNA analysis is capable of accurately determining the tumor progression, prognosis and assisting in targeted therapy. Therefore, using ctDNA as a liquid biopsy may herald a revolution for tumor management. Herein, we review the biology of ctDNA, its detection methods and potential applications in tumor diagnosis, treatment and prognosis.
Circulating tumor DNA: a promising biomarker in the liquid biopsy of cancer
Cheng, Feifei; Su, Li; Qian, Cheng
2016-01-01
Tissue biopsy is the standard diagnostic procedure for cancers and also provides a material for genotyping, which can assist in the targeted therapies of cancers. However, tissue biopsy-based cancer diagnostic procedures have limitations in their assessment of cancer development, prognosis and genotyping, due to tumor heterogeneity and evolution. Circulating tumor DNA (ctDNA) is single- or double-stranded DNA released by the tumor cells into the blood and it thus harbors the mutations of the original tumor. In recent years, liquid biopsy based on ctDNA analysis has shed a new light on the molecular diagnosis and monitoring of cancer. Studies found that the screening of genetic mutations using ctDNA is highly sensitive and specific, suggesting that ctDNA analysis may significantly improve current systems of tumor diagnosis, even facilitating early-stage detection. Moreover, ctDNA analysis is capable of accurately determining the tumor progression, prognosis and assisting in targeted therapy. Therefore, using ctDNA as a liquid biopsy may herald a revolution for tumor management. Herein, we review the biology of ctDNA, its detection methods and potential applications in tumor diagnosis, treatment and prognosis. PMID:27223063
Consumption of garlic and risk of colorectal cancer: An updated meta-analysis of prospective studies
Hu, Ji-Yi; Hu, Yi-Wang; Zhou, Jiao-Jiao; Zhang, Meng-Wen; Li, Dan; Zheng, Shu
2014-01-01
AIM: To conduct an updated meta-analysis of prospective studies addressing the association between garlic consumption and colorectal cancer. METHODS: Eligible cohort studies were identified by searching MEDLINE (PubMed) and screening the references of related articles published up to October 2013. Meta-analyses were conducted for colorectal cancer in relation to consumption of raw and cooked (RC) garlic and garlic supplements, separately. The summary relative risks (RR) with 95%CI were calculated using fixed-effects or random-effects model depending on the heterogeneity among studies. RESULTS: A total of 5 prospective cohort studies were identified. In contrast to the previous meta-analysis, no significant associations were found between consumption of RC garlic (RR: 1.06; 95%CI: 0.95-1.19) or garlic supplements (RR: 1.12; 95%CI: 0.96-1.31) and risk of colorectal cancer. A non-significant protective effect of garlic supplement intake against colorectal cancer was observed in females (RR: 0.84; 95%CI: 0.64-1.11), but the opposite was the case in males (RR: 1.24; 95%CI: 0.96-1.59). CONCLUSION: Consumption of RC garlic or garlic supplements is not significantly associated with reduced colorectal cancer risk. PMID:25386091
NASA Astrophysics Data System (ADS)
Fatekurohman, Mohamat; Nurmala, Nita; Anggraeni, Dian
2018-04-01
Lungs are the most important organ, in the case of respiratory system. Problems related to disorder of the lungs are various, i.e. pneumonia, emphysema, tuberculosis and lung cancer. Comparing all those problems, lung cancer is the most harmful. Considering about that, the aim of this research applies survival analysis and factors affecting the endurance of the lung cancer patient using comparison of exact, Efron and Breslow parameter approach method on hazard ratio and stratified cox regression model. The data applied are based on the medical records of lung cancer patients in Jember Paru-paru hospital on 2016, east java, Indonesia. The factors affecting the endurance of the lung cancer patients can be classified into several criteria, i.e. sex, age, hemoglobin, leukocytes, erythrocytes, sedimentation rate of blood, therapy status, general condition, body weight. The result shows that exact method of stratified cox regression model is better than other. On the other hand, the endurance of the patients is affected by their age and the general conditions.
Gripsrud, Birgitta Haga; Brassil, Kelly J; Summers, Barbara; Søiland, Håvard; Kronowitz, Steven; Lode, Kirsten
2016-01-01
Expressive writing has been shown to improve quality of life, fatigue, and posttraumatic stress among breast cancer patients across cultures. Understanding how and why the method may be beneficial to patients can increase awareness of the psychosocial impact of breast cancer and enhance interventional work within this population. Qualitative research on experiential aspects of interventions may inform the theoretical understanding and generate hypotheses for future studies. The aim of the study was to explore and describe the experience and feasibility of expressive writing among women with breast cancer following mastectomy and immediate or delayed reconstructive surgery. Seven participants enrolled to undertake 4 episodes of expressive writing at home, with semistructured interviews conducted afterward and analyzed using experiential thematic analysis. Three themes emerged through analysis: writing as process, writing as therapeutic, and writing as a means to help others. Findings illuminate experiential variations in expressive writing and how storytelling encourages a release of cognitive and emotional strains, surrendering these to reside in the text. The method was said to process feelings and capture experiences tied to a new and overwhelming illness situation, as impressions became expressions through writing. Expressive writing, therefore, is a valuable tool for healthcare providers to introduce into the plan of care for patients with breast cancer and potentially other cancer patient groups. This study augments existing evidence to support the appropriateness of expressive writing as an intervention after a breast cancer diagnosis. Further studies should evaluate its feasibility at different time points in survivorship.
“Shielded from the Real World”: Perspectives on Internet Cancer Support Groups by Asian Americans
Im, Eun-Ok; Lee, Bok Im; Chee, Wonshik
2010-01-01
Background Despite positive reports about Internet cancer support groups (ICSGs), ethnic minorities, including Asian Americans, have been reported to be less likely to use ICSGs. Unique cultural values, beliefs, and attitudes have been considered reasons for the low usage rate of ICSGs among Asian Americans. However, studies have rarely looked at this issue. Objective The purpose of this study was to explore (a) how Asian Americans living with cancer who participated in ICSGs viewed ICSGs, (b) what facilitated or inhibited their participation in ICSGs, and (c) what cultural values and beliefs influenced their participation in ICSGs. Methods The study was a one-month qualitative online forum among 18 Asian American cancer patients recruited through a convenience sampling method. Nine topics on the use of ICSGs organized the forum discussion, and the data were analyzed using thematic analysis. Results Four themes emerged from the data analysis process: (a) “more than just my family,” (b) “part of my family,” (c) “anonymous me,” and (d) “shielded from the real world.” Conclusions The overarching theme was Asian Americans’ marginalized experience in the use of Internet cancer support groups. Implications for Practice Offering the most current information on cancer and cancer treatment is essential for nursing practice in developing a culturally competent ICSG for Asian Americans. Also, emotional familiarity should be incorporated into the design of the ICSG, and the ICSG needs to be based on non-judgmental and non-discriminative interactions. PMID:20357657
Alizadeh, Nastaran; Amiri, Mohammad Mehdi; Salek Moghadam, Alireza; Zarnani, Amir Hassan; Saadat, Farshid; Safavifar, Farnaz; Berahmeh, Azar; Khorramizadeh, Mohammad Reza
2013-05-15
There exists compelling evidence that Toll-like receptor 3 (TLR3) agonists can directly affect human cancer cells. The aim of this study was to investigate anti-cancer effects of TLR3 agonist in human breast cell line. We assessed potential effects of poly (A:U) on human breast cell line (MDA-MB-231) on a dose-response and time-course basis. Human breast cell line MDA-MB-231 was treated with different concentrations of poly (A:U) and lipopolysaccharide (LPS). Then, the following assays were performed on the treated cells: dose-response and time-course cytotoxicity using colorimetric method; matrix metalloproteinase-2 (MMP-2) activity using gelatin zymography method; apoptosis using annexin-v flowcytometry method; and relative expression of TLR3 and MMP-2 mRNA using reverse transcriptase polymerase chain reaction (RT-PCR) method. Following treatments, dose- response and time-course cytotoxicity using a colorimetric method, (MMP-2) activity (using gelatin zymography), apoptosis (using annexin-v flowcytometry method) assays and expression of TLR3 and MMP-2 genes (using PCR method) were performed. Cytotoxicity and flowcytometry analysis of poly (A:U) showed that poly (A:U) do not have any cytotoxic and apoptotic effects in different concentrations used. MMP-2 activity analysis showed significant decrease in higher concentrations (50 and 100 μg/ ml) between treated and untreated cells. Moreover, poly A:U treated cells demonstrated decreased expression of MMP-2 gene in higher concentrations. Collectively, our data indicated that human breast cancer cell line (MDA-MB-231) was highly responsive to poly (A:U). The antimetastatic effect of direct poly (A:U) and TLR3 interactions in MDA-MB-231 cells could provide new approaches in malignant tumor therapeutic strategy.
On behalf of the National Cancer Institute and the Office of Cancer Clinical Proteomics Research, you are invited to the First Annual CPTAC Scientific Symposium on Wednesday, November 13, 2013. The purpose of this symposium, which consists of plenary and poster sessions, is for investigators from CPTAC community and beyond to share and discuss novel biological discoveries, analytical methods, and translational approaches using CPTAC data.
2012-01-01
Background Non-small cell lung cancer, breast cancer, and colorectal cancer are commonly diagnosed cancers in Canada. Patients diagnosed with early-stage non-small cell lung, breast, or colorectal cancer represent potentially curable populations. For these patients, surgery is the primary mode of treatment, with (neo)adjuvant therapies (e.g., chemotherapy, radiotherapy) recommended according to disease stage. Data from our research in Nova Scotia, as well as others’, demonstrate that a substantial proportion of non-small cell lung cancer and colorectal cancer patients, for whom practice guidelines recommend (neo)adjuvant therapy, are not referred for an oncologist consultation. Conversely, surveillance data and clinical experience suggest that breast cancer patients have much higher referral rates. Since surgery is the primary treatment, the surgeon plays a major role in referring patients to oncologists. Thus, an improved understanding of how surgeons make decisions related to oncology services is important to developing strategies to optimize referral rates. Few studies have examined decision making for (neo)adjuvant therapy from the perspective of the cancer surgeon. This study will use qualitative methods to examine decision-making processes related to referral to oncology services for individuals diagnosed with potentially curable non-small cell lung, breast, or colorectal cancer. Methods A qualitative study will be conducted, guided by the principles of grounded theory. The study design is informed by our ongoing research, as well as a model of access to health services. The method of data collection will be in-depth, semi structured interviews. We will attempt to recruit all lung, breast, and/or colorectal cancer surgeons in Nova Scotia (n ≈ 42), with the aim of interviewing a minimum of 34 surgeons. Interviews will be audiotaped and transcribed verbatim. Data will be collected and analyzed concurrently, with two investigators independently coding and analyzing the data. Analysis will involve an inductive, grounded approach using constant comparative analysis. Discussion The primary outcomes will be (1) identification of the patient, surgeon, institutional, and health-system factors that influence surgeons’ decisions to refer non-small cell lung, breast, and colorectal cancer patients to oncology services when consideration for (neo)adjuvant therapy is recommended and (2) identification of potential strategies that could optimize referral to oncology for appropriate individuals. PMID:23098262
Prades, Joan; Morando, Verdiana; Tozzi, Valeria D; Verhoeven, Didier; Germà, Jose R; Borras, Josep M
2017-01-01
Background The study examines two meso-strategic cancer networks, exploring to what extent collaboration can strengthen or hamper network effectiveness. Unlike macro-strategic networks, meso-strategic networks have no hierarchical governance structures nor are they institutionalised within healthcare services' delivery systems. This study aims to analyse the models of professional cooperation and the tools developed for managing clinical practice within two meso-strategic, European cancer networks. Methods Multiple case study design based on the comparative analysis of two cancer networks: Iridium, in Antwerp, Belgium and the Institut Català d'Oncologia in Catalonia, Spain. The case studies applied mixed methods, with qualitative research based on semi-structured interviews ( n = 35) together with case-site observation and material collection. Results The analysis identified four levels of collaborative intensity within medical specialties as well as in multidisciplinary settings, which became both platforms for crosscutting clinical work between hubs' experts and local care teams and the levers for network-based tools development. The organisation of clinical practice relied on professional-based cooperative processes and tiers, lacking vertical integration mechanisms. Conclusions The intensity of professional linkages largely shaped the potential of meso-strategic cancer networks to influence clinical practice organisation. Conversely, the introduction of managerial techniques or network governance structures, without introducing vertical hierarchies, was found to be critical solutions.
Kashyap, Anamika; Jain, Manjula; Shukla, Shailaja; Andley, Manoj
2018-01-01
Background: Fine needle aspiration cytology (FNAC) is a simple, rapid, inexpensive, and reliable method of diagnosis of breast mass. Cytoprognostic grading in breast cancers is important to identify high-grade tumors. Computer-assisted image morphometric analysis has been developed to quantitate as well as standardize various grading systems. Aims: To apply nuclear morphometry on cytological aspirates of breast cancer and evaluate its correlation with cytomorphological grading with derivation of suitable cutoff values between various grades. Settings and Designs: Descriptive cross-sectional hospital-based study. Materials and Methods: This study included 64 breast cancer cases (29 of grade 1, 22 of grade 2, and 13 of grade 3). Image analysis was performed on Papanicolaou stained FNAC slides by NIS –Elements Advanced Research software (Ver 4.00). Nuclear morphometric parameters analyzed included 5 nuclear size, 2 shape, 4 texture, and 2 density parameters. Results: Nuclear size parameters showed an increase in values with increasing cytological grades of carcinoma. Nuclear shape parameters were not found to be significantly different between the three grades. Among nuclear texture parameters, sum intensity, and sum brightness were found to be different between the three grades. Conclusion: Nuclear morphometry can be applied to augment the cytology grading of breast cancer and thus help in classifying patients into low and high-risk groups. PMID:29403169
Image classification of human carcinoma cells using complex wavelet-based covariance descriptors.
Keskin, Furkan; Suhre, Alexander; Kose, Kivanc; Ersahin, Tulin; Cetin, A Enis; Cetin-Atalay, Rengul
2013-01-01
Cancer cell lines are widely used for research purposes in laboratories all over the world. Computer-assisted classification of cancer cells can alleviate the burden of manual labeling and help cancer research. In this paper, we present a novel computerized method for cancer cell line image classification. The aim is to automatically classify 14 different classes of cell lines including 7 classes of breast and 7 classes of liver cancer cells. Microscopic images containing irregular carcinoma cell patterns are represented by subwindows which correspond to foreground pixels. For each subwindow, a covariance descriptor utilizing the dual-tree complex wavelet transform (DT-[Formula: see text]WT) coefficients and several morphological attributes are computed. Directionally selective DT-[Formula: see text]WT feature parameters are preferred primarily because of their ability to characterize edges at multiple orientations which is the characteristic feature of carcinoma cell line images. A Support Vector Machine (SVM) classifier with radial basis function (RBF) kernel is employed for final classification. Over a dataset of 840 images, we achieve an accuracy above 98%, which outperforms the classical covariance-based methods. The proposed system can be used as a reliable decision maker for laboratory studies. Our tool provides an automated, time- and cost-efficient analysis of cancer cell morphology to classify different cancer cell lines using image-processing techniques, which can be used as an alternative to the costly short tandem repeat (STR) analysis. The data set used in this manuscript is available as supplementary material through http://signal.ee.bilkent.edu.tr/cancerCellLineClassificationSampleImages.html.
Image Classification of Human Carcinoma Cells Using Complex Wavelet-Based Covariance Descriptors
Keskin, Furkan; Suhre, Alexander; Kose, Kivanc; Ersahin, Tulin; Cetin, A. Enis; Cetin-Atalay, Rengul
2013-01-01
Cancer cell lines are widely used for research purposes in laboratories all over the world. Computer-assisted classification of cancer cells can alleviate the burden of manual labeling and help cancer research. In this paper, we present a novel computerized method for cancer cell line image classification. The aim is to automatically classify 14 different classes of cell lines including 7 classes of breast and 7 classes of liver cancer cells. Microscopic images containing irregular carcinoma cell patterns are represented by subwindows which correspond to foreground pixels. For each subwindow, a covariance descriptor utilizing the dual-tree complex wavelet transform (DT-WT) coefficients and several morphological attributes are computed. Directionally selective DT-WT feature parameters are preferred primarily because of their ability to characterize edges at multiple orientations which is the characteristic feature of carcinoma cell line images. A Support Vector Machine (SVM) classifier with radial basis function (RBF) kernel is employed for final classification. Over a dataset of 840 images, we achieve an accuracy above 98%, which outperforms the classical covariance-based methods. The proposed system can be used as a reliable decision maker for laboratory studies. Our tool provides an automated, time- and cost-efficient analysis of cancer cell morphology to classify different cancer cell lines using image-processing techniques, which can be used as an alternative to the costly short tandem repeat (STR) analysis. The data set used in this manuscript is available as supplementary material through http://signal.ee.bilkent.edu.tr/cancerCellLineClassificationSampleImages.html. PMID:23341908
Dietary Inflammatory Potential Score and Risk of Breast Cancer: Systematic Review and Meta-analysis.
Zahedi, Hoda; Djalalinia, Shirin; Sadeghi, Omid; Asayesh, Hamid; Noroozi, Mehdi; Gorabi, Armita Mahdavi; Mohammadi, Rasool; Qorbani, Mostafa
2018-02-07
Several studies have been conducted on the relationship between dietary inflammatory potential (DIP) and breast cancer. However, the findings are conflicting. This systematic review and meta-analysis summarizes the findings on the association between DIP and the risk of breast cancer. We used relevant keywords and searched online international electronic databases, including PubMed and NLM Gateway (for Medline), Institute for Scientific Information (ISI), and Scopus for articles published through February 2017. All cross-sectional, case-control, and cohort studies were included in this meta-analysis. Meta-analysis was performed using the random effects meta-analysis method to address heterogeneity among studies. Findings were analyzed statistically. Nine studies were included in the present systematic review and meta-analysis. The total sample size of these studies was 296,102, and the number of participants varied from 1453 to 122,788. The random effects meta-analysis showed a positive and significant association between DIP and the risk of breast cancer (pooled odds ratio, 1.14; 95% confidence interval, 1.01-1.27). The pooled effect size was not statistically significant because of the type of studies, including cohort (pooled relative risk, 1.04; 95% confidence interval, 0.98-1.10) and case-control (pooled odds ratio, 1.63; 95% confidence interval, 0.89-2.37) studies. We found a significant and positive association between higher DIP score and risk of breast cancer. Modifying inflammatory characteristics of diet can substantially reduce the risk of breast cancer. Copyright © 2018 Elsevier Inc. All rights reserved.
Li, Hongru; Xu, Yadong; Li, Hui
2017-01-01
Objective To assess the prognostic and clinicopathological characteristics of CD147 in human bladder cancer. Methods Studies on CD147 expression in bladder cancer were retrieved from PubMed, EMBASE, the Cochrane Library, Web of Science, China National Knowledge Infrastructure, and the WanFang databases. Outcomes were pooled with meta-analyzing softwares RevMan 5.3 and STATA 14.0. Results Twenty-four studies with 25 datasets demonstrated that CD147 expression was higher in bladder cancer than in non-cancer tissues (OR=43.64, P<0.00001). Moreover, this increase was associated with more advanced clinical stages (OR=73.89, P<0.0001), deeper invasion (OR=3.22, P<0.00001), lower histological differentiation (OR=4.54, P=0.0005), poorer overall survival (univariate analysis, HR=2.63, P<0.00001; multivariate analysis, HR=1.86, P=0.00036), disease specific survival (univariate analysis, HR=1.65, P=0.002), disease recurrence-free survival (univariate analysis, HR=2.78, P=0.001; multivariate analysis, HR=5.51, P=0.017), rate of recurrence (OR=1.91, P=0.0006), invasive depth (pT2∼T4 vs. pTa∼T1; OR=3.22, P<0.00001), and histological differentiation (low versus moderate-to-high; OR=4.54, P=0.0005). No difference was found among disease specific survival in multivariate analysis (P=0.067), lymph node metastasis (P=0.12), and sex (P=0.15). Conclusion CD147 could be a biomarker for early diagnosis, treatment, and prognosis of bladder cancer. PMID:28977970
Calle, M. Luz; Rothman, Nathaniel; Urrea, Víctor; Kogevinas, Manolis; Petrus, Sandra; Chanock, Stephen J.; Tardón, Adonina; García-Closas, Montserrat; González-Neira, Anna; Vellalta, Gemma; Carrato, Alfredo; Navarro, Arcadi; Lorente-Galdós, Belén; Silverman, Debra T.; Real, Francisco X.; Wu, Xifeng; Malats, Núria
2013-01-01
The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk. PMID:24391818
Measuring Integration of Cancer Services to Support Performance Improvement: The CSI Survey
Dobrow, Mark J.; Paszat, Lawrence; Golden, Brian; Brown, Adalsteinn D.; Holowaty, Eric; Orchard, Margo C.; Monga, Neerav; Sullivan, Terrence
2009-01-01
Objective: To develop a measure of cancer services integration (CSI) that can inform clinical and administrative decision-makers in their efforts to monitor and improve cancer system performance. Methods: We employed a systematic approach to measurement development, including review of existing cancer/health services integration measures, key-informant interviews and focus groups with cancer system leaders. The research team constructed a Web-based survey that was field- and pilot-tested, refined and then formally conducted on a sample of cancer care providers and administrators in Ontario, Canada. We then conducted exploratory factor analysis to identify key dimensions of CSI. Results: A total of 1,769 physicians, other clinicians and administrators participated in the survey, responding to a 67-item questionnaire. The exploratory factor analysis identified 12 factors that were linked to three broader dimensions: clinical, functional and vertical system integration. Conclusions: The CSI Survey provides important insights on a range of typically unmeasured aspects of the coordination and integration of cancer services, representing a new tool to inform performance improvement efforts. PMID:20676250
Radon and lung cancer: a cost-effectiveness analysis.
Ford, E S; Kelly, A E; Teutsch, S M; Thacker, S B; Garbe, P L
1999-01-01
OBJECTIVES: This study examined the cost-effectiveness of general and targeted strategies for residential radon testing and mitigation in the United States. METHODS: A decision-tree model was used to perform a cost-effectiveness analysis of preventing radon-associated deaths from lung cancer. RESULTS: For a radon threshold of 4 pCi/L, the estimated costs to prevent 1 lung cancer death are about $3 million (154 lung cancer deaths prevented), or $480,000 per life-year saved, based on universal radon screening and mitigation, and about $2 million (104 lung cancer deaths prevented), or $330,000 per life-year saved, if testing and mitigation are confined to geographic areas at high risk for radon exposure. For mitigation undertaken after a single screening test and after a second confirmatory test, the estimated costs are about $920,000 and $520,000, respectively, to prevent a lung cancer death with universal screening and $130,000 and $80,000 per life-year for high risk screening. The numbers of preventable lung cancer deaths are 811 and 527 for universal and targeted approaches, respectively. CONCLUSIONS: These data suggest possible alternatives to current recommendations. PMID:10076484
Novel signatures of cancer-associated fibroblasts.
Bozóky, Benedek; Savchenko, Andrii; Csermely, Péter; Korcsmáros, Tamás; Dúl, Zoltán; Pontén, Fredrik; Székely, László; Klein, George
2013-07-15
Increasing evidence indicates the importance of the tumor microenvironment, in particular cancer-associated fibroblasts, in cancer development and progression. In our study, we developed a novel, visually based method to identify new immunohistochemical signatures of these fibroblasts. The method employed a protein list based on 759 protein products of genes identified by RNA profiling from our previous study, comparing fibroblasts with differential growth-modulating effect on human cancers cells, and their first neighbors in the human protein interactome. These 2,654 proteins were analyzed in the Human Protein Atlas online database by comparing their immunohistochemical expression patterns in normal versus tumor-associated fibroblasts. Twelve new proteins differentially expressed in cancer-associated fibroblasts were identified (DLG1, BHLHE40, ROCK2, RAB31, AZI2, PKM2, ARHGAP31, ARHGAP26, ITCH, EGLN1, RNF19A and PLOD2), four of them can be connected to the Rho kinase signaling pathway. They were further analyzed in several additional tumor stromata and revealed that the majority showed congruence among the different tumors. Many of them were also positive in normal myofibroblast-like cells. The new signatures can be useful in immunohistochemical analysis of different tumor stromata and may also give us an insight into the pathways activated in them in their true in vivo context. The method itself could be used for other similar analysis to identify proteins expressed in other cell types in tumors and their surrounding microenvironment. Copyright © 2013 UICC.
Long-term health effects among testicular cancer survivors
Hashibe, Mia; Abdelaziz, Sarah; Al-Temimi, Mohammed; Fraser, Alison; Boucher, Kenneth M.; Smith, Ken; Lee, Yuan-chin Amy; Rowe, Kerry; Rowley, Braden; Daurelle, Micky; Holton, Avery E.; VanDerslice, James; Richiardi, Lorenzo; Bishoff, Jay; Lowrance, Will; Stroup, Antoinette
2016-01-01
Purpose Testicular cancer is diagnosed at a young age and survival rates are high, thus the long term effects of cancer treatment need to be assessed. Our objectives are to estimate the incidence rates and determinants of late effects in testicular cancer survivors. Methods We conducted a population-based cohort study of testicular cancer survivors, diagnosed 1991 – 2007, followed up for a median of 10 years. We identified 785 testicular cancer patients who survived ≥5 years and 3,323 men free of cancer for the comparison group. Multivariate Cox regression analysis was used to compare the hazard ratio between the cases and the comparison group and for internal analysis among case patients. Results Testicular cancer survivors experienced a 24% increase in risk of long-term health effects >5 years after diagnosis. The overall incidence rate of late effects among testicular cancer survivors was 66.3 per 1,000 person years. Higher risks were observed among testicular cancer survivors for hypercholesterolemia, infertility and orchitis. Chemotherapy and retroperitoneal lymph node dissection appeared to increase the risk of late effects. Being obese prior to cancer diagnosis appeared to be the strongest factor associated with late effects. Conclusions Testicular cancer survivors were more likely to develop chronic health conditions when compared to cancer-free men. Implications for Cancer Survivors While the late effects risk was increased among testicular cancer survivors, the incidence rates of late effects after cancer diagnosis was fairly low. PMID:27169992
Screening and staging for non-small cell lung cancer by serum laser Raman spectroscopy.
Wang, Hong; Zhang, Shaohong; Wan, Limei; Sun, Hong; Tan, Jie; Su, Qiucheng
2018-08-05
Lung cancer is the leading cause of cancer-related death worldwide. Current clinical screening methods to detect lung cancer are expensive and associated with many complications. Raman spectroscopy is a spectroscopic technique that offers a convenient method to gain molecular information about biological samples. In this study, we measured the serum Raman spectral intensity of healthy volunteers and patients with different stages of non-small cell lung cancer. The purpose of this study was to evaluate the application of serum laser Raman spectroscopy as a low cost alternative method in the screening and staging of non-small cell lung cancer (NSCLC). The Raman spectra of the sera of peripheral venous blood were measured with a LabRAM HR 800 confocal Micro Raman spectrometer for individuals from five groups including 14 healthy volunteers (control group), 23 patients with stage I NSCLC (stage I group), 24 patients with stage II NSCLC (stage II group), 19 patients with stage III NSCLC (stage III group), 11 patients with stage IV NSCLC (stage IV group). Each serum sample was measured 3 times at different spots and the average spectra represented the signal of Raman spectra in each case. The Raman spectrum signal data of the five groups were statistically analyzed by analysis of variance (ANOVA), principal component analysis (PCA), linear discriminant analysis (LDA), and cross-validation. Raman spectral intensity was sequentially reduced in serum samples from control group, stage I group, stage II group and stage III/IV group. The strongest peak intensity was observed in the control group, and the weakest one was found in the stage III/IV group at bands of 848 cm -1 , 999 cm -1 , 1152 cm -1 , 1446 cm -1 and 1658 cm -1 (P < 0.05). Linear discriminant analysis showed that the sensitivity to identify healthy people, stage I, stage II, and stage III/IV NSCLC was 86%, 65%, 75%, and 87%, respectively; the specificity was 95%, 94%, 88%, and 93%, respectively; and the overall accuracy rate was 92% (71/77). The laser Raman spectroscopy can effectively identify patients with stage I, stage II or stage III/IV Non-Small Cell Lung cancer using patient serum samples. Copyright © 2018 Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Banerjee, Robyn, E-mail: robynbanerjee@gmail.com; Chakraborty, Santam; Nygren, Ian
Purpose: To determine whether volumes based on contours of the peritoneal space can be used instead of individual small bowel loops to predict for grade ≥3 acute small bowel toxicity in patients with rectal cancer treated with neoadjuvant chemoradiation therapy. Methods and Materials: A standardized contouring method was developed for the peritoneal space and retrospectively applied to the radiation treatment plans of 67 patients treated with neoadjuvant chemoradiation therapy for rectal cancer. Dose-volume histogram (DVH) data were extracted and analyzed against patient toxicity. Receiver operating characteristic analysis and logistic regression were carried out for both contouring methods. Results: Grade ≥3more » small bowel toxicity occurred in 16% (11/67) of patients in the study. A highly significant dose-volume relationship between small bowel irradiation and acute small bowel toxicity was supported by the use of both small bowel loop and peritoneal space contouring techniques. Receiver operating characteristic analysis demonstrated that, for both contouring methods, the greatest sensitivity for predicting toxicity was associated with the volume receiving between 15 and 25 Gy. Conclusion: DVH analysis of peritoneal space volumes accurately predicts grade ≥3 small bowel toxicity in patients with rectal cancer receiving neoadjuvant chemoradiation therapy, suggesting that the contours of the peritoneal space provide a reasonable surrogate for the contours of individual small bowel loops. The study finds that a small bowel V15 less than 275 cc and a peritoneal space V15 less than 830 cc are associated with a less than 10% risk of grade ≥3 acute toxicity.« less
2013-01-01
Background The field of cancer genomics has rapidly adopted next-generation sequencing (NGS) in order to study and characterize malignant tumors with unprecedented resolution. In particular for cancer, one is often trying to identify somatic mutations – changes specific to a tumor and not within an individual’s germline. However, false positive and false negative detections often result from lack of sufficient variant evidence, contamination of the biopsy by stromal tissue, sequencing errors, and the erroneous classification of germline variation as tumor-specific. Results We have developed a generalized Bayesian analysis framework for matched tumor/normal samples with the purpose of identifying tumor-specific alterations such as single nucleotide mutations, small insertions/deletions, and structural variation. We describe our methodology, and discuss its application to other types of paired-tissue analysis such as the detection of loss of heterozygosity as well as allelic imbalance. We also demonstrate the high level of sensitivity and specificity in discovering simulated somatic mutations, for various combinations of a) genomic coverage and b) emulated heterogeneity. Conclusion We present a Java-based implementation of our methods named Seurat, which is made available for free academic use. We have demonstrated and reported on the discovery of different types of somatic change by applying Seurat to an experimentally-derived cancer dataset using our methods; and have discussed considerations and practices regarding the accurate detection of somatic events in cancer genomes. Seurat is available at https://sites.google.com/site/seuratsomatic. PMID:23642077
Christoforides, Alexis; Carpten, John D; Weiss, Glen J; Demeure, Michael J; Von Hoff, Daniel D; Craig, David W
2013-05-04
The field of cancer genomics has rapidly adopted next-generation sequencing (NGS) in order to study and characterize malignant tumors with unprecedented resolution. In particular for cancer, one is often trying to identify somatic mutations--changes specific to a tumor and not within an individual's germline. However, false positive and false negative detections often result from lack of sufficient variant evidence, contamination of the biopsy by stromal tissue, sequencing errors, and the erroneous classification of germline variation as tumor-specific. We have developed a generalized Bayesian analysis framework for matched tumor/normal samples with the purpose of identifying tumor-specific alterations such as single nucleotide mutations, small insertions/deletions, and structural variation. We describe our methodology, and discuss its application to other types of paired-tissue analysis such as the detection of loss of heterozygosity as well as allelic imbalance. We also demonstrate the high level of sensitivity and specificity in discovering simulated somatic mutations, for various combinations of a) genomic coverage and b) emulated heterogeneity. We present a Java-based implementation of our methods named Seurat, which is made available for free academic use. We have demonstrated and reported on the discovery of different types of somatic change by applying Seurat to an experimentally-derived cancer dataset using our methods; and have discussed considerations and practices regarding the accurate detection of somatic events in cancer genomes. Seurat is available at https://sites.google.com/site/seuratsomatic.
Afshari, Mahdi; Janbabaei, Ghasem; Bahrami, Mohammad Amin
2017-01-01
Objective The association between opium use and bladder cancer has been investigated in many studies, with varying reporting results reported. This study aims to estimate the total odds ratio for the association between bladder cancer and opium consumption using meta-analysis. Methods The study was designed according to PRISMA guidelines. Two independent researchers searched for the relevant studies using PubMed, Web of Science, Scopus, OVID, Embase, and Google Scholar. After systematic screening of the studies identified during the first step, Cochrane risk of bias tool was determined for the selected studies. The case-control and the cohort studies were investigated to assess risk of bladder cancer due to opium use. In addition, the cross-sectional studies were analysed separately to assess frequency of opium consumption. These estimates were combined using the inverse variance method. Fixed or random effect models were applied to combine the point odds ratios. The heterogeneity between the primary results was assessed using the Cochran test and I-square index. The suspected factors for heterogeneity were investigated using meta-regression models. An Egger test was conducted to identify any probable publication bias. Forest plots illustrated the point and pooled estimates. All analyses were performed using Stata version 14 software and RevMan version 5.3. Results We included 17 primary studies (11 case-control, one cohort and five cross-sectional) in the final meta-analysis. The total odds ratios (95% confidence intervals) for developing bladder cancer by opium use alone, and concurrent use of opium and cigarettes were estimated as 3.85 (3.05–4.87) and 5.7 (1.9–16.3) respectively. The odds ratio (95% confidence interval) for opium use with or without cigarette smoking was estimated as 5.3 (3.6–7.7). Conclusion This meta-analysis showed that opium use similar to cigarette smoking and maybe with similar mechanisms can be a risk factor for bladder cancer. It is therefore expected to be a risk factor for other cancers. PMID:28586371
MicroRNA meta-signature of oral cancer: evidence from a meta-analysis.
Zeljic, Katarina; Jovanovic, Ivan; Jovanovic, Jasmina; Magic, Zvonko; Stankovic, Aleksandra; Supic, Gordana
2018-03-01
It was the aim of the study to identify commonly deregulated miRNAs in oral cancer patients by performing a meta-analysis of previously published miRNA expression profiles in cancer and matched normal non-cancerous tissue in such patients. Meta-analysis included seven independent studies analyzed by a vote-counting method followed by bioinformatic enrichment analysis. Amongst seven independent studies included in the meta-analysis, 20 miRNAs were found to be deregulated in oral cancer when compared with non-cancerous tissue. Eleven miRNAs were consistently up-regulated in three or more studies (miR-21-5p, miR-31-5p, miR-135b-5p, miR-31-3p, miR-93-5p, miR-34b-5p, miR-424-5p, miR-18a-5p, miR-455-3p, miR-450a-5p, miR-21-3p), and nine were down-regulated (miR-139-5p, miR-30a-3p, miR-376c-3p, miR-885-5p, miR-375, miR-486-5p, miR-411-5p, miR-133a-3p, miR-30a-5p). The meta-signature of identified miRNAs was functionally characterized by KEGG enrichment analysis. Twenty-four KEGG pathways were significantly enriched, and TGF-beta signaling was the most enriched signaling pathway. The highest number of meta-signature miRNAs was involved in the sphingolipid signaling pathway. Natural killer cell-mediated cytotoxicity was the pathway with most genes regulated by identified miRNAs. The rest of the enriched pathways in our miRNA list describe different malignancies and signaling. The identified miRNA meta-signature might be considered as a potential battery of biomarkers when distinguishing oral cancer tissue from normal, non-cancerous tissue. Further mechanistic studies are warranted in order to confirm and fully elucidate the role of deregulated miRNAs in oral cancer.
Liu, Fang-Teng; Dong, Qing; Gao, Hui; Zhu, Zheng-Ming
2017-06-20
Urothelial Carcinoma Associated 1 (UCA1) was an originally identified lncRNA in bladder cancer. Previous studies have reported that UCA1 played a significant role in various types of cancer. This study aimed to clarify the prognostic value of UCA1 in digestive system cancers. The meta-analysis of 15 studies were included, comprising 1441 patients with digestive system cancers. The pooled results of 14 studies indicated that high expression of UCA1 was significantly associated with poorer OS in patients with digestive system cancers (HR: 1.89, 95 % CI: 1.52-2.26). In addition, UCA1 could be as an independent prognostic factor for predicting OS of patients (HR: 1.85, 95 % CI: 1.45-2.25). The pooled results of 3 studies indicated a significant association between UCA1 and DFS in patients with digestive system cancers (HR = 2.50; 95 % CI = 1.30-3.69). Statistical significance was also observed in subgroup meta-analysis. Furthermore, the clinicopathological values of UCA1 were discussed in esophageal cancer, colorectal cancer and pancreatic cancer. A comprehensive retrieval was performed to search studies evaluating the prognostic value of UCA1 in digestive system cancers. Many databases were involved, including PubMed, Web of Science, Embase and Chinese National Knowledge Infrastructure and Wanfang database. Quantitative meta-analysis was performed with standard statistical methods and the prognostic significance of UCA1 in digestive system cancers was qualified. Elevated level of UCA1 indicated the poor clinical outcome for patients with digestive system cancers. It may serve as a new biomarker related to prognosis in digestive system cancers.
Seo, Mirinae; Jahng, Geon-Ho; Sohn, Yu-Mee; Rhee, Sun Jung; Oh, Jang-Hoon; Won, Kyu-Yeoun
2017-01-01
Objective The purpose of this study was to estimate the T2* relaxation time in breast cancer, and to evaluate the association between the T2* value with clinical-imaging-pathological features of breast cancer. Materials and Methods Between January 2011 and July 2013, 107 consecutive women with 107 breast cancers underwent multi-echo T2*-weighted imaging on a 3T clinical magnetic resonance imaging system. The Student's t test and one-way analysis of variance were used to compare the T2* values of cancer for different groups, based on the clinical-imaging-pathological features. In addition, multiple linear regression analysis was performed to find independent predictive factors associated with the T2* values. Results Of the 107 breast cancers, 92 were invasive and 15 were ductal carcinoma in situ (DCIS). The mean T2* value of invasive cancers was significantly longer than that of DCIS (p = 0.029). Signal intensity on T2-weighted imaging (T2WI) and histologic grade of invasive breast cancers showed significant correlation with T2* relaxation time in univariate and multivariate analysis. Breast cancer groups with higher signal intensity on T2WI showed longer T2* relaxation time (p = 0.005). Cancer groups with higher histologic grade showed longer T2* relaxation time (p = 0.017). Conclusion The T2* value is significantly longer in invasive cancer than in DCIS. In invasive cancers, T2* relaxation time is significantly longer in higher histologic grades and high signal intensity on T2WI. Based on these preliminary data, quantitative T2* mapping has the potential to be useful in the characterization of breast cancer. PMID:28096732
Dietary Flavonoid Intake and Smoking-Related Cancer Risk: A Meta-Analysis
Woo, Hae Dong; Kim, Jeongseon
2013-01-01
Purpose To systematically investigate the effects of dietary flavonoids and flavonoid subclasses on the risk of smoking-related cancer in observational studies. Methods Summary estimates and corresponding standard errors were calculated using the multivariate-adjusted odds ratio (OR) or relative risk (RR) and 95% CI of selected studies and weighted by the inverse variance. Results A total of 35 studies, including 19 case-controls (9,525 cases and 15,835 controls) and 15 cohort studies (988,082 subjects and 8,161 cases), were retrieved for the meta-analysis. Total dietary flavonoids and most of the flavonoid subclasses were inversely associated with smoking-related cancer risk (OR: 0.82, 95% CI: 0.72-0.93). In subgroup analyses by cancer site, significant associations were observed in aerodigestive tract and lung cancers. Total dietary flavonoid intake was significantly associated with aerodigestive tract cancer risk (OR: 0.67, 95% CI: 0.54-0.83) marginally associated with lung cancer risk (OR: 0.84, 95% CI: 0.71-1.00). Subgroup analyses by smoking status showed significantly different results. The intake of total flavonoids, flavonols, flavones, and flavanones, as well as the flavonols quercetin and kaempferol was significantly associated with decreased risk of smoking-related cancer in smokers, whereas no association was observed in non-smokers, except for flavanones. In meta-analysis for the effect of subclasses of dietary flavonoids by cancer type, aerodigestive tract cancer was inversely associated with most flavonoid subclasses. Conclusion The protective effects of flavonoids on smoking-related cancer risk varied across studies, but the overall results indicated that intake of dietary flavonoids, especially flavonols, was inversely associated with smoking-related cancer risk. The protective effects of flavonoids on smoking-related cancer risk were more prominent in smokers. PMID:24069431
Petimar, Joshua; Wilson, Kathryn M; Wu, Kana; Wang, Molin; Albanes, Demetrius; van den Brandt, Piet A; Cook, Michael B; Giles, Graham G; Giovannucci, Edward L; Goodman, Gary E; Goodman, Phyllis J; Håkansson, Niclas; Helzlsouer, Kathy; Key, Timothy J; Kolonel, Laurence N; Liao, Linda M; Männistö, Satu; McCullough, Marjorie L; Milne, Roger L; Neuhouser, Marian L; Park, Yikyung; Platz, Elizabeth A; Riboli, Elio; Sawada, Norie; Schenk, Jeannette M; Tsugane, Shoichiro; Verhage, Bas; Wang, Ying; Wilkens, Lynne R; Wolk, Alicja; Ziegler, Regina G; Smith-Warner, Stephanie A
2017-08-01
Background: Relationships between fruit, vegetable, and mature bean consumption and prostate cancer risk are unclear. Methods: We examined associations between fruit and vegetable groups, specific fruits and vegetables, and mature bean consumption and prostate cancer risk overall, by stage and grade, and for prostate cancer mortality in a pooled analysis of 15 prospective cohorts, including 52,680 total cases and 3,205 prostate cancer-related deaths among 842,149 men. Diet was measured by a food frequency questionnaire or similar instrument at baseline. We calculated study-specific relative risks using Cox proportional hazards regression, and then pooled these estimates using a random effects model. Results: We did not observe any statistically significant associations for advanced prostate cancer or prostate cancer mortality with any food group (including total fruits and vegetables, total fruits, total vegetables, fruit and vegetable juice, cruciferous vegetables, and tomato products), nor specific fruit and vegetables. In addition, we observed few statistically significant results for other prostate cancer outcomes. Pooled multivariable relative risks comparing the highest versus lowest quantiles across all fruit and vegetable exposures and prostate cancer outcomes ranged from 0.89 to 1.09. There was no evidence of effect modification for any association by age or body mass index. Conclusions: Results from this large, international, pooled analysis do not support a strong role of collective groupings of fruits, vegetables, or mature beans in prostate cancer. Impact: Further investigation of other dietary exposures, especially indicators of bioavailable nutrient intake or specific phytochemicals, should be considered for prostate cancer risk. Cancer Epidemiol Biomarkers Prev; 26(8); 1276-87. ©2017 AACR . ©2017 American Association for Cancer Research.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shaffer, Richard, E-mail: rickyshaffer@yahoo.co.u; Department of Clinical Oncology, Imperial College London National Health Service Trust, London; Pickles, Tom
Purpose: Prior studies have derived low values of alpha-beta ratio (a/ss) for prostate cancer of approximately 1-2 Gy. These studies used poorly matched groups, differing definitions of biochemical failure, and insufficient follow-up. Methods and Materials: National Comprehensive Cancer Network low- or low-intermediate risk prostate cancer patients, treated with external beam radiotherapy or permanent prostate brachytherapy, were matched for prostate-specific antigen, Gleason score, T-stage, percentage of positive cores, androgen deprivation therapy, and era, yielding 118 patient pairs. The Phoenix definition of biochemical failure was used. The best-fitting value for a/ss was found for up to 90-month follow-up using maximum likelihood analysis,more » and the 95% confidence interval using the profile likelihood method. Linear quadratic formalism was applied with the radiobiological parameters of relative biological effectiveness = 1.0, potential doubling time = 45 days, and repair half-time = 1 hour. Bootstrap analysis was performed to estimate uncertainties in outcomes, and hence in a/ss. Sensitivity analysis was performed by varying the values of the radiobiological parameters to extreme values. Results: The value of a/ss best fitting the outcomes data was >30 Gy, with lower 95% confidence limit of 5.2 Gy. This was confirmed on bootstrap analysis. Varying parameters to extreme values still yielded best-fit a/ss of >30 Gy, although the lower 95% confidence interval limit was reduced to 0.6 Gy. Conclusions: Using carefully matched groups, long follow-up, the Phoenix definition of biochemical failure, and well-established statistical methods, the best estimate of a/ss for low and low-tier intermediate-risk prostate cancer is likely to be higher than that of normal tissues, although a low value cannot be excluded.« less
Self-care Concept Analysis in Cancer Patients: An Evolutionary Concept Analysis
Hasanpour-Dehkordi, Ali
2016-01-01
Background: Self-care is a frequently used concept in both the theory and the clinical practice of nursing and is considered an element of nursing theory by Orem. The aim of this paper is to identify the core attributes of the self-care concept in cancer patients. Materials and Methods: We used Rodgers’ evolutionary method of concept analysis. The articles published in English language from 1980 to 2015 on nursing and non-nursing disciplines were analyzed. Finally, 85 articles, an MSc thesis, and a PhD thesis were selected, examined, and analyzed in-depth. Two experts checked the process of analysis and monitored and reviewed the articles. Results: The analysis showed that self-care concept is determined by four attributes of education, interaction, self-control, and self-reliance. Three types of antecedents in the present study were client-related (self-efficacy, self-esteem), system-related (adequate sources, social networks, and cultural factors), and healthcare professionals-related (participation). Conclusion: The self-care concept has considerably evolved among patients with chronic diseases, particularly cancer, over the past 35 years, and nurses have managed to enhance their knowledge about self-care remarkably for the clients so that the nurses in healthcare teams have become highly efficient and able to assume the responsibility for self-care teams. PMID:27803559
Margolin, Adam A.; Bilal, Erhan; Huang, Erich; Norman, Thea C.; Ottestad, Lars; Mecham, Brigham H.; Sauerwine, Ben; Kellen, Michael R.; Mangravite, Lara M.; Furia, Matthew D.; Vollan, Hans Kristian Moen; Rueda, Oscar M.; Guinney, Justin; Deflaux, Nicole A.; Hoff, Bruce; Schildwachter, Xavier; Russnes, Hege G.; Park, Daehoon; Vang, Veronica O.; Pirtle, Tyler; Youseff, Lamia; Citro, Craig; Curtis, Christina; Kristensen, Vessela N.; Hellerstein, Joseph; Friend, Stephen H.; Stolovitzky, Gustavo; Aparicio, Samuel; Caldas, Carlos; Børresen-Dale, Anne-Lise
2013-01-01
Although molecular prognostics in breast cancer are among the most successful examples of translating genomic analysis to clinical applications, optimal approaches to breast cancer clinical risk prediction remain controversial. The Sage Bionetworks–DREAM Breast Cancer Prognosis Challenge (BCC) is a crowdsourced research study for breast cancer prognostic modeling using genome-scale data. The BCC provided a community of data analysts with a common platform for data access and blinded evaluation of model accuracy in predicting breast cancer survival on the basis of gene expression data, copy number data, and clinical covariates. This approach offered the opportunity to assess whether a crowdsourced community Challenge would generate models of breast cancer prognosis commensurate with or exceeding current best-in-class approaches. The BCC comprised multiple rounds of blinded evaluations on held-out portions of data on 1981 patients, resulting in more than 1400 models submitted as open source code. Participants then retrained their models on the full data set of 1981 samples and submitted up to five models for validation in a newly generated data set of 184 breast cancer patients. Analysis of the BCC results suggests that the best-performing modeling strategy outperformed previously reported methods in blinded evaluations; model performance was consistent across several independent evaluations; and aggregating community-developed models achieved performance on par with the best-performing individual models. PMID:23596205
Hamashima, Chisato; Sasazuki, Shizuka; Inoue, Manami; Tsugane, Shoichiro
2017-03-09
Chronic Helicobacter pylori infection plays a central role in the development of gastric cancer as shown by biological and epidemiological studies. The H. pylori antibody and serum pepsinogen (PG) tests have been anticipated to predict gastric cancer development. We determined the predictive sensitivity and specificity of gastric cancer development using these tests. Receiver operating characteristic analysis was performed, and areas under the curve were estimated. The predictive sensitivity and specificity of gastric cancer development were compared among single tests and combined methods using serum pepsinogen and H. pylori antibody tests. From a large-scale population-based cohort of over 100,000 subjects followed between 1990 and 2004, 497 gastric cancer subjects and 497 matched healthy controls were chosen. The predictive sensitivity and specificity were low in all single tests and combination methods. The highest predictive sensitivity and specificity were obtained for the serum PG I/II ratio. The optimal PG I/II cut-off values were 2.5 and 3.0. At a PG I/II cut-off value of 3.0, the sensitivity was 86.9% and the specificity was 39.8%. Even if three biomarkers were combined, the sensitivity was 97.2% and the specificity was 21.1% when the cut-off values were 3.0 for PG I/II, 70 ng/mL for PG I, and 10.0 U/mL for H. pylori antibody. The predictive accuracy of gastric cancer development was low with the serum pepsinogen and H. pylori antibody tests even if these tests were combined. To adopt these biomarkers for gastric cancer screening, a high specificity is required. When these tests are adopted for gastric cancer screening, they should be carefully interpreted with a clear understanding of their limitations.
Cole, Allison M; Jackson, J Elizabeth; Doescher, Mark
2012-01-01
Despite the existence of effective screening, colorectal cancer remains the second leading cause of cancer death in the United States. Identification of disparities in colorectal cancer screening will allow for targeted interventions to achieve national goals for screening. The objective of this study was to contrast colorectal cancer screening rates in urban and rural populations in the United States. The study design comprised a cross-sectional study in the United States 1998–2005. Behavioral Risk Factor Surveillance System data from 1998 to 2005 were the method and data source. The primary outcome was self-report up-to-date colorectal cancer screening (fecal occult blood test in last 12 months, flexible sigmoidoscopy in last 5 years, or colonoscopy in last 10 years). Geographic location (urban vs. rural) was used as independent variable. Multivariate analysis controlled for demographic and health characteristics of respondents. After adjustment for demographic and health characteristics, rural residents had lower colorectal cancer screening rates (48%; 95% CI 48, 49%) as compared with urban residents (54%, 95% CI 53, 55%). Remote rural residents had the lowest screening rates overall (45%, 95% CI 43, 46%). From 1998 to 2005, rates of screening by colonoscopy or flexible sigmoidoscopy increased in both urban and rural populations. During the same time, rates of screening by fecal occult blood test decreased in urban populations and increased in rural populations. Persistent disparities in colorectal cancer screening affect rural populations. The types of screening tests used for colorectal cancer screening are different in rural and urban areas. Future research to reduce this disparity should focus on screening methods that are acceptable and feasible in rural areas. PMID:23342284
The clinical phenotype of Lynch syndrome due to germline PMS2 mutations
Senter, Leigha; Clendenning, Mark; Sotamaa, Kaisa; Hampel, Heather; Green, Jane; Potter, John D.; Lindblom, Annika; Lagerstedt, Kristina; Thibodeau, Stephen N.; Lindor, Noralane M.; Young, Joanne; Winship, Ingrid; Dowty, James G.; White, Darren M.; Hopper, John L.; Baglietto, Laura; Jenkins, Mark A.; de la Chapelle, Albert
2009-01-01
Background and Aims Although the clinical phenotype of Lynch syndrome (also known as Hereditary Nonpolyposis Colorectal Cancer) has been well described, little is known about disease in PMS2 mutation carriers. Now that mutation detection methods can discern mutations in PMS2 from mutations in its pseudogenes, more mutation carriers have been identified. Information about the clinical significance of PMS2 mutations is crucial for appropriate counseling. Here, we report the clinical characteristics of a large series of PMS2 mutation carriers. Methods We performed PMS2 mutation analysis using long range PCR and MLPA for 99 probands diagnosed with Lynch syndrome-associated tumors showing isolated loss of PMS2 by immunohistochemistry. Penetrance was calculated using a modified segregation analysis adjusting for ascertainment. Results Germline PMS2 mutations were detected in 62% of probands (n = 55 monoallelic; 6 biallelic). Among families with monoallelic PMS2 mutations, 65.5% met revised Bethesda guidelines. Compared with the general population, in mutation carriers, the incidence of colorectal cancer was 5.2 fold higher and the incidence of endometrial cancer was 7.5 fold higher. In North America, this translates to a cumulative cancer risk to age 70 of 15–20% for colorectal cancer, 15% for endometrial cancer, and 25–32% for any Lynch syndrome-associated cancer. No elevated risk for non-Lynch syndrome-associated cancers was observed. Conclusions PMS2 mutations contribute significantly to Lynch syndrome but the penetrance for monoallelic mutation carriers appears to be lower than that for the other mismatch repair genes. Modified counseling and cancer surveillance guidelines for PMS2 mutation carriers are proposed. PMID:18602922
Treglia, Giorgio; Sadeghi, Ramin; Annunziata, Salvatore; Lococo, Filippo; Cafarotti, Stefano; Prior, John O; Bertagna, Francesco; Ceriani, Luca; Giovanella, Luca
2014-01-01
To systematically review and meta-analyze published data about the diagnostic performance of Fluorine-18-Fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET) and PET/computed tomography (PET/CT) in the assessment of pleural abnormalities in cancer patients. A comprehensive literature search of studies published through June 2013 regarding the role of (18)F-FDG-PET and PET/CT in evaluating pleural abnormalities in cancer patients was performed. All retrieved studies were reviewed and qualitatively analyzed. Pooled sensitivity, specificity, positive and negative likelihood ratio (LR+ and LR-) and diagnostic odd ratio (DOR) of (18)F-FDG-PET or PET/CT on a per patient-based analysis were calculated. The area under the summary ROC curve (AUC) was calculated to measure the accuracy of these methods in the assessment of pleural abnormalities. Sub-analyses considering (18)F-FDG-PET/CT and patients with lung cancer only were carried out. Eight studies comprising 360 cancer patients (323 with lung cancer) were included. The meta-analysis of these selected studies provided the following results: sensitivity 86% [95% confidence interval (95%CI): 80-91%], specificity 80% [95%CI: 73-85%], LR+ 3.7 [95%CI: 2.8-4.9], LR- 0.18 [95%CI: 0.09-0.34], DOR 27 [95%CI: 13-56]. The AUC was 0.907. No significant improvement considering PET/CT studies only and patients with lung cancer was found. (18)F-FDG-PET and PET/CT demonstrated to be useful diagnostic imaging methods in the assessment of pleural abnormalities in cancer patients, nevertheless possible sources of false-negative and false-positive results should be kept in mind. The literature focusing on the use of (18)F-FDG-PET and PET/CT in this setting remains still limited and prospective studies are needed. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Liu, Weimin; Wang, Cunchuan
2018-01-01
Background The relationship between TP53 codon 72 Pro/Arg gene polymorphism and colorectal cancer risk in Asians is still controversial, and this bioinformatics analysis and meta-analysis was performed to assess the associations. Methods The association studies were identified from PubMed, and eligible reports were included. RevMan 5.3.1 software, Oncolnc, cBioPortal, and Oncomine online tools were used for statistical analysis. A random/fixed effects model was used in meta-analysis. The data were reported as risk ratios or mean differences with corresponding 95% CI. Results We confirmed that TP53 was associated with colorectal cancer, the alteration frequency of TP53 was 53% mutation and 7% deep deletion, and TP53 mRNA expression was different in different types of colorectal cancer based on The Cancer Genome Atlas database. Then, 18 studies were included that examine the association of TP53 codon 72 gene polymorphism with colorectal cancer risk in Asians. The meta-analysis indicated that TP53 Pro allele and Pro/Pro genotype were associated with colorectal cancer risk in Asian population, but Arg/Arg genotype was not (Pro allele: odds ratios [OR]=1.20, 95% CI: 1.06 to 1.35, P=0.003; Pro/Pro genotype: OR=1.39, 95% CI: 1.15 to 1.69, P=0.0007; Arg/Arg genotype: OR=0.86, 95% CI: 0.74 to 1.00, P=0.05). Interestingly, in the meta-analysis of the controls from the population-based studies, we found that TP53 codon 72 Pro/Arg gene polymorphism was associated with colorectal cancer risk (Pro allele: OR=1.33, 95% CI: 1.15 to 1.55, P=0.0002; Pro/Pro genotype: OR=1.61, 95% CI: 1.28 to 2.02, P<0.0001; Arg/Arg genotype: OR=0.77, 95% CI: 0.63 to 0.93, P=0.009). Conclusion TP53 was associated with colorectal cancer, but the different value levels of mRNA expression were not associated with survival rate of colon and rectal cancer. TP53 Pro allele and Pro/Pro genotype were associated with colorectal cancer risk in Asians. PMID:29872345
Tse, Genevieve; Eslick, Guy D
2016-02-01
Evidence suggests that soy foods have chemoprotective properties that may reduce the risk of certain cancers such as breast and prostate cancer. However, data involving gastrointestinal (GI) have been limited, and the evidence remains controversial. This study aims to determine the potential relationship between dietary soy intake and GI cancer risk with an evaluation of the effects of isoflavone as an active soy constituent. Relevant studies were identified after literature search via electronic databases through May 2014. Subgroup analysis for isoflavone intake (studies n = 10) was performed. Covariants including gender types, anatomical subsites and preparation methods were also evaluated. Pooled adjusted odds ratios (ORs) comparing highest and lowest categories of dietary pattern scores were calculated using a random effects model. Twenty-two case-control and 18 cohort studies were included for meta-analysis, which contained a total of 633,476 participants and 13,639 GI cancer cases. The combined OR was calculated as 0.93 (95% CI 0.87-0.99; p value heterogeneity = 0.01), showing only a slight decrease in risk, the association was stronger for colon cancer (OR 0.92; 95% CI 0.96-0.99; p value heterogeneity = 0.163) and colorectal cancer (CRC) (OR 0.92; 95% CI 0.87-0.97; p value heterogeneity = 0.3). Subgroup analysis for isoflavone intake showed a statistically significant risk reduction with a risk estimate of 0.73 (95% CI 0.59-0.92; p value heterogeneity = 0), and particularly for CRC (OR 0.76; 95% CI 0.59-0.98; p value heterogeneity = 0). This study provides evidence that soy intake as a food group is only associated with a small reduction in GI cancer risk. Separate analysis for dietary isoflavone intakes suggests a stronger inverse association.
Hypoxia-Inducible Factor-1α Polymorphisms and Risk of Cancer Metastasis: A Meta-Analysis
Shi, Bin; Weng, Wenjun; Chen, Zhipeng; Guo, Nannan; Hua, Yibing; Zhu, Lingjun
2013-01-01
Background HIF-1α is a major regulator in tumor progression and metastasis which responds to hypoxia. Many studies have demonstrated that hypoxia-inducible factor1-α (HIF-1α) polymorphisms are significantly associated with cancer metastasis, but the results are inconsistent. We conducted a comprehensive meta-analysis to estimate the associations between HIF-1α C1772 T polymorphism and cancer metastasis. Methods Comprehensive searches were conducted on PubMed and EMBASE database. Fifteen studies were included in the meta-analysis. We used the OR and 95%CI to assess the associations between HIF-1α C1772T polymorphism and cancer metastasis. Heterogeneity and publication bias were also assessed by Q test, I 2, and funnel plot. Results Totally, fifteen studies including 1239 cases with metastasis-positive (M+) and 2711 cases with metastasis-negative (M−) were performed in this meta-analysis. The results showed that HIF-1a C1772T polymorphism was associated with the increased risk of cancer metastasis (T allele vs. C allele, OR = 1.36, 95% CI = 1.12–1.64; TT+ TC vs. CC, OR = 1.39, 95% CI = 1.13–1.71; TT vs. TC+ CC, OR = 1.93, 95% CI = 0.86–4.36). In the subgroup analyses, the significant associations remained significant among Asians, Caucasians and other cancers in the dominant model. Publication bias was not observed in the analysis. Conclusions Our results indicate that the HIF-1αC1772T polymorphism T allele may increase the risk of cancer metastasis, which might be a potential risk factor of cancer progress. PMID:24015181
Lu, Zhe; Liu, Yi; Xu, Junfeng; Yin, Hongping; Yuan, Haiying; Gu, Jinjing; Chen, Yan-Hua; Shi, Liyun; Chen, Dan; Xie, Bin
2018-03-01
Tight junction proteins are correlated with cancer development. As the pivotal proteins in epithelial cells, altered expression and distribution of different claudins have been reported in a wide variety of human malignancies. We have previously reported that claudin-7 was strongly expressed in benign bronchial epithelial cells at the cell-cell junction while expression of claudin-7 was either altered with discontinued weak expression or completely absent in lung cancers. Based on these results, we continued working on the expression pattern of claudin-7 and its relationship with lung cancer development. We herein proposed a new Digital Image Classification, Fragmentation index, Morphological analysis (DICFM) method for differentiating the normal lung tissues and lung cancer tissues based on the claudin-7 immunohistochemical staining. Seventy-seven lung cancer samples were obtained from the Second Affiliated Hospital of Zhejiang University and claudin-7 immunohistochemical staining was performed. Based on C++ and Open Source Computer Vision Library (OpenCV, version 2.4.4), the DICFM processing module was developed. Intensity and fragmentation of claudin-7 expression, as well as the morphological parameters of nuclei were calculated. Evaluation of results was performed using Receiver Operator Characteristic (ROC) analysis. Agreement between these computational results and the results obtained by two pathologists was demonstrated. The intensity of claudin-7 expression was significantly decreased while the fragmentation was significantly increased in the lung cancer tissues compared to the normal lung tissues and the intensity was strongly positively associated with the differentiation of lung cancer cells. Moreover, the perimeters of the nuclei of lung cancer cells were significantly greater than that of the normal lung cells, while the parameters of area and circularity revealed no statistical significance. Taken together, our DICFM approach may be applied as an appropriate approach to quantify the immunohistochemical staining of claudin-7 on the cell membrane and claudin-7 may serve as a marker for identification of lung cancer. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
El Mhamdi, S; Bouanene, I; Mhirsi, A; Bouden, W; Soussi Soltani, M
2012-12-01
In Tunisia, cervical cancer is considered the second leading cancer in women and causes high morbidity and mortality. This study aimed to investigate women's knowledge, attitudes, and practices of cervical cancer screening in the region of Monastir (Tunisia). We conducted a cross-sectional study exploring the cervical cancer screening knowledge, attitudes, and practices of women in the region of Monastir. The study was conducted in health centers in this region from 1st March to 30th June 2009. Data were collected using a structured questionnaire containing 15 items on demographic status, knowledge of risk factors and screening methods, and attitudes toward the relevance and effectiveness of cervical cancer screening. A total of 900 women agreed to take part in the study. Their mean age was 41.6±12.4 years and 64% did not exceed the primary level of education. According to the constructed scores, 22.8% of the participants had good knowledge of cervical cancer risk factors and 38.2% had good knowledge of screening methods. Multiple logistic regression analysis showed that women aged 45 and older, married, with good knowledge of risk factors and screening methods were more likely to undergo cervical cancer screening (P-value<0.01). This study provides useful information that could be utilized by both researchers and those involved in public health programs. The results show the need for educational programs to enhance women's adherence to cervical cancer screening programs in Tunisia. Copyright © 2012 Elsevier Masson SAS. All rights reserved.
Samsonov, Roman; Shtam, Tatiana; Burdakov, Vladimir; Glotov, Andrey; Tsyrlina, Evgenia; Berstein, Lev; Nosov, Alexander; Evtushenko, Vladimir; Filatov, Michael; Malek, Anastasia
2016-01-01
Prostate cancer is the most common cancer in men. Prostate-specific antigen has, however, insufficient diagnostic specificity. Novel complementary diagnostic approaches are greatly needed. MiRNAs are small regulatory RNAs which play an important role in tumorogenesis and are being investigated as a cancer biomarker. In addition to their intracellular regulatory functions, miRNAs are secreted into the extracellular space and can be found in various body fluids, including urine. The stability of extracellular miRNAs is defined by association with proteins, lipoprotein particles, and membrane vesicles. Among the known forms of miRNA packaging, tumour-derived exosome-enclosed miRNAs is thought to reflect the vital activity of cancer cells. The assessment of the exosomal fraction of urinary miRNA may present a new and highly specific method for prostate cancer diagnostics; however, this is challenged by the absence of reliable and inexpensive methods for isolation of exosomes. Prostate cancer (PC) cell lines and urine samples collected from 35 PC patients and 35 healthy donors were used in the study. Lectins, phytohemagglutinin, and concanavalin A were used to induce agglutination of exosomes. The efficiency of isolation process was evaluated by AFM and DLS assays. The protein content of isolated exosomes was analysed by western blotting. Exosomal RNA was assayed by automated electrophoresis and expression level of selected miRNAs was evaluated by RT-qPCR. The diagnostic potency of the urinary exosomal miRNA assessment was estimated by the ROC method. The formation of multi-vesicular agglutinates in urine can be induced by incubation with lectin at a final concentration of 2 mg/ml. These agglutinates contain urinary exosomes and may be pelleted by centrifugation with a relatively low G-force. The analysis of PC-related miRNA in urinary exosomes revealed significant up-regulation of miR-574-3p, miR-141-5p, and miR-21-5p associated with PC. Lectin-induced aggregation is a low-cost and easily performed method for isolation of exosomes from urine. Isolated exosomes can be further analysed in terms of miRNA content. The miRNA profile of urinary exosomes reflects development of prostate cancer and may present a promising diagnostic tool. © 2015 Wiley Periodicals, Inc.
Kuperstein, I; Bonnet, E; Nguyen, H-A; Cohen, D; Viara, E; Grieco, L; Fourquet, S; Calzone, L; Russo, C; Kondratova, M; Dutreix, M; Barillot, E; Zinovyev, A
2015-01-01
Cancerogenesis is driven by mutations leading to aberrant functioning of a complex network of molecular interactions and simultaneously affecting multiple cellular functions. Therefore, the successful application of bioinformatics and systems biology methods for analysis of high-throughput data in cancer research heavily depends on availability of global and detailed reconstructions of signalling networks amenable for computational analysis. We present here the Atlas of Cancer Signalling Network (ACSN), an interactive and comprehensive map of molecular mechanisms implicated in cancer. The resource includes tools for map navigation, visualization and analysis of molecular data in the context of signalling network maps. Constructing and updating ACSN involves careful manual curation of molecular biology literature and participation of experts in the corresponding fields. The cancer-oriented content of ACSN is completely original and covers major mechanisms involved in cancer progression, including DNA repair, cell survival, apoptosis, cell cycle, EMT and cell motility. Cell signalling mechanisms are depicted in detail, together creating a seamless ‘geographic-like' map of molecular interactions frequently deregulated in cancer. The map is browsable using NaviCell web interface using the Google Maps engine and semantic zooming principle. The associated web-blog provides a forum for commenting and curating the ACSN content. ACSN allows uploading heterogeneous omics data from users on top of the maps for visualization and performing functional analyses. We suggest several scenarios for ACSN application in cancer research, particularly for visualizing high-throughput data, starting from small interfering RNA-based screening results or mutation frequencies to innovative ways of exploring transcriptomes and phosphoproteomes. Integration and analysis of these data in the context of ACSN may help interpret their biological significance and formulate mechanistic hypotheses. ACSN may also support patient stratification, prediction of treatment response and resistance to cancer drugs, as well as design of novel treatment strategies. PMID:26192618
Bopanna, Sawan; Ananthakrishnan, Ashwin N; Kedia, Saurabh; Yajnik, Vijay; Ahuja, Vineet
2017-01-01
Summary Background The increased risk of colorectal cancer in ulcerative colitis is well known. The risk of sporadic colorectal cancer in Asian populations is considered low and risk estimates of colorectal cancer related to ulcerative colitis from Asia vary. This meta-analysis is an Asian perspective on the risk of colorectal cancer related to ulcerative colitis. Methods We searched PubMed and Embase for terms related to colorectal cancer in ulcerative colitis from inception to July 1, 2016. The search for published articles was done by country for all countries in Asia. We included studies with information on the prevalence and cumulative risk of colorectal cancer at various timepoints. A random-effects meta-analysis was done to calculate the pooled prevalence as well as a cumulative risk at 10 years, 20 years, and 30 years of disease. Findings Our search identified 2575 articles; of which 44 were eligible for inclusion. Our analysis included a total of 31 287 patients with ulcerative colitis with a total of 293 reported colorectal cancers. Using pooled prevalence estimates from various studies, the overall prevalence was 0·85% (95% CI 0·65–1·04). The risks for colorectal cancer were 0·02% (95% CI 0·00–0·04) at 10 years, 4·81% (3·26–6·36) at 20 years, and 13·91% (7·09–20·72) at 30 years. Subgroup analysis by stratifying the studies according to region or period of the study did not reveal any significant differences. Interpretation We found the risk of colorectal cancer in Asian patients with ulcerative colitis was similar to recent estimates in Europe and North America. Adherence to screening is therefore necessary. Larger population-based, prospective studies are required for better estimates of the risk. PMID:28404156
Lang, Robert; Leinenbach, Andreas; Karl, Johann; Swiatek-de Lange, Magdalena; Kobold, Uwe; Vogeser, Michael
2018-05-01
Recently, site-specific fucosylation of glycoproteins has attracted attention as it can be associated with several types of cancers including prostate cancer. However, individual glycoproteins, which might serve as potential cancer markers, often are very low-concentrated in complex serum matrices and distinct glycan structures are hard to detect by immunoassays. Here, we present a mass spectrometry-based strategy for the simultaneous analysis of core-fucosylated and total prostate-specific antigen (PSA) in human serum in the low ng/ml concentration range. Sample preparation comprised an immunoaffinity capture step to enrich total PSA from human serum using anti-PSA antibody coated magnetic beads followed by consecutive two-step on-bead partial deglycosylation with endoglycosidase F3 and tryptic digestion prior to LC-MS/MS analysis. The method was shown to be linear from 0.5 to 60 ng/ml total PSA concentrations and allows the simultaneous quantification of core-fucosylated PSA down to 1 ng/ml and total PSA lower than 0.5 ng/ml. The imprecision of the method over two days ranged from 9.7-23.2% for core-fucosylated PSA and 10.3-18.3% for total PSA depending on the PSA level. The feasibility of the method in native sera was shown using three human specimens. To our knowledge, this is the first MS-based method for quantification of core-fucosylated PSA in the low ng/ml concentration range in human serum. This method could be used in large patient cohorts as core-fucosylated PSA may be a diagnostic biomarker for the differentiation of prostate cancer and other prostatic diseases, such as benign prostatic hyperplasia (BPH). Furthermore, the described strategy could be used to monitor potential changes in site-specific core-fucosylation of other low-concentrated glycoproteins, which could serve as more specific markers ("marker refinement") in cancer research. Copyright © 2018 Elsevier B.V. All rights reserved.
Evaluating the evaluation of cancer driver genes
Tokheim, Collin J.; Papadopoulos, Nickolas; Kinzler, Kenneth W.; Vogelstein, Bert; Karchin, Rachel
2016-01-01
Sequencing has identified millions of somatic mutations in human cancers, but distinguishing cancer driver genes remains a major challenge. Numerous methods have been developed to identify driver genes, but evaluation of the performance of these methods is hindered by the lack of a gold standard, that is, bona fide driver gene mutations. Here, we establish an evaluation framework that can be applied to driver gene prediction methods. We used this framework to compare the performance of eight such methods. One of these methods, described here, incorporated a machine-learning–based ratiometric approach. We show that the driver genes predicted by each of the eight methods vary widely. Moreover, the P values reported by several of the methods were inconsistent with the uniform values expected, thus calling into question the assumptions that were used to generate them. Finally, we evaluated the potential effects of unexplained variability in mutation rates on false-positive driver gene predictions. Our analysis points to the strengths and weaknesses of each of the currently available methods and offers guidance for improving them in the future. PMID:27911828
[CT-Screening for Lung Cancer - what is the Evidence?
Watermann, Iris; Reck, Martin
2018-04-01
In patients with lung cancer treatment opportunities and prognosis are correlated to the stage of disease with a chance for curative treatment in patients with early stage disease. Therefore, early detection of lung cancer is of paramount importance for improving the prognosis of lung cancer patients.The National Lung Screening Trial (NLST) has already shown that low-dose CT increases the number of identified early stage lung cancer patients and reduces lung cancer related mortality. Critically considered in terms of CT-screening are false-positive results, overdiagnosis and unessential invasive clarification. Preliminary results of relatively small European trials haven´t yet confirmed the results of the NLST-study.Until now Lung Cancer Screening by low dose CT-scan or other methods is neither approved nor available in Germany.To improve the efficacy of CT-Screening and to introduce early detection of lung cancer in standard practice, additional, complementing methods should be further evaluated. One option might be the supplementary analysis of biomarkers in liquid biopsies or exhaled breath condensates. In addition, defining the high-risk population is of great relevance to identify candidates who might benefit of early detection programs. © Georg Thieme Verlag KG Stuttgart · New York.
Zhang, Hai-Min; Yan, Yang; Wang, Fang; Gu, Wen-Yu; Hu, Guang-Hui; Zheng, Jun-Hua
2014-01-01
As a definite diagnosis of prostate cancer, puncture biopsy of the prostate is invasive method. The aim of this study was to evaluate the value of OPSAD (the ratio of PSA to the outer gland volume of prostate) as a non-invasive screening and diagnosis method for prostate cancer in a select population. The diagnosis data of 490 subjects undergoing ultrasound-guided biopsy of the prostate were retrospectively analyzed. This included 133 patients with prostate cancer, and 357 patients with benign prostate hyperplasia (BPH). The OPSAD was significantly greater in patients with prostate cancer (1.87 ± 1.26 ng/ml(2)) than those with BPH (0.44 ± 0.21 ng/ml(2)) (P < 0.05). Receiver operating characteristic (ROC) curve analysis revealed that the performance of OPSAD as a diagnostic tool is superior to PSA and PSAD for the diagnosis of prostate cancer. In the different groups divided according to the Gleason score of prostate cancer, OPSAD is elevated with the rise of the Gleason score. OPSAD may be used as a new indicator for the diagnosis and prognosis of prostate cancer, and it can reduce the use of unnecessary puncture biopsy of the prostate.
NASA Astrophysics Data System (ADS)
Suzuki, H.; Mizuguchi, R.; Matsuhiro, M.; Kawata, Y.; Niki, N.; Nakano, Y.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.; Moriyama, N.
2015-03-01
Computed tomography has been used for assessing structural abnormalities associated with emphysema. It is important to develop a robust CT based imaging biomarker that would allow quantification of emphysema progression in early stage. This paper presents effect of smoking on emphysema progression using annual changes of low attenuation volume (LAV) by each lung lobe acquired from low-dose CT images in longitudinal screening for lung cancer. The percentage of LAV (LAV%) was measured after applying CT value threshold method and small noise reduction. Progression of emphysema was assessed by statistical analysis of the annual changes represented by linear regression of LAV%. This method was applied to 215 participants in lung cancer CT screening for five years (18 nonsmokers, 85 past smokers, and 112 current smokers). The results showed that LAV% is useful to classify current smokers with rapid progression of emphysema (0.2%/year, p<0.05). This paper demonstrates effectiveness of the proposed method in diagnosis and prognosis of early emphysema in CT screening for lung cancer.
Shin, Sangjin; Kim, Youn Hee; Hwang, Jin Sub; Lee, Yoon Jae; Lee, Sang Moo; Ahn, Jeonghoon
2014-01-01
Prostate cancer is rapidly increasing in Korea and professional societies have requested adding prostate specific antigen (PSA) testing to the National Cancer Screening Program (NCSP), but this started a controversy in Korea and neutral evidence on this issue is required more than ever. The purpose of this study was to provide economic evidence to the decision makers of the NCSP. A cost-utility analysis was performed on the adoption of PSA screening program among men aged 50-74-years in Korea from the healthcare system perspective. Several data sources were used for the cost-utility analysis, including general health screening data, the Korea Central Cancer Registry, national insurance claims data, and cause of mortality from the National Statistical Office. To solicit the utility index of prostate cancer, a face-to-face interview for typical men aged 40 to 69 was conducted using a Time-Trade Off method. As a result, the increase of effectiveness was estimated to be very low, when adopting PSA screening, and the incremental cost effectiveness ratio (ICER) was analyzed as about 94 million KRW. Sensitivity analyses were performed on the incidence rate, screening rate, cancer stage distribution, utility index, and treatment costs but the results were consistent with the base analysis. Under Korean circumstances with a relatively low incidence rate of prostate cancer, PSA screening is not cost-effective. Therefore, we conclude that adopting national prostate cancer screening would not be beneficial until further evidence is provided in the future.
Websites in Japan: A Qualitative Analysis
Okuhara, Tsuyoshi; Ishikawa, Hirono; Okada, Masahumi; Kato, Mio; Kiuchi, Takahiro
2018-02-26
Background: Cancer screening rates are lower in Japan than in Western countries. Meanwhile, anti-cancer-screening activists take to the internet to spread their messages that cancer screening has little or no efficacy, poses substantial health risks such as side effects from radiation exposure, and that people should forgo cancer screening. We applied a qualitative approach to explore the beliefs underlying the messages of anti-cancer-screening websites, by focusing on perceived value the beliefs provided to those who held them. Methods: We conducted online searches using Google Japan and Yahoo! Japan, targeting websites we classified as “pro,” “anti,” or “neutral” depending on their claims. We applied a dual analytic approach- inductive thematic analysis and deductive interpretative analysis- to the textual data of the anti websites. Results: Of the 88 websites analyzed, five themes that correspond to beliefs were identified: destruction of common knowledge, denial of standard cancer control, education about right cancer control, education about hidden truths, and sense of superiority that only I know the truth. Authors of anti websites ascribed two values (“safety of people” and “self-esteem”) to their beliefs. Conclusion: The beliefs of authors of anti-cancer-screening websites were supposed to be strong. It would be better to target in cancer screening promotion not outright screening refusers but screening hesitant people who are more amenable to changing their attitudes toward screening. The possible means to persuade them were discussed. Creative Commons Attribution License
Design and analysis of group-randomized trials in cancer: A review of current practices.
Murray, David M; Pals, Sherri L; George, Stephanie M; Kuzmichev, Andrey; Lai, Gabriel Y; Lee, Jocelyn A; Myles, Ranell L; Nelson, Shakira M
2018-06-01
The purpose of this paper is to summarize current practices for the design and analysis of group-randomized trials involving cancer-related risk factors or outcomes and to offer recommendations to improve future trials. We searched for group-randomized trials involving cancer-related risk factors or outcomes that were published or online in peer-reviewed journals in 2011-15. During 2016-17, in Bethesda MD, we reviewed 123 articles from 76 journals to characterize their design and their methods for sample size estimation and data analysis. Only 66 (53.7%) of the articles reported appropriate methods for sample size estimation. Only 63 (51.2%) reported exclusively appropriate methods for analysis. These findings suggest that many investigators do not adequately attend to the methodological challenges inherent in group-randomized trials. These practices can lead to underpowered studies, to an inflated type 1 error rate, and to inferences that mislead readers. Investigators should work with biostatisticians or other methodologists familiar with these issues. Funders and editors should ensure careful methodological review of applications and manuscripts. Reviewers should ensure that studies are properly planned and analyzed. These steps are needed to improve the rigor and reproducibility of group-randomized trials. The Office of Disease Prevention (ODP) at the National Institutes of Health (NIH) has taken several steps to address these issues. ODP offers an online course on the design and analysis of group-randomized trials. ODP is working to increase the number of methodologists who serve on grant review panels. ODP has developed standard language for the Application Guide and the Review Criteria to draw investigators' attention to these issues. Finally, ODP has created a new Research Methods Resources website to help investigators, reviewers, and NIH staff better understand these issues. Published by Elsevier Inc.
Exploration of life experiences of positive growth in long-term childhood cancer survivors.
Kim, Yoonjung
2017-10-01
The aim of this study was to explore experiences of positive growth in long-term childhood cancer survivors, from their perspective. Fifteen long-term survivors of childhood cancer provided descriptions of their experiences. Data were collected through face-to-face interviews and the analysis was based on Giorgi's phenomenological research method. The analysis of positive growth experienced by long-term childhood cancer survivors revealed three themes: self-directed life, normalcy in life, and inner maturity. Long-term survivors defined positive growth as a successful transition to a self-satisfactory life based on motivation acquired through their cancer experience and on subjective goal-setting, as well as becoming cancer-free and living a normal life within society. They seemed to have acquired optimistic, flexible, active attitudes toward life while demonstrating profound gratefulness and consideration of people around them, as well as prudent approaches to health. The findings of this study verified that long-term survivors of childhood cancer have grown positively due to their negative past experience. We expect these findings to contribute to the development of programs that promote positive growth in long-term childhood cancer survivors. Copyright © 2017 Elsevier Ltd. All rights reserved.
Zhao, Li-Ting; Xiang, Yu-Hong; Dai, Yin-Mei; Zhang, Zhuo-Yong
2010-04-01
Near infrared spectroscopy was applied to measure the tissue slice of endometrial tissues for collecting the spectra. A total of 154 spectra were obtained from 154 samples. The number of normal, hyperplasia, and malignant samples was 36, 60, and 58, respectively. Original near infrared spectra are composed of many variables, for example, interference information including instrument errors and physical effects such as particle size and light scatter. In order to reduce these influences, original spectra data should be performed with different spectral preprocessing methods to compress variables and extract useful information. So the methods of spectral preprocessing and wavelength selection have played an important role in near infrared spectroscopy technique. In the present paper the raw spectra were processed using various preprocessing methods including first derivative, multiplication scatter correction, Savitzky-Golay first derivative algorithm, standard normal variate, smoothing, and moving-window median. Standard deviation was used to select the optimal spectral region of 4 000-6 000 cm(-1). Then principal component analysis was used for classification. Principal component analysis results showed that three types of samples could be discriminated completely and the accuracy almost achieved 100%. This study demonstrated that near infrared spectroscopy technology and chemometrics method could be a fast, efficient, and novel means to diagnose cancer. The proposed methods would be a promising and significant diagnosis technique of early stage cancer.
Sabeena, Sasidharanpillai; Bhat, Parvati V; Kamath, Veena; Bhat, Shashikala K; Nair, Sreekumaran; N, Ravishankar; Chandrabharani, Kiran; Arunkumar, Govindakarnavar
2017-01-01
Introduction: Cervical cancer probably represents the best-studied human cancer caused by a viral infection and the causal association of this preventable cancer with human papilloma virus (HPV) is well established. Worldwide there is a scarcity of data regarding HPV prevalence with vast differences existing among populations. Objective: The aim of this meta-analysis was to determine the community-based HPV prevalence estimates among asymptomatic women from urban and rural set ups and in participants of cancer screening clinics. Study design: Systematic review and meta-analysis. Methods: PubMed-Medline, CINAHL, Scopus, and Google scholar were systematically searched for studies providing prevalence data for HPV infection among asymptomatic women between 1986 and 2016. Results: The final analysis included 32 studies comprising a population of 224,320 asymptomatic women. The overall pooled HPV prevalence was 11% (95% confidence interval (CI), 9%-12%). The pooled HPV prevalence of 11% (95% CI, 9%-11%) was observed among women attending cervical cancer screening clinics. The pooled HPV prevalences were 10% (95% CI 8%-12%) and 11% (95% CI 4%-18%) from urban and rural areas respectively, indicating higher infection rates among the rural women with the least access to cancer screening and cancer care. Conclusion: The prevalence rates in this systematic quantitative review provide a reliable estimate of the burden of HPV infection among asymptomatic women from developed as well as developing nations. Rural women and women attending cervical cancer screening programmes feature higher genital HPV prevalences compared to their urban counterparts. PMID:28240509
Skin cancer margin analysis within minutes with full-field OCT (Conference Presentation)
NASA Astrophysics Data System (ADS)
Dalimier, Eugénie; Ogrich, Lauren; Morales, Diego; Cusack, Carrie Ann; Abdelmalek, Mark; Boccara, Claude; Durkin, John
2017-02-01
Non-melanoma skin cancer (NMSC) is the most common cancer. Treatment consists of surgical removal of the skin cancer. Traditional excision involves the removal of the visible skin cancer with a significant margin of normal skin. On cosmetically sensitive areas, Mohs micrographic tissue is the standard of care. Mohs uses intraoperative microscopic margin assessment which minimizes the surgical defect and can help reduce the recurrence rate by a factor of 3. The current Mohs technique relies on frozen section tissue slide preparation which significantly lengthens operative time and requires on-site trained histotechnicians. Full-Field Optical Coherence Tomography (FFOCT) is a novel optical imaging technique which provides a quick and efficient method to visualize cancerous areas in minutes, without any preparation or destruction of the tissue. This study aimed to evaluate the potential of FFOCT for the analysis of skin cancer margins during Mohs surgery. Over 150 images of Mohs specimens were acquired intraoperatively with FFOCT before frozen section analysis. The imaging procedure took less than 5 minutes for each specimen. No artifacts on histological preparation were found arising from FFOCT manipulation; however frozen section artifact was readily seen on FFOCT. An atlas was established with FFOCT images and corresponding histological slides to reveal FFOCT reading criteria of normal and cancerous structures. Blind analysis showed high concordance between FFOCT and histology. FFOCT can potentially reduce recurrence rates while maintaining short surgery times, optimize clinical workflow, and decrease healthcare costs. For the patient, this translates into smaller infection risk, decreased stress, and better comfort.
Sabeena, Sasidharanpillai; Bhat, Parvati V; Kamath, Veena; Bhat, Shashikala K; Nair, Sreekumaran; n, Ravishankar; Chandrabharani, Kiran; Arunkumar, Govindakarnavar
2017-01-01
Introduction: Cervical cancer probably represents the best-studied human cancer caused by a viral infection and the causal association of this preventable cancer with human papilloma virus (HPV) is well established. Worldwide there is a scarcity of data regarding HPV prevalence with vast differences existing among populations. Objective: The aim of this meta-analysis was to determine the community-based HPV prevalence estimates among asymptomatic women from urban and rural set ups and in participants of cancer screening clinics. Study design: Systematic review and meta-analysis. Methods: PubMed-Medline, CINAHL, Scopus, and Google scholar were systematically searched for studies providing prevalence data for HPV infection among asymptomatic women between 1986 and 2016. Results: The final analysis included 32 studies comprising a population of 224,320 asymptomatic women. The overall pooled HPV prevalence was 11% (95% confidence interval (CI), 9%-12%). The pooled HPV prevalence of 11% (95% CI, 9%-11%) was observed among women attending cervical cancer screening clinics. The pooled HPV prevalences were 10% (95% CI 8%-12%) and 11% (95% CI 4%-18%) from urban and rural areas respectively, indicating higher infection rates among the rural women with the least access to cancer screening and cancer care. Conclusion: The prevalence rates in this systematic quantitative review provide a reliable estimate of the burden of HPV infection among asymptomatic women from developed as well as developing nations. Rural women and women attending cervical cancer screening programmes feature higher genital HPV prevalences compared to their urban counterparts. Creative Commons Attribution License
Han, Chao-Dong; Ge, Wen-Sheng
2016-11-01
BACKGROUND The angiotensin-converting enzyme (ACE, CD143) gene plays a crucial role in the pathology of many cancers. Previous studies mostly focused on the gene polymorphism, but the other functions of ACE have rarely been reported. The purpose of this study was to investigate the expression of ACE and its biological function, as well as its prognostic value, in laryngeal cancer. MATERIAL AND METHODS The expression of ACE was detected by quantitative real-time polymerase chain reaction (qRT-PCR) analysis in 106 patients with laryngeal cancer and 85 healthy people. Then the cell proliferation was estimated after the cell lines Hep-2 were transfected with pGL3-ACE and empty vector, respectively. In addition, the relationship between ACE expression and clinicopathologic characteristics was analyzed. Finally, Kaplan-Meier analysis was used to evaluate the overall survival of patients with different ACE expression, while Cox regression analysis was conducted to reveal the prognostic value of ACE in laryngeal cancer. RESULTS Our results demonstrate that ACE is over-expressed in laryngeal cancer and thus promotes cell proliferation. The up-regulation of ACE was significantly influenced by tumor stage and lymph node metastasis. Patients with high ACE expression had a shorter overall survival compared with those with low ACE expression according to Kaplan-Meier analysis. The ACE gene was also found to be an important factor in the prognosis of laryngeal cancer. CONCLUSIONS Our study shows that the ACE gene was up-regulated, which promoted the cell proliferation, and it could be an independent prognostic marker in laryngeal cancer.
Pellegrini, Kathryn L; Patil, Dattatraya; Douglas, Kristen J S; Lee, Grace; Wehrmeyer, Kathryn; Torlak, Mersiha; Clark, Jeremy; Cooper, Colin S; Moreno, Carlos S; Sanda, Martin G
2017-06-01
The measurement of gene expression in post-digital rectal examination (DRE) urine specimens provides a non-invasive method to determine a patient's risk of prostate cancer. Many currently available assays use whole urine or cell pellets for the analysis of prostate cancer-associated genes, although the use of extracellular vesicles (EVs) has also recently been of interest. We investigated the expression of prostate-, kidney-, and bladder-specific transcripts and known prostate cancer biomarkers in urine EVs. Cell pellets and EVs were recovered from post-DRE urine specimens, with the total RNA yield and quality determined by Bioanalyzer. The levels of prostate, kidney, and bladder-associated transcripts in EVs were assessed by TaqMan qPCR and targeted sequencing. RNA was more consistently recovered from the urine EV specimens, with over 80% of the patients demonstrating higher RNA yields in the EV fraction as compared to urine cell pellets. The median EV RNA yield of 36.4 ng was significantly higher than the median urine cell pellet RNA yield of 4.8 ng. Analysis of the post-DRE urine EVs indicated that prostate-specific transcripts were more abundant than kidney- or bladder-specific transcripts. Additionally, patients with prostate cancer had significantly higher levels of the prostate cancer-associated genes PCA3 and ERG. Post-DRE urine EVs are a viable source of prostate-derived RNAs for biomarker discovery and prostate cancer status can be distinguished from analysis of these specimens. Continued analysis of urine EVs offers the potential discovery of novel biomarkers for pre-biopsy prostate cancer detection. © 2017 Wiley Periodicals, Inc.
Guo, How-Ran
2011-10-20
Despite its limitations, ecological study design is widely applied in epidemiology. In most cases, adjustment for age is necessary, but different methods may lead to different conclusions. To compare three methods of age adjustment, a study on the associations between arsenic in drinking water and incidence of bladder cancer in 243 townships in Taiwan was used as an example. A total of 3068 cases of bladder cancer, including 2276 men and 792 women, were identified during a ten-year study period in the study townships. Three methods were applied to analyze the same data set on the ten-year study period. The first (Direct Method) applied direct standardization to obtain standardized incidence rate and then used it as the dependent variable in the regression analysis. The second (Indirect Method) applied indirect standardization to obtain standardized incidence ratio and then used it as the dependent variable in the regression analysis instead. The third (Variable Method) used proportions of residents in different age groups as a part of the independent variables in the multiple regression models. All three methods showed a statistically significant positive association between arsenic exposure above 0.64 mg/L and incidence of bladder cancer in men and women, but different results were observed for the other exposure categories. In addition, the risk estimates obtained by different methods for the same exposure category were all different. Using an empirical example, the current study confirmed the argument made by other researchers previously that whereas the three different methods of age adjustment may lead to different conclusions, only the third approach can obtain unbiased estimates of the risks. The third method can also generate estimates of the risk associated with each age group, but the other two are unable to evaluate the effects of age directly.
Zheng, Mingyue; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong
2015-01-01
Lung cancer causes over one million deaths every year worldwide. However, prevention and treatment methods for this serious disease are limited. The identification of new chemicals related to lung cancer may aid in disease prevention and the design of more effective treatments. This study employed a weighted network, constructed using chemical-chemical interaction information, to identify new chemicals related to two types of lung cancer: non-small lung cancer and small-cell lung cancer. Then, a randomization test as well as chemical-chemical interaction and chemical structure information were utilized to make further selections. A final analysis of these new chemicals in the context of the current literature indicates that several chemicals are strongly linked to lung cancer. PMID:26047514
Nevo, Daniel; Nishihara, Reiko; Ogino, Shuji; Wang, Molin
2017-08-04
In the analysis of time-to-event data with multiple causes using a competing risks Cox model, often the cause of failure is unknown for some of the cases. The probability of a missing cause is typically assumed to be independent of the cause given the time of the event and covariates measured before the event occurred. In practice, however, the underlying missing-at-random assumption does not necessarily hold. Motivated by colorectal cancer molecular pathological epidemiology analysis, we develop a method to conduct valid analysis when additional auxiliary variables are available for cases only. We consider a weaker missing-at-random assumption, with missing pattern depending on the observed quantities, which include the auxiliary covariates. We use an informative likelihood approach that will yield consistent estimates even when the underlying model for missing cause of failure is misspecified. The superiority of our method over naive methods in finite samples is demonstrated by simulation study results. We illustrate the use of our method in an analysis of colorectal cancer data from the Nurses' Health Study cohort, where, apparently, the traditional missing-at-random assumption fails to hold.
Cancer Salivary Biomarkers for Tumours Distant to the Oral Cavity
Rapado-González, Óscar; Majem, Blanca; Muinelo-Romay, Laura; López-López, Rafa; Suarez-Cunqueiro, María Mercedes
2016-01-01
The analysis of saliva as a diagnostic approach for systemic diseases was proposed just two decades ago, but recently great interest in the field has emerged because of its revolutionary potential as a liquid biopsy and its usefulness as a non-invasive sampling method. Multiple molecules isolated in saliva have been proposed as cancer biomarkers for diagnosis, prognosis, drug monitoring and pharmacogenetic studies. In this review, we focus on the current status of the salivary diagnostic biomarkers for different cancers distant to the oral cavity, noting their potential use in the clinic and their applicability in personalising cancer therapies. PMID:27626410
Sasahira, Naoki; Hamada, Tsuyoshi; Togawa, Osamu; Yamamoto, Ryuichi; Iwai, Tomohisa; Tamada, Kiichi; Kawaguchi, Yoshiaki; Shimura, Kenji; Koike, Takero; Yoshida, Yu; Sugimori, Kazuya; Ryozawa, Shomei; Kakimoto, Toshiharu; Nishikawa, Ko; Kitamura, Katsuya; Imamura, Tsunao; Mizuide, Masafumi; Toda, Nobuo; Maetani, Iruru; Sakai, Yuji; Itoi, Takao; Nagahama, Masatsugu; Nakai, Yousuke; Isayama, Hiroyuki
2016-01-01
AIM: To determine the optimal method of endoscopic preoperative biliary drainage for malignant distal biliary obstruction. METHODS: Multicenter retrospective study was conducted in patients who underwent plastic stent (PS) or nasobiliary catheter (NBC) placement for resectable malignant distal biliary obstruction followed by surgery between January 2010 and March 2012. Procedure-related adverse events, stent/catheter dysfunction (occlusion or migration of PS/NBC, development of cholangitis, or other conditions that required repeat endoscopic biliary intervention), and jaundice resolution (bilirubin level < 3.0 mg/dL) were evaluated. Cumulative incidence of jaundice resolution and dysfunction of PS/NBC were estimated using competing risk analysis. Patient characteristics and preoperative biliary drainage were also evaluated for association with the time to jaundice resolution and PS/NBC dysfunction using competing risk regression analysis. RESULTS: In total, 419 patients were included in the study (PS, 253 and NBC, 166). Primary cancers included pancreatic cancer in 194 patients (46%), bile duct cancer in 172 (41%), gallbladder cancer in three (1%), and ampullary cancer in 50 (12%). The median serum total bilirubin was 7.8 mg/dL and 324 patients (77%) had ≥ 3.0 mg/dL. During the median time to surgery of 29 d [interquartile range (IQR), 30-39 d]. PS/NBC dysfunction rate was 35% for PS and 18% for NBC [Subdistribution hazard ratio (SHR) = 4.76; 95%CI: 2.44-10.0, P < 0.001]; the pig-tailed tip was a risk factor for PS dysfunction. Jaundice resolution was achieved in 85% of patients and did not depend on the drainage method (PS or NBC). CONCLUSION: PS has insufficient patency for preoperative biliary drainage. Given the drawbacks of external drainage via NBC, an alternative method of internal drainage should be explored. PMID:27076764
Analysis of digitized cervical images to detect cervical neoplasia
NASA Astrophysics Data System (ADS)
Ferris, Daron G.
2004-05-01
Cervical cancer is the second most common malignancy in women worldwide. If diagnosed in the premalignant stage, cure is invariably assured. Although the Papanicolaou (Pap) smear has significantly reduced the incidence of cervical cancer where implemented, the test is only moderately sensitive, highly subjective and skilled-labor intensive. Newer optical screening tests (cervicography, direct visual inspection and speculoscopy), including fluorescent and reflective spectroscopy, are fraught with certain weaknesses. Yet, the integration of optical probes for the detection and discrimination of cervical neoplasia with automated image analysis methods may provide an effective screening tool for early detection of cervical cancer, particularly in resource poor nations. Investigative studies are needed to validate the potential for automated classification and recognition algorithms. By applying image analysis techniques for registration, segmentation, pattern recognition, and classification, cervical neoplasia may be reliably discriminated from normal epithelium. The National Cancer Institute (NCI), in cooperation with the National Library of Medicine (NLM), has embarked on a program to begin this and other similar investigative studies.
NASA Astrophysics Data System (ADS)
Marcó P., L. M.; Jiménez, E.; Hernández C., E. A.; Rojas, A.; Greaves, E. D.
2001-11-01
The method of quantification using the Compton peak as an internal standard, developed in a previous work, was applied to the routine determination of Fe, Cu, Zn and Se in serum samples from normal individuals and cancer patients by total reflection X-ray fluorescence spectrometry. Samples were classified according to age and sex of the donor, in order to determine reference values for normal individuals. Results indicate that the Zn/Cu ratio and the Cu concentration could prove to be useful tools for cancer diagnosis. Significant differences in these parameters between the normal and cancer group were found for all age ranges. The multielemental character of the technique, coupled with the small amounts of sample required and the short analysis time make it a valuable tool in clinical analysis.
Ortega-Ortega, Marta; Oliva-Moreno, Juan; Jiménez-Aguilera, Juan de Dios; Romero-Aguilar, Antonio; Espigado-Tocino, Ildefonso
2015-01-01
Stem cell transplantation has been used for many years to treat haematological malignancies that could not be cured by other treatments. Despite this medical breakthrough, mortality rates remain high. Our purpose was to evaluate labour productivity losses associated with premature mortality due to blood cancer in recipients of stem cell transplantations. We collected primary data from the clinical histories of blood cancer patients who had undergone stem cell transplantation between 2006 and 2011 in two Spanish hospitals. We carried out a descriptive analysis and calculated the years of potential life lost and years of potential productive life lost. Labour productivity losses due to premature mortality were estimated using the Human Capital method. An alternative approach, the Friction Cost method, was used as part of the sensitivity analysis. Our findings suggest that, in a population of 179 transplanted and deceased patients, males and people who die between the ages of 30 and 49 years generate higher labour productivity losses. The estimated loss amounts to over €31.4 million using the Human Capital method (€480,152 using the Friction Cost method), which means an average of €185,855 per death. The highest labour productivity losses are produced by leukaemia. However, lymphoma generates the highest loss per death. Further efforts are needed to reduce premature mortality in blood cancer patients undergoing transplantations and reduce economic losses. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.
Giri, Veda N.; Coups, Elliot J.; Ruth, Karen; Goplerud, Julia; Raysor, Susan; Kim, Taylor Y.; Bagden, Loretta; Mastalski, Kathleen; Zakrzewski, Debra; Leimkuhler, Suzanne; Watkins-Bruner, Deborah
2009-01-01
Purpose Men with a family history (FH) of prostate cancer (PCA) and African American (AA) men are at higher risk for PCA. Recruitment and retention of these high-risk men into early detection programs has been challenging. We report a comprehensive analysis on recruitment methods, show rates, and participant factors from the Prostate Cancer Risk Assessment Program (PRAP), which is a prospective, longitudinal PCA screening study. Materials and Methods Men 35–69 years are eligible if they have a FH of PCA, are AA, or have a BRCA1/2 mutation. Recruitment methods were analyzed with respect to participant demographics and show to the first PRAP appointment using standard statistical methods Results Out of 707 men recruited, 64.9% showed to the initial PRAP appointment. More individuals were recruited via radio than from referral or other methods (χ2 = 298.13, p < .0001). Men recruited via radio were more likely to be AA (p<0.001), less educated (p=0.003), not married or partnered (p=0.007), and have no FH of PCA (p<0.001). Men recruited via referrals had higher incomes (p=0.007). Men recruited via referral were more likely to attend their initial PRAP visit than those recruited by radio or other methods (χ2 = 27.08, p < .0001). Conclusions This comprehensive analysis finds that radio leads to higher recruitment of AA men with lower socioeconomic status. However, these are the high-risk men that have lower show rates for PCA screening. Targeted motivational measures need to be studied to improve show rates for PCA risk assessment for these high-risk men. PMID:19758657
2014-01-01
Background Using immunohistochemistry (IHC) to select cases for mismatch repair (MMR) genetic testing, we failed to identify a large kindred with the deleterious PMS2 mutation c.989-1G > T. The purpose of the study was to examine the sensitivity of IHC and microsatellite instability-analysis (MSI) to identify carriers of the mutation, and to estimate its penetrance and expressions. Methods All carriers and obligate carriers of the mutation were identified. All cancer diagnoses were confirmed. IHC and MSI-analysis were performed on available tumours. Penetrances of cancers included in the Amsterdam and the Bethesda Criteria, for MSI-high tumours and MSI-high and low tumours were calculated by the Kaplan-Meier algorithm. Results Probability for co-segregation of the mutation and cancers by chance was 0.000004. Fifty-six carriers or obligate carriers were identified. There was normal staining for PMS2 in 15/18 (83.3%) of tumours included in the AMS1/AMS2/Bethesda criteria. MSI-analysis showed that 15/21 (71.4%) of tumours were MSI-high and 4/21 (19.0%) were MSI-low. Penetrance at 70 years was 30.6% for AMS1 cancers (colorectal cancers), 42.8% for AMS2 cancers, 47.2% for Bethesda cancers, 55.6% for MSI-high and MSI-low cancers and 52.2% for MSI-high cancers. Conclusions The mutation met class 5 criteria for pathogenicity. IHC was insensitive in detecting tumours caused by the mutation. Penetrance of cancers that displayed MSI was 56% at 70 years. Besides colorectal cancers, the most frequent expressions were carcinoma of the endometrium and breast in females and stomach and prostate in males. PMID:24790682
This week, we are excited to announce the launch of the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomics Computational DREAM Challenge. The aim of this Challenge is to encourage the generation of computational methods for extracting information from the cancer proteome and for linking those data to genomic and transcriptomic information. The specific goals are to predict proteomic and phosphoproteomic data from other multiple data types including transcriptomics and genetics.
Epidemiologic studies of the human microbiome and cancer.
Vogtmann, Emily; Goedert, James J
2016-02-02
The human microbiome, which includes the collective genome of all bacteria, archaea, fungi, protists, and viruses found in and on the human body, is altered in many diseases and may substantially affect cancer risk. Previously detected associations of individual bacteria (e.g., Helicobacter pylori), periodontal disease, and inflammation with specific cancers have motivated studies considering the association between the human microbiome and cancer risk. This short review summarises microbiome research, focusing on published epidemiological associations with gastric, oesophageal, hepatobiliary, pancreatic, lung, colorectal, and other cancers. Large, prospective studies of the microbiome that employ multidisciplinary laboratory and analysis methods, as well as rigorous validation of case status, are likely to yield translational opportunities to reduce cancer morbidity and mortality by improving prevention, screening, and treatment.
Epidemiologic studies of the human microbiome and cancer
Vogtmann, Emily; Goedert, James J
2016-01-01
The human microbiome, which includes the collective genome of all bacteria, archaea, fungi, protists, and viruses found in and on the human body, is altered in many diseases and may substantially affect cancer risk. Previously detected associations of individual bacteria (e.g., Helicobacter pylori), periodontal disease, and inflammation with specific cancers have motivated studies considering the association between the human microbiome and cancer risk. This short review summarises microbiome research, focusing on published epidemiological associations with gastric, oesophageal, hepatobiliary, pancreatic, lung, colorectal, and other cancers. Large, prospective studies of the microbiome that employ multidisciplinary laboratory and analysis methods, as well as rigorous validation of case status, are likely to yield translational opportunities to reduce cancer morbidity and mortality by improving prevention, screening, and treatment. PMID:26730578
Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K
2017-01-01
The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.
Improving information retrieval in functional analysis.
Rodriguez, Juan C; González, Germán A; Fresno, Cristóbal; Llera, Andrea S; Fernández, Elmer A
2016-12-01
Transcriptome analysis is essential to understand the mechanisms regulating key biological processes and functions. The first step usually consists of identifying candidate genes; to find out which pathways are affected by those genes, however, functional analysis (FA) is mandatory. The most frequently used strategies for this purpose are Gene Set and Singular Enrichment Analysis (GSEA and SEA) over Gene Ontology. Several statistical methods have been developed and compared in terms of computational efficiency and/or statistical appropriateness. However, whether their results are similar or complementary, the sensitivity to parameter settings, or possible bias in the analyzed terms has not been addressed so far. Here, two GSEA and four SEA methods and their parameter combinations were evaluated in six datasets by comparing two breast cancer subtypes with well-known differences in genetic background and patient outcomes. We show that GSEA and SEA lead to different results depending on the chosen statistic, model and/or parameters. Both approaches provide complementary results from a biological perspective. Hence, an Integrative Functional Analysis (IFA) tool is proposed to improve information retrieval in FA. It provides a common gene expression analytic framework that grants a comprehensive and coherent analysis. Only a minimal user parameter setting is required, since the best SEA/GSEA alternatives are integrated. IFA utility was demonstrated by evaluating four prostate cancer and the TCGA breast cancer microarray datasets, which showed its biological generalization capabilities. Copyright © 2016 Elsevier Ltd. All rights reserved.
Vasavada, Shaleen R; Dobbs, Ryan W; Kajdacsy-Balla, André A; Abern, Michael R; Moreira, Daniel M
2018-05-01
We performed a comprehensive literature review and meta-analysis to evaluate the association of inflammation on prostate needle biopsies and prostate cancer risk. We searched Embase®, PubMed® and Web of Science™ from January 1, 1990 to October 1, 2016 for abstracts containing the key words prostate cancer, inflammation and biopsy. Study inclusion criteria were original research, adult human subjects, cohort or case-control study design, histological inflammation on prostate needle biopsy and prostate cancer on histology. Two independent teams reviewed abstracts and extracted data from the selected manuscripts. Combined ORs and 95% CIs of any, acute and chronic inflammation were calculated using the random effects method. Of the 1,030 retrieved abstracts 46 underwent full text review and 25 were included in the final analysis, comprising a total of 20,585 subjects and 6,641 patients with prostate cancer. There was significant heterogeneity among studies (I 2 = 84.4%, p <0.001). The presence of any inflammation was significantly associated with a lower prostate cancer risk in 25 studies (OR 0.455, 95% CI 0.337-0.573). There was no evidence of publication bias (p >0.05). When subanalyzed by inflammation type, acute inflammation in 4 studies and chronic inflammation in 15 were each associated with a lower prostate cancer risk (OR 0.681, 95% CI 0.450-0.913 and OR 0.499, 95% CI 0.334-0.665, respectively). In a meta-analysis of 25 studies inflammation on prostate needle biopsy was associated with a lower prostate cancer risk. Clinically the presence of inflammation on prostate needle biopsy may lower the risk of a subsequent prostate cancer diagnosis. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Malhotra, Jyoti; Sartori, Samantha; Brennan, Paul; Zaridze, David; Szeszenia-Dabrowska, Neonila; Świątkowska, Beata; Rudnai, Peter; Lissowska, Jolanta; Fabianova, Eleonora; Mates, Dana; Bencko, Vladimir; Gaborieau, Valerie; Stücker, Isabelle; Foretova, Lenka; Janout, Vladimir; Boffetta, Paolo
2015-03-01
Occupational exposures are known risk factors for lung cancer. Role of genetically determined host factors in occupational exposure-related lung cancer is unclear. We used genome-wide association (GWA) data from a case-control study conducted in 6 European countries from 1998 to 2002 to identify gene-occupation interactions and related pathways for lung cancer risk. GWA analysis was performed for each exposure using logistic regression and interaction term for genotypes, and exposure was included in this model. Both SNP-based and gene-based interaction P values were calculated. Pathway analysis was performed using three complementary methods, and analyses were adjusted for multiple comparisons. We analyzed 312,605 SNPs and occupational exposure to 70 agents from 1,802 lung cancer cases and 1,725 cancer-free controls. Mean age of study participants was 60.1 ± 9.1 years and 75% were male. Largest number of significant associations (P ≤ 1 × 10(-5)) at SNP level was demonstrated for nickel, brick dust, concrete dust, and cement dust, and for brick dust and cement dust at the gene-level (P ≤ 1 × 10(-4)). Approximately 14 occupational exposures showed significant gene-occupation interactions with pathways related to response to environmental information processing via signal transduction (P < 0.001 and FDR < 0.05). Other pathways that showed significant enrichment were related to immune processes and xenobiotic metabolism. Our findings suggest that pathways related to signal transduction, immune process, and xenobiotic metabolism may be involved in occupational exposure-related lung carcinogenesis. Our study exemplifies an integrative approach using pathway-based analysis to demonstrate the role of genetic variants in occupational exposure-related lung cancer susceptibility. Cancer Epidemiol Biomarkers Prev; 24(3); 570-9. ©2015 AACR. ©2015 American Association for Cancer Research.
Esmaeili, Rezvan; Abdoli, Nasrin; Yadegari, Fatemeh; Neishaboury, Mohamadreza; Farahmand, Leila; Kaviani, Ahmad; Majidzadeh-A, Keivan
2018-01-01
CD44 encoded by a single gene is a cell surface transmembrane glycoprotein. Exon 2 is one of the important exons to bind CD44 protein to hyaluronan. Experimental evidences show that hyaluronan-CD44 interaction intensifies the proliferation, migration, and invasion of breast cancer cells. Therefore, the current study aimed at investigating the association between specific polymorphisms in exon 2 and its flanking region of CD44 with predisposition to breast cancer. In the current study, 175 Iranian female patients with breast cancer and 175 age-matched healthy controls were recruited in biobank, Breast Cancer Research Center, Tehran, Iran. Single nucleotide polymorphisms of CD44 exon 2 and its flanking were analyzed via polymerase chain reaction and gene sequencing techniques. Association between the observed variation with breast cancer risk and clinico-pathological characteristics were studied. Subsequently, bioinformatics analysis was conducted to predict potential exonic splicing enhancer (ESE) motifs changed as the result of a mutation. A unique polymorphism of the gene encoding CD44 was identified at position 14 nucleotide upstream of exon 2 (A37692→G) by the sequencing method. The A > G polymorphism exhibited a significant association with higher-grades of breast cancer, although no significant relation was found between this polymorphism and breast cancer risk. Finally, computational analysis revealed that the intronic mutation generated a new consensus-binding motif for the splicing factor, SC35, within intron 1. The current study results indicated that A > G polymorphism was associated with breast cancer development; in addition, in silico analysis with ESE finder prediction software showed that the change created a new SC35 binding site.
Chu, Qi; Gan, Yong; Ren, Hui; Zhang, Liyan; Wang, Liwei; Li, Xiaoxiu; Wang, Wei
2016-01-01
Objective High expression of phosphorylated signal transducer and activator of transcription 3 (p-STAT3) has been detected in a variety of human tumors. However, the association of positive p-STAT3 expression with clinicopathological parameters and the prognosis of colorectal cancer patients remain controversial. To identify the relationship between p-STAT3 expression and clinicopathological parameters and prognosis in patients with colorectal cancer, a systematic review and meta-analysis were performed. Methods We performed a comprehensive literature search from PubMed, EMBASE, and SinoMed through 27 March, 2016. Hazard ratios (HRs) with 95% confidence intervals (CI) were combined to evaluate the association between p-STAT3 expression and overall survival of colorectal cancer patients. Odds ratios (ORs) with 95% CI were combined to evaluate the association between p-STAT3 expression and clinicopathological parameters in patients with colorectal cancer. Results Seventeen studies including a total of 2,346 colorectal cancer patients were included in this meta-analysis. The combined HR was 1.43 (95% CI: 1.23–1.67, P < 0.001), which suggested a positive relationship between p-STAT3 overexpression and poorer overall survival of colorectal cancer patients. In addition, the results indicated that positive p-STAT3 expression was significantly associated with the presence of lymph node metastasis (OR: 2.43, 95% CI: 1.18–5.01, P = 0.02) but was not associated with TNM stage, tumor differentiation or gender. Conclusion The meta-analysis results suggest that p-STAT3 overexpression is unfavorable for the prognosis of colorectal cancer patients, and p-STAT3 overexpression is associated with the presence of lymph node metastasis among colorectal cancer patients. PMID:27504822
A genetic variant in MiR-146a modifies digestive system cancer risk: a meta-analysis.
Li, Ying-Jun; Zhang, Zhen-Yu; Mao, Ying-Ying; Jin, Ming-Juan; Jing, Fang-Yuan; Ye, Zhen-Hua; Chen, Kun
2014-01-01
MicroRNAs (miRNAs) negatively regulate gene expression and act as tumor suppressors or oncogenes in oncogenesis. The association between a single nucleotide polymorphism (SNP) in miR-146a rs2910164 and susceptibility to digestive system cancers was inconsistent in previous studies. In this study, we conducted a literature search of PubMed to identify all relevant studies published before August 31, 2013. A total of 21 independent case-control studies were included in this updated meta-analysis with 9,558 cases and 10,614 controls. We found that the miR-146a rs2910164 polymorphism was significantly associated with decreased risk of digestive system cancers in an allele model (OR=0.90, 95%CI 0.87-0.94), homozygote model (OR=0.84, 95%CI 0.77-0.91), dominant model (OR=0.90, 95%CI 0.84-0.96), and recessive model (OR=0.85, 95%CI 0.79-0.91), while in a heterozygous model (OR = 0.99, 95% CI 0.89-1.11) the association showed marginal significance. Subgroup analysis by cancer site revealed decreased risk in colorectal cancer above allele model (OR=0.90, 95%CI 0.83- 0.97) and homozygote model (OR=0.85, 95%CI 0.72-1.00). Similarly, decreased cancer risk was observed when compared with allele model (OR=0.87, 95%CI 0.81-0.93) and recessive model (OR=0.81, 95%CI 0.72-0.90) in gastric cancer. When stratified by ethnicity, genotyping methods and quality score, decreased cancer risks were also observed. This current meta-analysis indicated that miR-146a rs2910164 polymorphism may decrease the susceptibility to digestive system cancers, especially in Asian populations.
Chisaki, Yugo; Nakamura, Nobuhiko; Yano, Yoshitaka
2017-01-01
The purpose of this study was to propose a time-series modeling and simulation (M&S) strategy for probabilistic cost-effective analysis in cancer chemotherapy using a Monte-Carlo method based on data available from the literature. The simulation included the cost for chemotherapy, for pharmaceutical care for adverse events (AEs) and other medical costs. As an application example, we describe the analysis for the comparison of four regimens, cisplatin plus irinotecan, carboplatin plus paclitaxel, cisplatin plus gemcitabine (GP), and cisplatin plus vinorelbine, for advanced non-small cell lung cancer. The factors, drug efficacy explained by overall survival or time to treatment failure, frequency and severity of AEs, utility value of AEs to determine QOL, the drugs' and other medical costs in Japan, were included in the model. The simulation was performed and quality adjusted life years (QALY) and incremental cost-effectiveness ratios (ICER) were calculated. An index, percentage of superiority (%SUP) which is the rate of the increased cost vs. QALY-gained plots within the area of positive QALY-gained and also below some threshold values of the ICER, was calculated as functions of threshold values of the ICER. An M&S process was developed, and for the simulation example, the GP regimen was the most cost-effective, in case of threshold values of the ICER=$70000/year, the %SUP for the GP are more than 50%. We developed an M&S process for probabilistic cost-effective analysis, this method would be useful for decision-making in choosing a cancer chemotherapy regimen in terms of pharmacoeconomic.
Marshall, Sarah A.; Yang, Christopher C.; Ping, Qing; Zhao, Mengnan; Avis, Nancy E.
2016-01-01
Purpose User-generated content on social media sites, such as health-related online forums, offers researchers a tantalizing amount of information, but concerns regarding scientific application of such data remain. This paper compares and contrasts symptom cluster patterns derived from messages on a breast cancer forum with those from a symptom checklist completed by breast cancer survivors participating in a research study. Methods Over 50,000 messages generated by 12,991 users of the breast cancer forum on MedHelp.org were transformed into a standard form and examined for the co-occurrence of 25 symptoms. The k-medoid clustering method was used to determine appropriate placement of symptoms within clusters. Findings were compared with a similar analysis of a symptom checklist administered to 653 breast cancer survivors participating in a research study. Results The following clusters were identified using forum data: menopausal/psychological, pain/fatigue, gastrointestinal, and miscellaneous. Study data generated the clusters: menopausal, pain, fatigue/sleep/gastrointestinal, psychological, and increased weight/appetite. Although the clusters are somewhat different, many symptoms that clustered together in the social media analysis remained together in the analysis of the study participants. Density of connections between symptoms, as reflected by rates of co-occurrence and similarity, was higher in the study data. Conclusions The copious amount of data generated by social media outlets can augment findings from traditional data sources. When different sources of information are combined, areas of overlap and discrepancy can be detected, perhaps giving researchers a more accurate picture of reality. However, data derived from social media must be used carefully and with understanding of its limitations. PMID:26476836
NASA Astrophysics Data System (ADS)
Petersen, D.; Naveed, P.; Ragheb, A.; Niedieker, D.; El-Mashtoly, S. F.; Brechmann, T.; Kötting, C.; Schmiegel, W. H.; Freier, E.; Pox, C.; Gerwert, K.
2017-06-01
Endoscopy plays a major role in early recognition of cancer which is not externally accessible and therewith in increasing the survival rate. Raman spectroscopic fiber-optical approaches can help to decrease the impact on the patient, increase objectivity in tissue characterization, reduce expenses and provide a significant time advantage in endoscopy. In gastroenterology an early recognition of malign and precursor lesions is relevant. Instantaneous and precise differentiation between adenomas as precursor lesions for cancer and hyperplastic polyps on the one hand and between high and low-risk alterations on the other hand is important. Raman fiber-optical measurements of colon biopsy samples taken during colonoscopy were carried out during a clinical study, and samples of adenocarcinoma (22), tubular adenomas (141), hyperplastic polyps (79) and normal tissue (101) from 151 patients were analyzed. This allows us to focus on the bioinformatic analysis and to set stage for Raman endoscopic measurements. Since spectral differences between normal and cancerous biopsy samples are small, special care has to be taken in data analysis. Using a leave-one-patient-out cross-validation scheme, three different outlier identification methods were investigated to decrease the influence of systematic errors, like a residual risk in misplacement of the sample and spectral dilution of marker bands (esp. cancerous tissue) and therewith optimize the experimental design. Furthermore other validations methods like leave-one-sample-out and leave-one-spectrum-out cross-validation schemes were compared with leave-one-patient-out cross-validation. High-risk lesions were differentiated from low-risk lesions with a sensitivity of 79%, specificity of 74% and an accuracy of 77%, cancer and normal tissue with a sensitivity of 79%, specificity of 83% and an accuracy of 81%. Additionally applied outlier identification enabled us to improve the recognition of neoplastic biopsy samples.
Copy-number analysis and inference of subclonal populations in cancer genomes using Sclust.
Cun, Yupeng; Yang, Tsun-Po; Achter, Viktor; Lang, Ulrich; Peifer, Martin
2018-06-01
The genomes of cancer cells constantly change during pathogenesis. This evolutionary process can lead to the emergence of drug-resistant mutations in subclonal populations, which can hinder therapeutic intervention in patients. Data derived from massively parallel sequencing can be used to infer these subclonal populations using tumor-specific point mutations. The accurate determination of copy-number changes and tumor impurity is necessary to reliably infer subclonal populations by mutational clustering. This protocol describes how to use Sclust, a copy-number analysis method with a recently developed mutational clustering approach. In a series of simulations and comparisons with alternative methods, we have previously shown that Sclust accurately determines copy-number states and subclonal populations. Performance tests show that the method is computationally efficient, with copy-number analysis and mutational clustering taking <10 min. Sclust is designed such that even non-experts in computational biology or bioinformatics with basic knowledge of the Linux/Unix command-line syntax should be able to carry out analyses of subclonal populations.
Mueller coherency matrix method for contrast image in tissue polarimetry
NASA Astrophysics Data System (ADS)
Arce-Diego, J. L.; Fanjul-Vélez, F.; Samperio-García, D.; Pereda-Cubián, D.
2007-07-01
In this work, we propose the use of the Mueller Coherency matrix of biological tissues in order to increase the information from tissue images and so their contrast. This method involves different Mueller Coherency matrix based parameters, like the eigenvalues analysis, the entropy factor calculation, polarization components crosstalks, linear and circular polarization degrees, hermiticity or the Quaternions analysis in case depolarisation properties of tissue are sufficiently low. All these parameters make information appear clearer and so increase image contrast, so pathologies like cancer could be detected in a sooner stage of development. The election will depend on the concrete pathological process under study. This Mueller Coherency matrix method can be applied to a single tissue point, or it can be combined with a tomographic technique, so as to obtain a 3D representation of polarization contrast parameters in pathological tissues. The application of this analysis to concrete diseases can lead to tissue burn depth estimation or cancer early detection.
Goungounga, Juste Aristide; Gaudart, Jean; Colonna, Marc; Giorgi, Roch
2016-10-12
The reliability of spatial statistics is often put into question because real spatial variations may not be found, especially in heterogeneous areas. Our objective was to compare empirically different cluster detection methods. We assessed their ability to find spatial clusters of cancer cases and evaluated the impact of the socioeconomic status (e.g., the Townsend index) on cancer incidence. Moran's I, the empirical Bayes index (EBI), and Potthoff-Whittinghill test were used to investigate the general clustering. The local cluster detection methods were: i) the spatial oblique decision tree (SpODT); ii) the spatial scan statistic of Kulldorff (SaTScan); and, iii) the hierarchical Bayesian spatial modeling (HBSM) in a univariate and multivariate setting. These methods were used with and without introducing the Townsend index of socioeconomic deprivation known to be related to the distribution of cancer incidence. Incidence data stemmed from the Cancer Registry of Isère and were limited to prostate, lung, colon-rectum, and bladder cancers diagnosed between 1999 and 2007 in men only. The study found a spatial heterogeneity (p < 0.01) and an autocorrelation for prostate (EBI = 0.02; p = 0.001), lung (EBI = 0.01; p = 0.019) and bladder (EBI = 0.007; p = 0.05) cancers. After introduction of the Townsend index, SaTScan failed in finding cancers clusters. This introduction changed the results obtained with the other methods. SpODT identified five spatial classes (p < 0.05): four in the Western and one in the Northern parts of the study area (standardized incidence ratios: 1.68, 1.39, 1.14, 1.12, and 1.16, respectively). In the univariate setting, the Bayesian smoothing method found the same clusters as the two other methods (RR >1.2). The multivariate HBSM found a spatial correlation between lung and bladder cancers (r = 0.6). In spatial analysis of cancer incidence, SpODT and HBSM may be used not only for cluster detection but also for searching for confounding or etiological factors in small areas. Moreover, the multivariate HBSM offers a flexible and meaningful modeling of spatial variations; it shows plausible previously unknown associations between various cancers.
Aguirre-Gamboa, Raul; Trevino, Victor
2014-06-01
MicroRNAs (miRNAs) play a key role in post-transcriptional regulation of mRNA levels. Their function in cancer has been studied by high-throughput methods generating valuable sources of public information. Thus, miRNA signatures predicting cancer clinical outcomes are emerging. An important step to propose miRNA-based biomarkers before clinical validation is their evaluation in independent cohorts. Although it can be carried out using public data, such task is time-consuming and requires a specialized analysis. Therefore, to aid and simplify the evaluation of prognostic miRNA signatures in cancer, we developed SurvMicro, a free and easy-to-use web tool that assesses miRNA signatures from publicly available miRNA profiles using multivariate survival analysis. SurvMicro is composed of a wide and updated database of >40 cohorts in different tissues and a web tool where survival analysis can be done in minutes. We presented evaluations to portray the straightforward functionality of SurvMicro in liver and lung cancer. To our knowledge, SurvMicro is the only bioinformatic tool that aids the evaluation of multivariate prognostic miRNA signatures in cancer. SurvMicro and its tutorial are freely available at http://bioinformatica.mty.itesm.mx/SurvMicro. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Dolan, James G.; Boohaker, Emily; Allison, Jeroan; Imperiale, Thomas F.
2013-01-01
Background Current US colorectal cancer screening guidelines that call for shared decision making regarding the choice among several recommended screening options are difficult to implement. Multi-criteria decision analysis (MCDA) is an established methodology well suited for supporting shared decision making. Our study goal was to determine if a streamlined form of MCDA using rank order based judgments can accurately assess patients’ colorectal cancer screening priorities. Methods We converted priorities for four decision criteria and three sub-criteria regarding colorectal cancer screening obtained from 484 average risk patients using the Analytic Hierarchy Process (AHP) in a prior study into rank order-based priorities using rank order centroids. We compared the two sets of priorities using Spearman rank correlation and non-parametric Bland-Altman limits of agreement analysis. We assessed the differential impact of using the rank order-based versus the AHP-based priorities on the results of a full MCDA comparing three currently recommended colorectal cancer screening strategies. Generalizability of the results was assessed using Monte Carlo simulation. Results Correlations between the two sets of priorities for the seven criteria ranged from 0.55 to 0.92. The proportions of absolute differences between rank order-based and AHP-based priorities that were more than ± 0.15 ranged from 1% to 16%. Differences in the full MCDA results were minimal and the relative rankings of the three screening options were identical more than 88% of the time. The Monte Carlo simulation results were similar. Conclusion Rank order-based MCDA could be a simple, practical way to guide individual decisions and assess population decision priorities regarding colorectal cancer screening strategies. Additional research is warranted to further explore the use of these methods for promoting shared decision making. PMID:24300851
Nguyen, Bich-Lien; Tremblay, Dominique; Mathieu, Luc; Groleau, Danielle
2016-06-01
When dealing with health issues, older cancer patients are likely to visit emergency rooms (ER), which are known to expose these patients to the risk of adverse outcomes. Little is known about the profile and reasons for such visits. The aim of this study is (1) to describe the profile of elderly cancer patients aged 70 years and older who visited the ER of a regional hospital in Québec, Canada, and (2) to explain the medical reasons and factors determining such visits from the patients' perspective. A concurrent mixed method design was used. Descriptive analysis of administrative databases was conducted to describe the socio-demographic, clinical, and service utilization profile of 792 cancer patients aged 70 years and older. Content analysis of 11 semi-structured interviews of a sub-sample was subsequently performed to better understand the experience and meaning these patients attribute to this health behaviour. The sample of 792 older cancer patients made a total of 1572 ER visits. Most visits occurred during the daytime. More than half (53 %) of the patients were discharged, and close to 40 % were hospitalized. The most frequent reasons for consulting were respiratory (15.8 %), digestive (13.4 %), neurological (8.3 %), fever or infection-related (8.3 %), and cardiovascular (8.2 %). Content analysis of the qualitative data suggested that patients made ER visits mostly when other cancer care services were unavailable or because of a serious life-threatening health condition. The study suggests areas of improvement to prevent ER visits when health issues can be addressed by other care services.
Worksite Cancer Prevention Activities in the National Comprehensive Cancer Control Program
Nahmias, Zachary; Townsend, Julie S.; Neri, Antonio; Stewart, Sherri L.
2016-01-01
Background Workplaces are one setting for cancer control planners to reach adults at risk for cancer and other chronic diseases. However, the extent to which Centers for Disease Control and Prevention-funded National Comprehensive Cancer Control Programs (NCCCP) implement interventions in the workplace setting is not well characterized. Methods We conducted a qualitative content analysis of program action plans submitted by NCCCP grantees from 2013–2015 to identify and describe cancer prevention objectives and interventions in the workplace setting. Results Nearly half of NCCCP action reports contained at least one cancer prevention objective or intervention in the workplace setting. Common interventions included education about secondhand smoke exposure in the workplace, and the importance of obtaining colorectal cancer screening. Conclusion Workplace interventions were relatively common among NCCCP action plans, and serve as one way to address low percentages of CRC screening, and reduce risk for obesity- and tobacco-related cancers. PMID:26874944
Hu, Yuan Yuan; Yuan, Hua; Jiang, Guang Bing; Chen, Ning; Wen, Li; Leng, Wei Dong; Zeng, Xian Tao; Niu, Yu Ming
2012-01-01
Background To investigate the association between XPD Asp312Asn polymorphism and head and neck cancer risk through this meta-analysis. Methods We performed a meta-analysis of 9 published case-control studies including 2,670 patients with head and neck cancer and 4,452 controls. An odds ratio (OR) with a 95% confidence interval (CI) was applied to assess the association between XPD Asp312Asn polymorphism and head and neck cancer risk. Results Overall, no significant association between XPD Asp312Asn polymorphism and head and neck cancer risk was found in this meta-analysis (Asn/Asn vs. Asp/Asp: OR = 0.95, 95%CI = 0.80–1.13, P = 0.550, P heterogeneity = 0.126; Asp/Asn vs. Asp/Asp: OR = 1.11, 95%CI = 0.99–1.24, P = 0.065, P heterogeneity = 0.663; Asn/Asn+Asp/Asn vs. Asp/Asp: OR = 1.07, 95%CI = 0.97–1.19, P = 0.189, P heterogeneity = 0.627; Asn/Asn vs. Asp/Asp+Asp/Asn: OR = 0.87, 95%CI = 0.68–1.10, P = 0.243, P heterogeneity = 0.089). In the subgroup analysis by HWE, ethnicity, and study design, there was still no significant association detected in all genetic models. Conclusions This meta-analysis demonstrates that XPD Asp312Asn polymorphism may not be a risk factor for developing head and neck cancer. PMID:22536360
Chen, Zenggan; Yu, Yanmin
2013-01-01
Background CYP2C19 encodes a member of the cytochrome P450 superfamily of enzymes, which play a central role in activating and detoxifying many carcinogens and endogenous compounds thought to be involved in the development of cancer. In the past decade, two common polymorphisms among CYP2C19 (CYP2C19*2 and CYP2C19*3) that are responsible for the poor metabolizers (PMs) phenotype in humans and cancer susceptibility have been investigated extensively; however, these studies have yielded contradictory results. Methods and Results To investigate this inconsistency, we conducted a comprehensive meta-analysis of 11,554 cases and 16,592 controls from 30 case-control studies. Overall, the odds ratio (OR) of cancer was 1.52 [95% confidence interval (CI): 1.23–1.88, P<10-4] for CYP2C19 PMs genotypes. However, this significant association vanished when the analyses were restricted to 5 larger studies (no. of cases ≥ 500 cases). In the subgroup analysis for different cancer types, PMs genotypes had an effect of increasing the risks of esophagus cancer, gastric cancer, lung cancer and hepatocellular carcinoma as well as head neck cancer. Significant results were found in Asian populations when stratified by ethnicity; whereas no significant associations were found among Caucasians. Stratified analyses according to source of controls, significant associations were found only in hospital base controls. Conclusions Our meta-analysis suggests that the CYP2C19 PMs genotypes most likely contributes to cancer susceptibility, particularly in the Asian populations. PMID:24015291
Toyoshima, Osamu; Yamaji, Yutaka; Yoshida, Shuntaro; Matsumoto, Shuhei; Yamashita, Hiroharu; Kanazawa, Takamitsu; Hata, Keisuke
2017-05-01
Risk factors for gastric cancer during continuous infection with Helicobacter pylori have been well documented; however, little has been reported on the risk factors for primary gastric cancer after H. pylori eradication. We conducted a retrospective, endoscopy-based, long-term, large-cohort study to clarify the risk factors for gastric cancer following H. pylori eradication. Patients who achieved successful H. pylori eradication and periodically underwent esophagogastroduodenoscopy surveillance thereafter at Toyoshima Endoscopy Clinic were enrolled. The primary endpoint was the development of gastric cancer. Statistical analysis was performed using the Kaplan-Meier method and Cox's proportional hazards models. Gastric cancer developed in 15 of 1232 patients. The cumulative incidence rates were 1.0 % at 2 years, 2.6 % at 5 years, and 6.8 % at 10 years. Histology showed that all gastric cancers (17 lesions) in the 15 patients were of the intestinal type, within the mucosal layer, and <20 mm in diameter. Based on univariate analysis, older age and higher endoscopic grade of gastric atrophy were significantly associated with gastric cancer development after eradication of H. pylori, and gastric ulcers were marginally associated. Multivariate analysis identified higher grade of gastric atrophy (hazard ratio 1.77; 95 % confidence interval 1.12-2.78; P = 0.01) as the only independently associated parameter. Endoscopic gastric atrophy is a major risk factor for gastric cancer development after H. pylori eradication. Further long-term studies are required to determine whether H. pylori eradication leads to regression of H. pylori-related gastritis and reduces the risk of gastric cancer.
Chen, X; Wang, K; Chen, W; Jiang, H; Deng, P C; Li, Z J; Peng, J; Zhou, Z Y; Yang, H; Huang, G X; Zeng, J
2016-07-01
By combining the metabolomics and computational biology, to explore the relationship between metabolic phenotype and pathological stage in esophageal cancer patients, to find the mechanism of metabolic network disturbance and develop a new method for fast preoperative clinical staging. A prospective cohort study (from April 2013 to January 2016) was conducted. The preoperative patients from Sichuan Provincial People's Hospital, who were diagnosed with esophageal cancer from May 2013 to April 2014 were included, and their serum samples were collected to detect (1)H-nuclear magnetic resonance (NMR) metabolomics for the purpose of drawing the metabolic fingerprinting in different stages of patients with esophageal cancer. The data were processed with these methods-principal components analysis: partial least squares regression and support vector machine, for the exploration of the enzyme-gene network regulatory mechanism in abnormal esophageal cancer metabolic network regulation and to build the quantitative prediction model of esophageal cancer staging in the end. All data were processed on high-performance computing platforms Matalab. The comparison of data had used Wilcoxon test, variance analysis, χ(2) test and Fisher exact test. Twenty patients with different stages of esophageal cancer were included; and their serum metabolic fingerprinting could differentiate different tumor stages. There were no difference among the five teams in the age (F=1.086, P>0.05), the body mass index (F=1.035, P>0.05), the distance from the incisors to tumor (F=1.078, P>0.05). Among the patients with different TNM stages, there was a significant difference in plasma metabolome. Compared to ⅡB, ⅢA, Ⅳstage patients, increased levels of butanone, ethanol amine, homocysteine, hydroxy acids and estriol, together with decreased levels of glycoprotein, creatine, choline, isobutyricacid, alanine, leucine, valine, were observed inⅠB, ⅡA stage patients. Four metabolic markers (ethanol amine, hydroxy-propionic acid, homocysteine and estriol) were eventually selected. gene ontology analysis showed that 54 enzymes and genes regulated the 4 key metabolic markers. The quantitative prediction model of esophageal cancer staging based on esophageal cancer NMR spectrum were established. Cross-validation results showed that the predicted effect was good (root mean square error=5.3, R(2)=0.47, P=0.036). The systems biology approaches based on metabolomics and enzyme-gene regulatory network analysis can be used to quantify the metabolic network disturbance of patients with advanced esophageal cancer, and to predict preoperative clinical staging of esophageal cancer patients by plasma NMR metabolomics.
A study of the breast cancer dynamics in North Carolina.
Christakos, G; Lai, J J
1997-11-01
This work is concerned with the study of breast cancer incidence in the State of North Carolina. Methodologically, the current analysis illustrates the importance of spatiotemporal random field modelling and introduces a mode of reasoning that is based on a combination of inductive and deductive processes. The composite space/time analysis utilizes the variability characteristics of incidence and the mathematical features of the random field model to fit it to the data. The analysis is significantly general and can efficiently represent non-homogeneous and non-stationary characteristics of breast cancer variation. Incidence predictions are produced using data at the same time period as well as data from other time periods and disease registries. The random field provides a rigorous and systematic method for generating detailed maps, which offer a quantitative description of the incidence variation from place to place and from time to time, together with a measure of the accuracy of the incidence maps. Spatiotemporal mapping accounts for the geographical locations and the time instants of the incidence observations, which is not usually the case with most empirical Bayes methods. It is also more accurate than purely spatial statistics methods, and can offer valuable information about the breast cancer risk and dynamics in North Carolina. Field studies could be initialized in high-rate areas identified by the maps in an effort to uncover environmental or life-style factors that might be responsible for the high risk rates. Also, the incidence maps can help elucidate causal mechanisms, explain disease occurrences at a certain scale, and offer guidance in health management and administration.
Sample entropy analysis of cervical neoplasia gene-expression signatures
Botting, Shaleen K; Trzeciakowski, Jerome P; Benoit, Michelle F; Salama, Salama A; Diaz-Arrastia, Concepcion R
2009-01-01
Background We introduce Approximate Entropy as a mathematical method of analysis for microarray data. Approximate entropy is applied here as a method to classify the complex gene expression patterns resultant of a clinical sample set. Since Entropy is a measure of disorder in a system, we believe that by choosing genes which display minimum entropy in normal controls and maximum entropy in the cancerous sample set we will be able to distinguish those genes which display the greatest variability in the cancerous set. Here we describe a method of utilizing Approximate Sample Entropy (ApSE) analysis to identify genes of interest with the highest probability of producing an accurate, predictive, classification model from our data set. Results In the development of a diagnostic gene-expression profile for cervical intraepithelial neoplasia (CIN) and squamous cell carcinoma of the cervix, we identified 208 genes which are unchanging in all normal tissue samples, yet exhibit a random pattern indicative of the genetic instability and heterogeneity of malignant cells. This may be measured in terms of the ApSE when compared to normal tissue. We have validated 10 of these genes on 10 Normal and 20 cancer and CIN3 samples. We report that the predictive value of the sample entropy calculation for these 10 genes of interest is promising (75% sensitivity, 80% specificity for prediction of cervical cancer over CIN3). Conclusion The success of the Approximate Sample Entropy approach in discerning alterations in complexity from biological system with such relatively small sample set, and extracting biologically relevant genes of interest hold great promise. PMID:19232110
Zhou, Huaqiang; Huang, Yan; Qiu, Zeting; Zhao, Hongyun; Fang, Wenfeng; Yang, Yunpeng; Zhao, Yuanyuan; Hou, Xue; Ma, Yuxiang; Hong, Shaodong; Zhou, Ting; Zhang, Yaxiong; Zhang, Li
2018-04-18
The population of cancer survivors with prior cancer is rapidly growing. Whether a prior cancer diagnosis interferes with outcome is unknown. We conducted a pan-cancer analysis to determine the impact of prior cancer history for patients newly diagnosed with cancer. We identified 20 types of primary solid tumors between 2004 and 2008 in the Surveillance, Epidemiology, and End Results database. Demographic and clinicopathologic variables were compared by χ 2 test and t-test as appropriate. The propensity score-adjusted Kaplan-Meier method and Cox proportional hazards models were used to evaluate the impact of prior cancer on overall survival (OS). Among 1,557,663 eligible patients, 261,474 (16.79%) had a history of prior cancer. More than 65% of prior cancers were diagnosed within 5 years. We classified 20 cancer sites into two groups (PCI and PCS) according to the different impacts of prior cancer on OS. PCI patients with a prior cancer history, which involved the colon and rectum, bone and soft tissues, melanoma, breast, cervix uteri, corpus and uterus, prostate, urinary bladder, kidney and renal pelvis, eye and orbits, thyroid, had inferior OS. The PCS patients (nasopharynx, esophagus, stomach, liver, gallbladder, pancreas, lung, ovary and brain) with a prior cancer history showed similar OS to that of patients without prior cancer. Our pan-cancer study presents the landscape for the survival impact of prior cancer across 20 cancer types. Compared to the patients without prior cancer, the PCI group had inferior OS, while the PCS group had similar OS. Further studies are still needed. © 2018 UICC.
Ray, Partha; Rialon-Guevara, Kristy L.; Veras, Emanuela; Sullenger, Bruce A.; White, Rebekah R.
2012-01-01
Most cases of pancreatic cancer are not diagnosed until they are no longer curable with surgery. Therefore, it is critical to develop a sensitive, preferably noninvasive, method for detecting the disease at an earlier stage. In order to identify biomarkers for pancreatic cancer, we devised an in vitro positive/negative selection strategy to identify RNA ligands (aptamers) that could detect structural differences between the secretomes of pancreatic cancer and non-cancerous cells. Using this molecular recognition approach, we identified an aptamer (M9-5) that differentially bound conditioned media from cancerous and non-cancerous human pancreatic cell lines. This aptamer further discriminated between the sera of pancreatic cancer patients and healthy volunteers with high sensitivity and specificity. We utilized biochemical purification methods and mass-spectrometric analysis to identify the M9-5 target as cyclophilin B (CypB). This molecular recognition–based strategy simultaneously identified CypB as a serum biomarker and generated a new reagent to recognize it in body fluids. Moreover, this approach should be generalizable to other diseases and complementary to traditional approaches that focus on differences in expression level between samples. Finally, we suggest that the aptamer we identified has the potential to serve as a tool for the early detection of pancreatic cancer. PMID:22484812
Ray, Partha; Rialon-Guevara, Kristy L; Veras, Emanuela; Sullenger, Bruce A; White, Rebekah R
2012-05-01
Most cases of pancreatic cancer are not diagnosed until they are no longer curable with surgery. Therefore, it is critical to develop a sensitive, preferably noninvasive, method for detecting the disease at an earlier stage. In order to identify biomarkers for pancreatic cancer, we devised an in vitro positive/negative selection strategy to identify RNA ligands (aptamers) that could detect structural differences between the secretomes of pancreatic cancer and non-cancerous cells. Using this molecular recognition approach, we identified an aptamer (M9-5) that differentially bound conditioned media from cancerous and non-cancerous human pancreatic cell lines. This aptamer further discriminated between the sera of pancreatic cancer patients and healthy volunteers with high sensitivity and specificity. We utilized biochemical purification methods and mass-spectrometric analysis to identify the M9-5 target as cyclophilin B (CypB). This molecular recognition-based strategy simultaneously identified CypB as a serum biomarker and generated a new reagent to recognize it in body fluids. Moreover, this approach should be generalizable to other diseases and complementary to traditional approaches that focus on differences in expression level between samples. Finally, we suggest that the aptamer we identified has the potential to serve as a tool for the early detection of pancreatic cancer.
Diagnosis of skin cancer by correlation and complexity analyses of damaged DNA
Namazi, Hamidreza; Kulish, Vladimir V.; Delaviz, Fatemeh; Delaviz, Ali
2015-01-01
Skin cancer is a common, low-grade cancerous (malignant) growth of the skin. It starts from cells that begin as normal skin cells and transform into those with the potential to reproduce in an out-of-control manner. Cancer develops when DNA, the molecule found in cells that encodes genetic information, becomes damaged and the body cannot repair the damage. A DNA walk of a genome represents how the frequency of each nucleotide of a pairing nucleotide couple changes locally. In this research in order to diagnose the skin cancer, first DNA walk plots of genomes of patients with skin cancer were generated. Then, the data so obtained was checked for complexity by computing the fractal dimension. Furthermore, the Hurst exponent has been employed in order to study the correlation of damaged DNA. By analysing different samples it has been found that the damaged DNA sequences are exhibiting higher degree of complexity and less correlation compared to normal DNA sequences. This investigation confirms that this method can be used for diagnosis of skin cancer. The method discussed in this research is useful not only for diagnosis of skin cancer but can be applied for diagnosis and growth analysis of different types of cancers. PMID:26497203
Flow Cytometric Methods for Circulating Tumor Cell Isolation and Molecular Analysis.
Bhagwat, Neha; Carpenter, Erica L
2017-01-01
Circulating tumor cells provide a non-invasive source of tumor material that can be valuable at all stages of disease management, including screening and early diagnosis, monitoring response to therapy, identifying therapeutic targets, and assessing development of drug resistance. Cells isolated from the blood of cancer patients can be used for phenotypic analysis, tumor genotyping, transcriptional profiling, as well as for ex vivo culture of isolated cells. There are a variety of novel technologies currently being developed for the detection and analysis of rare cells in circulation of cancer patients. Flow cytometry is a powerful cell analysis platform that is increasingly being used in this field of study due to its relatively high throughput and versatility with respect to the large number of commercially available antibodies and fluorescent probes available to translational and clinical researchers. More importantly, it offers the ability to easily recover viable cells with high purity that are suitable for downstream molecular analysis, thus making it an attractive technology for cancer research and as a diagnostic tool.
Mooney, Ryan; Samhouri, Mahasen; Holton, Avery; Devine, Katie A.; Kirchhoff, Anne C.; Wright, Jennifer
2017-01-01
Purpose: To explore adolescent and young adult (AYA) cancer survivors' internet use in seeking healthy lifestyle behavior (HLB) information on diet and exercise. Methods: Twenty-five AYA cancer survivors participated in focus groups or interviews. Data were analyzed using qualitative content analysis. Results: Most survivors (92%) sought HLB information from internet sources. Key issues included the following: (1) too much information available, (2) information not meeting survivors' unique needs, and (3) concerns about trustworthiness of information. Conclusion: Although AYA cancer survivors use the internet to seek HLB information, internet resources could be modified to better meet the needs of AYA cancer survivors. PMID:27845844
Prostate cancer region prediction using MALDI mass spectra
NASA Astrophysics Data System (ADS)
Vadlamudi, Ayyappa; Chuang, Shao-Hui; Sun, Xiaoyan; Cazares, Lisa; Nyalwidhe, Julius; Troyer, Dean; Semmes, O. John; Li, Jiang; McKenzie, Frederic D.
2010-03-01
For the early detection of prostate cancer, the analysis of the Prostate-specific antigen (PSA) in serum is currently the most popular approach. However, previous studies show that 15% of men have prostate cancer even their PSA concentrations are low. MALDI Mass Spectrometry (MS) proves to be a better technology to discover molecular tools for early cancer detection. The molecular tools or peptides are termed as biomarkers. Using MALDI MS data from prostate tissue samples, prostate cancer biomarkers can be identified by searching for molecular or molecular combination that can differentiate cancer tissue regions from normal ones. Cancer tissue regions are usually identified by pathologists after examining H&E stained histological microscopy images. Unfortunately, histopathological examination is currently done on an adjacent slice because the H&E staining process will change tissue's protein structure and it will derogate MALDI analysis if the same tissue is used, while the MALDI imaging process will destroy the tissue slice so that it is no longer available for histopathological exam. For this reason, only the most confident cancer region resulting from the histopathological examination on an adjacent slice will be used to guide the biomarker identification. It is obvious that a better cancer boundary delimitation on the MALDI imaging slice would be beneficial. In this paper, we proposed methods to predict the true cancer boundary, using the MALDI MS data, from the most confident cancer region given by pathologists on an adjacent slice.
Medical cost analysis: application to colorectal cancer data from the SEER Medicare database.
Bang, Heejung
2005-10-01
Incompleteness is a key feature of most survival data. Numerous well established statistical methodologies and algorithms exist for analyzing life or failure time data. However, induced censorship invalidates the use of those standard analytic tools for some survival-type data such as medical costs. In this paper, some valid methods currently available for analyzing censored medical cost data are reviewed. Some cautionary findings under different assumptions are envisioned through application to medical costs from colorectal cancer patients. Cost analysis should be suitably planned and carefully interpreted under various meaningful scenarios even with judiciously selected statistical methods. This approach would be greatly helpful to policy makers who seek to prioritize health care expenditures and to assess the elements of resource use.
Gu, Zhan; Qi, Xiuzhong; Zhai, Xiaofeng; Lang, Qingbo; Lu, Jianying; Ma, Changping; Liu, Long; Yue, Xiaoqiang
2015-01-01
Primary liver cancer (PLC) is one of the most common malignant tumors because of its high incidence and high mortality. Traditional Chinese medicine (TCM) plays an active role in the treatment of PLC. As the most important part in the TCM system, syndrome differentiation based on the clinical manifestations from traditional four diagnostic methods has met great challenges and questions with the lack of statistical validation support. In this study, we provided evidences for TCM syndrome differentiation of PLC using the method of analysis of latent structural model from clinic data, thus providing basis for establishing TCM syndrome criteria. And also we obtain the common syndromes of PLC as well as their typical clinical manifestations, respectively.
Jang, Min Hye; Kim, Hyun Jung; Chung, Yul Ri; Lee, Yangkyu
2017-01-01
In spite of the usefulness of the Ki-67 labeling index (LI) as a prognostic and predictive marker in breast cancer, its clinical application remains limited due to variability in its measurement and the absence of a standard method of interpretation. This study was designed to compare the two methods of assessing Ki-67 LI: the average method vs. the hot spot method and thus to determine which method is more appropriate in predicting prognosis of luminal/HER2-negative breast cancers. Ki-67 LIs were calculated by direct counting of three representative areas of 493 luminal/HER2-negative breast cancers using the two methods. We calculated the differences in the Ki-67 LIs (ΔKi-67) between the two methods and the ratio of the Ki-67 LIs (H/A ratio) of the two methods. In addition, we compared the performance of the Ki-67 LIs obtained by the two methods as prognostic markers. ΔKi-67 ranged from 0.01% to 33.3% and the H/A ratio ranged from 1.0 to 2.6. Based on the receiver operating characteristic curve method, the predictive powers of the KI-67 LI measured by the two methods were similar (Area under curve: hot spot method, 0.711; average method, 0.700). In multivariate analysis, high Ki-67 LI based on either method was an independent poor prognostic factor, along with high T stage and node metastasis. However, in repeated counts, the hot spot method did not consistently classify tumors into high vs. low Ki-67 LI groups. In conclusion, both the average and hot spot method of evaluating Ki-67 LI have good predictive performances for tumor recurrence in luminal/HER2-negative breast cancers. However, we recommend using the average method for the present because of its greater reproducibility. PMID:28187177
Jang, Min Hye; Kim, Hyun Jung; Chung, Yul Ri; Lee, Yangkyu; Park, So Yeon
2017-01-01
In spite of the usefulness of the Ki-67 labeling index (LI) as a prognostic and predictive marker in breast cancer, its clinical application remains limited due to variability in its measurement and the absence of a standard method of interpretation. This study was designed to compare the two methods of assessing Ki-67 LI: the average method vs. the hot spot method and thus to determine which method is more appropriate in predicting prognosis of luminal/HER2-negative breast cancers. Ki-67 LIs were calculated by direct counting of three representative areas of 493 luminal/HER2-negative breast cancers using the two methods. We calculated the differences in the Ki-67 LIs (ΔKi-67) between the two methods and the ratio of the Ki-67 LIs (H/A ratio) of the two methods. In addition, we compared the performance of the Ki-67 LIs obtained by the two methods as prognostic markers. ΔKi-67 ranged from 0.01% to 33.3% and the H/A ratio ranged from 1.0 to 2.6. Based on the receiver operating characteristic curve method, the predictive powers of the KI-67 LI measured by the two methods were similar (Area under curve: hot spot method, 0.711; average method, 0.700). In multivariate analysis, high Ki-67 LI based on either method was an independent poor prognostic factor, along with high T stage and node metastasis. However, in repeated counts, the hot spot method did not consistently classify tumors into high vs. low Ki-67 LI groups. In conclusion, both the average and hot spot method of evaluating Ki-67 LI have good predictive performances for tumor recurrence in luminal/HER2-negative breast cancers. However, we recommend using the average method for the present because of its greater reproducibility.
Liang, Yong; Chai, Hua; Liu, Xiao-Ying; Xu, Zong-Ben; Zhang, Hai; Leung, Kwong-Sak
2016-03-01
One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles. Both Cox proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients' clinical treatment. Nevertheless, two main dilemmas limit the accuracy of these prediction methods. One is that the small sample size and censored data remain a bottleneck for training robust and accurate Cox classification model. In addition to that, similar phenotype tumours and prognoses are actually completely different diseases at the genotype and molecular level. Thus, the utility of the AFT model for the survival time prediction is limited when such biological differences of the diseases have not been previously identified. To try to overcome these two main dilemmas, we proposed a novel semi-supervised learning method based on the Cox and AFT models to accurately predict the treatment risk and the survival time of the patients. Moreover, we adopted the efficient L1/2 regularization approach in the semi-supervised learning method to select the relevant genes, which are significantly associated with the disease. The results of the simulation experiments show that the semi-supervised learning model can significant improve the predictive performance of Cox and AFT models in survival analysis. The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets. The advantages of our proposed semi-supervised learning method include: 1) significantly increase the available training samples from censored data; 2) high capability for identifying the survival risk classes of patient in Cox model; 3) high predictive accuracy for patients' survival time in AFT model; 4) strong capability of the relevant biomarker selection. Consequently, our proposed semi-supervised learning model is one more appropriate tool for survival analysis in clinical cancer research.
Gupta, Shalini; Singh, Rajender; Gupta, O. P.; Tripathi, Anurag
2014-01-01
Background: Oral cancer is one of the most common life-threatening diseases all over the world. Developing countries face several challenges to identify and remove potential risk factors. Chewing tobacco/pan masala is considered to be the most potent risk factor for oral precancerous lesions and oral cancer. Objectives: To investigate the relative occurrence of different oral pre-cancerous lesions and oral cancer in North India and to identify the associated risk factors. Materials and Methods: A hospital-based study was conducted and 471 subjects were recruited in the study. The subjects comprised patients with squamous cell carcinoma (n = 85), oral submucous fibrosis (n = 240), leukoplakia (n = 32), lichen planus (n = 15), and controls (n = 99). Statistical analysis of the data was done using Chi-square and regression analysis. Results: A strong correlation was observed between the presence of the chewing habit in all the oral precancerous lesions and oral cancer. Duration of the habit and intensity of habit ware also strongly correlated with the risk of oral precancerous lesions and oral cancer. Other factors such as alcohol and smoking were found to be less important in concern with oral cancer and precancerous lesions. PMID:25937723
Reliability and Validity Study of a Tool to Measure Cancer Stigma: Patient Version
Yılmaz, Medine; Dişsiz, Gülçin; Demir, Filiz; Irız, Sibel; Alacacioglu, Ahmet
2017-01-01
Objective: The aim of this methodological study is to establish the validity and reliability of the Turkish version of “A Questionnaire for Measuring Attitudes toward Cancer (Cancer Stigma) - Patient version.” Methods: The sample comprised oncology patients who had active cancer treatment. The construct validity was assessed using the confirmatory and exploratory factor analysis. Results: The mean age of the participants was 54.9±12.3 years. In the confirmatory factor analysis, fit values were determined as comparative fit index = 0.93, goodness of fit index = 0.91, normed-fit index=0.91, and root mean square error of approximation RMSEA = 0.09 (P <0.05) (Kaiser–Meyer–Olkin = 0.88, χ2 = 1084.41, Df = 66, and Barletta's test P <0.000). The first factor was “impossibility of recovery and experience of social discrimination” and the second factor was “stereotypes of cancer patients.” The two-factor structure accounted for 56.74% of the variance. The Cronbach's alpha value was determined as 0.88 for the two-factor scale. Conclusions: “A questionnaire for measuring attitudes toward cancer (cancer stigma) - Patient version” is a reliable and valid questionnaire to assess stigmatization of cancer in cancer patients. PMID:28503649
Bollig-Fischer, Aliccia; Michelhaugh, Sharon K.; Wijesinghe, Priyanga; Dyson, Greg; Kruger, Adele; Palanisamy, Nallasivam; Choi, Lydia; Alosh, Baraa; Ali-Fehmi, Rouba; Mittal, Sandeep
2015-01-01
Breast cancer brain metastases remain a significant clinical problem. Chemotherapy is ineffective and a lack of treatment options result in poor patient outcomes. Targeted therapeutics have proven to be highly effective in primary breast cancer, but lack of molecular genomic characterization of metastatic brain tumors is hindering the development of new treatment regimens. Here we contribute to fill this void by reporting on gene copy number variation (CNV) in 10 breast cancer metastatic brain tumors, assayed by array comparative genomic hybridization (aCGH). Results were compared to a list of cancer genes verified by others to influence cancer. Cancer gene aberrations were identified in all specimens and pathway-level analysis was applied to aggregate data, which identified stem cell pluripotency pathway enrichment and highlighted recurring, significant amplification of SOX2, PIK3CA, NTRK1, GNAS, CTNNB1, and FGFR1. For a subset of the metastatic brain tumor samples (n=4) we compared patient-matched primary breast cancer specimens. The results of our CGH analysis and validation by alternative methods indicate that oncogenic signals driving growth of metastatic tumors exist in the original cancer. This report contributes support for more rapid development of new treatments of metastatic brain tumors, the use of genomic-based diagnostic tools and repurposed drug treatments. PMID:25970776
Bollig-Fischer, Aliccia; Michelhaugh, Sharon K; Wijesinghe, Priyanga; Dyson, Greg; Kruger, Adele; Palanisamy, Nallasivam; Choi, Lydia; Alosh, Baraa; Ali-Fehmi, Rouba; Mittal, Sandeep
2015-06-10
Breast cancer brain metastases remain a significant clinical problem. Chemotherapy is ineffective and a lack of treatment options result in poor patient outcomes. Targeted therapeutics have proven to be highly effective in primary breast cancer, but lack of molecular genomic characterization of metastatic brain tumors is hindering the development of new treatment regimens. Here we contribute to fill this void by reporting on gene copy number variation (CNV) in 10 breast cancer metastatic brain tumors, assayed by array comparative genomic hybridization (aCGH). Results were compared to a list of cancer genes verified by others to influence cancer. Cancer gene aberrations were identified in all specimens and pathway-level analysis was applied to aggregate data, which identified stem cell pluripotency pathway enrichment and highlighted recurring, significant amplification of SOX2, PIK3CA, NTRK1, GNAS, CTNNB1, and FGFR1. For a subset of the metastatic brain tumor samples (n = 4) we compared patient-matched primary breast cancer specimens. The results of our CGH analysis and validation by alternative methods indicate that oncogenic signals driving growth of metastatic tumors exist in the original cancer. This report contributes support for more rapid development of new treatments of metastatic brain tumors, the use of genomic-based diagnostic tools and repurposed drug treatments.
High Incidence of Breast Cancer in Light-Polluted Areas with Spatial Effects in Korea.
Kim, Yun Jeong; Park, Man Sik; Lee, Eunil; Choi, Jae Wook
2016-01-01
We have reported a high prevalence of breast cancer in light-polluted areas in Korea. However, it is necessary to analyze the spatial effects of light polluted areas on breast cancer because light pollution levels are correlated with region proximity to central urbanized areas in studied cities. In this study, we applied a spatial regression method (an intrinsic conditional autoregressive [iCAR] model) to analyze the relationship between the incidence of breast cancer and artificial light at night (ALAN) levels in 25 regions including central city, urbanized, and rural areas. By Poisson regression analysis, there was a significant correlation between ALAN, alcohol consumption rates, and the incidence of breast cancer. We also found significant spatial effects between ALAN and the incidence of breast cancer, with an increase in the deviance information criterion (DIC) from 374.3 to 348.6 and an increase in R2 from 0.574 to 0.667. Therefore, spatial analysis (an iCAR model) is more appropriate for assessing ALAN effects on breast cancer. To our knowledge, this study is the first to show spatial effects of light pollution on breast cancer, despite the limitations of an ecological study. We suggest that a decrease in ALAN could reduce breast cancer more than expected because of spatial effects.
Automated image based prominent nucleoli detection
Yap, Choon K.; Kalaw, Emarene M.; Singh, Malay; Chong, Kian T.; Giron, Danilo M.; Huang, Chao-Hui; Cheng, Li; Law, Yan N.; Lee, Hwee Kuan
2015-01-01
Introduction: Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Materials and Methods: Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. Results: The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Conclusions: Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings. PMID:26167383
Häggström, Christel; Van Hemelrijck, Mieke; Garmo, Hans; Robinson, David; Stattin, Pär; Rowley, Mark; Coolen, Anthony C C; Holmberg, Lars
2018-05-09
Most previous studies of prostate cancer have not taken into account that men in the studied populations are also at risk of competing event, and that these men may have different susceptibility to prostate cancer risk. The aim of this study was to investigate heterogeneity in risk of prostate cancer, using a recently developed latent class regression method for competing risks. We further aimed to elucidate the association between type 2 diabetes mellitus (T2DM) and prostate cancer risk, and to compare the results with conventional methods for survival analysis. We analysed the risk of prostate cancer in 126,482 men from the comparison cohort of the Prostate Cancer Data base Sweden (PCBaSe) 3.0. During a mean follow-up of 6 years 6,036 men were diagnosed with prostate cancer and 22,393 men died. We detected heterogeneity in risk of prostate cancer with two distinct latent classes in the study population. The smaller class included 9% of the study population in which men had a higher risk of prostate cancer and the risk was stronger associated with class membership than any of the covariates included in the study. Moreover, we found no association between T2DM and risk of prostate cancer after removal of the effect of informative censoring due to competing risks. The recently developed latent class for competing risks method could be used to provide new insights in precision medicine with the target to classify individuals regarding different susceptibility to a particular disease, reaction to a risk factor or response to treatment. This article is protected by copyright. All rights reserved. © 2018 UICC.
Edwards, Lynn Barbara; Greeff, Linda Estelle
2017-01-01
Introduction Cancer is an important health problem in Africa with projections that incidence could double by 2030. While sparse, the literature on cancer control in African low- and middle-income countries suggests poor cancer planning, overburdened services and poor outcomes. South Africa has established oncology health care services but also has low cancer awareness, poor cancer surveillance and widespread service challenges. Methods Data for this study was derived from 316 photovoice interviews with cancer patients, families of cancer patients and oncology workers across South Africa. The objectives of the study were to collect first-hand feedback about cancer challenges and to develop recommendations for the improvement of cancer control strategies. Results 9 themes of cancer challenges were distinguished via thematic content analysis of the photo-narratives. The identified themes of cancer challenges were physical and treatment challenges, emotional, poor services, transport, finances, information, powerlessness, stigma, and schooling challenges. Conclusion The findings of this study offer the patient and family perspective of cancer challenges as a valid contribution to our body of cancer knowledge. The 9 themes of cancer challenges profile the emotional, physical and social impact of cancer on patients and families, and offer detailed subjective information about problem occurrence in the trajectory of care. Recommendations following from the 9 themes of cancer challenges include training for improved patient-centred care standards, the need for cancer surveillance, innovative and locally appropriate cancer awareness campaigns, private and government health care partnerships and the development of psychosocial services. The advocating of findings and recommendations to influence cancer control strategies in South Africa, is indicated. PMID:29541319
Rodgers, Jacqui; Martin, Colin R; Morse, Rachel C; Kendell, Kate; Verrill, Mark
2005-01-01
Background To determine the psychometric properties of the Hospital Anxiety and Depression Scale (HADS) in patients with breast cancer and determine the suitability of the instrument for use with this clinical group. Methods A cross-sectional design was used. The study used a pooled data set from three breast cancer clinical groups. The dependent variables were HADS anxiety and depression sub-scale scores. Exploratory and confirmatory factor analyses were conducted on the HADS to determine its psychometric properties in 110 patients with breast cancer. Seven models were tested to determine model fit to the data. Results Both factor analysis methods indicated that three-factor models provided a better fit to the data compared to two-factor (anxiety and depression) models for breast cancer patients. Clark and Watson's three factor tripartite and three factor hierarchical models provided the best fit. Conclusion The underlying factor structure of the HADS in breast cancer patients comprises three distinct, but correlated factors, negative affectivity, autonomic anxiety and anhedonic depression. The clinical utility of the HADS in screening for anxiety and depression in breast cancer patients may be enhanced by using a modified scoring procedure based on a three-factor model of psychological distress. This proposed alternate scoring method involving regressing autonomic anxiety and anhedonic depression factors onto the third factor (negative affectivity) requires further investigation in order to establish its efficacy. PMID:16018801
2014-01-01
Background Physical activity has been inversely associated with risk of several cancers. We performed a systematic review and meta-analysis to evaluate the association between physical activity and risk of esophageal cancer (esophageal adenocarcinoma [EAC] and/or esophageal squamous cell carcinoma [ESCC]). Methods We conducted a comprehensive search of bibliographic databases and conference proceedings from inception through February 2013 for observational studies that examined associations between recreational and/or occupational physical activity and esophageal cancer risk. Summary adjusted odds ratio (OR) estimates with 95% confidence intervals (CI) were estimated using the random-effects model. Results The analysis included 9 studies (4 cohort, 5 case–control) reporting 1,871 cases of esophageal cancer among 1,381,844 patients. Meta-analysis demonstrated that the risk of esophageal cancer was 29% lower among the most physically active compared to the least physically active subjects (OR, 0.71; 95% CI, 0.57-0.89), with moderate heterogeneity (I2 = 47%). On histology-specific analysis, physical activity was associated with a 32% decreased risk of EAC (4 studies, 503 cases of EAC; OR, 0.68; 95% CI, 0.55-0.85) with minimal heterogeneity (I2 = 0%). There were only 3 studies reporting the association between physical activity and risk of ESCC with conflicting results, and the meta-analysis demonstrated a null association (OR, 1.10; 95% CI, 0.21-5.64). The results were consistent across study design, geographic location and study quality, with a non-significant trend towards a dose–response relationship. Conclusions Meta-analysis of published observational studies indicates that physical activity may be associated with reduced risk of esophageal adenocarcinoma. Lifestyle interventions focusing on increasing physical activity may decrease the global burden of EAC. PMID:24886123
Highly sensitive detection of DNA methylation levels by using a quantum dot-based FRET method
NASA Astrophysics Data System (ADS)
Ma, Yunfei; Zhang, Honglian; Liu, Fangming; Wu, Zhenhua; Lu, Shaohua; Jin, Qinghui; Zhao, Jianlong; Zhong, Xinhua; Mao, Hongju
2015-10-01
DNA methylation is the most frequently studied epigenetic modification that is strongly involved in genomic stability and cellular plasticity. Aberrant changes in DNA methylation status are ubiquitous in human cancer and the detection of these changes can be informative for cancer diagnosis. Herein, we reported a facile quantum dot-based (QD-based) fluorescence resonance energy transfer (FRET) technique for the detection of DNA methylation. The method relies on methylation-sensitive restriction enzymes for the differential digestion of genomic DNA based on its methylation status. Digested DNA is then subjected to PCR amplification for the incorporation of Alexa Fluor-647 (A647) fluorophores. DNA methylation levels can be detected qualitatively through gel analysis and quantitatively by the signal amplification from QDs to A647 during FRET. Furthermore, the methylation levels of three tumor suppressor genes, PCDHGB6, HOXA9 and RASSF1A, in 20 lung adenocarcinoma and 20 corresponding adjacent nontumorous tissue (NT) samples were measured to verify the feasibility of the QD-based FRET method and a high sensitivity for cancer detection (up to 90%) was achieved. Our QD-based FRET method is a convenient, continuous and high-throughput method, and is expected to be an alternative for detecting DNA methylation as a biomarker for certain human cancers.DNA methylation is the most frequently studied epigenetic modification that is strongly involved in genomic stability and cellular plasticity. Aberrant changes in DNA methylation status are ubiquitous in human cancer and the detection of these changes can be informative for cancer diagnosis. Herein, we reported a facile quantum dot-based (QD-based) fluorescence resonance energy transfer (FRET) technique for the detection of DNA methylation. The method relies on methylation-sensitive restriction enzymes for the differential digestion of genomic DNA based on its methylation status. Digested DNA is then subjected to PCR amplification for the incorporation of Alexa Fluor-647 (A647) fluorophores. DNA methylation levels can be detected qualitatively through gel analysis and quantitatively by the signal amplification from QDs to A647 during FRET. Furthermore, the methylation levels of three tumor suppressor genes, PCDHGB6, HOXA9 and RASSF1A, in 20 lung adenocarcinoma and 20 corresponding adjacent nontumorous tissue (NT) samples were measured to verify the feasibility of the QD-based FRET method and a high sensitivity for cancer detection (up to 90%) was achieved. Our QD-based FRET method is a convenient, continuous and high-throughput method, and is expected to be an alternative for detecting DNA methylation as a biomarker for certain human cancers. Electronic supplementary information (ESI) available: Synthesis of CdSe/CdS/ZnS core/shell/shell QDs. Sequences of primers used for amplifying the promoter regions in bisulfate-modified DNA. Comparison of detected methylation levels in different gene promoters using the QD-based FRET method versus bisulfite pyrosequencing. Methylation levels of the RASSF1A gene in one pair of NT and cancer samples as indicated by pyrosequencing. Theoretical calculation of the Förster distance R0. See DOI: 10.1039/c5nr04956c
Cheng, Ming-Jun; Cao, Yun-Gui
2017-07-03
The aim of the present study was to investigate the potential effects of the 5,10,15,20-tetrakis (1-methylpyridinium-4-yl) porphyrin (TMPyP4) on the proliferation and apoptosis of human cervical cancer cells and the underlying mechanisms by which TMPyP4 exerted its actions. After human cervical cancer cells were treated with different doses of TMPyP4, cell viability was determined by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) method, the apoptosis was observed by flow cytometry (FCM), and the expression of p38 mitogen-activated protein kinase (MAPK), phosphated p38 MAPK (p-p38 MAPK), capase-3, MAPKAPK2 (MK-2) and poly ADP-ribose polymerase (PARP) was measured by Western blot analysis. The analysis revealed that TMPyP4 potently suppressed cell viability and induced the apoptosis of human cervical cancer cells in a dose-dependent manner. In addition, the up-regulation of p-p38 MAPK expression levels was detected in TMPyP4-treated human cervical cancer cells. However, followed by the block of p38 MAPK signaling pathway using the inhibitor SB203580, the effects of TMPyP4 on proliferation and apoptosis of human cervical cancer cells were significantly changed. It was indicated that TMPyP4-inhibited proliferation and -induced apoptosis in human cervical cancer cells was accompanied by activating the p38 MAPK signaling pathway. Taken together, our study demonstrates that TMPyP4 may represent a potential therapeutic method for the treatment of cervical carcinoma.
Lung cancer perfusion: can we measure pulmonary and bronchial circulation simultaneously?
Yuan, Xiaodong; Zhang, Jing; Ao, Guokun; Quan, Changbin; Tian, Yuan; Li, Hong
2012-08-01
To describe a new CT perfusion technique for assessing the dual blood supply in lung cancer and present the initial results. This study was approved by the institutional review board. A CT protocol was developed, and a dual-input CT perfusion (DI-CTP) analysis model was applied and evaluated regarding the blood flow fractions in lung tumours. The pulmonary trunk and the descending aorta were selected as the input arteries for the pulmonary circulation and the bronchial circulation respectively. Pulmonary flow (PF), bronchial flow (BF), and a perfusion index (PI, = PF/ (PF + BF)) were calculated using the maximum slope method. After written informed consent was obtained, 13 consecutive subjects with primary lung cancer underwent DI-CTP. Perfusion results are as follows: PF, 13.45 ± 10.97 ml/min/100 ml; BF, 48.67 ± 28.87 ml/min/100 ml; PI, 21 % ± 11 %. BF is significantly larger than PF, P < 0.001. There is a negative correlation between the tumour volume and perfusion index (r = 0.671, P = 0.012). The dual-input CT perfusion analysis method can be applied successfully to lung tumours. Initial results demonstrate a dual blood supply in primary lung cancer, in which the systemic circulation is dominant, and that the proportion of the two circulation systems is moderately dependent on tumour size. A new CT perfusion technique can assess lung cancer's dual blood supply. A dual blood supply was confirmed with dominant bronchial circulation in lung cancer. The proportion of the two circulations is moderately dependent on tumour size. This new technique may benefit the management of lung cancer.
Athirajan, Vimmitra; Razak, Ishak Abdul; Thurairajah, Nalina; Ghani, Wan Maria Nabillah; Ching, Helen-Ng Lee; Yang, Yi-Hsin; Peng, Karen-Ng Lee; Abdul Rahman, Zainal Ariff; Mustafa, Wan Mahadzir Wan; Abraham, Mannil Thomas; Kiong, Tay Keng; Mun, Yuen Kar; Jalil, Norma; Zain, Rosnah Binti
2014-01-01
A comparative cross-sectional study involving oral cancer patients and healthy individuals was designed to investigate associations between retinol, α-tocopherol and β-carotene with the risk of oral cancer. This study included a total of 240 matched cases and controls where subjects were selected from the Malaysian Oral Cancer Database and Tissue Bank System (MOCDTBS). Retinol, α-tocopherol and β-carotene levels and intake were examined by high-performance liquid chromatography (HPLC) and food frequency questionnaire (FFQ) respectively. It was found that results from the two methods applied did not correlate, so that further analysis was done using the HPLC method utilising blood serum. Serum levels of retinol and α-tocopherol among cases (0.177±0.081, 1.649±1.670μg/ml) were significantly lower than in controls (0.264±0.137, 3.225±2.054μg/ml) (p<0.005). Although serum level of β-carotene among cases (0.106±0.159 μg/ml) were lower compared to controls (0.134±0.131μg/ml), statistical significance was not observed. Logistic regression analysis showed that high serum level of retinol (OR=0.501, 95% CI=0.254-0.992, p<0.05) and α-tocopherol (OR=0.184, 95% CI=0.091-0.370, p<0.05) was significantly related to lower risk of oral cancer, whereas no relationship was observed between β-carotene and oral cancer risk. High serum levels of retinol and α-tocopherol confer protection against oral cancer risk.
Yuan, Changrong; Wei, Chunlan; Wang, Jichuan; Qian, Huijuan; Ye, Xianghong; Liu, Yingyan; Hinds, Pamela S
2014-06-01
Although the relationship between partial socioeconomic status (SES) and self-efficacy has been studied in previous studies, few research have examined self-efficacy difference among patients with cancer with different SES. A cross-sectional survey involving 764 patients with cancer was completed. Latent class analysis (LCA) was applied to identify distinct groups of patients with cancer using four SES indicators (education, income, employment status and health insurance status). Standardization and decomposition analysis (SDA) was then used to examine differences in patients' self-efficacy among SES groups and the components of the differences attributed to confounding factors, such as gender, age, anxiety, depression and social support. Participants were classified into four distinctive SES groups via using LCA method, and the observed self-efficacy level significantly varied by SES groups; as theorized, higher self-efficacy was associated with higher SES. The self-efficacy differences by SES groups were decomposed into "real" group differences and factor component effects that are attributed to group differences in confounding factor compositions. Self-efficacy significantly varies by SES. Social support significantly confounded the observed differences in self-efficacy between different SES groups among Chinese patients with cancer. Copyright © 2014 Elsevier Ltd. All rights reserved.
Qin, Changjiang; Ren, Xuequn; Xu, Kaiwu; Chen, Zhihui; He, Yulong; Song, Xinming
2014-01-01
Objective. Preoperative radio(chemo)therapy (pR(C)T) appears to increase postoperative complications of rectal cancer resection, but clinical trials have reported conflicting results. The objective of this meta-analysis was performed to assess the effects of pR(C)T on anastomotic leak after rectal cancer resection. Methods. PubMed, Embase, and the Cochrane Library were searched from January 1980 to January 2014. Randomized controlled trials included all original articles reporting anastomotic leak in patients with rectal cancer, among whom some received preoperative radiotherapy or chemoradiotherapy while others did not. The analysed end-points were the anastomotic leak. Result. Seven randomized controlled trials with 3375 patients were included in the meta-analysis. 1660 forming the group undergoing preoperative radiotherapy or chemoradiotherapy versus 1715 patients undergoing without preoperative radiotherapy or chemoradiotherapy. The meta-analyses found that pR(C)T was not an independent risk factor for anastomotic leakage (OR 1.02, 95% CI 0.80–1.30; P = 0.88). Subgroups analysis was performed and the result was not altered. Conclusions. Current evidence demonstrates that pR(C)T did not increase the risk of postoperative anastomotic leak after rectal cancer resection in patients. PMID:25477955
Body-Mind Healing Strategies in Patients with Cancer: a Qualitative Content Analysis
Khoshnood, Zohreh; Iranmanesh, Sedigheh; Rayyani, Masoud; Dehghan, Mahlegha
2018-06-25
Background: Cancer is a major health problem around the world. The use of coping strategies among patients with cancer depends on several issues. This study was conducted to determine coping strategies used by patients with cancer in south-east Iran. Methods: This study is a conventional, qualitative content analysis with a descriptive explorative approach. Data saturation achieved after interviewing 13 participants in 15 interviews. Using an in-depth individual semi-structured approach the participants were asked to narrate their experiences of strategies that they used to cope with cancer. The following were considered: unit of analysis, meaning unit, condensation, code, sub-category, category, and main category. Results: Data analysis led to extraction of two main categories of body-mind healing strategies: being connected to the body and mindfully reconnected to the self. The first category was explained with reference to two sub-categories, being aware of intelligence and body nurturing. The second category was explained with the three sub-categories of using embodying knowledge, living for the moment, and being connected to nature. Conclusion: According to the results of this qualitative study, it is possible to form discussion groups with peers or to have self-reflective practice learning groups to reflect patients’ questions and strategies that they use for body-mind healing. Creative Commons Attribution License
[Microcytomorphometric video-image detection of nuclear chromatin in ovarian cancer].
Grzonka, Dariusz; Kamiński, Kazimierz; Kaźmierczak, Wojciech
2003-09-01
Technology of detection of tissue preparates precisious evaluates contents of nuclear chromatine, largeness and shape of cellular nucleus, indicators of mitosis, DNA index, ploidy, phase-S fraction and other parameters. Methods of detection of picture are: microcytomorphometry video-image (MCMM-VI), flow, double flow and activated by fluorescence. Diagnostic methods of malignant neoplasm of ovary are still nonspecific and not precise, that is a reason of unsatisfied results of treatment. Evaluation of microcytomorphometric measurements of nuclear chromatine histopathologic tissue preparates (HP) of ovarian cancer and comparison to normal ovarian tissue. Estimated 10 paraffin embedded tissue preparates of serous ovarian cancer, 4 preparates mucinous cancer and 2 cases of tumor Kruckenberg patients operated in Clinic of Perinatology and Gynaecology Silesian Medical Academy in Zabrze in period 2001-2002, MCMM-VI estimation based on computer aided analysis system: microscope Axioscop 20, camera tv JVCTK-C 1380, CarlZeiss KS Vision 400 rel.3.0 software. Following MCMM-VI parameters assessed: count of pathologic nucleus, diameter of nucleus, area, min/max diameter ratio, equivalent circle diameter (Dcircle), mean of brightness (mean D), integrated optical density (IOD = area x mean D), DNA index and 2.5 c exceeding rate percentage (2.5 c ER%). MCMM-VI performed on the 160 areas of 16 preparates of cancer and 100 areas of normal ovarian tissue. Statistical analysis was performed by used t-Student test. We obtained stastistically significant higher values parameters of nuclear chromatine, DI, 2.5 c ER of mucinous cancer and tumor Kruckenberg comparison to serous cancer. MCMM-VI parameters of chromatine malignant ovarian neoplasm were statistically significantly higher than normal ovarian tissue. Cytometric and karyometric parametres of nuclear chromatine estimated MCMM-VI are useful in the diagnostics and prognosis of ovarian cancer.
Mertens, Ann C; Yong, Jian; Dietz, Andrew; Kreiter, Erin; Yasui, Yutaka; Bleyer, Archie; Armstrong, Gregory T; Robison, Leslie L; Wasilewski-Masker, Karen
2015-01-01
Background Long-term survivors of pediatric cancer are at risk for life-threatening late effects of their cancer. Previous studies have shown excesses in long-term mortality within high-risk groups defined by demographic and treatment characteristics. Methods To investigate conditional survival in a pediatric cancer population, we performed an analysis of conditional survival in the original Childhood Cancer Survivor Study (CCSS) cohort and the Surveillance, Epidemiology and End Results (SEER) database registry. The overall probability of death for patients in 5 years and 10 years after they survived 5, 10, 15, and 20 years since cancer diagnosis, and cause-specific death in 10 years for 5-year survivors were estimated using the cumulative incidence method. Results Among CCSS and SEER patients who were alive 5 years post cancer diagnosis, within each diagnosis group at least 92% are alive in the subsequent 5 years, except leukemia patients of whom only 88% of 5-year survivors remain alive in the subsequent 5 years. The probability of all-cause mortality in the next 10 years on patients who survived at least 5 years after diagnosis, was 8.8% in CCSS and 10.6% in SEER, approximately three quarter of which were due to neoplasms as causes of death. Conclusion The risk of death of pediatric cancer survivors in 10 years can vary between diagnosis groups by at most 12% even up to 20 years post diagnosis. This information is clinically important in counseling patients on their conditional survival, particularly when survivors are seen in long-term follow-up. PMID:25557134
A Panel of MicroRNAs as Diagnostic Biomarkers for the Identification of Prostate Cancer.
Daniel, Rhonda; Wu, Qianni; Williams, Vernell; Clark, Gene; Guruli, Georgi; Zehner, Zendra
2017-06-16
Prostate cancer is the most common non-cutaneous cancer among men; yet, current diagnostic methods are insufficient, and more reliable diagnostic markers need to be developed. One answer that can bridge this gap may lie in microRNAs. These small RNA molecules impact protein expression at the translational level, regulating important cellular pathways, the dysregulation of which can exert tumorigenic effects contributing to cancer. In this study, high throughput sequencing of small RNAs extracted from blood from 28 prostate cancer patients at initial stages of diagnosis and prior to treatment was used to identify microRNAs that could be utilized as diagnostic biomarkers for prostate cancer compared to 12 healthy controls. In addition, a group of four microRNAs (miR-1468-3p, miR-146a-5p, miR-1538 and miR-197-3p) was identified as normalization standards for subsequent qRT-PCR confirmation. qRT-PCR analysis corroborated microRNA sequencing results for the seven top dysregulated microRNAs. The abundance of four microRNAs (miR-127-3p, miR-204-5p, miR-329-3p and miR-487b-3p) was upregulated in blood, whereas the levels of three microRNAs (miR-32-5p, miR-20a-5p and miR-454-3p) were downregulated. Data analysis of the receiver operating curves for these selected microRNAs exhibited a better correlation with prostate cancer than PSA (prostate-specific antigen), the current gold standard for prostate cancer detection. In summary, a panel of seven microRNAs is proposed, many of which have prostate-specific targets, which may represent a significant improvement over current testing methods.
Munoz, Alexis R; Kaiser, Karen; Yanez, Betina; Victorson, David; Garcia, Sofia F; Snyder, Mallory A; Salsman, John M
2016-12-01
Young adult (YA) racial and ethnic minority survivors of cancer (diagnosed ages 18-39) experience significant disparities in health outcomes and survivorship compared to non-minorities of the same age. However, little is known about the survivorship experiences of this population. The purpose of this study is to explore the cancer experiences and health-related quality of life (HRQOL) among YA racial/ethnic minorities in an urban US city. Racial and ethnic minority YA cancer survivors (0 to 5 years posttreatment) were recruited from a comprehensive cancer center using a purposive sampling approach. Participants (n = 31) completed semi-structured interviews, the FACT-G (physical, emotional, social well-being) and the FACIT-Sp (spiritual well-being). Mixed methods data were evaluated using thematic analysis and analysis of covariance (ANCOVA). The majority of survivors were women (65 %), single (52 %), and Hispanic (42 %). Across interviews, the most common themes were the following: "changes in perspective," "emotional impacts," "received support," and "no psychosocial changes." Other themes varied by racial/ethnic subgroups, including "treatment effects" (Hispanics), "behavior changes" (Blacks), and "appreciation for life" (Asians). ANCOVAs (controlling for gender and ECOG performance status scores) revealed that race/ethnicity had a significant main effect on emotional (P = 0.05), but not physical, social, or spiritual HRQOL (P > 0.05). Our findings suggest that minority YA cancer survivors report complex positive and negative experiences. In spite of poor health outcomes, survivors report experiencing growth and positive change due to cancer. Variations in experiences and HRQOL highlight the importance of assessing cultural background to tailor survivorship care among YA racial and ethnic minorities.
Automated texture-based identification of ovarian cancer in confocal microendoscope images
NASA Astrophysics Data System (ADS)
Srivastava, Saurabh; Rodriguez, Jeffrey J.; Rouse, Andrew R.; Brewer, Molly A.; Gmitro, Arthur F.
2005-03-01
The fluorescence confocal microendoscope provides high-resolution, in-vivo imaging of cellular pathology during optical biopsy. There are indications that the examination of human ovaries with this instrument has diagnostic implications for the early detection of ovarian cancer. The purpose of this study was to develop a computer-aided system to facilitate the identification of ovarian cancer from digital images captured with the confocal microendoscope system. To achieve this goal, we modeled the cellular-level structure present in these images as texture and extracted features based on first-order statistics, spatial gray-level dependence matrices, and spatial-frequency content. Selection of the best features for classification was performed using traditional feature selection techniques including stepwise discriminant analysis, forward sequential search, a non-parametric method, principal component analysis, and a heuristic technique that combines the results of these methods. The best set of features selected was used for classification, and performance of various machine classifiers was compared by analyzing the areas under their receiver operating characteristic curves. The results show that it is possible to automatically identify patients with ovarian cancer based on texture features extracted from confocal microendoscope images and that the machine performance is superior to that of the human observer.
NASA Astrophysics Data System (ADS)
Catalano, E.; Di Benedetto, A.
2017-05-01
Superparamagnetic iron oxide nanoparticles have recently been investigated for their potential to kill cancer cells with promising results, owing to their ability to be targeted and heated by magnetic fields. In this study, novel hydrogel, chitosan Fe3O4 magnetic nanoparticles were synthesized to induce magnetic hyperthermia, and targeted delivering of chemotherapeutics in the cancer microenvironment. The characteristic properties of synthesized bare and CS-MNPs were analyzed by various analytical methods: X-ray diffraction, Fourier transformed infrared spectroscopy, Scanning electron microscopy and Thermo-gravimetric analysis/differential thermal analysis. Magnetic nanoparticles were successfully synthesized using the co-precipitation method. This synthesis technique resulted in nanoparticles with an average particle size of 16 nm. The pure obtained nanoparticles were then successfully encapsulated with 4-nm-thick chitosan coating. The formation of chitosan on the surface of nanoparticles was confirmed by physicochemical analyses. Heating experiments at safe magnetic field (f = 100 kHz, H =10-20 kA m-1) revealed that the maximum achieved temperature of water stable chitosan-coated nanoparticles (50 mg ml-1) is fully in agreement with cancer therapy and biomedical applications.
Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T
2015-01-01
MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.