Science.gov

Sample records for 1975-2004 featuring cancer

  1. Annual report to the nation on the status of cancer, 1975-2004, featuring cancer in American Indians and Alaska Natives.

    PubMed

    Espey, David K; Wu, Xiao-Cheng; Swan, Judith; Wiggins, Charles; Jim, Melissa A; Ward, Elizabeth; Wingo, Phyllis A; Howe, Holly L; Ries, Lynn A G; Miller, Barry A; Jemal, Ahmedin; Ahmed, Faruque; Cobb, Nathaniel; Kaur, Judith S; Edwards, Brenda K

    2007-11-15

    The American Cancer Society, the Centers for Disease Control and Prevention, the National Cancer Institute, and the North American Association of Central Cancer Registries collaborate annually to provide updated information on cancer occurrence and trends in the U.S. The 2007 report features a comprehensive compilation of cancer information for American Indians and Alaska Natives (AI/AN). Cancer incidence data were available for up to 82% of the U.S. population. Cancer deaths were available for the entire U.S. population. Long-term (1975 through 2004) and fixed-interval (1995 through 2004) incidence and mortality trends were evaluated by annual percent change using regression analyses (2-sided P < .05). Cancer screening, risk factors, socioeconomic characteristics, incidence data, and stage were compiled for non-Hispanic whites (NHW) and AI/AN across 6 regions of the U.S. Overall cancer death rates decreased by 2.1% per year from 2002 through 2004, nearly twice the annual decrease of 1.1% per year from 1993 through 2002. Among men and women, death rates declined for most cancers. Among women, lung cancer incidence rates no longer were increasing and death rates, although they still were increasing slightly, were increasing at a much slower rate than in the past. Breast cancer incidence rates in women decreased 3.5% per year from 2001 to 2004, the first decrease observed in 20 years. Colorectal cancer incidence and death rates and prostate cancer death rates declined, with colorectal cancer death rates dropping more sharply from 2002 through 2004. Overall, rates for AI/AN were lower than for NHW from 1999 through 2004 for most cancers, but they were higher for cancers of the stomach, liver, cervix, kidney, and gallbladder. Regional analyses, however, revealed high rates for AI/AN in the Northern and Southern Plains and Alaska. For cancers of the breast, colon and rectum, prostate, and cervix, AI/AN were less likely than NHW to be diagnosed at localized stages. For

  2. Motor neuron disease mortality in Great Britain continues to rise: examination of mortality rates 1975 - 2004.

    PubMed

    Day, Thomas G; Scott, Martin; Perring, Roslyn; Doyle, Pat

    2007-12-01

    Motor neuron disease (MND) mortality rates are rising in Europe and the USA. The most comprehensive UK study was conducted more than 15 years ago. This study examines trends in mortality from MND in England & Wales, and Scotland, between 1975 and 2004. Age, gender, and cause-specific mortality rates were calculated for the period 1975-2004 using national data from England & Wales, and Scotland. Rates were directly age-standardized to the European standard population. Trends in mortality rates over time were examined for men and women separately, as well as by the age groups 0-59 years, and 60 or more years. MND mortality rates rose steadily over the 30-year period 1975-2004 in both sexes in England & Wales, and Scotland. There is a clear upward trend in all four groups (p for trend <0.001). All increases were largely restricted to the age group 60 years and above, with rates showing increases of 70-80%, and no evidence of a flattening of this trajectory. Rates for the 0-59 years age group remained stable over the period. There is evidence of a narrowing of the male-female gap in mortality rates for the age group over 60 years in England and Wales.

  3. Breast Cancers Between Mammograms Have Aggressive Features

    Cancer.gov

    Breast cancers that are discovered in the period between regular screening mammograms—known as interval cancers—are more likely to have features associated with aggressive behavior and a poor prognosis than cancers found via screening mammograms.

  4. Trends in nutrient concentrations, loads, and yields in streams in the Sacramento, San Joaquin, and Santa Ana Basins, California, 1975-2004

    USGS Publications Warehouse

    Kratzer, Charles R.; Kent, Robert; Seleh, Dina K.; Knifong, Donna L.; Dileanis, Peter D.; Orlando, James L.

    2011-01-01

    A comprehensive database was assembled for the Sacramento, San Joaquin, and Santa Ana Basins in California on nutrient concentrations, flows, and point and nonpoint sources of nutrients for 1975-2004. Most of the data on nutrient concentrations (nitrate, ammonia, total nitrogen, orthophosphate, and total phosphorus) were from the U.S. Geological Survey's National Water Information System database (35.2 percent), the California Department of Water Resources (21.9 percent), the University of California at Davis (21.6 percent), and the U.S. Environmental Protection Agency's STOrage and RETrieval database (20.0 percent). Point-source discharges accounted for less than 1 percent of river flows in the Sacramento and San Joaquin Rivers, but accounted for close to 80 percent of the nonstorm flow in the Santa Ana River. Point sources accounted for 4 and 7 percent of the total nitrogen and total phosphorus loads, respectively, in the Sacramento River at Freeport for 1985-2004. Point sources accounted for 8 and 17 percent of the total nitrogen and total phosphorus loads, respectively, in the San Joaquin River near Vernalis for 1985-2004. The volume of wastewater discharged into the Santa Ana River increased almost three-fold over the study period. However, due to improvements in wastewater treatment, the total nitrogen load to the Santa Ana River from point sources in 2004 was approximately the same as in 1975 and the total phosphorus load in 2004 was less than in 1975. Nonpoint sources of nutrients estimated in this study included atmospheric deposition, fertilizer application, manure production, and tile drainage. The estimated dry deposition of nitrogen exceeded wet deposition in the Sacramento and San Joaquin Valleys and in the basin area of the Santa Ana Basin, with ratios of dry to wet deposition of 1.7, 2.8, and 9.8, respectively. Fertilizer application increased appreciably from 1987 to 2004 in all three California basins, although manure production increased in the

  5. Features of aggressive breast cancer.

    PubMed

    Arpino, Grazia; Milano, Monica; De Placido, Sabino

    2015-10-01

    Aggressive breast cancer is a term commonly used in literature to describe breast cancer with a poor prognosis. Identifying and understanding the factors associated with aggressiveness could be helpful to the management of patients with breast cancer. Breast cancer is a heterogeneous disease, both clinically and biologically, which may be responsible for the wide range of survival durations for patients with metastatic disease. The goal of this study was to identify the factors most often described in association with aggressive metastatic breast cancer (MBC). A systematic review was performed by querying PubMed from January 1, 2012 to June 1, 2014 for "metastatic breast cancer" ("aggressive" or "poor prognosis" or "high risk"). The level of evidence to support each potential prognostic factor of aggressive MBC was also reviewed. The identified factors were grouped into 3 principle categories: clinical, biological, and patient related. Because patient-related factors may not be indicative of inherent cancer aggressiveness, this review focused only on clinical and biological factors. The factors with the highest levels of evidence to support associations with survival in metastatic breast cancer were visceral metastases, number of metastatic sites, disease-free interval, presence of CTCs, triple-negative disease, and tumour grade. Identification of these factors and understanding their contribution to the aggressiveness of MBC and disease progression may lead to more personalized treatment in this patient population. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  6. Mammographic features of early breast cancer

    SciTech Connect

    Sickles, E.A.

    1984-09-01

    Mammographic detection of breast cancer at the earliest possible stage requires optimal radiographic technique and a full knowledge of the subtle features with which very small cancers can present. Although some early cancers are identified as characteristic clusters of calcifications or as spiculated or multinodular (knobby) masses, others demonstrate less typical and sometimes much less obvious mammographic signs: the single dilated duct, focal architectural distortion, asymmetry, and the developing density sign. Although these indirect signs are nonspecific, they provide mammographers with the important opportunity to discover breast cancer at a very early stage, when the likelihood for cure is great.

  7. Breast Cancer Detection with Reduced Feature Set.

    PubMed

    Mert, Ahmet; Kılıç, Niyazi; Bilgili, Erdem; Akan, Aydin

    2015-01-01

    This paper explores feature reduction properties of independent component analysis (ICA) on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC) dataset is reduced to one-dimensional feature vector computing an independent component (IC). The original data with 30 features and reduced one feature (IC) are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN), artificial neural network (ANN), radial basis function neural network (RBFNN), and support vector machine (SVM). The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations) and partitioning (20%-40%) methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden's index, discriminant power, and the receiver operating characteristic (ROC) curve with its criterion values including area under curve (AUC) and 95% confidential interval (CI). This represents an improvement in diagnostic decision support system, while reducing computational complexity.

  8. Breast Cancer Detection with Reduced Feature Set

    PubMed Central

    Kılıç, Niyazi; Bilgili, Erdem

    2015-01-01

    This paper explores feature reduction properties of independent component analysis (ICA) on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC) dataset is reduced to one-dimensional feature vector computing an independent component (IC). The original data with 30 features and reduced one feature (IC) are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN), artificial neural network (ANN), radial basis function neural network (RBFNN), and support vector machine (SVM). The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations) and partitioning (20%–40%) methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden's index, discriminant power, and the receiver operating characteristic (ROC) curve with its criterion values including area under curve (AUC) and 95% confidential interval (CI). This represents an improvement in diagnostic decision support system, while reducing computational complexity. PMID:26078774

  9. Posterior breast cancer - mammographic and ultrasonographic features.

    PubMed

    Janković, Ana; Nadrljanski, Mirjan; Karapandzić, Vesna Plesinac; Ivanović, Nebojsa; Radojicić, Zoran; Milosević, Zorica

    2013-11-01

    Posterior breast cancers are located in the prepectoral region of the breast. Owing to this distinctive anatomical localization, physical examination and mammographic or ultrasonographic evaluation can be difficult. The purpose of the study was to assess possibilities of diagnostic mammography and breast ultrasonography in detection and differentiation of posterior breast cancers. The study included 40 women with palpable, histopathological confirmed posterior breast cancer. Mammographic and ultrasonographic features were defined according to Breast Imaging Reporting and Data System (BI-RADS) lexicon. Based on standard two-view mammography 87.5%, of the cases were classified as BI-RADS 4 and 5 categories, while after additional mammographic views all the cases were defined as BI-RADS 4 and 5 categories. Among 96 mammographic descriptors, the most frequent were: spiculated mass (24.0%), architectural distortion (16.7%), clustered micro-calcifications (12.6%) and focal asymmetric density (12.6%). The differentiation of the spiculated mass was significantly associated with the possibility to visualize the lesion at two-view mammography (p = 0.009), without the association with lesion diameter (p = 0.083) or histopathological type (p = 0.055). Mammographic signs of invasive lobular carcinoma were significantly different from other histopathological types (architectural distortion, p = 0.003; focal asymmetric density, p = 0.019; association of four or five subtle signs of malignancy, p = 0.006). All cancers were detectable by ultrasonography. Mass lesions were found in 82.0% of the cases. Among 153 ultrasonographic descriptors, the most frequent were: irregular mass (15.7%), lobulated mass (7.2%), abnormal color Doppler signals (20.3%), posterior acoustic attenuation (18.3%). Ultrasonographic BI-RADS 4 and 5 categories were defined in 72.5% of the cases, without a significant difference among various histopathological types (p = 0.109). Standard two-view mammography

  10. Identifying DNA Methylation Features that Underlie Prostate Cancer Disparities

    DTIC Science & Technology

    2015-10-01

    after diagnosis , AA men are more likely to die from prostate cancer than EA men. We hypothesize that differences in DNA methylation patterns across...AD AWARD NUMBER: W81XWH-14-1-0529 TITLE: Identifying DNA Methylation Features that Underlie Prostate Cancer Disparities PRINCIPAL INVESTIGATOR...Methylation Features that Underlie Prostate Cancer Disparities 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-14-1-0529 5c. PROGRAM ELEMENT NUMBER 6

  11. Identifying DNA Methylation Features that Underlie Prostate Cancer Disparities

    DTIC Science & Technology

    2016-10-01

    1 AD______________ AWARD NUMBER: W81XWH-14-1-0529 TITLE: Identifying DNA Methylation Features that Underlie Prostate Cancer Disparities...Identifying DNA Methylation Features that Underlie Prostate Cancer Disparities 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-14-0529 5c. PROGRAM...American (EA), and after diagnosis, AA men are more likely to die from prostate cancer than EA men. We hypothesize that differences in DNA methylation

  12. feature - Office of Cancer Clinical Proteomics Research

    Cancer.gov

    "Cancer is a disease of the genome," noted Lynda Chin, M.D., professor of dermatology, Harvard Medical School and Dana-Farber Cancer Institute. "And understanding the impact of genomic changes in the proteome is critically important for converting genomic knowledge into something that a clinician can use on their patients."

  13. Regulation of breast cancer stem cell features.

    PubMed

    Czerwinska, Patrycja; Kaminska, Bozena

    2015-01-01

    Cancer stem cells (CSCs) are rare, tumour-initiating cells that exhibit stem cell properties: capacity of self-renewal, pluripotency, highly tumorigenic potential, and resistance to therapy. Cancer stem cells have been characterised and isolated from many cancers, including breast cancer. Developmental pathways, such as the Wnt/β-catenin, Notch/γ-secretase/Jagged, Shh (sonic hedgehog), and BMP signalling pathways, which direct proliferation and differentiation of normal stem cells, have emerged as major signalling pathways that contribute to the self-renewal of stem and/or progenitor cells in a variety of organs and cancers. Deregulation of these signalling pathways is frequently linked to an epithelial-mesenchymal transition (EMT), and breast CSCs often possess properties of cells that have undergone the EMT process. Signalling networks mediated by microRNAs and EMT-inducing transcription factors tie the EMT process to regulatory networks that maintain "stemness". Recent studies have elucidated epigenetic mechanisms that control pluripotency and stemness, which allows an assessment on how embryonic and normal tissue stem cells are deregulated during cancerogenesis to give rise to CSCs. Epigenetic-based mechanisms are reversible, and the possibility of "resetting" the abnormal cancer epigenome by applying pharmacological compounds targeting epigenetic enzymes is a promising new therapeutic strategy. Chemoresistance of CSCs is frequently driven by various mechanisms, including aberrant expression/activity of ABC transporters, aldehyde dehydrogenase and anti-oncogenic proteins (i.e. BCL2, B-cell lymphoma-2), enhanced DNA damage response, activation of pro-survival signalling pathways, and epigenetic deregulations. Despite controversy surrounding the CSC hypothesis, there is substantial evidence for their role in cancer, and a number of drugs intended to specifically target CSCs have entered clinical trials.

  14. Clinical and Biological Features of Interval Colorectal Cancer

    PubMed Central

    Lee, Yu Mi; Huh, Kyu Chan

    2017-01-01

    Interval colorectal cancer (I-CRC) is defined as a CRC diagnosed within 60 months after a negative colonoscopy, taking into account that 5 years is the “mean sojourn time.” It is important to prevent the development of interval cancer. The development of interval colon cancer is associated with female sex, old age, family history of CRC, comorbidities, diverticulosis, and the skill of the endoscopist. During carcinogenesis, sessile serrated adenomas/polyps (SSA/Ps) share many genomic and colonic site characteristics with I-CRCs. The clinical and biological features of I-CRC should be elucidated to prevent the development of interval colon cancer. PMID:28320200

  15. Clinicopathological features and surgical options for synchronous colorectal cancer

    PubMed Central

    Lee, Byoung Chul; Yu, Chang Sik; Kim, Jihun; Lee, Jong Lyul; Kim, Chan Wook; Yoon, Yong Sik; Park, In Ja; Lim, Seok-Byung; Kim, Jin Cheon

    2017-01-01

    Abstract This study was conducted to investigate the clinicopathological features of synchronous cancers and treatment options according to their locations. Records of 8368 patients with colorectal cancer treated at our center between July 2003 and December 2010 were analyzed retrospectively. All synchronous colorectal cancer patients who underwent surgical treatment were included. Synchronous cancers were identified in 217 patients (2.6%). Seventy-nine patients underwent either total colectomy, subtotal colectomy, or total proctocolectomy; 116 underwent 1 regional resection, including local excision; and 22 underwent 2 regional resections. The mean age was 62 years, slightly higher than that for the single-cancer patients. Synchronous cancers were more common in male patients, more frequently located in the left colon, had more microsatellite instability-high status, and showed more advanced stage than single cancer. Extensive resection was mainly performed for synchronous cancers located in both the right and left colon. Two regional resections were performed for cancers in the right colon and rectum. There were no differences in complication rates or the occurrence of metachronous cancer between the 2-region resection and extensive resection groups. Eight years postoperatively, the mean number of daily bowel movements for these 2 groups were 1.9 and 4.3, respectively. We found that synchronous cancer was different from single cancer in terms of age, gender, location, and pathologic features. Synchronous colorectal cancer requires different treatment strategy according to the distribution of lesions. Comparison between the 2 regional resections and extensive resection approaches suggests that 2 regional resections are preferable. PMID:28248880

  16. Predictive features of breast cancer on Mexican screening mammography patients

    NASA Astrophysics Data System (ADS)

    Rodriguez-Rojas, Juan; Garza-Montemayor, Margarita; Trevino-Alvarado, Victor; Tamez-Pena, José Gerardo

    2013-02-01

    Breast cancer is the most common type of cancer worldwide. In response, breast cancer screening programs are becoming common around the world and public programs now serve millions of women worldwide. These programs are expensive, requiring many specialized radiologists to examine all images. Nevertheless, there is a lack of trained radiologists in many countries as in Mexico, which is a barrier towards decreasing breast cancer mortality, pointing at the need of a triaging system that prioritizes high risk cases for prompt interpretation. Therefore we explored in an image database of Mexican patients whether high risk cases can be distinguished using image features. We collected a set of 200 digital screening mammography cases from a hospital in Mexico, and assigned low or high risk labels according to its BIRADS score. Breast tissue segmentation was performed using an automatic procedure. Image features were obtained considering only the segmented region on each view and comparing the bilateral di erences of the obtained features. Predictive combinations of features were chosen using a genetic algorithms based feature selection procedure. The best model found was able to classify low-risk and high-risk cases with an area under the ROC curve of 0.88 on a 150-fold cross-validation test. The features selected were associated to the differences of signal distribution and tissue shape on bilateral views. The model found can be used to automatically identify high risk cases and trigger the necessary measures to provide prompt treatment.

  17. Visually Meaningful Histopathological Features for Automatic Grading of Prostate Cancer.

    PubMed

    Niazi, M Khalid Khan; Keluo Yao; Zynger, Debra L; Clinton, Steven K; Chen, James; Koyuturk, Mehmet; LaFramboise, Thomas; Gurcan, Metin

    2017-07-01

    Histopathologic features, particularly Gleason grading system, have contributed significantly to the diagnosis, treatment, and prognosis of prostate cancer for decades. However, prostate cancer demonstrates enormous heterogeneity in biological behavior, thus establishing improved prognostic and predictive markers is particularly important to personalize therapy of men with clinically localized and newly diagnosed malignancy. Many automated grading systems have been developed for Gleason grading but acceptance in the medical community has been lacking due to poor interpretability. To overcome this problem, we developed a set of visually meaningful features to differentiate between low- and high-grade prostate cancer. The visually meaningful feature set consists of luminal and architectural features. For luminal features, we compute: 1) the shortest path from the nuclei to their closest luminal spaces; 2) ratio of the epithelial nuclei to the total number of nuclei. A nucleus is considered an epithelial nucleus if the shortest path between it and the luminal space does not contain any other nucleus; 3) average shortest distance of all nuclei to their closest luminal spaces. For architectural features, we compute directional changes in stroma and nuclei using directional filter banks. These features are utilized to create two subspaces; one for prostate images histopathologically assessed as low grade and the other for high grade. The grade associated with a subspace, which results in the minimum reconstruction error is considered as the prediction for the test image. For training, we utilized 43 regions of interest (ROI) images, which were extracted from 25 prostate whole slide images of The Cancer Genome Atlas (TCGA) database. For testing, we utilized an independent dataset of 88 ROIs extracted from 30 prostate whole slide images. The method resulted in 93.0% and 97.6% training and testing accuracies, respectively, for the spectrum of cases considered. The

  18. Feature extraction via composite scoring and voting in breast cancer.

    PubMed

    Koch, Martin; Hanl, Markus; Wiese, Michael

    2012-08-01

    Identification and characterization of tumor subtypes using gene expression profiles of triple negative breast cancer patients. Microarray data of four breast cancer studies were pooled and evaluated. Molecular subtype classification was performed using random forest and a novel algorithm for feature extraction via composite scoring and voting. Biological and clinical properties were evaluated via GSEA, functional annotation clustering and clinical endpoint analysis. The subtype signatures are highly predictive for distant metastasis free survival of tamoxifen-treated patients. Consensus clustering and the novel algorithm proposed three triple negative subtypes. One subtype shows low E2F4 gene expression and is predictive for survival of ER negative breast cancer patients. The other two subtypes share commonalities with luminal B tumors. Classification of breast cancer expression profiles may reveal novel tumor subtypes, possessing clinical impact. Furthermore, subtype characterizing gene signatures might hold potential for novel strategies in cancer therapy.

  19. Feature statistic analysis of ultrasound images of liver cancer

    NASA Astrophysics Data System (ADS)

    Huang, Shuqin; Ding, Mingyue; Zhang, Songgeng

    2007-12-01

    In this paper, a specific feature analysis of liver ultrasound images including normal liver, liver cancer especially hepatocellular carcinoma (HCC) and other hepatopathy is discussed. According to the classification of hepatocellular carcinoma (HCC), primary carcinoma is divided into four types. 15 features from single gray-level statistic, gray-level co-occurrence matrix (GLCM), and gray-level run-length matrix (GLRLM) are extracted. Experiments for the discrimination of each type of HCC, normal liver, fatty liver, angioma and hepatic abscess have been conducted. Corresponding features to potentially discriminate them are found.

  20. Prognostic features and markers for testicular cancer management.

    PubMed

    Leman, Eddy S; Gonzalgo, Mark L

    2010-01-01

    Testicular neoplasm accounts for about 1% of all cancers in men. Over the last 40 years, the incidence of testicular cancer has increased in northern European male populations for unknown reasons. When diagnosed at early stage, testicular cancer is usually curable with a high survival rate. In the past three decades, successful multidisciplinary approaches for the management of testicular cancer have significantly increased patient survival rates. Utilization of tumor markers and accurate prognostic classification has also contributed to successful therapy. In this article, we highlight the most commonly used tumor markers and several potential "novel" markers for testicular cancer as part of the ongoing effort in biomarker research and discovery. In addition, this article also identifies several key prognostic features that have been demonstrated to play a role in predicting relapse. These features include tumor size, rete testis invasion, lymphovascular invasion, and tumor histology. Together with tumor markers, these prognostic factors should be taken into account for risk-adapted management of testicular cancer.

  1. Breast cancer detection in rotational thermography images using texture features

    NASA Astrophysics Data System (ADS)

    Francis, Sheeja V.; Sasikala, M.; Bhavani Bharathi, G.; Jaipurkar, Sandeep D.

    2014-11-01

    Breast cancer is a major cause of mortality in young women in the developing countries. Early diagnosis is the key to improve survival rate in cancer patients. Breast thermography is a diagnostic procedure that non-invasively images the infrared emissions from breast surface to aid in the early detection of breast cancer. Due to limitations in imaging protocol, abnormality detection by conventional breast thermography, is often a challenging task. Rotational thermography is a novel technique developed in order to overcome the limitations of conventional breast thermography. This paper evaluates this technique's potential for automatic detection of breast abnormality, from the perspective of cold challenge. Texture features are extracted in the spatial domain, from rotational thermogram series, prior to and post the application of cold challenge. These features are fed to a support vector machine for automatic classification of normal and malignant breasts, resulting in a classification accuracy of 83.3%. Feature reduction has been performed by principal component analysis. As a novel attempt, the ability of this technique to locate the abnormality has been studied. The results of the study indicate that rotational thermography holds great potential as a screening tool for breast cancer detection.

  2. Clinicopathological features of stomach cancer with invasive micropapillary component.

    PubMed

    Fujita, Takeo; Gotohda, Naoto; Kato, Yuichiro; Kinoshita, Takahiro; Takahashi, Shinichiro; Konishi, Masaru; Daiko, Hiroyuki; Nishimura, Mitsuyo; Kuwata, Takeshi; Ochiai, Atsushi; Kinoshita, Taira

    2012-04-01

    Invasive micropapillary carcinoma has been recognized as a rare disease entity with aggressive tumor behavior. However, few reports have described invasive micropapillary carcinoma in the gastrointestinal tract, particularly its involvement in gastric cancer. We retrospectively analyzed 930 patients diagnosed with gastric cancer who underwent gastrectomy, and we then histopathologically evaluated the existence of a regional invasive micropapillary component. Clinicopathological features were investigated in patients with an invasive micropapillary component and compared with such features in 100 patients with gastric adenocarcinoma, selected as stage-matched controls, who underwent gastrectomy during the same period. Of the 930 patients, 14 were histopathologically diagnosed with gastric cancer with a regional invasive micropapillary component. There were no significant differences in age, gender, tumor location, macroscopic type, or type of surgery between patients with an invasive micropapillary component and the pT-matched controls. Histopathologically, significant differences were observed in lymphatic infiltration, venous invasion, the percentage of cases with lymph node metastasis, and the median number of metastatic lymph nodes. The three-year disease-free and overall survival rates of patients with an invasive micropapillary component were 40.5 and 59.3%, respectively, compared with those for the stage-matched controls, which were 72.6 and 80.6%, respectively (p = 0.02 and 0.07). Patients with gastric cancer with a regional invasive micropapillary component showed marked cancer infiltration in the lymphatic pathway and poor prognosis after gastrectomy.

  3. Feature Extraction and Analysis of Breast Cancer Specimen

    NASA Astrophysics Data System (ADS)

    Bhattacharyya, Debnath; Robles, Rosslin John; Kim, Tai-Hoon; Bandyopadhyay, Samir Kumar

    In this paper, we propose a method to identify abnormal growth of cells in breast tissue and suggest further pathological test, if necessary. We compare normal breast tissue with malignant invasive breast tissue by a series of image processing steps. Normal ductal epithelial cells and ductal / lobular invasive carcinogenic cells also consider for comparison here in this paper. In fact, features of cancerous breast tissue (invasive) are extracted and analyses with normal breast tissue. We also suggest the breast cancer recognition technique through image processing and prevention by controlling p53 gene mutation to some greater extent.

  4. Neural network feature selection for breast cancer diagnosis

    NASA Astrophysics Data System (ADS)

    Kocur, Catherine M.; Rogers, Steven K.; Bauer, Kenneth W., Jr.; Steppe, Jean M.; Hoffmeister, Jeffrey W.

    1995-04-01

    More than 50 million women over the age of 40 are currently at risk for breast cancer in the United States. Computer-aided diagnosis, as a second opinion to radiologists, will aid in decreasing the number of false readings of mammograms. Neural network benefits are exploited at both the classification and feature selection stages in the development of a computer-aided breast cancer diagnostic system. The multilayer perceptron is used to classify and contrast three features (angular second moment, eigenmasses, and wavelets) developed to distinguish benign from malignant lesion in a database of 94 difficult-to-diagnose digitized microcalcification cases. System performance of 74 percent correct classifications is achieved. Feature selection techniques are presented which further improve performance. Neural and decision boundary-based methods are implemented, compared, and validated to isolate and remove useless features. The contribution from this analysis is an increase to 88 percent correct classification in system performance. These feature selection techniques can also process risk factor data.

  5. Family history of cancer associated with breast tumor clinicopathological features.

    PubMed

    Ricks, Luisel J; Ewing, Altovise; Thompson, Nicole; Harrison, Barbara; Wilson, Bradford; Richardson, Finie; Carter-Nolan, Pamela; Spencer, Cherie; Laiyemo, Adeyinka; Williams, Carla

    2014-07-01

    Hereditary breast cancers have unique clinicopathological characteristics. Therefore, the objective of this study was to establish the relationship between self-reported family history of cancer and clinicopathological features in breast cancer patients from Washington, DC. Data on incident breast cancer cases from 2000 to 2010 were obtained from the Washington, DC Cancer Registry. Variables such as estrogen (ER), progesterone (PR), and human epidermal growth factor 2 (HER2) receptor status, as well as stage and grade, were analyzed in those that self-reported with (n = 1,734) and without a family history of cancer (n = 1,712). The breast cancer molecular subtypes were compared when ER, PR, and HER2 statuses were available. Furthermore, tumor characteristics were compared by race/ethnicity. Regression and chi-square analyses were performed. A report of family history was associated with age (OR = 1.27 95 % CI: 1.09-1.48; p < 0.0001), high grade tumors (OR = 1.29 95 % CI: 1.05-1.58; p = 0.02), and having ER and PR negative breast cancer (OR = 1.26 95 % CI: 1.02-1.57; p = 0.029). When tumor characteristics were compared by race/ethnicity, those that self-reported as African American with a family history had a higher frequency of ER negative tumors (OR = 1.51 95 % CI: 1.09-2.08; p = 0.008), PR negative tumors (OR = 1.46 95 % CI: 1.09-1.94; p = 0.028), grade 3 tumors (OR = 1.42 95 % CI: 1.05-1.93; p < 0.0001), and ER/PR negative tumors (OR = 1.5 95 % CI: 1.088-2.064; p = 0.01). These results suggest that a positive family history of cancer in African Americans should increase suspicions of hereditary cancer. Therefore, behavioral risk reduction activities, such as collecting a family history, may reduce late stage diagnosis and cancer mortality.

  6. Obesity, age, ethnicity, and clinical features of prostate cancer patients

    PubMed Central

    Wu, Victor J; Pang, Darren; Tang, Wendell W; Zhang, Xin; Li, Li; You, Zongbing

    2017-01-01

    Approximately 36.5% of the U.S. adults (≥ 20 years old) are obese. Obesity has been associated with type 2 diabetes mellitus, cardiovascular disease, stroke, and several types of cancer. The present study included 1788 prostate cancer patients who were treated with radical prostatectomy at the Ochsner Health System, New Orleans, Louisiana, from January, 2001 to March, 2016. The patient’s medical records were retrospectively reviewed. Body mass index (BMI), age, ethnicity (Caucasians versus African Americans), clinical stage, Gleason score, and prostate-specific antigen (PSA) levels were retrieved. The relative risk of the patients was stratified into low risk and high risk groups. Associative analyses found that BMI was associated with age, clinical stage, Gleason score, but not ethnicity, PSA levels, or the relative risk in this cohort. Age was associated with ethnicity, clinical stage, Gleason score, and PSA levels, as well as the relative risk. Ethnicity was associated with Gleason score and PSA levels as well as the relative risk, but not clinical stage. These findings suggest that obesity is associated with advanced prostate cancer with stage T3 or Gleason score ≥ 7 diseases, and age and ethnicity are important factors that are associated with the clinical features of prostate cancer patients. PMID:28337464

  7. Feature of amenorrhea in postoperative tamoxifen users with breast cancer

    PubMed Central

    Choi, Young Min

    2017-01-01

    Objective Tamoxifen has been used to prevent the recurrence of breast cancer. However, tamoxifen-users frequently experience amenorrhea and it can be confused from that caused by other hormonal abnormalities. In amenorrheic patients without breast cancer, clinicians usually measure the sex hormone levels that are known to be associated with ovarian or menstrual function. This study aimed to investigate the feature of female sex hormones in premenopausal breast cancer patients undergoing tamoxifen treatment. Methods The medical records of fifty-nine premenopausal breast cancer patients who underwent tamoxifen treatment were reviewed retrospectively. The study population consisted of amenorrheic patients (n=36) and patients with menstruation (n=23). Serum hormone levels were measured either specifically between cycle days 2 and 5 in menstruating patients or at any time in amenorrheic participants. Results Serum levels of lutenizing hormone and estradiol were not statistically different according to the presence of menstruation. Serum follicle stimulating hormone level was significantly higher in amenorrheic patients (8.1±5.7 mIU/mL) than those in menstruating subjects (5.1±2.2 mIU/mL) (p=0.01). Serum concentration of thyroid stimulating hormone was lower in patients with amenorrhea (1.5±0.9 vs. 2.3±2.2 μIU/mL, p=0.04), although the prevalence of hypo- or hyperthyroidism was not different according to the pattern of menstruation. Conclusion Menstruation status and hormone levels can be influenced by tamoxifen use in reproductive age breast cancer patients. Physicians should be attentive to the alteration of pituitary hormone levels in addition to sex steroid hormones in this population. PMID:27894163

  8. Feature of amenorrhea in postoperative tamoxifen users with breast cancer.

    PubMed

    Kim, Hoon; Han, Wonshik; Ku, Seung Yup; Suh, Chang Suk; Kim, Seok Hyun; Choi, Young Min

    2017-03-01

    Tamoxifen has been used to prevent the recurrence of breast cancer. However, tamoxifen-users frequently experience amenorrhea and it can be confused from that caused by other hormonal abnormalities. In amenorrheic patients without breast cancer, clinicians usually measure the sex hormone levels that are known to be associated with ovarian or menstrual function. This study aimed to investigate the feature of female sex hormones in premenopausal breast cancer patients undergoing tamoxifen treatment. The medical records of fifty-nine premenopausal breast cancer patients who underwent tamoxifen treatment were reviewed retrospectively. The study population consisted of amenorrheic patients (n=36) and patients with menstruation (n=23). Serum hormone levels were measured either specifically between cycle days 2 and 5 in menstruating patients or at any time in amenorrheic participants. Serum levels of lutenizing hormone and estradiol were not statistically different according to the presence of menstruation. Serum follicle stimulating hormone level was significantly higher in amenorrheic patients (8.1±5.7 mIU/mL) than those in menstruating subjects (5.1±2.2 mIU/mL) (p=0.01). Serum concentration of thyroid stimulating hormone was lower in patients with amenorrhea (1.5±0.9 vs. 2.3±2.2 μIU/mL, p=0.04), although the prevalence of hypo- or hyperthyroidism was not different according to the pattern of menstruation. Menstruation status and hormone levels can be influenced by tamoxifen use in reproductive age breast cancer patients. Physicians should be attentive to the alteration of pituitary hormone levels in addition to sex steroid hormones in this population.

  9. Ultrasonographic features of triple-negative breast cancer: a comparison with other breast cancer subtypes.

    PubMed

    Yang, Qi; Liu, Hong-Yan; Liu, Dan; Song, Yan-Qiu

    2015-01-01

    Triple-negative breast cancer (TNBC) is known to be associated with aggressive biologic features and a poor clinical outcome. Therefore, early detection of TNBC without missed diagnosis is a requirement to improve prognosis. Preoperative ultrasound features of TNBC may potentially assist in early diagnosis as characteristics of disease. To retrospectively evaluate the sonographic features of TNBC compared to ER (+) cancers which include HER(-) and HER2 (+), and HER2 (+) cancers which are ER (-). From June 2012 through June 2014, sonographic features of 321 surgically confirmed ER (+) cancers (n=214), HER2 (+) cancers (n=66), and TNBC (n=41) were retrospectively reviewed by two ultrasound specialists in consensus. The preoperative ultrasound and clinicopathological features were compared between the three subtypes. In addition, all cases were analyzed using morphologic criteria of the ACR BI-RADS lexicon. Ultrasonographically, TNBC presented as microlobulated nodules without microcalcification (p=0.034). A lower incidence of ductal carcinoma in situ (p<0.001), invasive tumor size that is>2 cm (p=0.011) and BI-RADS category 4 (p<0.001) were significantly associated with TNBC. With regard to morphologic features of 41 TNBC cases, ultrasonographically were most likely to be masses with irregular (70.7%) microlobulated shape (48.8%), be circumscribed (17.1%) or have indistinct margins (17.1%) and parallel orientation (68.9%). Especially TNBC microlobulated mass margins were more more frequent than with ER (+) (2.0%) and HER2 (+) (4.8%) cancers. TNBC have specific characteristic in sonograms. Ultrasonography may be useful to avoid missed diagnosis and false-negative cases of TNBC.

  10. Clinical and molecular features of young-onset colorectal cancer

    PubMed Central

    Ballester, Veroushka; Rashtak, Shahrooz; Boardman, Lisa

    2016-01-01

    Colorectal cancer (CRC) is one of the leading causes of cancer related mortality worldwide. Although young-onset CRC raises the possibility of a hereditary component, hereditary CRC syndromes only explain a minority of young-onset CRC cases. There is evidence to suggest that young-onset CRC have a different molecular profile than late-onset CRC. While the pathogenesis of young-onset CRC is well characterized in individuals with an inherited CRC syndrome, knowledge regarding the molecular features of sporadic young-onset CRC is limited. Understanding the molecular mechanisms of young-onset CRC can help us tailor specific screening and management strategies. While the incidence of late-onset CRC has been decreasing, mainly attributed to an increase in CRC screening, the incidence of young-onset CRC is increasing. Differences in the molecular biology of these tumors and low suspicion of CRC in young symptomatic individuals, may be possible explanations. Currently there is no evidence that supports that screening of average risk individuals less than 50 years of age will translate into early detection or increased survival. However, increasing understanding of the underlying molecular mechanisms of young-onset CRC could help us tailor specific screening and management strategies. The purpose of this review is to evaluate the current knowledge about young-onset CRC, its clinicopathologic features, and the newly recognized molecular alterations involved in tumor progression. PMID:26855533

  11. [Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

    PubMed

    Li, Jing; Hong, Wenxue

    2014-12-01

    The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

  12. Quantitative imaging features to predict cancer status in lung nodules

    NASA Astrophysics Data System (ADS)

    Liu, Ying; Balagurunathan, Yoganand; Atwater, Thomas; Antic, Sanja; Li, Qian; Walker, Ronald; Smith, Gary T.; Massion, Pierre P.; Schabath, Matthew B.; Gillies, Robert J.

    2016-03-01

    Background: We propose a systematic methodology to quantify incidentally identified lung nodules based on observed radiological traits on a point scale. These quantitative traits classification model was used to predict cancer status. Materials and Methods: We used 102 patients' low dose computed tomography (LDCT) images for this study, 24 semantic traits were systematically scored from each image. We built a machine learning classifier in cross validation setting to find best predictive imaging features to differentiate malignant from benign lung nodules. Results: The best feature triplet to discriminate malignancy was based on long axis, concavity and lymphadenopathy with average AUC of 0.897 (Accuracy of 76.8%, Sensitivity of 64.3%, Specificity of 90%). A similar semantic triplet optimized on Sensitivity/Specificity (Youden's J index) included long axis, vascular convergence and lymphadenopathy which had an average AUC of 0.875 (Accuracy of 81.7%, Sensitivity of 76.2%, Specificity of 95%). Conclusions: Quantitative radiological image traits can differentiate malignant from benign lung nodules. These semantic features along with size measurement enhance the prediction accuracy.

  13. Feature Subset Selection for Cancer Classification Using Weight Local Modularity

    PubMed Central

    Zhao, Guodong; Wu, Yan

    2016-01-01

    Microarray is recently becoming an important tool for profiling the global gene expression patterns of tissues. Gene selection is a popular technology for cancer classification that aims to identify a small number of informative genes from thousands of genes that may contribute to the occurrence of cancers to obtain a high predictive accuracy. This technique has been extensively studied in recent years. This study develops a novel feature selection (FS) method for gene subset selection by utilizing the Weight Local Modularity (WLM) in a complex network, called the WLMGS. In the proposed method, the discriminative power of gene subset is evaluated by using the weight local modularity of a weighted sample graph in the gene subset where the intra-class distance is small and the inter-class distance is large. A higher local modularity of the gene subset corresponds to a greater discriminative of the gene subset. With the use of forward search strategy, a more informative gene subset as a group can be selected for the classification process. Computational experiments show that the proposed algorithm can select a small subset of the predictive gene as a group while preserving classification accuracy. PMID:27703256

  14. Feature Subset Selection for Cancer Classification Using Weight Local Modularity

    NASA Astrophysics Data System (ADS)

    Zhao, Guodong; Wu, Yan

    2016-10-01

    Microarray is recently becoming an important tool for profiling the global gene expression patterns of tissues. Gene selection is a popular technology for cancer classification that aims to identify a small number of informative genes from thousands of genes that may contribute to the occurrence of cancers to obtain a high predictive accuracy. This technique has been extensively studied in recent years. This study develops a novel feature selection (FS) method for gene subset selection by utilizing the Weight Local Modularity (WLM) in a complex network, called the WLMGS. In the proposed method, the discriminative power of gene subset is evaluated by using the weight local modularity of a weighted sample graph in the gene subset where the intra-class distance is small and the inter-class distance is large. A higher local modularity of the gene subset corresponds to a greater discriminative of the gene subset. With the use of forward search strategy, a more informative gene subset as a group can be selected for the classification process. Computational experiments show that the proposed algorithm can select a small subset of the predictive gene as a group while preserving classification accuracy.

  15. Metaplastic breast cancer: clinicopathological features and its prognosis.

    PubMed

    Lee, Hyewon; Jung, So-Youn; Ro, Jae Yun; Kwon, Youngmee; Sohn, Joo Hyuk; Park, In Hae; Lee, Keun Seok; Lee, Seeyoun; Kim, Seok Won; Kang, Han Sung; Ko, Kyoung Lan; Ro, Jungsil

    2012-05-01

    The prognosis of metaplastic breast cancer (MBC) is reportedly worse than that of triple-negative invasive ductal carcinoma (TN-IDC), but the determinants of poor prognosis are not yet known. Patients from two Korean cancer centres were included in this study (67 MBC and 520 TN-IDC). Characteristics of the two disease groups, including clinical parameters, histological features, chemoresponsiveness, disease recurrence and survival estimates, were evaluated. MBC presented with larger tumours, more frequent distant metastasis and higher histological grade compared with TN-IDC (p<0.001). All but nine patients with MBC had triple-negative disease. Disease-free survival and overall survival (OS) of MBC were worse than TN-IDC (p<0.001). Multivariable analysis of disease-free survival revealed MBC type as an independent prognostic factor (HR 2.53; 95% CI 1.32 to 4.84) along with lymph node metastasis and implementation of breast conserving surgery. For OS, MBC type remained a significant prognostic factor (HR 2.56; 95% CI 1.18 to 5.54). Chemoresponsiveness of MBC and TN-IDC were similar in both neoadjuvant (p=1.000) and advanced disease settings (p=0.508). For a given MBC type, risk factors for disease recurrence included the presence of a squamous component (HR 4.0; 95% CI 1.46 to 10.99) and lymph node metastasis (HR 4.76; 95% CI 1.67 to 13.60); the risk factor for OS was initial distant metastasis (HR 10.77; 95% CI 2.59 to 44.76). MBC had worse survival outcomes compared with TN-IDC. Poor prognosis for MBC was likely caused by frequent recurrence with high initial stage and the unique biology of MBC itself.

  16. Histological Image Feature Mining Reveals Emergent Diagnostic Properties for Renal Cancer.

    PubMed

    Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D

    2011-11-01

    Computer-aided histological image classification systems are important for making objective and timely cancer diagnostic decisions. These systems use combinations of image features that quantify a variety of image properties. Because researchers tend to validate their diagnostic systems on specific cancer endpoints, it is difficult to predict which image features will perform well given a new cancer endpoint. In this paper, we define a comprehensive set of common image features (consisting of 12 distinct feature subsets) that quantify a variety of image properties. We use a data-mining approach to determine which feature subsets and image properties emerge as part of an "optimal" diagnostic model when applied to specific cancer endpoints. Our goal is to assess the performance of such comprehensive image feature sets for application to a wide variety of diagnostic problems. We perform this study on 12 endpoints including 6 renal tumor subtype endpoints and 6 renal cancer grade endpoints. Keywords-histology, image mining, computer-aided diagnosis.

  17. Analysis of cancer genomes reveals basic features of human aging and its role in cancer development

    PubMed Central

    Podolskiy, Dmitriy I.; Lobanov, Alexei V.; Kryukov, Gregory V.; Gladyshev, Vadim N.

    2016-01-01

    Somatic mutations have long been implicated in aging and disease, but their impact on fitness and function is difficult to assess. Here by analysing human cancer genomes we identify mutational patterns associated with aging. Our analyses suggest that age-associated mutation load and burden double approximately every 8 years, similar to the all-cause mortality doubling time. This analysis further reveals variance in the rate of aging among different human tissues, for example, slightly accelerated aging of the reproductive system. Age-adjusted mutation load and burden correlate with the corresponding cancer incidence and precede it on average by 15 years, pointing to pre-clinical cancer development times. Behaviour of mutation load also exhibits gender differences and late-life reversals, explaining some gender-specific and late-life patterns in cancer incidence rates. Overall, this study characterizes some features of human aging and offers a mechanism for age being a risk factor for the onset of cancer. PMID:27515585

  18. PREDICTING FIFTEEN-YEAR CANCER-SPECIFIC MORTALITY BASED ON THE PATHOLOGICAL FEATURES OF PROSTATE CANCER

    PubMed Central

    Eggener, Scott E.; Scardino, Peter T.; Walsh, Patrick C.; Han, Misop; Partin, Alan W.; Trock, Bruce J.; Feng, Zhaoyong; Wood, David P.; Eastham, James A.; Yossepowitch, Ofer; Rabah, Danny M.; Kattan, Michael W.; Yu, Changhong; Klein, Eric A.; Stephenson, Andrew J.

    2014-01-01

    Purpose Long-term prostate cancer-specific mortality (PCSM) after radical prostatectomy is poorly defined in the era of widespread screening. An understanding of the treated natural history of screen-detected cancers and the pathological risk factors for PCSM are needed for treatment decision-making. Methods Using Fine and Gray competing risk regression analysis, the clinical and pathological data and follow-up information of 11,521 patients treated by radical prostatectomy at four academic centers from 1987 to 2005 were modeled to predict PCSM. The model was validated on 12,389 patients treated at a separate institution during the same period. Results The overall 15-year PCSM was 7%. Primary and secondary pathological Gleason grade 4–5 (P < 0.001 for both), seminal vesicle invasion (P < 0.001), and year of surgery (P = 0.002) were significant predictors of PCSM. A nomogram predicting 15-year PCSM based on standard pathological parameters was accurate and discriminating with an externally-validated concordance index of 0.92. Stratified by patient age, 15-year PCSM for Gleason score ≤ 6, 3+4, 4+3, and 8–10 ranged from 0.2–1.2%, 4.2–6.5%, 6.6–11%, and 26–37%, respectively. The 15-year PCSM risks ranged from 0.8–1.5%, 2.9–10%, 15–27%, and 22–30% for organ-confined cancer, extraprostatic extension, seminal vesicle invasion, and lymph node metastasis, respectively. Only 3 of 9557 patients with organ-confined, Gleason score ≤ 6 cancers have died from prostate cancer. Conclusions The presence of poorly differentiated cancer and seminal vesicle invasion are the prime determinants of PCSM after radical prostatectomy. The risk of PCSM can be predicted with unprecedented accuracy once the pathological features of prostate cancer are known. PMID:21239008

  19. Feature selection using genetic algorithm for breast cancer diagnosis: experiment on three different datasets.

    PubMed

    Aalaei, Shokoufeh; Shahraki, Hadi; Rowhanimanesh, Alireza; Eslami, Saeid

    2016-05-01

    This study addresses feature selection for breast cancer diagnosis. The present process uses a wrapper approach using GA-based on feature selection and PS-classifier. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer datasets. To evaluate effectiveness of proposed feature selection method, we employed three different classifiers artificial neural network (ANN) and PS-classifier and genetic algorithm based classifier (GA-classifier) on Wisconsin breast cancer datasets include Wisconsin breast cancer dataset (WBC), Wisconsin diagnosis breast cancer (WDBC), and Wisconsin prognosis breast cancer (WPBC). For WBC dataset, it is observed that feature selection improved the accuracy of all classifiers expect of ANN and the best accuracy with feature selection achieved by PS-classifier. For WDBC and WPBC, results show feature selection improved accuracy of all three classifiers and the best accuracy with feature selection achieved by ANN. Also specificity and sensitivity improved after feature selection. The results show that feature selection can improve accuracy, specificity and sensitivity of classifiers. Result of this study is comparable with the other studies on Wisconsin breast cancer datasets.

  20. Functional features of cancer stem cells in melanoma cell lines.

    PubMed

    Zimmerer, Rüdiger M; Korn, Philippe; Demougin, Philippe; Kampmann, Andreas; Kokemüller, Horst; Eckardt, André M; Gellrich, Nils-Claudius; Tavassol, Frank

    2013-08-06

    Recent evidence suggests a subset of cells within a tumor with "stem-like" characteristics. These cells are able to transplant tumors in immunodeficient hosts. Distinct from non-malignant stem cells, cancer stem cells (CSC) show low proliferative rates, high self-renewing capacity, propensity to differentiate into actively proliferating tumor cells, and resistance to chemotherapy or radiation. They are often characterized by elevated expression of stem cell surface markers, in particular CD133, and sets of differentially expressed stem cell-associated genes. CSC are usually rare in clinical specimens and hardly amenable to functional studies and gene expression profiling. In this study, a panel of heterogenous melanoma cell lines was screened for typical CSC features. Nine heterogeneous metastatic melanoma cell lines including D10 and WM115 were studied. Cell lines were phenotyped using flow cytometry and clonogenic assays were performed by limiting dilution analysis on magnetically sorted cells. Spheroidal growth was investigated in pretreated flasks. Gene expression profiles were assessed by using real-time rt-PCR and DNA microarrays. Magnetically sorted tumor cells were subcutaneously injected into the flanks of immunodeficient mice. Comparative immunohistochemistry was performed on xenografts and primary human melanoma sections. D10 cells expressed CD133 with a significantly higher clonogenic capacity as compared to CD133- cells. Na8, D10, and HBL cells formed spheroids on poly-HEMA-coated flasks. D10, Me39, RE, and WM115 cells expressed at least 2 of the 3 regulatory core transcription factors SOX2, NANOG, and OCT4 involved in the maintenance of stemness in mesenchymal stem cells. Gene expression profiling on CD133+ and CD133- D10 cells revealed 68 up- and 47 downregulated genes (+/-1.3 fold). Two genes, MGP and PROM1 (CD133), were outstandingly upregulated. CD133+ D10 cells formed tumors in NSG mice contrary to CD133- cells and CD133 expression was detected

  1. Automated colon cancer detection using hybrid of novel geometric features and some traditional features.

    PubMed

    Rathore, Saima; Hussain, Mutawarra; Khan, Asifullah

    2015-10-01

    Automatic classification of colon into normal and malignant classes is complex due to numerous factors including similar colors in different biological constituents of histopathological imagery. Therefore, such techniques, which exploit the textural and geometric properties of constituents of colon tissues, are desired. In this paper, a novel feature extraction strategy that mathematically models the geometric characteristics of constituents of colon tissues is proposed. In this study, we also show that the hybrid feature space encompassing diverse knowledge about the tissues׳ characteristics is quite promising for classification of colon biopsy images. This paper thus presents a hybrid feature space based colon classification (HFS-CC) technique, which utilizes hybrid features for differentiating normal and malignant colon samples. The hybrid feature space is formed to provide the classifier different types of discriminative features such as features having rich information about geometric structure and image texture. Along with the proposed geometric features, a few conventional features such as morphological, texture, scale invariant feature transform (SIFT), and elliptic Fourier descriptors (EFDs) are also used to develop a hybrid feature set. The SIFT features are reduced using minimum redundancy and maximum relevancy (mRMR). Various kernels of support vector machines (SVM) are employed as classifiers, and their performance is analyzed on 174 colon biopsy images. The proposed geometric features have achieved an accuracy of 92.62%, thereby showing their effectiveness. Moreover, the proposed HFS-CC technique achieves 98.07% testing and 99.18% training accuracy. The better performance of HFS-CC is largely due to the discerning ability of the proposed geometric features and the developed hybrid feature space. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Breast cancer in very young women (<30 years): Correlation of imaging features with clinicopathological features and immunohistochemical subtypes.

    PubMed

    An, Yeong Yi; Kim, Sung Hun; Kang, Bong Joo; Park, Chang Suk; Jung, Na Young; Kim, Ji Youn

    2015-10-01

    Early diagnosis of breast cancer in very young women (<30 years) is challenging and the characteristic imaging findings are not yet fully understood. We evaluated the imaging findings of breast cancer in very young women (<30 years) and to correlate them with clinicopathological features. A total of 50 surgically confirmed breast cancers were included in our retrospective study. The medical records were reviewed and the radiological features were analyzed according to the new 5th edition of the ACR BI-RADS lexicon. The breast cancers in our study population most commonly presented as a self-detected mass (74%), T2-3 stage (58%), histological grade III (52.3%) and ER-positive (80%) subtype. The most common finding was an irregular (87.5%) hyperdense (66.7%) mass with indistinct margins (50%) on mammography and an irregular (75.6%) indistinct (57.8%) hypoechoic/heterogeneous (77.8%) mass without a posterior acoustic feature (60%) on ultrasonography. MRI revealed an irregular shape (63.3%), irregular margins (43.3%), and heterogeneous enhancement (60%) with washout kinetics (69.4%). Mammographically, microcalcifications were correlated with the HER2-enriched type, and mass-type lesions were correlated with triple-negative cancer (p=0.04). An oval/round mass on ultrasound (p=0.005), rim enhancement (p=0.004) and intralesional T2 high signal intensity (p=0.04) on MRI were associated with the triple-negative type. On all imaging modalities, breast cancer in very young women usually presented as an irregular mass, and certain radiological features could be used for predicting the specific tumor type. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  3. Breast cancer in young women: Pathologic features and molecular phenotype.

    PubMed

    Sabiani, Laura; Houvenaeghel, Gilles; Heinemann, Mellie; Reyal, Fabien; Classe, Jean Marc; Cohen, Monique; Garbay, Jean Rémy; Giard, Sylvia; Charitansky, Hélène; Chopin, Nicolas; Rouzier, Roman; Daraï, Emile; Coutant, Charles; Azuar, Pierre; Gimbergues, Pierre; Villet, Richard; Tunon de Lara, Christine; Lambaudie, Eric

    2016-10-01

    Controversy exists about the prognosis of breast cancer in young women. Our objective was to describe clinicopathological and prognostic features to improve adjuvant treatment indications. We conducted a retrospective multi centre study including fifteen French hospitals. Disease-free survival's data, clinical and pathological criteria were collected. 5815 patients were included, 15.6% of them where between 35 and 40 years old and 8.7% below 35. In 94% of the cases, a palpable masse was found in patients ≤35 years old. Triple negative and HER2 tumors were predominantly found in patients ≤35 (22.2% and 22.1%, p < 0.01). A young age ≤40 years (p < 0.001; hazard ratio [HR]: 2.05; 95% confidence limit [CL]: 1.60-2.63) or ≤35 years (p < 0.001; [HR]: 3.86; 95% [CL]: 2.69-5.53) impacted on the indication of chemotherapy. Age ≤35 (p < 0.001; [HR]: 2.01; 95% [CL]: 1.36-2.95) was a significantly negative factor on disease-free survival. Chemotherapy (p < 0.006; [HR]: 0.6; 95% [CL]: 0.40-0.86) and positive hormone receptor status (p < 0.001; [HR]: 0.6; 95% [CL]: 0.54-0.79) appeared to be protector factors. Patients under 36, had a significantly higher rate of local recurrence and distant metastasis compared to patients >35-40 (21.5 vs. 15.4% and 21.8 vs. 12.6%, p < 0.01). Young women present a different distribution of molecular phenotypes with more luminal B and triple negative tumors with a higher grade and more lymph node involvement. A young age, must be taken as a pejorative prognostic factor and must play a part in indication of adjuvant therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. A novel class dependent feature selection method for cancer biomarker discovery.

    PubMed

    Zhou, Wengang; Dickerson, Julie A

    2014-04-01

    Identifying key biomarkers for different cancer types can improve diagnosis accuracy and treatment. Gene expression data can help differentiate between cancer subtypes. However the limitation of having a small number of samples versus a larger number of genes represented in a dataset leads to the overfitting of classification models. Feature selection methods can help select the most distinguishing feature sets for classifying different cancers. A new class dependent feature selection approach integrates the F-statistic, Maximum Relevance Binary Particle Swarm Optimization (MRBPSO) and Class Dependent Multi-category Classification (CDMC) system. This feature selection method combines filter and wrapper based methods. A set of highly differentially expressed genes (features) are pre-selected using the F statistic for each dataset as a filter for selecting the most meaningful features. MRBPSO and CDMC function as a wrapper to select desirable feature subsets for each class and classify the samples using those chosen class-dependent feature subsets. The performance of the proposed methods is evaluated on eight real cancer datasets. The results indicate that the class-dependent approaches can effectively identify biomarkers related to each cancer type and improve classification accuracy compared to class independent feature selection methods.

  5. Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer

    PubMed Central

    Parmar, Chintan; Leijenaar, Ralph T. H.; Grossmann, Patrick; Rios Velazquez, Emmanuel; Bussink, Johan; Rietveld, Derek; Rietbergen, Michelle M.; Haibe-Kains, Benjamin; Lambin, Philippe; Aerts, Hugo J.W.L.

    2015-01-01

    Radiomics provides a comprehensive quantification of tumor phenotypes by extracting and mining large number of quantitative image features. To reduce the redundancy and compare the prognostic characteristics of radiomic features across cancer types, we investigated cancer-specific radiomic feature clusters in four independent Lung and Head & Neck (H∓N) cancer cohorts (in total 878 patients). Radiomic features were extracted from the pre-treatment computed tomography (CT) images. Consensus clustering resulted in eleven and thirteen stable radiomic feature clusters for Lung and H & N cancer, respectively. These clusters were validated in independent external validation cohorts using rand statistic (Lung RS = 0.92, p < 0.001, H & N RS = 0.92, p < 0.001). Our analysis indicated both common as well as cancer-specific clustering and clinical associations of radiomic features. Strongest associations with clinical parameters: Prognosis Lung CI = 0.60 ± 0.01, Prognosis H & N CI = 0.68 ± 0.01; Lung histology AUC = 0.56 ± 0.03, Lung stage AUC = 0.61 ± 0.01, H & N HPV AUC = 0.58 ± 0.03, H & N stage AUC = 0.77 ± 0.02. Full utilization of these cancer-specific characteristics of image features may further improve radiomic biomarkers, providing a non-invasive way of quantifying and monitoring tumor phenotypic characteristics in clinical practice. PMID:26251068

  6. Radiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer.

    PubMed

    Parmar, Chintan; Leijenaar, Ralph T H; Grossmann, Patrick; Rios Velazquez, Emmanuel; Bussink, Johan; Rietveld, Derek; Rietbergen, Michelle M; Haibe-Kains, Benjamin; Lambin, Philippe; Aerts, Hugo J W L

    2015-06-05

    Radiomics provides a comprehensive quantification of tumor phenotypes by extracting and mining large number of quantitative image features. To reduce the redundancy and compare the prognostic characteristics of radiomic features across cancer types, we investigated cancer-specific radiomic feature clusters in four independent Lung and Head &Neck (H) cancer cohorts (in total 878 patients). Radiomic features were extracted from the pre-treatment computed tomography (CT) images. Consensus clustering resulted in eleven and thirteen stable radiomic feature clusters for Lung and H cancer, respectively. These clusters were validated in independent external validation cohorts using rand statistic (Lung RS = 0.92, p < 0.001, H RS = 0.92, p < 0.001). Our analysis indicated both common as well as cancer-specific clustering and clinical associations of radiomic features. Strongest associations with clinical parameters: Prognosis Lung CI = 0.60 ± 0.01, Prognosis H CI = 0.68 ± 0.01; Lung histology AUC = 0.56 ± 0.03, Lung stage AUC = 0.61 ± 0.01, H HPV AUC = 0.58 ± 0.03, H stage AUC = 0.77 ± 0.02. Full utilization of these cancer-specific characteristics of image features may further improve radiomic biomarkers, providing a non-invasive way of quantifying and monitoring tumor phenotypic characteristics in clinical practice.

  7. The I1307K APC polymorphism in Ashkenazi Jews with colorectal cancer: clinical and pathologic features.

    PubMed

    Locker, Gershon Y; Kaul, Karen; Weinberg, David S; Gatalica, Zoran; Gong, Gordon; Peterman, Amy; Lynch, Jane; Klatzco, Lucy; Olopade, Olufunmilayo I; Bomzer, Charles A; Newlin, Anna; Keenan, Eileen; Tajuddin, Mohammed; Knezetic, Joseph; Coronel, Stephanie; Lynch, Henry T

    2006-08-01

    Colorectal cancer is common in Ashkenazi Jews. The I1307K APC mutation occurs in 6-7% of Ashkenazi Jews and increases the risk of colorectal cancer. This study aimed to describe the clinical, pathologic and epidemiologic features of colorectal cancer in I1307K carriers to determine whether there were any features which might warrant individual screening for the mutation. In all, 215 Ashkenazi Jews with a personal history of colorectal cancer were enrolled. Clinical and family history, pathology reports, and slides were obtained and blood drawn for I1307K determination. The presence of the mutation was determined by PCR from white blood cell DNA. Colorectal cancer pathology slides were read in a blinded fashion. Of the 215 enrolled patients, 26 (12.1%) tested positive for I1307K. There was no difference in the pathologic features between colorectal cancers in Ashkenazi carriers compared to noncarriers. There was no difference in the age at diagnosis or history of second or other primaries. Carriers had an increased likelihood of having a first-degree relative with colorectal cancer (50%) compared to noncarriers (28%, P < 0.04). We could find no distinguishing feature other than family history that characterizes I1307K positive colorectal cancers. We could find no group of Ashkenazi Jews with colorectal cancer for whom screening for I1307K would be clinically useful.

  8. [Particular features of lymph dissection in operations for gastric cancer].

    PubMed

    Iaitskiĭ, A N; Danilov, I N

    2008-01-01

    In order to optimize the technique of lymph dissection, a method of intraoperative mapping of lymph outflow tracts was used with a lymphotropic dye Blue patente V. It allowed better orientation during lymphodissection in operations for gastric cancer. The detection and investigation of the "signal" lymph node as the most probable object of lymphogenic metastazing can improve the accuracy of postoperative staging of gastric cancer. Visualization of the lymph nodes in the preparation made it possible to increase the number of lymph nodes sent for histological investigation.

  9. Cancer Stem Cells: A Minor Cancer Subpopulation that Redefines Global Cancer Features.

    PubMed

    Enderling, Heiko; Hlatky, Lynn; Hahnfeldt, Philip

    2013-01-01

    In recent years cancer stem cells (CSCs) have been hypothesized to comprise only a minor subpopulation in solid tumors that drives tumor initiation, progression, and metastasis; the so-called "cancer stem cell hypothesis." While a seemingly trivial statement about numbers, much is put at stake. If true, the conclusions of many studies of cancer cell populations could be challenged, as the bulk assay methods upon which they depend have, by, and large, taken for granted the notion that a "typical" cell of the population possesses the attributes of a cell capable of perpetuating the cancer, i.e., a CSC. In support of the CSC hypothesis, populations enriched for so-called "tumor-initiating" cells have demonstrated a corresponding increase in tumorigenicity as measured by dilution assay, although estimates have varied widely as to what the fractional contribution of tumor-initiating cells is in any given population. Some have taken this variability to suggest the CSC fraction may be nearly 100% after all, countering the CSC hypothesis, and that there are simply assay-dependent error rates in our ability to "reconfirm" CSC status at the cell level. To explore this controversy more quantitatively, we developed a simple cellular automaton model of CSC-driven tumor growth dynamics. Assuming CSC and non-stem cancer cells (CC) subpopulations coexist to some degree, we evaluated the impact of an environmentally dependent CSC symmetric division probability and a CC proliferation capacity on tumor progression and morphology. Our model predicts, as expected, that the frequency of CSC divisions that are symmetric highly influences the frequency of CSCs in the population, but goes on to predict the two frequencies can be widely divergent, and that spatial constraints will tend to increase the CSC fraction over time. Further, tumor progression times show a marked dependence on both the frequency of CSC divisions that are symmetric and on the proliferation capacities of CC. Together

  10. (18)F-FDG PET radiomics approaches: comparing and clustering features in cervical cancer.

    PubMed

    Tsujikawa, Tetsuya; Rahman, Tasmiah; Yamamoto, Makoto; Yamada, Shizuka; Tsuyoshi, Hideaki; Kiyono, Yasushi; Kimura, Hirohiko; Yoshida, Yoshio; Okazawa, Hidehiko

    2017-08-16

    The aims of our study were to find the textural features on (18)F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between (18)F-FDG PET textural features in cervical cancer. Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment (18)F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. (18)F-FDG PET textural features might reflect

  11. An intelligent system for lung cancer diagnosis using a new genetic algorithm based feature selection method.

    PubMed

    Lu, Chunhong; Zhu, Zhaomin; Gu, Xiaofeng

    2014-09-01

    In this paper, we develop a novel feature selection algorithm based on the genetic algorithm (GA) using a specifically devised trace-based separability criterion. According to the scores of class separability and variable separability, this criterion measures the significance of feature subset, independent of any specific classification. In addition, a mutual information matrix between variables is used as features for classification, and no prior knowledge about the cardinality of feature subset is required. Experiments are performed by using a standard lung cancer dataset. The obtained solutions are verified with three different classifiers, including the support vector machine (SVM), the back-propagation neural network (BPNN), and the K-nearest neighbor (KNN), and compared with those obtained by the whole feature set, the F-score and the correlation-based feature selection methods. The comparison results show that the proposed intelligent system has a good diagnosis performance and can be used as a promising tool for lung cancer diagnosis.

  12. Evaluation of the association between perineural invasion and clinical and histopathological features of cervical cancer.

    PubMed

    Wei, You-Sheng; Yao, De-Sheng; Long, Ying

    2016-09-01

    Perineural invasion (PNI) has been investigated as a new prognostic factor in a number of carcinomas. However, studies on PNI in cervical cancer are limited, and inconsistent conclusions have been reported by different groups. The aim of the present study was to analyze the relationship between perineural invasion (PNI) and clinical and histopathological features of cervical cancer, and to evaluate the clinical significance of PNI of cervical cancer. Retrospective review identified 206 patients with cervical cancer who underwent radical hysterectomy plus pelvic lymphadenectomy between December 2012 and August 2014. The association between PNI and clinical and histopathological features of cervical cancer and post-operative radiotherapy was evaluated based on univariate and multivariate analyses. PNI of cervical cancer was identified in 33 of 206 (16%) cervical cancer patients. Univariate analysis demonstrated that PNI was associated with clinical stage, tumor grade, tumor size, depth of invasion, lymphovascular space invasion (LVSI), and lymph node metastasis (P<0.05), but not associated with age and histopathological types (P>0.05). Multivariate analysis suggests that LVSI and lymph node metastasis were associated with PNI of cervical cancer (P<0.05). In addition, post-operative radiotherapy was significantly more recommended for patients with PNI than those without PNI (P<0.001). In conclusion, PNI of cervical cancer is associated with LVSI and lymph node metastasis and can be used as an index for the determination of post-operative radiotherapy for cervical cancer patients.

  13. Breast cancer in young women: clinicopathological features and biological specificity.

    PubMed

    Sidoni, A; Cavaliere, A; Bellezza, G; Scheibel, M; Bucciarelli, E

    2003-08-01

    Literature data suggest that breast cancers occurring in young patients may be different from those arising in older women. In this study the clinicopathologic characteristics of 50 patients under 40 years of age were compared with those of patients aged over 60. Patients under 40 years old more frequently had a family history of breast cancer than did older patients (24% vs 17%) and had more often used oral contraceptives (29% vs 13%); on average they had experienced menarche 1 year earlier. For early onset breast carcinomas there was a higher frequency of grade 3 tumours (38% vs 17%) and oestrogen receptor negativity (46% vs 20%). In addition, in younger patients the carcinomas were mostly DNA aneuploid (78% vs 58%), with a higher proliferation rate (48% vs 26%) and more frequent c-erbB-2 overexpression (48% vs 26%) and p53 alteration (30% vs 8%). Our data demonstrate that breast cancers arising in young women have a significantly different biopathological profile from those in older patients, with a predominance of unfavourable prognostic parameters.

  14. Cancer microarray data feature selection using multi-objective binary particle swarm optimization algorithm.

    PubMed

    Annavarapu, Chandra Sekhara Rao; Dara, Suresh; Banka, Haider

    2016-01-01

    Cancer investigations in microarray data play a major role in cancer analysis and the treatment. Cancer microarray data consists of complex gene expressed patterns of cancer. In this article, a Multi-Objective Binary Particle Swarm Optimization (MOBPSO) algorithm is proposed for analyzing cancer gene expression data. Due to its high dimensionality, a fast heuristic based pre-processing technique is employed to reduce some of the crude domain features from the initial feature set. Since these pre-processed and reduced features are still high dimensional, the proposed MOBPSO algorithm is used for finding further feature subsets. The objective functions are suitably modeled by optimizing two conflicting objectives i.e., cardinality of feature subsets and distinctive capability of those selected subsets. As these two objective functions are conflicting in nature, they are more suitable for multi-objective modeling. The experiments are carried out on benchmark gene expression datasets, i.e., Colon, Lymphoma and Leukaemia available in literature. The performance of the selected feature subsets with their classification accuracy and validated using 10 fold cross validation techniques. A detailed comparative study is also made to show the betterment or competitiveness of the proposed algorithm.

  15. Histological Image Feature Mining Reveals Emergent Diagnostic Properties for Renal Cancer

    PubMed Central

    Kothari, Sonal; Phan, John H.; Young, Andrew N.; Wang, May D.

    2016-01-01

    Computer-aided histological image classification systems are important for making objective and timely cancer diagnostic decisions. These systems use combinations of image features that quantify a variety of image properties. Because researchers tend to validate their diagnostic systems on specific cancer endpoints, it is difficult to predict which image features will perform well given a new cancer endpoint. In this paper, we define a comprehensive set of common image features (consisting of 12 distinct feature subsets) that quantify a variety of image properties. We use a data-mining approach to determine which feature subsets and image properties emerge as part of an “optimal” diagnostic model when applied to specific cancer endpoints. Our goal is to assess the performance of such comprehensive image feature sets for application to a wide variety of diagnostic problems. We perform this study on 12 endpoints including 6 renal tumor subtype endpoints and 6 renal cancer grade endpoints. Keywords-histology, image mining, computer-aided diagnosis PMID:28163980

  16. Endoscopic and histological features of gastric cancers after successful Helicobacter pylori eradication therapy.

    PubMed

    Saka, Akiko; Yagi, Kazuyoshi; Nimura, Satoshi

    2016-04-01

    Gastric cancer after successful Helicobacter pylori eradication therapy is often difficult to diagnose by endoscopy because of its indistinct borderline or lack of obviously cancerous characteristics. Furthermore, it has become evident that non-neoplastic epithelium covers cancerous areas in gastric cancer after eradication. Here, we investigated these endoscopic features and their relationship to histological findings. We studied 24 and 47 gastric cancers in patients who had (eradication group) and had not (control group) undergone H. pylori eradication, respectively. A gastritis-like appearance revealed by conventional endoscopy was defined as a mucosal pattern with no marked difference from the surrounding non-cancerous area and that revealed by narrow-band imaging (NBI)-magnifying endoscopy (ME) as the mucosal pattern observed in H. pylori-associated atrophic gastritis. We investigated a gastritis-like appearance revealed by conventional endoscopy (A), a gastritis-like appearance at the margin (B) and within (C) the cancerous area revealed by NBI-ME, and the histological characteristics of the overlying non-neoplastic epithelium. We also evaluated the relationship between endoscopic and histological findings in the eradication group. Endoscopy showed that features A, B and C were significantly more frequent in the eradication group (P = 0.031, P < 0.001, P < 0.001, respectively). Non-neoplastic epithelium covered more than 10 % of the cancerous area more frequently in the eradication group. In the eradication group, more than 90 % of cancers showing a gastritis-like appearance had non-neoplastic epithelium extending over 10 % of the cancerous area. Gastric cancer after successful H. pylori eradication tends to have gastritis-like features due to non-neoplastic epithelium covering the cancerous tissue.

  17. Computerized lung cancer malignancy level analysis using 3D texture features

    NASA Astrophysics Data System (ADS)

    Sun, Wenqing; Huang, Xia; Tseng, Tzu-Liang; Zhang, Jianying; Qian, Wei

    2016-03-01

    Based on the likelihood of malignancy, the nodules are classified into five different levels in Lung Image Database Consortium (LIDC) database. In this study, we tested the possibility of using threedimensional (3D) texture features to identify the malignancy level of each nodule. Five groups of features were implemented and tested on 172 nodules with confident malignancy levels from four radiologists. These five feature groups are: grey level co-occurrence matrix (GLCM) features, local binary pattern (LBP) features, scale-invariant feature transform (SIFT) features, steerable features, and wavelet features. Because of the high dimensionality of our proposed features, multidimensional scaling (MDS) was used for dimension reduction. RUSBoost was applied for our extracted features for classification, due to its advantages in handling imbalanced dataset. Each group of features and the final combined features were used to classify nodules highly suspicious for cancer (level 5) and moderately suspicious (level 4). The results showed that the area under the curve (AUC) and accuracy are 0.7659 and 0.8365 when using the finalized features. These features were also tested on differentiating benign and malignant cases, and the reported AUC and accuracy were 0.8901 and 0.9353.

  18. Using cell nuclei features to detect colon cancer tissue in hematoxylin and eosin stained slides.

    PubMed

    Jørgensen, Alex Skovsbo; Rasmussen, Anders Munk; Andersen, Niels Kristian Mäkinen; Andersen, Simon Kragh; Emborg, Jonas; Røge, Rasmus; Østergaard, Lasse Riis

    2017-08-01

    Currently, diagnosis of colon cancer is based on manual examination of histopathological images by a pathologist. This can be time consuming and interpretation of the images is subject to inter- and intra-observer variability. This may be improved by introducing a computer-aided diagnosis (CAD) system for automatic detection of cancer tissue within whole slide hematoxylin and eosin (H&E) stains. Cancer disrupts the normal control mechanisms of cell proliferation and differentiation, affecting the structure and appearance of the cells. Therefore, extracting features from segmented cell nuclei structures may provide useful information to detect cancer tissue. A framework for automatic classification of regions of interest (ROI) containing either benign or cancerous colon tissue extracted from whole slide H&E stained images using cell nuclei features was proposed. A total of 1,596 ROI's were extracted from 87 whole slide H&E stains (44 benign and 43 cancer). A cell nuclei segmentation algorithm consisting of color deconvolution, k-means clustering, local adaptive thresholding, and cell separation was performed within the ROI's to extract cell nuclei features. From the segmented cell nuclei structures a total of 750 texture and intensity-based features were extracted for classification of the ROI's. The nine most discriminative cell nuclei features were used in a random forest classifier to determine if the ROI's contained benign or cancer tissue. The ROI classification obtained an area under the curve (AUC) of 0.96, sensitivity of 0.88, specificity of 0.92, and accuracy of 0.91 using an optimized threshold. The developed framework showed promising results in using cell nuclei features to classify ROIs into containing benign or cancer tissue in H&E stained tissue samples. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

  19. Modified Bat Algorithm for Feature Selection with the Wisconsin Diagnosis Breast Cancer (WDBC) Dataset

    PubMed

    Jeyasingh, Suganthi; Veluchamy, Malathi

    2017-05-01

    Early diagnosis of breast cancer is essential to save lives of patients. Usually, medical datasets include a large variety of data that can lead to confusion during diagnosis. The Knowledge Discovery on Database (KDD) process helps to improve efficiency. It requires elimination of inappropriate and repeated data from the dataset before final diagnosis. This can be done using any of the feature selection algorithms available in data mining. Feature selection is considered as a vital step to increase the classification accuracy. This paper proposes a Modified Bat Algorithm (MBA) for feature selection to eliminate irrelevant features from an original dataset. The Bat algorithm was modified using simple random sampling to select the random instances from the dataset. Ranking was with the global best features to recognize the predominant features available in the dataset. The selected features are used to train a Random Forest (RF) classification algorithm. The MBA feature selection algorithm enhanced the classification accuracy of RF in identifying the occurrence of breast cancer. The Wisconsin Diagnosis Breast Cancer Dataset (WDBC) was used for estimating the performance analysis of the proposed MBA feature selection algorithm. The proposed algorithm achieved better performance in terms of Kappa statistic, Mathew’s Correlation Coefficient, Precision, F-measure, Recall, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Relative Absolute Error (RAE) and Root Relative Squared Error (RRSE). Creative Commons Attribution License

  20. Asymmetry features for classification of thermograms in breast cancer detection

    NASA Astrophysics Data System (ADS)

    Nowak, Robert M.; Okuniewski, Rafał; Oleszkiewicz, Witold; Cichosz, Paweł; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz

    2016-09-01

    The computer system for an automatic interpretation of thermographic pictures created by the Br-aster devices uses image processing and machine learning algorithms. The huge set of attributes analyzed by this software includes the asymmetry measurements between corresponding images, and these features are analyzed in presented paper. The system was tested on real data and achieves accuracy comparable to other popular techniques used for breast tumour detection.

  1. Robustness of chemometrics-based feature selection methods in early cancer detection and biomarker discovery.

    PubMed

    Lee, Hae Woo; Lawton, Carl; Na, Young Jeong; Yoon, Seongkyu

    2013-03-13

    In omics studies aimed at the early detection and diagnosis of cancer, bioinformatics tools play a significant role when analyzing high dimensional, complex datasets, as well as when identifying a small set of biomarkers. However, in many cases, there are ambiguities in the robustness and the consistency of the discovered biomarker sets, since the feature selection methods often lead to irreproducible results. To address this, both the stability and the classification power of several chemometrics-based feature selection algorithms were evaluated using the Monte Carlo sampling technique, aiming at finding the most suitable feature selection methods for early cancer detection and biomarker discovery. To this end, two data sets were analyzed, which comprised of MALDI-TOF-MS and LC/TOF-MS spectra measured on serum samples in order to diagnose ovarian cancer. Using these datasets, the stability and the classification power of multiple feature subsets found by different feature selection methods were quantified by varying either the number of selected features, or the number of samples in the training set, with special emphasis placed on the property of stability. The results show that high consistency does not necessarily guarantee high predictive power. In addition, differences in the stability, as well as agreement in feature lists between several feature selection methods, depend on several factors, such as the number of available samples, feature sizes, quality of the information in the dataset, etc. Among the tested methods, only the variable importance in projection (VIP)-based method shows complementary properties, providing both highly consistent and accurate subsets of features. In addition, successive projection analysis (SPA) was excellent with regards to maintaining high stability over a wide range of experimental conditions. The stability of several feature selection methods is highly variable, stressing the importance of making the proper choice among

  2. MicroRNAs: molecular features and role in cancer

    PubMed Central

    Lages, Elodie; Ipas, Hélène; Guttin, Audrey; Nesr, Houssam; Berger, François; Issartel, Jean-Paul

    2012-01-01

    microRNAs (miRNAs) are small noncoding endogenously produced RNAs that play key roles in controlling the expression of many cellular proteins. Once they are recruited and incorporated into a ribonucleoprotein complex miRISC, they can target specific mRNAs in a miRNA sequence-dependent process and interfere in the translation into proteins of the targeted mRNAs via several mechanisms. Consequently, miRNAs can regulate many cellular pathways and processes. Dysregulation of their physiological roles may largely contribute to disease. In particular, in cancer, miRNAs can be involved in the deregulation of the expression of important genes that play key roles in tumorigenesis, tumor development, and angiogenesis and have oncogenic or tumor suppressor roles. This review focuses on the biogenesis and maturation of miRNAs, their mechanisms of gene regulation, and the way their expression is deregulated in cancer. The involvement of miRNAs in several oncogenic pathways such as angiogenesis and apoptosis, and in the inter-cellular dialog mediated by miRNA-loaded exosomes as well as the development of new therapeutical strategies based on miRNAs will be discussed. PMID:22652795

  3. Targeting Breast Cancers Featuring Activating Mutations in PIK3CA by Generating a Lethal Dose of PIP3

    DTIC Science & Technology

    2009-02-01

    AD_________________ AWARD NUMBER: W81XWH-06-1-0341 TITLE: Targeting Breast Cancers Featuring...ORGANIZATION: Dana-Farber Cancer Institute Boston, MA 02115 REPORT DATE...2006 – 31 Jan 2009 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Targeting Breast Cancers Featuring Activating Mutations in PIK3CA by Generating a

  4. A Retrospective Study on Pathologic Features and Racial Disparities in Prostate Cancer

    PubMed Central

    Bigler, Steven A.; Pound, Charles R.; Zhou, Xinchun

    2011-01-01

    We reviewed more than 3,000 pathology reports on prostate cancer-related surgical specimens and analyzed racial disparities in histological and clinical features at the time of initial biopsy, diagnosis of prostate cancer, and prostatectomy, as well as in characteristics of tumor evolution between African American and Caucasian patients. As compared to Caucasians, African American patients had younger age, higher cancer detection rate, higher Gleason score of prostate cancer, and more bilateral involvement of the prostate. African Americans also had larger prostates, greater volume of tumor, and more positive margins. The diagnosis of HGPIN or ASAP in prostate biopsies and African American race conferred an increased risk of diagnosis of prostate cancer. The interval between prior noncancerous biopsy and the subsequent biopsy with diagnosis of prostate cancer was shorter in men with HGPIN, with ASAP, or of African American race. PMID:22135747

  5. The clinicopathological features of second primary cancer in patients with prior breast cancer.

    PubMed

    Liu, YiHui; Dong, ChunHui; Chen, Ling

    2017-04-01

    Nowadays, the risk of developing second primary cancers among women diagnosed with prior breast cancer represents a public health issue worldwide.Twenty-eight cases of the primary breast cancer with the multiple primary cancers (MPC) between 2008 and 2015 at our hospital were retrospectively analyzed in regards to age of patients, family history, interval time of the 2 cancers, and survival time of these patients.A total 28 cases were analyzed, at the mean age of 44.57 years at the diagnosis of the first primary cancer. The most common primary cancer in these breast cancer patients was contralateral breast cancer. Of 28 patients with breast cancer, 16 developed a second malignant tumor of the opposite breast, there were no significant difference both median age at first breast cancer and second breast cancer (P > .05). The difference of interval time of 2 cancers also had no statistical significance. There was no statistically significant difference in overall survival between the bilateral primary breast cancers (BPBC) group and the group of breast cancer patients who diagnosed with another cancer (P > .05). If we grouped patients age of diagnosed with the first cancer (<45, ≥45 years), no statistical different between 2 groups (P > .05). However, the survival time with positive-node patients was lower than in patients with node-negative, the difference had a notable significant difference (P < .01). And there are 3 cases had a positive family history for malignant tumor in the form of first-degree relative.Multiple primary carcinoma in patients with prior breast cancer is not the influencing factor of prognosis. It is crucial to detect, diagnose, and treat cancers at their early stage for improving the cure rate of cancer and the survival rate of patients.

  6. Detection and Classification of Cancer from Microscopic Biopsy Images Using Clinically Significant and Biologically Interpretable Features

    PubMed Central

    Kumar, Rajesh; Srivastava, Subodh

    2015-01-01

    A framework for automated detection and classification of cancer from microscopic biopsy images using clinically significant and biologically interpretable features is proposed and examined. The various stages involved in the proposed methodology include enhancement of microscopic images, segmentation of background cells, features extraction, and finally the classification. An appropriate and efficient method is employed in each of the design steps of the proposed framework after making a comparative analysis of commonly used method in each category. For highlighting the details of the tissue and structures, the contrast limited adaptive histogram equalization approach is used. For the segmentation of background cells, k-means segmentation algorithm is used because it performs better in comparison to other commonly used segmentation methods. In feature extraction phase, it is proposed to extract various biologically interpretable and clinically significant shapes as well as morphology based features from the segmented images. These include gray level texture features, color based features, color gray level texture features, Law's Texture Energy based features, Tamura's features, and wavelet features. Finally, the K-nearest neighborhood method is used for classification of images into normal and cancerous categories because it is performing better in comparison to other commonly used methods for this application. The performance of the proposed framework is evaluated using well-known parameters for four fundamental tissues (connective, epithelial, muscular, and nervous) of randomly selected 1000 microscopic biopsy images. PMID:27006938

  7. Classification of lung cancer using ensemble-based feature selection and machine learning methods.

    PubMed

    Cai, Zhihua; Xu, Dong; Zhang, Qing; Zhang, Jiexia; Ngai, Sai-Ming; Shao, Jianlin

    2015-03-01

    Lung cancer is one of the leading causes of death worldwide. There are three major types of lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and carcinoid. NSCLC is further classified into lung adenocarcinoma (LADC), squamous cell lung cancer (SQCLC) as well as large cell lung cancer. Many previous studies demonstrated that DNA methylation has emerged as potential lung cancer-specific biomarkers. However, whether there exists a set of DNA methylation markers simultaneously distinguishing such three types of lung cancers remains elusive. In the present study, ROC (Receiving Operating Curve), RFs (Random Forests) and mRMR (Maximum Relevancy and Minimum Redundancy) were proposed to capture the unbiased, informative as well as compact molecular signatures followed by machine learning methods to classify LADC, SQCLC and SCLC. As a result, a panel of 16 DNA methylation markers exhibits an ideal classification power with an accuracy of 86.54%, 84.6% and a recall 84.37%, 85.5% in the leave-one-out cross-validation (LOOCV) and independent data set test experiments, respectively. Besides, comparison results indicate that ensemble-based feature selection methods outperform individual ones when combined with the incremental feature selection (IFS) strategy in terms of the informative and compact property of features. Taken together, results obtained suggest the effectiveness of the ensemble-based feature selection approach and the possible existence of a common panel of DNA methylation markers among such three types of lung cancer tissue, which would facilitate clinical diagnosis and treatment.

  8. Estimation of T2* Relaxation Time of Breast Cancer: Correlation with Clinical, Imaging and Pathological Features

    PubMed Central

    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

  9. Estimation of T2* Relaxation Time of Breast Cancer: Correlation with Clinical, Imaging and Pathological Features.

    PubMed

    Seo, Mirinae; Ryu, Jung Kyu; Jahng, Geon-Ho; Sohn, Yu-Mee; Rhee, Sun Jung; Oh, Jang-Hoon; Won, Kyu-Yeoun

    2017-01-01

    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. 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. 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). 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.

  10. Breast Cancer Classification From Histological Images with Multiple Features and Random Subspace Classifier Ensemble

    NASA Astrophysics Data System (ADS)

    Zhang, Yungang; Zhang, Bailing; Lu, Wenjin

    2011-06-01

    Histological image is important for diagnosis of breast cancer. In this paper, we present a novel automatic breaset cancer classification scheme based on histological images. The image features are extracted using the Curvelet Transform, statistics of Gray Level Co-occurence Matrix (GLCM) and Completed Local Binary Patterns (CLBP), respectively. The three different features are combined together and used for classification. A classifier ensemble approach, called Random Subspace Ensemble (RSE), are used to select and aggregate a set of base neural network classifiers for classification. The proposed multiple features and random subspace ensemble offer the classification rate 95.22% on a publically available breast cancer image dataset, which compares favorably with the previously published result 93.4%.

  11. Lowered circulating aspartate is a metabolic feature of human breast cancer

    PubMed Central

    Xie, Guoxiang; Zhou, Bingsen; Zhao, Aihua; Qiu, Yunping; Zhao, Xueqing; Garmire, Lana; Shvetsov, Yurii B.; Yu, Herbert; Yen, Yun; Jia, Wei

    2015-01-01

    Distinct metabolic transformation is essential for cancer cells to sustain a high rate of proliferation and resist cell death signals. Such a metabolic transformation results in unique cellular metabolic phenotypes that are often reflected by distinct metabolite signatures in tumor tissues as well as circulating blood. Using a metabolomics platform, we find that breast cancer is associated with significantly (p = 6.27E-13) lowered plasma aspartate levels in a training group comprising 35 breast cancer patients and 35 controls. The result was validated with 103 plasma samples and 183 serum samples of two groups of primary breast cancer patients. Such a lowered aspartate level is specific to breast cancer as it has shown 0% sensitivity in serum from gastric (n = 114) and colorectal (n = 101) cancer patients. There was a significantly higher level of aspartate in breast cancer tissues (n = 20) than in adjacent non-tumor tissues, and in MCF-7 breast cancer cell line than in MCF-10A cell lines, suggesting that the depleted level of aspartate in blood of breast cancer patients is due to increased tumor aspartate utilization. Together, these findings suggest that lowed circulating aspartate is a key metabolic feature of human breast cancer. PMID:26452258

  12. Ovarian and breast cancer spheres are similar in transcriptomic features and sensitive to fenretinide.

    PubMed

    Wang, Haiwei; Zhang, Yuxing; Du, Yanzhi

    2013-01-01

    Cancer stem cells (CSCs) are resistant to chemotherapy and are ability to regenerate cancer cell populations, thus attracting much attention in cancer research. In this report, we first demonstrated that sphere cells from ovarian cancer cell line A2780 shared many features of CSCs, such as resistance to cisplatin and able to initiate tumors in an efficient manner. Then, we conducted cDNA microarray analysis on spheres from ovarian A2780 cells, and from breast MCF7 and SUM159 cells, and found that molecular pathways underlying spheres from these cancer cell lines were similar to a large extent, suggesting that similar mechanisms are involved in the genesis of CSCs in both ovarian and breast cancer types. In addition, we showed that spheres from these cancer types were highly sensitive to fenretinide, a stimulus of oxidative stress-mediated apoptosis in cancer cells. Thus, our results not only provide important insights into mechanisms underlying CSCs in ovarian and breast cancer, but also lead to the development of more sophisticated protocols of cancer therapy in near future.

  13. Ovarian and Breast Cancer Spheres Are Similar in Transcriptomic Features and Sensitive to Fenretinide

    PubMed Central

    Wang, Haiwei; Zhang, Yuxing; Du, Yanzhi

    2013-01-01

    Cancer stem cells (CSCs) are resistant to chemotherapy and are ability to regenerate cancer cell populations, thus attracting much attention in cancer research. In this report, we first demonstrated that sphere cells from ovarian cancer cell line A2780 shared many features of CSCs, such as resistance to cisplatin and able to initiate tumors in an efficient manner. Then, we conducted cDNA microarray analysis on spheres from ovarian A2780 cells, and from breast MCF7 and SUM159 cells, and found that molecular pathways underlying spheres from these cancer cell lines were similar to a large extent, suggesting that similar mechanisms are involved in the genesis of CSCs in both ovarian and breast cancer types. In addition, we showed that spheres from these cancer types were highly sensitive to fenretinide, a stimulus of oxidative stress-mediated apoptosis in cancer cells. Thus, our results not only provide important insights into mechanisms underlying CSCs in ovarian and breast cancer, but also lead to the development of more sophisticated protocols of cancer therapy in near future. PMID:24222909

  14. Association of Fusobacterium species in pancreatic cancer tissues with molecular features and prognosis.

    PubMed

    Mitsuhashi, Kei; Nosho, Katsuhiko; Sukawa, Yasutaka; Matsunaga, Yasutaka; Ito, Miki; Kurihara, Hiroyoshi; Kanno, Shinichi; Igarashi, Hisayoshi; Naito, Takafumi; Adachi, Yasushi; Tachibana, Mami; Tanuma, Tokuma; Maguchi, Hiroyuki; Shinohara, Toshiya; Hasegawa, Tadashi; Imamura, Masafumi; Kimura, Yasutoshi; Hirata, Koichi; Maruyama, Reo; Suzuki, Hiromu; Imai, Kohzoh; Yamamoto, Hiroyuki; Shinomura, Yasuhisa

    2015-03-30

    Recently, bacterial infection causing periodontal disease has attracted considerable attention as a risk factor for pancreatic cancer. Fusobacterium species is an oral bacterial group of the human microbiome. Some evidence suggests that Fusobacterium species promote colorectal cancer development; however, no previous studies have reported the association between Fusobacterium species and pancreatic cancer. Therefore, we examined whether Fusobacterium species exist in pancreatic cancer tissue. Using a database of 283 patients with pancreatic ductal adenocarcinoma (PDAC), we tested cancer tissue specimens for Fusobacterium species. We also tested the specimens for KRAS, NRAS, BRAF and PIK3CA mutations and measured microRNA-21 and microRNA-31. In addition, we assessed epigenetic alterations, including CpG island methylator phenotype (CIMP). Our data showed an 8.8% detection rate of Fusobacterium species in pancreatic cancers; however, tumor Fusobacterium status was not associated with any clinical and molecular features. In contrast, in multivariate Cox regression analysis, compared with the Fusobacterium species-negative group, we observed significantly higher cancer-specific mortality rates in the positive group (p = 0.023). In conclusion, Fusobacterium species were detected in pancreatic cancer tissue. Tumor Fusobacterium species status is independently associated with a worse prognosis of pancreatic cancer, suggesting that Fusobacterium species may be a prognostic biomarker of pancreatic cancer.

  15. Lowered circulating aspartate is a metabolic feature of human breast cancer.

    PubMed

    Xie, Guoxiang; Zhou, Bingsen; Zhao, Aihua; Qiu, Yunping; Zhao, Xueqing; Garmire, Lana; Shvetsov, Yurii B; Yu, Herbert; Yen, Yun; Jia, Wei

    2015-10-20

    Distinct metabolic transformation is essential for cancer cells to sustain a high rate of proliferation and resist cell death signals. Such a metabolic transformation results in unique cellular metabolic phenotypes that are often reflected by distinct metabolite signatures in tumor tissues as well as circulating blood. Using a metabolomics platform, we find that breast cancer is associated with significantly (p = 6.27E-13) lowered plasma aspartate levels in a training group comprising 35 breast cancer patients and 35 controls. The result was validated with 103 plasma samples and 183 serum samples of two groups of primary breast cancer patients. Such a lowered aspartate level is specific to breast cancer as it has shown 0% sensitivity in serum from gastric (n = 114) and colorectal (n = 101) cancer patients. There was a significantly higher level of aspartate in breast cancer tissues (n = 20) than in adjacent non-tumor tissues, and in MCF-7 breast cancer cell line than in MCF-10A cell lines, suggesting that the depleted level of aspartate in blood of breast cancer patients is due to increased tumor aspartate utilization. Together, these findings suggest that lowed circulating aspartate is a key metabolic feature of human breast cancer.

  16. Breast Cancer Arising Adjacent to an Involuting Fibroadenoma: Serial Changes in Radiologic Features.

    PubMed

    Park, Chae Jung; Kim, Eun-Kyung; Woo, Ha Young; Moon, Hee Jung; Yoon, Jung Hyun; Kim, Min Jung

    2015-09-01

    Fibroadenoma is a common benign breast lesion and its malignant transformation is rare. There have been several case reports and studies that retrospectively reviewed breast cancers that arose within fibroadenomas; however, none of these studies reported serial changes in radiologic features of the cancer, including findings from mammography and ultrasound (US). We report a case of breast cancer arising adjacent to an involuting fibro adenoma in a 39-year-old woman who was undergoing serial follow-up after her fibroadenoma was diagnosed. Seven years after her diagnosis, the lesion showed evidence of coarse calcifications, a typical sign of involution. Four years later, US revealed a newly developed hypoechoic lesion with irregular margins and peripherally located calcifications adjacent to the fibroadenoma. A core biopsy was performed, and histopathological examination resulted in a diagnosis of invasive ductal carcinoma. When new suspicious features are observed in a fibroadenoma, radiologists should raise the concern for breast cancer and proceed with diagnosis and treatment accordingly.

  17. Incorporating higher-order representative features improves prediction in network-based cancer prognosis analysis.

    PubMed

    Ma, Shuangge; Kosorok, Michael R; Huang, Jian; Dai, Ying

    2011-01-12

    In cancer prognosis studies with gene expression measurements, an important goal is to construct gene signatures with predictive power. In this study, we describe the coordination among genes using the weighted coexpression network, where nodes represent genes and nodes are connected if the corresponding genes have similar expression patterns across samples. There are subsets of nodes, called modules, that are tightly connected to each other. In several published studies, it has been suggested that the first principal components of individual modules, also referred to as "eigengenes", may sufficiently represent the corresponding modules. In this article, we refer to principal components and their functions as representative features". We investigate higher-order representative features, which include the principal components other than the first ones and second order terms (quadratics and interactions). Two gradient thresholding methods are adopted for regularized estimation and feature selection. Analysis of six prognosis studies on lymphoma and breast cancer shows that incorporating higher-order representative features improves prediction performance over using eigengenes only. Simulation study further shows that prediction performance can be less satisfactory if the representative feature set is not properly chosen. This study introduces multiple ways of defining the representative features and effective thresholding regularized estimation approaches. It provides convincing evidence that the higher-order representative features may have important implications for the prediction of cancer prognosis.

  18. Incorporating higher-order representative features improves prediction in network-based cancer prognosis analysis

    PubMed Central

    2011-01-01

    Background In cancer prognosis studies with gene expression measurements, an important goal is to construct gene signatures with predictive power. In this study, we describe the coordination among genes using the weighted coexpression network, where nodes represent genes and nodes are connected if the corresponding genes have similar expression patterns across samples. There are subsets of nodes, called modules, that are tightly connected to each other. In several published studies, it has been suggested that the first principal components of individual modules, also referred to as "eigengenes", may sufficiently represent the corresponding modules. Results In this article, we refer to principal components and their functions as representative features". We investigate higher-order representative features, which include the principal components other than the first ones and second order terms (quadratics and interactions). Two gradient thresholding methods are adopted for regularized estimation and feature selection. Analysis of six prognosis studies on lymphoma and breast cancer shows that incorporating higher-order representative features improves prediction performance over using eigengenes only. Simulation study further shows that prediction performance can be less satisfactory if the representative feature set is not properly chosen. Conclusions This study introduces multiple ways of defining the representative features and effective thresholding regularized estimation approaches. It provides convincing evidence that the higher-order representative features may have important implications for the prediction of cancer prognosis. PMID:21226928

  19. Influence of feature set reduction on breast cancer malignancy classification of fine needle aspiration biopsies.

    PubMed

    Jeleń, Łukasz; Krzyżak, Adam; Fevens, Thomas; Jeleń, Michał

    2016-12-01

    Grading of breast cancer malignancy is a key step in its diagnosis, which in turn helps to determine its prognosis and a course of treatment. In this paper, we consider the application of pattern recognition and image processing techniques to perform computer-assisted automatic breast cancer malignancy grading from cytological slides of fine needle aspiration biopsies. To determine a classification of the malignancy of the slide, a feature set is first determined from imagery of the slides. In this paper we investigated the nature of a wide set of features extracted from biopsy images to determine their discriminatory power and cross-correlation. Feature vector reduction is studied using a correlation map of the features, determining discriminatory power using the Kolmogorov-Smirnov test, significant feature selection, and stepwise feature selection. The reduction of the feature vector simplifies the complexity of classification scheme and does not impair the classification accuracy. In some cases a decrease of the error rate is noted. Based on this analysis, we present an improved classification system for cancer malignancy grading. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Correlation of SASH1 expression and ultrasonographic features in breast cancer

    PubMed Central

    Gong, Xuchu; Wu, Jinna; Wu, Jian; Liu, Jun; Gu, Hailin; Shen, Hao

    2017-01-01

    Objective SASH1 is a member of the SH3/SAM adapter molecules family and has been identified as a new tumor suppressor and critical protein in signal transduction. An ectopic expression of SASH1 is associated with decreased cell viability of breast cancer. The aim of this study was to explore the association between SASH1 expression and the ultrasonographic features in breast cancer. Patients and methods A total of 186 patients diagnosed with breast cancer were included in this study. The patients received preoperative ultrasound examination, and the expression of SASH1 was determined using immunohistochemistry methods. Spearman’s rank correlation analysis was used to analyze the correlation between SASH1-positive expression and the ultrasonographic features. Results The positive expression of SASH1 was observed in 63 (33.9%) patients. The positive expression rate of SASH1 was significantly decreased in patients with breast cancer (63/186, 33.9%) compared with controls (P<0.001). The positive expression rate of SASH1 was significantly decreased in patients with edge burr sign (P=0.025), lymph node metastasis (P=0.007), and a blood flow grade of III (P=0.013) compared with patients without those adverse ultrasonographic features. The expression of SASH1 was negatively correlated with edge burr sign (P=0.025), lymph node metastasis (P=0.007), and blood flow grade (P=0.003) of the patients with breast cancer. Conclusion The expression of SASH1 was inversely correlated with some critical ultrasonographic features, including edge burr sign, lymph node metastasis, and blood flow grade in breast cancer, and decreased SASH1 expression appears to be associated with adverse clinical and imaging features in breast cancer. PMID:28138250

  1. Correlation of SASH1 expression and ultrasonographic features in breast cancer.

    PubMed

    Gong, Xuchu; Wu, Jinna; Wu, Jian; Liu, Jun; Gu, Hailin; Shen, Hao

    2017-01-01

    SASH1 is a member of the SH3/SAM adapter molecules family and has been identified as a new tumor suppressor and critical protein in signal transduction. An ectopic expression of SASH1 is associated with decreased cell viability of breast cancer. The aim of this study was to explore the association between SASH1 expression and the ultrasonographic features in breast cancer. A total of 186 patients diagnosed with breast cancer were included in this study. The patients received preoperative ultrasound examination, and the expression of SASH1 was determined using immunohistochemistry methods. Spearman's rank correlation analysis was used to analyze the correlation between SASH1-positive expression and the ultrasonographic features. The positive expression of SASH1 was observed in 63 (33.9%) patients. The positive expression rate of SASH1 was significantly decreased in patients with breast cancer (63/186, 33.9%) compared with controls (P<0.001). The positive expression rate of SASH1 was significantly decreased in patients with edge burr sign (P=0.025), lymph node metastasis (P=0.007), and a blood flow grade of III (P=0.013) compared with patients without those adverse ultrasonographic features. The expression of SASH1 was negatively correlated with edge burr sign (P=0.025), lymph node metastasis (P=0.007), and blood flow grade (P=0.003) of the patients with breast cancer. The expression of SASH1 was inversely correlated with some critical ultrasonographic features, including edge burr sign, lymph node metastasis, and blood flow grade in breast cancer, and decreased SASH1 expression appears to be associated with adverse clinical and imaging features in breast cancer.

  2. Exploring new quantitative CT image features to improve assessment of lung cancer prognosis

    NASA Astrophysics Data System (ADS)

    Emaminejad, Nastaran; Qian, Wei; Kang, Yan; Guan, Yubao; Lure, Fleming; Zheng, Bin

    2015-03-01

    Due to the promotion of lung cancer screening, more Stage I non-small-cell lung cancers (NSCLC) are currently detected, which usually have favorable prognosis. However, a high percentage of the patients have cancer recurrence after surgery, which reduces overall survival rate. To achieve optimal efficacy of treating and managing Stage I NSCLC patients, it is important to develop more accurate and reliable biomarkers or tools to predict cancer prognosis. The purpose of this study is to investigate a new quantitative image analysis method to predict the risk of lung cancer recurrence of Stage I NSCLC patients after the lung cancer surgery using the conventional chest computed tomography (CT) images and compare the prediction result with a popular genetic biomarker namely, protein expression of the excision repair cross-complementing 1 (ERCC1) genes. In this study, we developed and tested a new computer-aided detection (CAD) scheme to segment lung tumors and initially compute 35 tumor-related morphologic and texture features from CT images. By applying a machine learning based feature selection method, we identified a set of 8 effective and non-redundant image features. Using these features we trained a naïve Bayesian network based classifier to predict the risk of cancer recurrence. When applying to a test dataset with 79 Stage I NSCLC cases, the computed areas under ROC curves were 0.77±0.06 and 0.63±0.07 when using the quantitative image based classifier and ERCC1, respectively. The study results demonstrated the feasibility of improving accuracy of predicting cancer prognosis or recurrence risk using a CAD-based quantitative image analysis method.

  3. Imaging features of sporadic breast cancer in women under 40 years old: 97 cases.

    PubMed

    Bullier, Bénédicte; MacGrogan, Gaétan; Bonnefoi, Hervé; Hurtevent-Labrot, Gabrielle; Lhomme, Edouard; Brouste, Véronique; Boisserie-Lacroix, Martine

    2013-12-01

    To evaluate characteristic features of mammography, ultrasound and magnetic resonance imaging (MRI) of sporadic breast cancer in women <40 years and to determine correlations with pathological and biological factors. A retrospective review of radiological, clinicopathological and biological features of sporadic breast cancers for women under 40 years at our institution between 2007-2012 covering 91 patients. Mammography was available for 97 lesions, ultrasound for 94 and MRI for 38. The most common imaging features were masses, nearly all classified BI-RADS 4 or 5. On mammography microcalcifications alone accounted for 31 %, all suspicious. There were 42.6 % luminal B, 24.5 % luminal A, 19.1 % HER2-enriched and 10.6 % triple-negative (TN) tumours by immunohistochemistry. HER2 overexpression was correlated with the presence of calcifications at mammography (P = 0.03). TN cancers more often had an oval shape and abrupt interface at ultrasound and rim enhancement on MRI. MRI features were suspicious for all cancers and rim enhancement of a mass was a significant predictor of triple-negative tumours (P = 0.01). The imaging characteristics of cancers in patients under 40 years without proven gene mutations do not differ from their older counterparts, but appear correlated to phenotypic profiles, which have a different distribution in young women compared to the general population.

  4. Effect of metabolic syndrome on pathologic features of prostate cancer.

    PubMed

    Kheterpal, Emil; Sammon, Jesse D; Diaz, Mireya; Bhandari, Akshay; Trinh, Quoc-Dien; Pokala, Naveen; Sharma, Pranav; Menon, Mani; Agarwal, Piyush K

    2013-10-01

    The prevalence of metabolic syndrome has been increasing worldwide, however its association with prostate cancer (CaP) is unclear. We reviewed patients undergoing robot assisted radical prostatectomy (RARP) to evaluate if those with metabolic syndrome had more aggressive disease. A prospective database of patients undergoing RARP between January 2005 and December 2008 (n = 2756) was queried for components of metabolic syndrome (BMI ≥ 30 and ≥ 2 of the following: hypertension, diabetes or elevated blood glucose, and dyslipidemia; n = 357). Patients with no components of metabolic syndrome were used as controls (n = 694). Biopsy and final pathology were compared between the 2 groups using all controls, and using best-matched controls (n = 357) based on greedy matching by propensity score. Compared with unmatched controls, metabolic syndrome patients had higher pathology Gleason grade (≥ 7: 78% vs. 64%, P < 0.001) and higher pathologic stage (≥ T3 disease: 43% vs. 31%, P < 0.001). After controlling for confounders, those with metabolic syndrome when compared with best-matched controls had maintained the greater pathology Gleason grade (≥ 7: 78% vs. 64%, P < 0.001) and pathologic stage (≥ T3 disease: 43% vs. 32%, P < 0.001). They also had significantly greater pathologic upgrading of Gleason grade 6 adenocarcinoma found on biopsy compared with best-matched controls (63% vs. 45%, P < 0.001). On pathology, a 2-fold increase in Gleason 8 and greater was noted between patients with metabolic syndrome and best-matched controls (15% vs. 8%). After controlling for confounders, patients with metabolic syndrome were found to have higher Gleason grade and tumor stage on final pathology and were more likely to have upgrading. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Correlation of NGX6 expression with clinicopathologic features and prognosis in colon cancer.

    PubMed

    Xiao, Jidong; Zhou, Yuanquan; Liu, Bo

    2015-01-01

    The aim was to explore the correlation of NGX6 expression with clinicopathological features and prognosis in colon cancer. Clinicopathological feature of 145 patients with colon cancer were analyzed.NGX6 expression was measured using immunohistochemistry methods. The correlation of NGX6 expression with clinicopathological features and prognosis were assessed. Among 145 cases of colon cancer, NGX6 positive expression were found in 76 (52.4%) cases and NGX6 negative expression were found in 69 (47.6%) cases. The expression of NGX6 was closely associated with size tumor, lymph node metastasis and TNM stage (P=0.002, 0.012, and 0.039, respectively). Kaplan-Meier analysis showed that NGX6 negative expression was associated with shorter disease-free survival (DFS) (P=0.029) and overall survival (OS) (P=0.015). Multivariate survival analysis demonstrated that NGX6 expression was the important independent prognostic factor for colon cancer (P=0.022). NGX6 is involved in the invasion and metastasis activity of colon cancer. NGX6 could may be applied as a novel and promising prognostic marker for colon cancer.

  6. Feature selection and definition for contours classification of thermograms in breast cancer detection

    NASA Astrophysics Data System (ADS)

    Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał; Oleszkiewicz, Witold; Cichosz, Paweł

    2016-09-01

    This contribution introduces the method of cancer pathologies detection on breast skin temperature distribution images. The use of thermosensitive foils applied to the breasts skin allows to create thermograms, which displays the amount of infrared energy emitted by all breast cells. The significant foci of hyperthermia or inflammation are typical for cancer cells. That foci can be recognized on thermograms as a contours, which are the areas of higher temperature. Every contour can be converted to a feature set that describe it, using the raw, central, Hu, outline, Fourier and colour moments of image pixels processing. This paper defines also the new way of describing a set of contours through theirs neighbourhood relations. Contribution introduces moreover the way of ranking and selecting most relevant features. Authors used Neural Network with Gevrey`s concept and recursive feature elimination, to estimate feature importance.

  7. Multi-parametric MR imaging of transition zone prostate cancer: Imaging features, detection and staging

    PubMed Central

    Kayhan, Arda; Fan, Xiaobing; Oommen, Jacob; Oto, Aytekin

    2010-01-01

    Magnetic resonance (MR) imaging has been increasingly used in the evaluation of prostate cancer. As studies have suggested that the majority of cancers arise from the peripheral zone (PZ), MR imaging has focused on the PZ of the prostate gland thus far. However, a considerable number of cancers (up to 30%) originate in the transition zone (TZ), substantially contributing to morbidity and mortality. Therefore, research is needed on the TZ of the prostate gland. Recently, MR imaging and advanced MR techniques have been gaining acceptance in evaluation of the TZ. In this article, the MR imaging features of TZ prostate cancers, the role of MR imaging in TZ cancer detection and staging, and recent advanced MR techniques will be discussed in light of the literature. PMID:21161033

  8. Clinicopathologic features and prognostic analysis of MSI-high colon cancer.

    PubMed

    Lin, Chun-Chi; Lai, Yi-Ling; Lin, Tzu-Chen; Chen, Wei-Shone; Jiang, Jeng-Kai; Yang, Shung-Haur; Wang, Huann-Sheng; Lan, Yuan-Tzu; Liang, Wen-Yih; Hsu, Hui-Mei; Lin, Jen-Kou; Chang, Shih-Ching

    2012-03-01

    The objectives of the study were to estimate the incidence and clarify the clinicopathologic feature of sporadic microsatellite instability (MSI)-high (MSI-H) colon cancer. Furthermore, the role of MSI in colon cancer prognosis was also investigated. Microsatellite status was identified by genotyping. The clinicopathologic differences between two groups (MSI-H vs. MSI-L/S) and the prognostic value of MSI were analyzed. From 1993 to 2006, 709 sporadic colon cancer patients were enrolled. MSI-H colon cancers showed significant association with poorly differentiated (28.3% vs. 7.2%, p = 0.001), proximally located (76.7% vs. 34.5%, p = 0.001), more high mucin-containing tumor (10.0% vs. 5.1%, p = 0.001) and female predominance (56.7% vs. 30.2%, p = 0.001). In multivariate analysis, MSI-H is an independent factor for better overall survival (HR, 0.459; 95% CI, 0.241-0.872, p = 0.017). Based on the hospital-based study, MSI-H colon cancers demonstrated distinguished clinicopathologic features from MSI-L/S colon cancers. MSI-H is an independent favorable prognostic factor for overall survival in colon cancer.

  9. Importance of Molecular Features of Non–Small Cell Lung Cancer for Choice of Treatment

    PubMed Central

    Moran, Cesar

    2011-01-01

    Lung cancer is the leading cause of cancer-related deaths in the United States. Approximately 85% of lung cancer is categorized as non–small cell lung cancer, and traditionally, non–small cell lung cancer has been treated with surgery, radiation, and chemotherapy. Targeted agents that inhibit the epidermal growth factor receptor pathway have been developed and integrated into the treatment regimens in non–small cell lung cancer. Currently, approved epidermal growth factor receptor inhibitors include the tyrosine kinase inhibitors erlotinib and gefitinib. Molecular determinants, such as epidermal growth factor receptor–activating mutations, have been associated with response to epidermal growth factor receptor tyrosine kinase inhibitors and may be used to guide treatment choices in patients with non–small cell lung cancer. Thus, treatment choice for patients with non–small cell lung cancer depends on molecular features of tumors; however, improved techniques are required to increase the specificity and efficiency of molecular profiling so that these methods can be incorporated into routine clinical practice. This review provides an overview of how genetic analysis is currently used to direct treatment choices in non–small cell lung cancer. PMID:21514411

  10. BRMS1 gene expression may be associated with clinico-pathological features of breast cancer.

    PubMed

    Lin, Li-Zhong; Cai, Miao-Guo; Dai, Yue-Chu; Zheng, Zhi-Bao; Jiang, Fang-Fang; Shi, Li-Li; Pan, Yin; Song, Han-Bing

    2017-08-31

    Our aim is to investigate whether or not the breast cancer metastasis suppressor 1 (BRMS1) gene expression is directly linked to clinico-pathological features of breast cancer. Following a stringent inclusion and exclusion criteria, case-control studies with associations between BRMS1 and breast cancer were selected from articles obtained by way of searches conducted through an electronic database. All statistical analyses were performed with Stata 12.0 (Stata Corp, College Station, TX, U.S.A.). Ultimately, 1,263 patients with breast cancer were found in a meta-analysis retrieved from a total that included 12 studies. Results of our meta-analysis suggested that BRMS1 protein in breast cancer tissues was significantly lower in comparison with normal breast tissues (odds ratio, OR = 0.08, 95% confidence interval (CI) = 0.04-0.15). The BRMS1 protein in metastatic breast cancer tissue was decreased than from that was found in non-metastatic breast cancer tissue (OR = 0.20, 95%CI = 0.13-0.29), and BRMS1 protein in tumor-node-metastasis (TNM) stages 1 and 2 was found to be higher than TNM stages 3 and 4 (OR = 4.62, 95%CI = 2.77-7.70). BRMS1 protein in all three major types of breast cancer was lower than that of control tissues respectively. We also found strong correlations between BRMS1 mRNA levels and TNM stage and tumor size. The results our meta-analysis showed that reduction in BRMS1 expression level was linked directly to clinico-pathological features of breast cancer significantly; therefore, suggesting the loss of expression or reduced levels of BRMS1 is potentially a strong indicator of the metastatic capacity of breast cancer with poor prognosis. © 2017 The Author(s).

  11. Quantitative Multiparametric MRI Features and PTEN Expression of Peripheral Zone Prostate Cancer: A Pilot Study.

    PubMed

    McCann, Stephanie M; Jiang, Yulei; Fan, Xiaobing; Wang, Jianing; Antic, Tatjana; Prior, Fred; VanderWeele, David; Oto, Aytekin

    2016-03-01

    The objective of our study was to investigate associations between quantitative image features of multiparametric MRI of the prostate and PTEN expression of peripheral zone prostate cancer. A total of 45 peripheral zone cancer foci from 30 patients who had undergone multiparametric prostate MRI before prostatectomy were identified by a genitourinary pathologist and a radiologist who reviewed histologic findings and MR images. Histologic sections of cancer foci underwent immunohistochemical analysis and were scored according to the percentage of tumor-positive cells expressing PTEN as negative (0-20%), mixed (20-80%), or positive (80-100%). Average and 10th percentile apparent diffusion coefficient (ADC) values, skewness of T2-weighted signal intensity histogram, and quantitative perfusion parameters (i.e., forward volume transfer constant [K(trans)], extravascular extracellular volume fraction [ve], and reverse reflux rate constant between the extracellular space and plasma [k(ep)]) from the Tofts model were calculated for each cancer focus. Associations between the quantitative image features and PTEN expression were analyzed with the Spearman rank correlation coefficient (r). Analysis of the 45 cancer foci revealed that 21 (47%) were PTEN-positive, 12 (27%) were PTEN-negative, and 12 (27%) were mixed. There was a weak but significant negative correlation between Gleason score and PTEN expression (r = -0.30, p = 0.04) and between k(ep) and PTEN expression (r = -0.35, p = 0.02). There was no significant correlation between other multiparametric MRI features and PTEN expression. This preliminary study of radiogenomics of peripheral zone prostate cancer revealed weak-but significant-associations between the quantitative dynamic contrast-enhanced MRI feature k(ep) and Gleason score with PTEN expression. These findings warrant further investigation and validation with the aim of using multiparametric MRI to improve risk assessment of patients with prostate cancer.

  12. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability.

    PubMed

    Sontrop, Herman M J; Moerland, Perry D; van den Ham, René; Reinders, Marcel J T; Verhaegh, Wim F J

    2009-11-26

    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. 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 different 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. Feature variability can have a strong impact on

  13. Radiomic analysis reveals DCE-MRI features for prediction of molecular subtypes of breast cancer.

    PubMed

    Fan, Ming; Li, Hui; Wang, Shijian; Zheng, Bin; Zhang, Juan; Li, Lihua

    2017-01-01

    The purpose of this study was to investigate the role of features derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and to incorporated clinical information to predict the molecular subtypes of breast cancer. In particular, 60 breast cancers with the following four molecular subtypes were analyzed: luminal A, luminal B, human epidermal growth factor receptor-2 (HER2)-over-expressing and basal-like. The breast region was segmented and the suspicious tumor was depicted on sequentially scanned MR images from each case. In total, 90 features were obtained, including 88 imaging features related to morphology and texture as well as dynamic features from tumor and background parenchymal enhancement (BPE) and 2 clinical information-based parameters, namely, age and menopausal status. An evolutionary algorithm was used to select an optimal subset of features for classification. Using these features, we trained a multi-class logistic regression classifier that calculated the area under the receiver operating characteristic curve (AUC). The results of a prediction model using 24 selected features showed high overall classification performance, with an AUC value of 0.869. The predictive model discriminated among the luminal A, luminal B, HER2 and basal-like subtypes, with AUC values of 0.867, 0.786, 0.888 and 0.923, respectively. An additional independent dataset with 36 patients was utilized to validate the results. A similar classification analysis of the validation dataset showed an AUC of 0.872 using 15 image features, 10 of which were identical to those from the first cohort. We identified clinical information and 3D imaging features from DCE-MRI as candidate biomarkers for discriminating among four molecular subtypes of breast cancer.

  14. Using multiscale texture and density features for near-term breast cancer risk analysis.

    PubMed

    Sun, Wenqing; Tseng, Tzu-Liang Bill; Qian, Wei; Zhang, Jianying; Saltzstein, Edward C; Zheng, Bin; Lure, Fleming; Yu, Hui; Zhou, Shi

    2015-06-01

    To help improve efficacy of screening mammography by eventually establishing a new optimal personalized screening paradigm, the authors investigated the potential of using the quantitative multiscale texture and density feature analysis of digital mammograms to predict near-term breast cancer risk. The authors' dataset includes digital mammograms acquired from 340 women. Among them, 141 were positive and 199 were negative/benign cases. The negative digital mammograms acquired from the "prior" screening examinations were used in the study. Based on the intensity value distributions, five subregions at different scales were extracted from each mammogram. Five groups of features, including density and texture features, were developed and calculated on every one of the subregions. Sequential forward floating selection was used to search for the effective combinations. Using the selected features, a support vector machine (SVM) was optimized using a tenfold validation method to predict the risk of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) was used as the performance assessment index. From a total number of 765 features computed from multiscale subregions, an optimal feature set of 12 features was selected. Applying this feature set, a SVM classifier yielded performance of AUC = 0.729 ± 0.021. The positive predictive value was 0.657 (92 of 140) and the negative predictive value was 0.755 (151 of 200). The study results demonstrated a moderately high positive association between risk prediction scores generated by the quantitative multiscale mammographic image feature analysis and the actual risk of a woman having an image-detectable breast cancer in the next subsequent examinations.

  15. Using multiscale texture and density features for near-term breast cancer risk analysis

    PubMed Central

    Sun, Wenqing; Tseng, Tzu-Liang (Bill); Qian, Wei; Zhang, Jianying; Saltzstein, Edward C.; Zheng, Bin; Lure, Fleming; Yu, Hui; Zhou, Shi

    2015-01-01

    Purpose: To help improve efficacy of screening mammography by eventually establishing a new optimal personalized screening paradigm, the authors investigated the potential of using the quantitative multiscale texture and density feature analysis of digital mammograms to predict near-term breast cancer risk. Methods: The authors’ dataset includes digital mammograms acquired from 340 women. Among them, 141 were positive and 199 were negative/benign cases. The negative digital mammograms acquired from the “prior” screening examinations were used in the study. Based on the intensity value distributions, five subregions at different scales were extracted from each mammogram. Five groups of features, including density and texture features, were developed and calculated on every one of the subregions. Sequential forward floating selection was used to search for the effective combinations. Using the selected features, a support vector machine (SVM) was optimized using a tenfold validation method to predict the risk of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) was used as the performance assessment index. Results: From a total number of 765 features computed from multiscale subregions, an optimal feature set of 12 features was selected. Applying this feature set, a SVM classifier yielded performance of AUC = 0.729 ± 0.021. The positive predictive value was 0.657 (92 of 140) and the negative predictive value was 0.755 (151 of 200). Conclusions: The study results demonstrated a moderately high positive association between risk prediction scores generated by the quantitative multiscale mammographic image feature analysis and the actual risk of a woman having an image-detectable breast cancer in the next subsequent examinations. PMID:26127038

  16. Radiomic analysis reveals DCE-MRI features for prediction of molecular subtypes of breast cancer

    PubMed Central

    Fan, Ming; Li, Hui; Wang, Shijian; Zheng, Bin; Zhang, Juan; Li, Lihua

    2017-01-01

    The purpose of this study was to investigate the role of features derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and to incorporated clinical information to predict the molecular subtypes of breast cancer. In particular, 60 breast cancers with the following four molecular subtypes were analyzed: luminal A, luminal B, human epidermal growth factor receptor-2 (HER2)-over-expressing and basal-like. The breast region was segmented and the suspicious tumor was depicted on sequentially scanned MR images from each case. In total, 90 features were obtained, including 88 imaging features related to morphology and texture as well as dynamic features from tumor and background parenchymal enhancement (BPE) and 2 clinical information-based parameters, namely, age and menopausal status. An evolutionary algorithm was used to select an optimal subset of features for classification. Using these features, we trained a multi-class logistic regression classifier that calculated the area under the receiver operating characteristic curve (AUC). The results of a prediction model using 24 selected features showed high overall classification performance, with an AUC value of 0.869. The predictive model discriminated among the luminal A, luminal B, HER2 and basal-like subtypes, with AUC values of 0.867, 0.786, 0.888 and 0.923, respectively. An additional independent dataset with 36 patients was utilized to validate the results. A similar classification analysis of the validation dataset showed an AUC of 0.872 using 15 image features, 10 of which were identical to those from the first cohort. We identified clinical information and 3D imaging features from DCE-MRI as candidate biomarkers for discriminating among four molecular subtypes of breast cancer. PMID:28166261

  17. Aberrant expression of DNA damage response proteins is associated with breast cancer subtype and clinical features

    PubMed Central

    Guler, Gulnur; Himmetoglu, Cigdem; Jimenez, Rafael E.; Geyer, Susan M.; Wang, Wenle P.; Costinean, Stefan; Pilarski, Robert T.; Morrison, Carl; Suren, Dinc; Liu, Jianhua; Chen, Jingchun; Kamal, Jyoti; Shapiro, Charles L.

    2013-01-01

    Landmark studies of the status of DNA damage checkpoints and associated repair functions in preneoplastic and neoplastic cells has focused attention on importance of these pathways in cancer development, and inhibitors of repair pathways are in clinical trials for treatment of triple negative breast cancer. Cancer heterogeneity suggests that specific cancer subtypes will have distinct mechanisms of DNA damage survival, dependent on biological context. In this study, status of DNA damage response (DDR)-associated proteins was examined in breast cancer subtypes in association with clinical features; 479 breast cancers were examined for expression of DDR proteins γH2AX, BRCA1, pChk2, and p53, DNA damage-sensitive tumor suppressors Fhit and Wwox, and Wwox-interacting proteins Ap2α, Ap2γ, ErbB4, and correlations among proteins, tumor subtypes, and clinical features were assessed. In a multivariable model, triple negative cancers showed significantly reduced Fhit and Wwox, increased p53 and Ap2γ protein expression, and were significantly more likely than other subtype tumors to exhibit aberrant expression of two or more DDR-associated proteins. Disease-free survival was associated with subtype, Fhit and membrane ErbB4 expression level and aberrant expression of multiple DDR-associated proteins. These results suggest that definition of specific DNA repair and checkpoint defects in subgroups of triple negative cancer might identify new treatment targets. Expression of Wwox and its interactor, ErbB4, was highly significantly reduced in metastatic tissues vs. matched primary tissues, suggesting that Wwox signal pathway loss contributes to lymph node metastasis, perhaps by allowing survival of tumor cells that have detached from basement membranes, as proposed for the role of Wwox in ovarian cancer spread. PMID:21069451

  18. Cuckoo search optimisation for feature selection in cancer classification: a new approach.

    PubMed

    Gunavathi, C; Premalatha, K

    2015-01-01

    Cuckoo Search (CS) optimisation algorithm is used for feature selection in cancer classification using microarray gene expression data. Since the gene expression data has thousands of genes and a small number of samples, feature selection methods can be used for the selection of informative genes to improve the classification accuracy. Initially, the genes are ranked based on T-statistics, Signal-to-Noise Ratio (SNR) and F-statistics values. The CS is used to find the informative genes from the top-m ranked genes. The classification accuracy of k-Nearest Neighbour (kNN) technique is used as the fitness function for CS. The proposed method is experimented and analysed with ten different cancer gene expression datasets. The results show that the CS gives 100% average accuracy for DLBCL Harvard, Lung Michigan, Ovarian Cancer, AML-ALL and Lung Harvard2 datasets and it outperforms the existing techniques in DLBCL outcome and prostate datasets.

  19. The prevalence and clinicopathological features of breast cancer patients with hepatitis B virus infection in China.

    PubMed

    Wu, He; Zhao, Chunxia; Adhikari, Vishnu Prasad; Lu, Linjie; Huang, Jianbo; Wei, Yuxian; Luo, Qingqing; Dai, Wei; Wu, Yutuan; Li, Xin; Wu, Kainan; Kong, Ling-Quan

    2017-03-14

    We performed a case-control study to investigate the prevalence and clinicopathological features of breast cancer patients with hepatitis B virus (HBV) infection in China. The clinical data for 2,796 female patients with newly diagnosed, primary breast cancer were evaluated. A total of 234 breast cancer patients with HBV infection (the case group; positive for hepatitis B surface antigen [HBsAg]) and 444 breast cancer patients without HBV infection (the control group; negative for HBsAg, hepatitis B surface antibody, hepatitis B envelope antigen, hepatitis B envelope antibody, and hepatitis B core antibody) were selected for study. Analysis of the clinicopathological features revealed that the metastatic axillary lymph node ratio was lower in the case group than the control group, as was the proportion of patients with pathological T stage ≥T2. No differences in the expression levels of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, p53, or Ki67 were observed between the case and control groups. These data indicate that the rate of HBV infection is high among female breast cancer patients in China, and that HBsAg-positive breast cancer patients were generally diagnosed at an earlier stage and had fewer lymph node metastases.

  20. Novel breast tissue feature strongly associated with risk of breast cancer.

    PubMed

    McKian, Kevin P; Reynolds, Carol A; Visscher, Daniel W; Nassar, Aziza; Radisky, Derek C; Vierkant, Robert A; Degnim, Amy C; Boughey, Judy C; Ghosh, Karthik; Anderson, Stephanie S; Minot, Douglas; Caudill, Jill L; Vachon, Celine M; Frost, Marlene H; Pankratz, V Shane; Hartmann, Lynn C

    2009-12-10

    Accurate, individualized risk prediction for breast cancer is lacking. Tissue-based features may help to stratify women into different risk levels. Breast lobules are the anatomic sites of origin of breast cancer. As women age, these lobular structures should regress, which results in reduced breast cancer risk. However, this does not occur in all women. We have quantified the extent of lobule regression on a benign breast biopsy in 85 patients who developed breast cancer and 142 age-matched controls from the Mayo Benign Breast Disease Cohort, by determining number of acini per lobule and lobular area. We also calculated Gail model 5-year predicted risks for these women. There is a step-wise increase in breast cancer risk with increasing numbers of acini per lobule (P = .0004). Adjusting for Gail model score, parity, histology, and family history did not attenuate this association. Lobular area was similarly associated with risk. The Gail model estimates were associated with risk of breast cancer (P = .03). We examined the individual accuracy of these measures using the concordance (c) statistic. The Gail model c statistic was 0.60 (95% CI, 0.50 to 0.70); the acinar count c statistic was 0.65 (95% CI, 0.54 to 0.75). Combining acinar count and lobular area, the c statistic was 0.68 (95% CI, 0.58 to 0.78). Adding the Gail model to these measures did not improve the c statistic. Novel, tissue-based features that reflect the status of a woman's normal breast lobules are associated with breast cancer risk. These features may offer a novel strategy for risk prediction.

  1. [Breast cancer with triple-negative phenotype in the Russian patient population. Clinical and morphologic features].

    PubMed

    Zhukova, L G

    2015-01-01

    The purpose of this study was to examine the incidence of breast cancer with triple-negative phenotype (TN BC) in the Russian population as well as to compare the clinical and morphological features and outcomes for women with TN BC with other types of breast cancer. We studied a cohort of 499 patients with breast cancer without distant metastases, diagnosed between 2002 and 2011 at N.N.Blokhin Russian Cancer Research Center in Moscow. Triple-negative breast cancers were defined as those that had "negative" level of estrogens and progesteron receptors and were HER2neu negative. 330 (66.2%) of patients has triple negative tumors, 81 (16.2%)--ER and PR negative and HER-2 positive tumors, and 88 (17.6%)--ER and/or ER positive and HER-2 negative tumors. Further was evaluated disease-free and overall survival. 18.5 % of all analyzed patients had triple negative phenotype. Median follow-up was 40.5 months. Characteristic features of the TN BC were: TN breast cancer, compared with other subtypes, characterized by a higher incidence of clinical and morphological features associated with an aggressive course of the disease: the age less than 35 years, grade 3, non- specified invasive histology, high level of Ki-67, the rapid development of the disease, which manifests itself in small terms of the first complaints before the diagnosis. TN BC patients has poorer 5-year overall survival (73.6 + 3.6%) and the 5-year disease-free survival (70.6 + 3.5%), which is significantly lower than the comparable survival of patients with other subtypes of breast cancer (p < 0.001). The results of our study confirm the similarity of majority of clinical and morphological characteristics, course and prognosis of the disease of the Russian population of TN BC patients with those in Europe and the United States.

  2. Prediction of near-term breast cancer risk based on bilateral mammographic feature asymmetry.

    PubMed

    Tan, Maxine; Zheng, Bin; Ramalingam, Pandiyarajan; Gur, David

    2013-12-01

    The objective of this study is to investigate the feasibility of predicting near-term risk of breast cancer development in women after a negative mammography screening examination. It is based on a statistical learning model that combines computerized image features related to bilateral mammographic tissue asymmetry and other clinical factors. A database of negative digital mammograms acquired from 994 women was retrospectively collected. In the next sequential screening examination (12 to 36 months later), 283 women were diagnosed positive for cancer, 349 were recalled for additional diagnostic workups and later proved to be benign, and 362 remain negative (not recalled). From an initial pool of 183 features, we applied a Sequential Forward Floating Selection feature selection method to search for effective features. Using 10 selected features, we developed and trained a support vector machine classification model to compute a cancer risk or probability score for each case. The area under the receiver operating characteristic curve and odds ratios (ORs) were used as the two performance assessment indices. The area under the receiver operating characteristic curve = 0.725 ± 0.018 was obtained for positive and negative/benign case classification. The ORs showed an increasing risk trend with increasing model-generated risk scores (from 1.00 to 12.34, between positive and negative/benign case groups). Regression analysis of ORs also indicated a significant increase trend in slope (P = .006). This study demonstrates that the risk scores computed by a new support vector machine model involving bilateral mammographic feature asymmetry have potential to assist the prediction of near-term risk of women for developing breast cancer. Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.

  3. Prediction of core cancer genes using a hybrid of feature selection and machine learning methods.

    PubMed

    Liu, Y X; Zhang, N N; He, Y; Lun, L J

    2015-08-03

    Machine learning techniques are of great importance in the analysis of microarray expression data, and provide a systematic and promising way to predict core cancer genes. In this study, a hybrid strategy was introduced based on machine learning techniques to select a small set of informative genes, which will lead to improving classification accuracy. First feature filtering algorithms were applied to select a set of top-ranked genes, and then hierarchical clustering and collapsing dense clusters were used to select core cancer genes. Through empirical study, our approach is capable of selecting relatively few core cancer genes while making high-accuracy predictions. The biological significance of these genes was evaluated using systems biology analysis. Extensive functional pathway and network analyses have confirmed findings in previous studies and can bring new insights into common cancer mechanisms.

  4. Metastatic breast cancer to the rectum: A case report with emphasis on MRI features.

    PubMed

    Lau, Li Ching; Wee, Bernard; Wang, Shi; Thian, Yee Liang

    2017-04-01

    Less than 1% of breast carcinomas metastasize to the gastrointestinal tract. The diagnosis is frequently not recognized especially when the history of breast carcinoma is remote. A 61-year-old female with a remote history of breast carcinoma presented with a 3-month history of change in bowel habits. Colonoscopy showed a circumferential rectal mass with initial impression of primary rectal cancer. MRI of the rectum showed findings that are atypical for primary rectal cancer. Deep biopsy of the rectal mass confirmed lobular breast carcinoma metastasis to the rectum. The patient was treated with radiotherapy and hormonal therapy. She is symptomatically well 2 years after presentation and remains on hormonal therapy. Lobular breast cancer which metastasizes to the rectum can mimic primary rectal cancer clinically. The unique MRI features described in our case when present with a concordant history of lobular breast carcinoma should alert the radiologist to the possibility of this diagnosis which has important treatment implications.

  5. Clinicopathological features and prognosis of coexistence of gastric gastrointestinal stromal tumor and gastric cancer

    PubMed Central

    Liu, Zhen; Liu, Shushang; Zheng, Gaozan; Yang, Jianjun; Hong, Liu; Sun, Li; Fan, Daiming; Zhang, Hongwei; Feng, Fan

    2016-01-01

    Abstract The coexistence of gastric gastrointestinal stromal tumor (GIST) and gastric cancer is relatively high, and its prognosis is controversial due to the complex and variant kinds of presentation. Thus, the present study aimed to explore the clinicopathological features and prognostic factors of gastric GIST with synchronous gastric cancer. From May 2010 to November 2015, a total of 241 gastric GIST patients were retrospectively enrolled in the present study. The patients with coexistence of gastric GIST and gastric cancer were recorded. The clinicopathological features and prognoses of patients were analyzed. Among 241 patients, 24 patients had synchronous gastric cancer (synchronous group) and 217 patients did not (no-synchronous group). The synchronous group presented a higher percentage of elders (66.7% vs 39.6%, P = 0.001) and males (87.5% vs 48.4%, P < 0.001) than the no-synchronous group. The tumor diameter, mitotic index, and National Institutes of Health degree were also significantly different between the 2 groups (all P < 0.05). The 5-year disease-free survival and disease-specific survival rates of synchronous group were significantly lower than those of no-synchronous group (54.9% vs 93.5%, P < 0.001; 37.9% vs 89.9%, P < 0.001, respectively). However, the 5-year overall survival rates between synchronous and gastric cancer groups were comparable (37.9% vs 57.6%, P = 0.474). The coexistence of gastric GIST and gastric cancer was common in elder male patients. The synchronous GIST was common in low-risk category. The prognosis of gastric GIST with synchronous gastric cancer was worse than that of primary-single gastric GIST, but was comparable with primary-single gastric cancer. PMID:27828865

  6. Clinicopathological Features of Cervical Esophageal Cancer: Retrospective Analysis of 63 Consecutive Patients Who Underwent Surgical Resection.

    PubMed

    Saeki, Hiroshi; Tsutsumi, Satoshi; Yukaya, Takafumi; Tajiri, Hirotada; Tsutsumi, Ryosuke; Nishimura, Sho; Nakaji, Yu; Kudou, Kensuke; Akiyama, Shingo; Kasagi, Yuta; Nakashima, Yuichiro; Sugiyama, Masahiko; Sonoda, Hideto; Ohgaki, Kippei; Oki, Eiji; Yasumatsu, Ryuji; Nakashima, Torahiko; Morita, Masaru; Maehara, Yoshihiko

    2017-01-01

    The objectives of this retrospective study were to elucidate the clinicopathological features and recent surgical results of cervical esophageal cancer. Cervical esophageal cancer has been reported to have a dismal prognosis. Accurate knowledge of the clinical characteristics of cervical esophageal cancer is warranted to establish appropriate therapeutic strategies. The clinicopathological features and treatment results of 63 consecutive patients with cervical esophageal cancer (Ce group) who underwent surgical resection from 1980 to 2013 were analyzed and compared with 977 patients with thoracic or abdominal esophageal cancer (T/A group) who underwent surgical resection during that time. Among the patients who received curative resection, the 5-year overall and disease-specific survival rates of the Ce patients were significantly better than those of the T/A patients (overall: 77.3% vs 46.5%, respectively, P = 0.0067; disease-specific: 81.9% vs 55.8%, respectively, P = 0.0135). Although total pharyngo-laryngo-esophagectomy procedures were less frequently performed in the recent period, the rate of curative surgical procedures was markedly higher in the recent period (2000-1013) than that in the early period (1980-1999) (44.4% vs 88.9%, P = 0.0001). The 5-year overall survival rate in the recent period (71.5%) was significantly better than that in the early period (40.7%, P = 0.0342). Curative resection for cervical esophageal cancer contributes to favorable outcomes compared with other esophageal cancers. Recent surgical results for cervical esophageal cancer have improved, and include an increased rate of curative resection and decreased rate of extensive surgery.

  7. Clinicopathological features and prognosis of coexistence of gastric gastrointestinal stromal tumor and gastric cancer.

    PubMed

    Liu, Zhen; Liu, Shushang; Zheng, Gaozan; Yang, Jianjun; Hong, Liu; Sun, Li; Fan, Daiming; Zhang, Hongwei; Feng, Fan

    2016-11-01

    The coexistence of gastric gastrointestinal stromal tumor (GIST) and gastric cancer is relatively high, and its prognosis is controversial due to the complex and variant kinds of presentation. Thus, the present study aimed to explore the clinicopathological features and prognostic factors of gastric GIST with synchronous gastric cancer.From May 2010 to November 2015, a total of 241 gastric GIST patients were retrospectively enrolled in the present study. The patients with coexistence of gastric GIST and gastric cancer were recorded. The clinicopathological features and prognoses of patients were analyzed.Among 241 patients, 24 patients had synchronous gastric cancer (synchronous group) and 217 patients did not (no-synchronous group). The synchronous group presented a higher percentage of elders (66.7% vs 39.6%, P = 0.001) and males (87.5% vs 48.4%, P < 0.001) than the no-synchronous group. The tumor diameter, mitotic index, and National Institutes of Health degree were also significantly different between the 2 groups (all P < 0.05). The 5-year disease-free survival and disease-specific survival rates of synchronous group were significantly lower than those of no-synchronous group (54.9% vs 93.5%, P < 0.001; 37.9% vs 89.9%, P < 0.001, respectively). However, the 5-year overall survival rates between synchronous and gastric cancer groups were comparable (37.9% vs 57.6%, P = 0.474).The coexistence of gastric GIST and gastric cancer was common in elder male patients. The synchronous GIST was common in low-risk category. The prognosis of gastric GIST with synchronous gastric cancer was worse than that of primary-single gastric GIST, but was comparable with primary-single gastric cancer.

  8. Quantitative shear wave elastography: correlation with prognostic histologic features and immunohistochemical biomarkers of breast cancer.

    PubMed

    Au, Frederick Wing-Fai; Ghai, Sandeep; Lu, Fang-I; Moshonov, Hadas; Crystal, Pavel

    2015-03-01

    To correlate prognostic histologic features and immunohistochemical biomarkers of breast cancer with quantitative shear wave elastography (SWE) parameters. B-mode ultrasound (US) and SWE were performed before core biopsy on 72 cancers in 68 patients. Mean cancer size was determined from US. Histologic grade, lymph node status, lymphovascular invasion (LVI), histologic type, and immunohistochemical biomarkers (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 [HER2]) were determined from surgical pathology reports. Correlation between these features and quantitative SWE parameters (mean elasticity [E mean], maximum elasticity [E max], and elasticity ratio [E ratio]) was made. There was significant correlation of mean cancer size with E mean, E max, and E ratio (correlation, 0.492, 0.500, and 0.435, respectively; all P < .001). Lymph node involvement was associated with significantly higher E max (P = .040). LVI was associated with significantly higher E mean, E max, and E ratio (P = .002, .004, and .042, respectively). There was no significant correlation of histologic grade with SWE parameters. HER2+ cancers were associated with significantly higher E ratio (P = .030). In multivariate analysis, only mean cancer size was significantly correlated with E mean and E max (P < .001). There was significant correlation of cancer size with SWE parameters. There was significant correlation of lymph node status and LVI with SWE, but only on univariate analysis. SWE has the potential to provide prognostic information of breast cancer in a noninvasive manner, but further study is required. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

  9. Feature selection for outcome prediction in oesophageal cancer using genetic algorithm and random forest classifier.

    PubMed

    Paul, Desbordes; Su, Ruan; Romain, Modzelewski; Sébastien, Vauclin; Pierre, Vera; Isabelle, Gardin

    2016-12-28

    The outcome prediction of patients can greatly help to personalize cancer treatment. A large amount of quantitative features (clinical exams, imaging, …) are potentially useful to assess the patient outcome. The challenge is to choose the most predictive subset of features. In this paper, we propose a new feature selection strategy called GARF (genetic algorithm based on random forest) extracted from positron emission tomography (PET) images and clinical data. The most relevant features, predictive of the therapeutic response or which are prognoses of the patient survival 3 years after the end of treatment, were selected using GARF on a cohort of 65 patients with a local advanced oesophageal cancer eligible for chemo-radiation therapy. The most relevant predictive results were obtained with a subset of 9 features leading to a random forest misclassification rate of 18±4% and an areas under the of receiver operating characteristic (ROC) curves (AUC) of 0.823±0.032. The most relevant prognostic results were obtained with 8 features leading to an error rate of 20±7% and an AUC of 0.750±0.108. Both predictive and prognostic results show better performances using GARF than using 4 other studied methods.

  10. Ataxin-3 expression correlates with the clinicopathologic features of gastric cancer

    PubMed Central

    Zeng, Li-Xia; Tang, Yong; Ma, Yun

    2014-01-01

    To investigate the expression of Ataxin-3 in human gastric cancer tissues and cell lines, and explore its clinical pathologic significance. Methods: The expression of Ataxin-3 in gastric cancer (n=536) and noncancerous gastric mucosa (n=312) was determined by immunohistochemistry and correlated to clinicopathologic features such as histologic differentiation and tumor size. The expression of Ataxin-3 protein in the human gastric cancer cell lines MKN45, SGC7901 and in normal human gastric epithelial cells (GES-1) was also evaluated by Western blot analysis. Quantitative real-time PCR was used to determine Ataxin-3 mRNA expression in human gastric cancer cell lines and tissues. Results: The expression of Ataxin-3 protein was decreased in the gastric cancer compared to noncancerous gastric tissue, and correlated with tumor size, Lauren classification, histologic differentiation, and mutant p53 protein (P < 0.05). Similarly, Ataxin-3 mRNA expression was decreased in the gastric cancers compared to the noncancerous gastric tissue. Ataxin-3 protein and mRNA expression was lower in MKN45, SGC7901 cells than in the normal GES-1 cells. Conclusion: Decreased expression of Ataxin-3 may play an important role in gastric carcinogenesis and development of gastric cancer. PMID:24955170

  11. Relationship between solitary pulmonary nodule lung cancer and CT image features based on gradual clustering

    NASA Astrophysics Data System (ADS)

    Zhang, Weipeng

    2017-06-01

    The relationship between the medical characteristics of lung cancers and computer tomography (CT) images are explored so as to improve the early diagnosis rate of lung cancers. This research collected CT images of patients with solitary pulmonary nodule lung cancer, and used gradual clustering methodology to classify them. Preliminary classifications were made, followed by continuous modification and iteration to determine the optimal condensation point, until iteration stability was achieved. Reasonable classification results were obtained. the clustering results fell into 3 categories. The first type of patients was mostly female, with ages between 50 and 65 years. CT images of solitary pulmonary nodule lung cancer for this group contain complete lobulation and burr, with pleural indentation; The second type of patients was mostly male with ages between 50 and 80 years. CT images of solitary pulmonary nodule lung cancer for this group contain complete lobulation and burr, but with no pleural indentation; The third type of patients was also mostly male with ages between 50 and 80 years. CT images for this group showed no abnormalities. the application of gradual clustering methodology can scientifically classify CT image features of patients with lung cancer in the initial lesion stage. These findings provide the basis for early detection and treatment of malignant lesions in patients with lung cancer.

  12. Clinicopathological features of nonspecific invasive breast cancer according to its molecular subtypes.

    PubMed

    2016-06-01

    The aim of the present study was to investigate the clinical and morphological features of nonspecific invasive breast cancer according to its molecular subtypes. 163 women with nonspecific invasive breast cancer (T1-4N0-3M0) were included in the present study. Luminal A type of breast cancer was detected in 101 women, luminal B type - in 23 women, overexpression of HER2/neu was identified in 14 women and triple-negative cancer - in 25 women. The study revealed that various molecular subtypes of breast cancer differ in the morphological structure, the expression characteristics of the primary tumor and the rate of lymphogenous and hematogenous metastasis. Lymphogenous metastases were more frequently (in 71%) detected in HER2/neu overexpressing breast cancer than in luminal A (41%), luminal B (39%) and triple-negative tumors (40%). Hematogenous metastasis did not depend on the morphological structure of carcinoma infiltrative component, the state of tumor stroma as well as the proliferative activity in all the investigated groups. The revealed clinicopathological characteristics of different molecular subtypes of invasive breast cancer allow to predict the possible outcome of the disease and select personalized treatment strategy for patients more reasonably.

  13. Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features

    PubMed Central

    Yu, Kun-Hsing; Zhang, Ce; Berry, Gerald J.; Altman, Russ B.; Ré, Christopher; Rubin, Daniel L.; Snyder, Michael

    2016-01-01

    Lung cancer is the most prevalent cancer worldwide, and histopathological assessment is indispensable for its diagnosis. However, human evaluation of pathology slides cannot accurately predict patients' prognoses. In this study, we obtain 2,186 haematoxylin and eosin stained histopathology whole-slide images of lung adenocarcinoma and squamous cell carcinoma patients from The Cancer Genome Atlas (TCGA), and 294 additional images from Stanford Tissue Microarray (TMA) Database. We extract 9,879 quantitative image features and use regularized machine-learning methods to select the top features and to distinguish shorter-term survivors from longer-term survivors with stage I adenocarcinoma (P<0.003) or squamous cell carcinoma (P=0.023) in the TCGA data set. We validate the survival prediction framework with the TMA cohort (P<0.036 for both tumour types). Our results suggest that automatically derived image features can predict the prognosis of lung cancer patients and thereby contribute to precision oncology. Our methods are extensible to histopathology images of other organs. PMID:27527408

  14. A novel feature ranking method for prediction of cancer stages using proteomics data.

    PubMed

    Saghapour, Ehsan; Kermani, Saeed; 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.

  15. Lung Cancer Prediction Using Neural Network Ensemble with Histogram of Oriented Gradient Genomic Features

    PubMed Central

    Adetiba, Emmanuel; Olugbara, Oludayo O.

    2015-01-01

    This paper reports an experimental comparison of artificial neural network (ANN) and support vector machine (SVM) ensembles and their “nonensemble” variants for lung cancer prediction. These machine learning classifiers were trained to predict lung cancer using samples of patient nucleotides with mutations in the epidermal growth factor receptor, Kirsten rat sarcoma viral oncogene, and tumor suppressor p53 genomes collected as biomarkers from the IGDB.NSCLC corpus. The Voss DNA encoding was used to map the nucleotide sequences of mutated and normal genomes to obtain the equivalent numerical genomic sequences for training the selected classifiers. The histogram of oriented gradient (HOG) and local binary pattern (LBP) state-of-the-art feature extraction schemes were applied to extract representative genomic features from the encoded sequences of nucleotides. The ANN ensemble and HOG best fit the training dataset of this study with an accuracy of 95.90% and mean square error of 0.0159. The result of the ANN ensemble and HOG genomic features is promising for automated screening and early detection of lung cancer. This will hopefully assist pathologists in administering targeted molecular therapy and offering counsel to early stage lung cancer patients and persons in at risk populations. PMID:25802891

  16. SU-D-207B-01: Radiomics Feature Reproducibility From Repeat CT Scans of Patients with Rectal Cancer

    SciTech Connect

    Hu, P; Wang, J; Zhong, H; Zhou, Z; Shen, L; Hu, W; Zhang, Z

    2016-06-15

    Purpose: To evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer. Methods: 40 rectal cancer patients were enrolled in this study, each of whom underwent two CT scans within average 8.7 days (5 days to 17 days), before any treatment was delivered. The rectal gross tumor volume (GTV) was distinguished and segmented by an experienced oncologist in both CTs. Totally, more than 2000 radiomics features were defined in this study, which were divided into four groups (I: GLCM, II: GLRLM III: Wavelet GLCM and IV: Wavelet GLRLM). For each group, five types of features were extracted (Max slice: features from the largest slice of target images, Max value: features from all slices of target images and choose the maximum value, Min value: minimum value of features for all slices, Average value: average value of features for all slices, Matrix sum: all slices of target images translate into GLCM and GLRLM matrices and superpose all matrices, then extract features from the superposed matrix). Meanwhile a LOG (Laplace of Gauss) filter with different parameters was applied to these images. Concordance correlation coefficients (CCC) and inter-class correlation coefficients (ICC) were calculated to assess the reproducibility. Results: 403 radiomics features were extracted from each type of patients’ medical images. Features of average type are the most reproducible. Different filters have little effect for radiomics features. For the average type features, 253 out of 403 features (62.8%) showed high reproducibility (ICC≥0.8), 133 out of 403 features (33.0%) showed medium reproducibility (0.8≥ICC≥0.5) and 17 out of 403 features (4.2%) showed low reproducibility (ICC≥0.5). Conclusion: The average type radiomics features are the most stable features in rectal cancer. Further analysis of these features of rectal cancer can be warranted for treatment monitoring and

  17. Screening of feature genes in distinguishing different types of breast cancer using support vector machine.

    PubMed

    Wang, Qi; Liu, Xudong

    2015-01-01

    To screen the feature genes in estrogen receptor-positive (ER+) breast cancer in comparison with estrogen receptor-negative (ER-) breast cancer. Nine microarray data of ER+ and ER- breast cancer samples were collected from Gene Expression Omnibus database. After preprocessing, data in five training sets were analyzed using significance analysis of microarrays to screen the differentially expressed genes (DEGs). The DEGs were further analyzed via support vector machine (SVM) function in e1071 package of R to construct a SVM classifier, the efficacy of which was verified by four testing sets and its combination with training sets using a leave-one-out cross-validation. Feature genes obtained by SVM classifier were subjected to function- and pathway-enrichment via the Database for Annotation, Visualization and Integrated Discovery and KEGG Orthology Based Annotation System, respectively. A total of 526 DEGs were screened between ER+ and ER- breast cancer. The SVM classifier demonstrated that these genes could distinguish different subtype samples with high accuracy of larger than 90%, and also showed good sensitivity, specificity, positive/negative predictive value, and area under receiver operating characteristic curve. The inflammatory and hormone biological processes were the common enriched results for two different function analyses, indicating that the inflammatory (ie, IL8) and hormone regulation (ie, CGA) genes may be the involved feature genes to distinguish ER+ and ER- types of breast cancer. The gene-expression profile data can provide feature genes to distinguish ER+ and ER- samples, and the identified genes can be used for biomarkers for ER+ samples.

  18. Expression of eag1 channel associated with the aggressive clinicopathological features and subtype of breast cancer.

    PubMed

    Liu, Guang-Xu; Yu, Yun-Cui; He, Xiang-Ping; Ren, Sheng-Nan; Fang, Xue-Dong; Liu, Fen; He, Yan

    2015-01-01

    Expression of eag1 channel (Eag1) is associated with cell malignant transformation, tumor cell metastasis and poor prognosis of the patient. This study aimed at examining whether expression of the Eag1 associated with aggressive clinicopathological feature and the molecular subtype of breast cancer. 109 patients who received breast cancer operation during January 2009 to December 2010 in Chinese-Japanese Friendship Hospital of Jilin University were recruited. We investigated the association of the Eag1 with clinicopathological features and molecular subtype of in triple negative breast cancer (TNBC) by univariate or multivariate analysis in a cross-section study. The positive rate of Eag1 was 18.5% higher in TNBC compared with non-triple negative breast cancer (Non-TNBC) (P = 0.012, OR = 2.83, 95% CI = 2.16-3.47). Compared with the Eag1 negative group, the expression of Eag1 was linked to the larger tumor size (P = 0.002), advanced TNM stage (P = 0.029), high proportion of positive lymph node (87.6% vs. 65%, P = 0.014) and invasive ductal carcinoma (91% vs. 75%, P = 0.046). The expression of Eag1 may be partially explained the aggressive behavior of TNBC in the breast cancer tissue.

  19. Clinicopathological features and treatment sensitivity of elderly Chinese breast cancer patients

    PubMed Central

    LI, JUN-JIE; YU, KE-DA; DI, GEN-HONG; SHAO, ZHI-MIN

    2010-01-01

    This study aimed to determine the clinicopathological features and treatment sensitivity of elderly breast cancer patients in China. The clinical data of 594 elderly breast cancer patients of 70 or more years of age were collected and compared to those of 657 patients of less than 70 years of age to analyze whether breast cancer in the elderly is different and whether the difference affected outcome. The median age was 75.2 years in the elderly patients and 49.8 years in the young patients. Age of menarche, parous status and body mass index were similar in the two groups. A higher frequency of steroid receptor-positive rate, a lower expression of HER-2 and p53, less axillary node-positive rate and earlier tumor stage were found in patients of 70 years or older. The 5-year relapse-free survival (RFS) and overall survival (OS) was 77 and 82% in the elderly and 86 and 93% in the young patients, respectively. Patients with estrogen receptor (ER)-positive or lymph node (LN)-negative cancers showed a more favorable outcome in the elderly patients. RFS and OS were increased in elderly patients who underwent endocrine therapy or omitted chemotherapy. Breast cancer in the elderly had more favorable tumor features, using estrogen receptor and lymph node status as prognostic factors. It was therefore concluded that adjuvant endocrine therapy may benefit elderly patients, while chemotherapy may not. PMID:22870109

  20. Surgical Management of Periocular Cancers: High- and Low-Risk Features Drive Treatment.

    PubMed

    Allen, Richard C

    2017-09-01

    Recent advances in the treatment of eyelid tumors have centered on the excision, evaluation of margins, role of sentinel lymph node biopsy, and adjunctive/adjuvant systemic and radiation therapy. The purpose of this review is to elaborate on these advances. Mohs excision of basal cell carcinoma and squamous cell carcinoma continues to provide the greatest success in complete excision of the cancer, especially in those cases of high-risk disease including medial canthal location and recurrent disease. Sentinel lymph node biopsy has proven useful in the assessment of early regional metastasis in sebaceous cell carcinoma, melanoma, and Merkel cell carcinoma. The pathologic finding of perineural invasion is a high-risk feature in all periocular cancers, and adjuvant therapy should be considered. Targeted therapy shows great potential in situations that are not amenable to complete excision without sacrificing the globe. Identification of high- and low-risk features in eyelid cancers allows a stratified approach to treatment. While high-risk features may require adjuvant therapy, larger margins, and sentinel lymph node biopsy, low-risk features may allow topical therapy to adequately address the condition. Monoclonal antibodies and small molecule inhibitors show great promise in the treatment of extensive disease.

  1. A new feature extraction framework based on wavelets for breast cancer diagnosis.

    PubMed

    Ergin, Semih; Kilinc, Onur

    2014-08-01

    This paper investigates a pattern recognition framework in order to determine and classify breast cancer cases. Initially, a two-class separation study classifying normal and abnormal (cancerous) breast tissues is achieved. The Histogram of Oriented Gradients (HOG), Dense Scale Invariant Feature Transform (DSIFT), and Local Configuration Pattern (LCP) methods are used to extract the rotation- and scale-invariant features for all tissue patches. A classification is made utilizing Support Vector Machine (SVM), k-Nearest Neighborhood (k-NN), Decision Tree, and Fisher Linear Discriminant Analysis (FLDA) via 10-fold cross validation. Then, a three-class study (normal, benign, and malignant cancerous cases) is carried out using similar procedures in a two-class case; however, the attained classification accuracies are not sufficiently satisfied. Therefore, a new feature extraction framework is proposed. The feature vectors are again extracted with this new framework, and more satisfactory results are obtained. Our new framework achieved a remarkable increase in recognition performance for the three-class study. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Examining applying high performance genetic data feature selection and classification algorithms for colon cancer diagnosis.

    PubMed

    Al-Rajab, Murad; Lu, Joan; Xu, Qiang

    2017-07-01

    This paper examines the accuracy and efficiency (time complexity) of high performance genetic data feature selection and classification algorithms for colon cancer diagnosis. The need for this research derives from the urgent and increasing need for accurate and efficient algorithms. Colon cancer is a leading cause of death worldwide, hence it is vitally important for the cancer tissues to be expertly identified and classified in a rapid and timely manner, to assure both a fast detection of the disease and to expedite the drug discovery process. In this research, a three-phase approach was proposed and implemented: Phases One and Two examined the feature selection algorithms and classification algorithms employed separately, and Phase Three examined the performance of the combination of these. It was found from Phase One that the Particle Swarm Optimization (PSO) algorithm performed best with the colon dataset as a feature selection (29 genes selected) and from Phase Two that the Support Vector Machine (SVM) algorithm outperformed other classifications, with an accuracy of almost 86%. It was also found from Phase Three that the combined use of PSO and SVM surpassed other algorithms in accuracy and performance, and was faster in terms of time analysis (94%). It is concluded that applying feature selection algorithms prior to classification algorithms results in better accuracy than when the latter are applied alone. This conclusion is important and significant to industry and society. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Features of breast cancer in developing countries, examples from North-Africa.

    PubMed

    Corbex, Marilys; Bouzbid, Sabiha; Boffetta, Paolo

    2014-07-01

    Epidemiological features of breast cancer appear to be different in developing countries compared to Western countries, with notably large proportions of young patients, male patients and aggressive forms of the disease. Using North-Africa (Morocco, Algeria, Tunisia, Libya and Egypt) as an example, we document the magnitude and explore possible explanations for such patterns. Articles and reports published since the seventies were reviewed. Results show that breast cancer incidence in females is 2-4 times lower in North-Africa than in Western countries while incidence in males is similar. Consequently, the relative proportion of male breast cancer is high (≈2% of all breast cancers). Similarly, the incidence of aggressive forms of the disease, like inflammatory or triple negative breast cancer (in females), is not higher in North Africa than in Western countries, but their relative proportion in case series (up to 10% for inflammatory and 15-25% for triple negative) is significantly higher because of low incidence of other forms of the disease. In North Africa, the incidence among women aged 15-49 is lower than in Western countries, but the very low incidence among women aged more than 50, combined to the young age pyramid of North-Africa, makes the relative proportions of young patients substantially higher (50-60% versus 20% in France). Such epidemiological features result mainly from peculiar risk factor profiles, which are typical for many developing countries and include notably rapid changes in reproductive behaviours. These features have important implications for breast cancer control and treatment.

  4. Computer-Aided Breast Cancer Diagnosis with Optimal Feature Sets: Reduction Rules and Optimization Techniques.

    PubMed

    Mathieson, Luke; Mendes, Alexandre; Marsden, John; Pond, Jeffrey; Moscato, Pablo

    2017-01-01

    This chapter introduces a new method for knowledge extraction from databases for the purpose of finding a discriminative set of features that is also a robust set for within-class classification. Our method is generic and we introduce it here in the field of breast cancer diagnosis from digital mammography data. The mathematical formalism is based on a generalization of the k-Feature Set problem called (α, β)-k-Feature Set problem, introduced by Cotta and Moscato (J Comput Syst Sci 67(4):686-690, 2003). This method proceeds in two steps: first, an optimal (α, β)-k-feature set of minimum cardinality is identified and then, a set of classification rules using these features is obtained. We obtain the (α, β)-k-feature set in two phases; first a series of extremely powerful reduction techniques, which do not lose the optimal solution, are employed; and second, a metaheuristic search to identify the remaining features to be considered or disregarded. Two algorithms were tested with a public domain digital mammography dataset composed of 71 malignant and 75 benign cases. Based on the results provided by the algorithms, we obtain classification rules that employ only a subset of these features.

  5. Targeting Breast Cancers Featuring Activating Mutations in PIK3CA by Generating a Lethal Dose of PIP3

    DTIC Science & Technology

    2008-02-01

    2003). Frequent monoallelic deletion of PTEN and its reciprocal associatioin with PIK3CA amplification in gastric carcinoma. Int J Cancer 104, 318-327...AD_________________ Award Number: W81XWH-06-1-0341 TITLE: Targeting Breast Cancers Featuring...ORGANIZATION: Dana-Farber Cancer Institute Boston, MA 02115 REPORT DATE: February 2008 TYPE OF REPORT: Annual Summary

  6. New Molecular Features of Colorectal Cancer Identified - Office of Cancer Clinical Proteomics Research

    Cancer.gov

    Investigators from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) who comprehensively analyzed 95 human colorectal tumor samples, have determined how gene alterations identified in previous analyses of the same samples

  7. Risk of Breast Cancer in Women with False-Positive Results according to Mammographic Features.

    PubMed

    Castells, Xavier; Torá-Rocamora, Isabel; Posso, Margarita; Román, Marta; Vernet-Tomas, Maria; Rodríguez-Arana, Ana; Domingo, Laia; Vidal, Carmen; Baré, Marisa; Ferrer, Joana; Quintana, María Jesús; Sánchez, Mar; Natal, Carmen; Espinàs, Josep A; Saladié, Francina; Sala, María

    2016-08-01

    Purpose To assess the risk of breast cancer in women with false-positive screening results according to radiologic classification of mammographic features. Materials and Methods Review board approval was obtained, with waiver of informed consent. This retrospective cohort study included 521 200 women aged 50-69 years who underwent screening as part of the Spanish Breast Cancer Screening Program between 1994 and 2010 and who were observed until December 2012. Cox proportional hazards regression analysis was used to estimate the age-adjusted hazard ratio (HR) of breast cancer and the 95% confidence interval (CI) in women with false-positive mammograms as compared with women with negative mammograms. Separate models were adjusted for screen-detected and interval cancers and for screen-film and digital mammography. Time without a breast cancer diagnosis was plotted by using Kaplan-Meier curves. Results When compared with women with negative mammograms, the age-adjusted HR of cancer in women with false-positive results was 1.84 (95% CI: 1.73, 1.95; P < .001). The risk was higher in women who had calcifications, whether they were (HR, 2.73; 95% CI: 2.28, 3.28; P < .001) or were not (HR, 2.24; 95% CI: 2.02, 2.48; P < .001) associated with masses. Women in whom mammographic features showed changes in subsequent false-positive results were those who had the highest risk (HR, 9.13; 95% CI: 8.28, 10.07; P < .001). Conclusion Women with false-positive results had an increased risk of breast cancer, particularly women who had calcifications at mammography. Women who had more than one examination with false-positive findings and in whom the mammographic features changed over time had a highly increased risk of breast cancer. Previous mammographic features might yield useful information for further risk-prediction models and personalized follow-up screening protocols. (©) RSNA, 2016 Online supplemental material is available for this article.

  8. Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection

    PubMed Central

    Hassan, S. Sakira; Ruusuvuori, Pekka; Latonen, Leena; Huttunen, Heikki

    2015-01-01

    In this paper, we study the problem of feature selection in cancer-related machine learning tasks. In particular, we study the accuracy and stability of different feature selection approaches within simplistic machine learning pipelines. Earlier studies have shown that for certain cases, the accuracy of detection can easily reach 100% given enough training data. Here, however, we concentrate on simplifying the classification models with and seek for feature selection approaches that are reliable even with extremely small sample sizes. We show that as much as 50% of features can be discarded without compromising the prediction accuracy. Moreover, we study the model selection problem among the ℓ1 regularization path of logistic regression classifiers. To this aim, we compare a more traditional cross-validation approach with a recently proposed Bayesian error estimator. PMID:27081305

  9. Aberrant expression of intelectin-1 in gastric cancer: its relationship with clinicopathological features and prognosis.

    PubMed

    Zheng, Liduan; Weng, Mixia; Qi, Meng; Qi, Teng; Tong, Ling; Hou, Xiaohua; Tong, Qiangsong

    2012-01-01

    Human intelectin-1 (ITLN-1) is a novel identified galactose-binding lectin that is expressed in the colonic goblet cells. Since gastric adenocarcinomas can arise through a process of intestinalization, we speculate that ITLN-1 may be aberrantly expressed in gastric cancer. This study was undertaken to examine the ITLN-1 expression in gastric cancer and correlate it with clinical outcomes. One hundred and ninety-six gastric cancer patients were evaluated for the ITLN-1 expression by immunohistochemistry. The ITLN-1 transcripts were measured by real-time quantitative PCR. ITLN-1 expression was absent in normal gastric mucosa, whereas areas of intestinal metaplasia revealed ITLN-1 immunoreactivity. One hundred and forty-two gastric cancer patients (72.4%) were positive for ITLN-1 expression. In a subtotal of 20 patients, ITLN-1 transcripts were significantly enhanced in gastric cancer tissues than in normal gastric mucosa (P < 0.001). The expression rate of ITLN-1 was higher in intestinal-type carcinomas than in diffuse-type carcinomas (P = 0.003). ITLN-1 positivity in gastric cancer was positively correlated with tumor differentiation (P = 0.001) and CDX2 expression (P < 0.001), and inversely correlated with depth of invasion (P = 0.007), lymph node metastasis (P = 0.001), distant metastasis (P = 0.014), clinical stage (P = 0.006), Ki-67 expression (P = 0.001), and heparanase expression (P < 0.001), without correlation with age, gender, tumor location, or tumor size. In univariate and multivariate analyses, ITLN-1 was an independent prognostic factor for longer survival of gastric cancer patients (P = 0.001). The aberrant ITLN-1 expression in gastric cancer is correlated with clinicopathological features and may be a useful prognostic factor for predicting the outcomes of gastric cancer patients.

  10. LETM1 overexpression is correlated with the clinical features and survival outcome of breast cancer.

    PubMed

    Li, Nan; Zheng, Yahui; Xuan, Chouhui; Lin, Zhenhua; Piao, Longzhen; Liu, Shuangping

    2015-01-01

    Leucine zipper/EF hand-containing transmembrane-1 (LETM1) is a mitochondrial inner membrane protein that was first identified in Wolf-Hirschhorn syndrome. However, high-level expression of LETM1 has been correlated with multiple human malignancies, suggesting roles in carcinogenesis and tumor progression. This study is aimed to explore the clinicopathological characteristics and prognostic value of LETM1 overexpression in breast cancer. Immunohistochemical (IHC) staining, and immunofluorescence (IF) were performed to examine LETM1 expression in breast cancer cell line/tissues compared with adjacent normal tissues. Statistical analysis was applied to evaluate the correlation between LETM1 overexpression and the clinicopathological features of breast cancer. Survival rates were calculated using the Kaplan-Meier method, and the relationship between prognostic factors and patient survival was analyzed using the Cox proportional hazard models. LETM1 protein showed cytoplasmic staining pattern in breast cancer. The strongly positive rate of LETM1 protein was 61.6% (98/159) in breast cancer, which was significantly higher than in DCIS (29.7%, 11/37), hyperplasia (16.7%, 3/18) and adjacent normal breast tissues (15.9%, 7/44). High-level expression of LETM1 protein was correlated with lymph node metastasis, poor differentiation, late clinical stage, disease-free survival (DFS) and overall survival (OS) rates in breast cancer. Moreover, multivariate analysis suggested that LETM1 emerged as a significant independent prognostic factor along with clinical stage of patients with breast cancer. LETM1 plays an important role in the progression of breast cancer. High level expression of LETM1 is an independent poor prognostic factor of breast cancer.

  11. Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine

    PubMed Central

    Gupta, Sudheer; Chaudhary, Kumardeep; Kumar, Rahul; Gautam, Ankur; Nanda, Jagpreet Singh; Dhanda, Sandeep Kumar; Brahmachari, Samir Kumar; Raghava, Gajendra P. S.

    2016-01-01

    In this study, we investigated drug profile of 24 anticancer drugs tested against a large number of cell lines in order to understand the relation between drug resistance and altered genomic features of a cancer cell line. We detected frequent mutations, high expression and high copy number variations of certain genes in both drug resistant cell lines and sensitive cell lines. It was observed that a few drugs, like Panobinostat, are effective against almost all types of cell lines, whereas certain drugs are effective against only a limited type of cell lines. Tissue-specific preference of drugs was also seen where a drug is more effective against cell lines belonging to a specific tissue. Genomic features based models have been developed for each anticancer drug and achieved average correlation between predicted and actual growth inhibition of cell lines in the range of 0.43 to 0.78. We hope, our study will throw light in the field of personalized medicine, particularly in designing patient-specific anticancer drugs. In order to serve the scientific community, a webserver, CancerDP, has been developed for predicting priority/potency of an anticancer drug against a cancer cell line using its genomic features (http://crdd.osdd.net/raghava/cancerdp/). PMID:27030518

  12. Early prediction of clinical benefit of treating ovarian cancer using quantitative CT image feature analysis.

    PubMed

    Qiu, Yuchen; Tan, Maxine; McMeekin, Scott; Thai, Theresa; Ding, Kai; Moore, Kathleen; Liu, Hong; Zheng, Bin

    2016-09-01

    In current clinical trials of treating ovarian cancer patients, how to accurately predict patients' response to the chemotherapy at an early stage remains an important and unsolved challenge. To investigate feasibility of applying a new quantitative image analysis method for predicting early response of ovarian cancer patients to chemotherapy in clinical trials. A dataset of 30 patients was retrospectively selected in this study, among which 12 were responders with 6-month progression-free survival (PFS) and 18 were non-responders. A computer-aided detection scheme was developed to segment tumors depicted on two sets of CT images acquired pre-treatment and 4-6 weeks post treatment. The scheme computed changes of three image features related to the tumor volume, density, and density variance. We analyzed performance of using each image feature and applying a decision tree to predict patients' 6-month PFS. The prediction accuracy of using quantitative image features was also compared with the clinical record based on the Response Evaluation Criteria in Solid Tumors (RECIST) guideline. The areas under receiver operating characteristic curve (AUC) were 0.773 ± 0.086, 0.680 ± 0.109, and 0.668 ± 0.101, when using each of three features, respectively. AUC value increased to 0.831 ± 0.078 when combining these features together. The decision-tree classifier achieved a higher predicting accuracy (76.7%) than using RECIST guideline (60.0%). This study demonstrated the potential of using a quantitative image feature analysis method to improve accuracy of predicting early response of ovarian cancer patients to the chemotherapy in clinical trials. © The Foundation Acta Radiologica 2015.

  13. Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression.

    PubMed

    Goli, Shahrbanoo; Mahjub, Hossein; Faradmal, Javad; Mashayekhi, Hoda; Soltanian, Ali-Reza

    2016-01-01

    The Support Vector Regression (SVR) model has been broadly used for response prediction. However, few researchers have used SVR for survival analysis. In this study, a new SVR model is proposed and SVR with different kernels and the traditional Cox model are trained. The models are compared based on different performance measures. We also select the best subset of features using three feature selection methods: combination of SVR and statistical tests, univariate feature selection based on concordance index, and recursive feature elimination. The evaluations are performed using available medical datasets and also a Breast Cancer (BC) dataset consisting of 573 patients who visited the Oncology Clinic of Hamadan province in Iran. Results show that, for the BC dataset, survival time can be predicted more accurately by linear SVR than nonlinear SVR. Based on the three feature selection methods, metastasis status, progesterone receptor status, and human epidermal growth factor receptor 2 status are the best features associated to survival. Also, according to the obtained results, performance of linear and nonlinear kernels is comparable. The proposed SVR model performs similar to or slightly better than other models. Also, SVR performs similar to or better than Cox when all features are included in model.

  14. Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression

    PubMed Central

    Goli, Shahrbanoo; Faradmal, Javad; Mashayekhi, Hoda; Soltanian, Ali-Reza

    2016-01-01

    The Support Vector Regression (SVR) model has been broadly used for response prediction. However, few researchers have used SVR for survival analysis. In this study, a new SVR model is proposed and SVR with different kernels and the traditional Cox model are trained. The models are compared based on different performance measures. We also select the best subset of features using three feature selection methods: combination of SVR and statistical tests, univariate feature selection based on concordance index, and recursive feature elimination. The evaluations are performed using available medical datasets and also a Breast Cancer (BC) dataset consisting of 573 patients who visited the Oncology Clinic of Hamadan province in Iran. Results show that, for the BC dataset, survival time can be predicted more accurately by linear SVR than nonlinear SVR. Based on the three feature selection methods, metastasis status, progesterone receptor status, and human epidermal growth factor receptor 2 status are the best features associated to survival. Also, according to the obtained results, performance of linear and nonlinear kernels is comparable. The proposed SVR model performs similar to or slightly better than other models. Also, SVR performs similar to or better than Cox when all features are included in model. PMID:27882074

  15. [Clinico-pathological features of papillary thyroid cancer coexistent with Hashimoto's thyroiditis].

    PubMed

    Molnár, Sarolta; Győry, Ferenc; Nagy, Endre; Méhes, Gábor; Molnár, Csaba

    2017-02-01

    Former studies suggest the frequent coexistence of Hashimoto's thyreoditis with papillary thyroid cancer, frequently featured by multifocal carcinogenesis but lower clinical stages compared to thyroid cancers lacking thyroiditis. We examined the clinico-pathological correlations between Hashimoto's thyroditis and papillary thyroid cancer in our region in the North-Eastern part of Hungary. We included a total of 230 patients with papillary thyroid cancer who underwent thyroid surgery at the Surgical Department of the University of Debrecen. Patients' sex, age, multifocality of thyroid cancer and clinical stage were evaluated. Cases included 40 patients (17.4%) with (4 male, 36 female) and 190 (82.6%) patients without HT (44 male, 146 female). Hashimoto's thyroiditis related thyroid cancer was almost exclusively associated with the papillary histological type. Multifocality of papillary cancer was significantly more frequent with coexisting Hashimoto's thyroiditis (16/40; 40.0%) compared to cases uninvolved (45/190; 23.7%; p = 0.034). In contrast, lymph node metastasis was significantly less frequent among patients with Hashimoto's thyroiditis (4 pN1 [36.4%]; 7 pN0 [63.6%]) then without it (34 pN1 [82.9%]; 7 pN0 [17.1%]; p = 0.002). Higher frequency and multifocality of papillary thyroid cancer might be the consequence of preexisting Hashimoto's thyroiditis to be considered as a preneoplastic stimulus supporting carcinogenesis, though the exact pathomechanism of this correlation is not clear yet. Orv. Hetil., 2017, 158(5), 178-182.

  16. Prediction of near-term risk of developing breast cancer using computerized features from bilateral mammograms.

    PubMed

    Sun, Wenqing; Zheng, Bin; Lure, Fleming; Wu, Teresa; Zhang, Jianying; Wang, Benjamin Y; Saltzstein, Edward C; Qian, Wei

    2014-07-01

    Asymmetry of bilateral mammographic tissue density and patterns is a potentially strong indicator of having or developing breast abnormalities or early cancers. The purpose of this study is to design and test the global asymmetry features from bilateral mammograms to predict the near-term risk of women developing detectable high risk breast lesions or cancer in the next sequential screening mammography examination. The image dataset includes mammograms acquired from 90 women who underwent routine screening examinations, all interpreted as negative and not recalled by the radiologists during the original screening procedures. A computerized breast cancer risk analysis scheme using four image processing modules, including image preprocessing, suspicious region segmentation, image feature extraction, and classification was designed to detect and compute image feature asymmetry between the left and right breasts imaged on the mammograms. The highest computed area under curve (AUC) is 0.754±0.024 when applying the new computerized aided diagnosis (CAD) scheme to our testing dataset. The positive predictive value and the negative predictive value were 0.58 and 0.80, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Pathological features and clinical outcomes of breast cancer according to levels of oestrogen receptor expression.

    PubMed

    Zhang, Zhang; Wang, Jianmin; Skinner, Kristin A; Shayne, Michelle; Hajdu, Steven I; Bu, Hong; Hicks, David G; Tang, Ping

    2014-10-01

    Historically, nuclear staining of ≥10% of invasive tumour cells has been used for oestrogen receptor (ER) positivity. In 2010, ASCO/CAP guidelines recommended the cut-off value be changed to nuclear staining of ≥1%. This study will analyse the relationships between levels of ER expression and clinicopathological features and clinical outcomes, with an emphasis on the ER 1-10% subgroup. We analysed clinicopathological features in five subgroups based on ER expression levels in 1700 consecutive invasive breast cancer patients diagnosed and treated at our institution between 2000 and 2011. Of the cases, 24% had ER expression <1%, 2% were ER 1-10%, 5% were 11-50%, 5% were 51-70% and 64% were 71-100%. We observed four subgroups of patient cohorts (ER <1%, 1-10%, 11-70% and 71-100%) that were unique in Nottingham grade, nuclear grade, progesterone receptor expression and disease-free survival. Of the 341 patients with follow-up data, we found no significant differences in pathological features between patients in the ER 11-50% and ER 51-70% subgroups. These data support the important role of ER in breast cancer, and the importance of accurate testing and quantitative reporting for ER. Tumours with ER 1-10% are not common, and further studies are needed to understand more clearly this subgroup of breast cancer. © 2014 John Wiley & Sons Ltd.

  18. The associations between mast cell infiltration, clinical features and molecular types of invasive breast cancer

    PubMed Central

    Tang, Xiaoqiao; Zhang, Yifen; Huang, Tao

    2016-01-01

    Associations between mast cell infiltration and the clinical features and known molecular profile of breast cancer remain unclear. The distribution difference of mast cell was evaluated, in 219 patients with no special type of invasive carcinoma, using sorts of age, max diameter of cancer, histological type, lymph node metastasis as well as the expressions of estrogen receptor (ER), progestogen receptor (PR), human epidermal growth factor receptor 2 (HER-2) and nuclear protein Ki67. The mast cell density (MCD) in patients younger than 50 years old was significantly higher than that in patients with age ≥ 50. The MCD in ER or PR positive patients was significantly higher than MCD in ER or PR negative patients. The MCD in patients with Ki67 ≤ 14% was also significantly higher than MDC in patients with Ki67 > 14%. The MCD of patients with invasive ductal carcinoma was significantly higher than MCD of patients with invasive lobular carcinoma. No significant distribution difference of MCD was found to be associated with max diameter of cancer, lymph node metastasis and HER-2. Further analysis found that MDC was significantly higher in patients after neo-adjuvant chemotherapy. The distribution difference of mast cell widely exists in patients with distinct clinical features, the role of mast cell in breast cancer need further research with detailed and reasonable classification to clarify. PMID:27835573

  19. Differentiating characteristic microstructural features of cancerous tissues using Mueller matrix microscope.

    PubMed

    Wang, Ye; He, Honghui; Chang, Jintao; Zeng, Nan; Liu, Shaoxiong; Li, Migao; Ma, Hui

    2015-12-01

    Polarized light imaging can provide rich microstructural information of samples, and has been applied to the detections of various abnormal tissues. In this paper, we report a polarized light microscope based on Mueller matrix imaging by adding the polarization state generator and analyzer (PSG and PSA) to a commercial transmission optical microscope. The maximum errors for the absolute values of Mueller matrix elements are reduced to 0.01 after calibration. This Mueller matrix microscope has been used to examine human cervical and liver cancerous tissues with fibrosis. Images of the transformed Mueller matrix parameters provide quantitative assessment on the characteristic features of the pathological tissues. Contrast mechanism of the experimental results are backed up by Monte Carlo simulations based on the sphere-cylinder birefringence model, which reveal the relationship between the pathological features in the cancerous tissues at the cellular level and the polarization parameters. Both the experimental and simulated data indicate that the microscopic transformed Mueller matrix parameters can distinguish the breaking down of birefringent normal tissues for cervical cancer, or the formation of birefringent surrounding structures accompanying the inflammatory reaction for liver cancer. With its simple structure, fast measurement and high precision, polarized light microscope based on Mueller matrix shows a good diagnosis application prospect.

  20. Feature extraction techniques using multivariate analysis for identification of lung cancer volatile organic compounds

    NASA Astrophysics Data System (ADS)

    Thriumani, Reena; Zakaria, Ammar; Hashim, Yumi Zuhanis Has-Yun; Helmy, Khaled Mohamed; Omar, Mohammad Iqbal; Jeffree, Amanina; Adom, Abdul Hamid; Shakaff, Ali Yeon Md; Kamarudin, Latifah Munirah

    2017-03-01

    In this experiment, three different cell cultures (A549, WI38VA13 and MCF7) and blank medium (without cells) as a control were used. The electronic nose (E-Nose) was used to sniff the headspace of cultured cells and the data were recorded. After data pre-processing, two different features were extracted by taking into consideration of both steady state and the transient information. The extracted data are then being processed by multivariate analysis, Linear Discriminant Analysis (LDA) to provide visualization of the clustering vector information in multi-sensor space. The Probabilistic Neural Network (PNN) classifier was used to test the performance of the E-Nose on determining the volatile organic compounds (VOCs) of lung cancer cell line. The LDA data projection was able to differentiate between the lung cancer cell samples and other samples (breast cancer, normal cell and blank medium) effectively. The features extracted from the steady state response reached 100% of classification rate while the transient response with the aid of LDA dimension reduction methods produced 100% classification performance using PNN classifier with a spread value of 0.1. The results also show that E-Nose application is a promising technique to be applied to real patients in further work and the aid of Multivariate Analysis; it is able to be the alternative to the current lung cancer diagnostic methods.

  1. Identification of Tumor Suppressors and Oncogenes from Genomic and Epigenetic Features in Ovarian Cancer

    PubMed Central

    Wrzeszczynski, Kazimierz O.; Varadan, Vinay; Byrnes, James; Lum, Elena; Kamalakaran, Sitharthan; Levine, Douglas A.; Dimitrova, Nevenka; Zhang, Michael Q.; Lucito, Robert

    2011-01-01

    The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatic analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We separately examined CNV and DNA methylation for 42 primary serous ovarian cancer samples using MOMA-ROMA assays and 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with altered copy number and correlated changes in expression. Among these genes CCNE1, POP4, UQCRB, PHF20L1 and C19orf2 were identified within both data sets. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We therefore identify changes in DNA methylation and expression for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic features for these modalities and perform a correlation analysis with expression. We predicted 611 potential oncogenes and tumor suppressors candidates by integrating these data types. Genes with a strong correlation for methylation dependent expression changes exhibited at varying copy number aberrations include CDCA8, ATAD2, CDKN2A, RAB25, AURKA, BOP1 and EIF2C3. We provide copy number variation and DNA methylation analysis for over 11,500 individual genes covering the genetic landscape of ovarian cancer tumors. We show the extent of genomic and epigenetic alterations for known tumor suppressors and oncogenes and also use these defined features to identify potential ovarian cancer gene candidates. PMID

  2. Immature truncated O-glycophenotype of cancer directly induces oncogenic features.

    PubMed

    Radhakrishnan, Prakash; Dabelsteen, Sally; Madsen, Frey Brus; Francavilla, Chiara; Kopp, Katharina L; Steentoft, Catharina; Vakhrushev, Sergey Y; Olsen, Jesper V; Hansen, Lars; Bennett, Eric P; Woetmann, Anders; Yin, Guangliang; Chen, Longyun; Song, Haiyan; Bak, Mads; Hlady, Ryan A; Peters, Staci L; Opavsky, Rene; Thode, Christenze; Qvortrup, Klaus; Schjoldager, Katrine T-B G; Clausen, Henrik; Hollingsworth, Michael A; Wandall, Hans H

    2014-09-30

    Aberrant expression of immature truncated O-glycans is a characteristic feature observed on virtually all epithelial cancer cells, and a very high frequency is observed in early epithelial premalignant lesions that precede the development of adenocarcinomas. Expression of the truncated O-glycan structures Tn and sialyl-Tn is strongly associated with poor prognosis and overall low survival. The genetic and biosynthetic mechanisms leading to accumulation of truncated O-glycans are not fully understood and include mutation or dysregulation of glycosyltransferases involved in elongation of O-glycans, as well as relocation of glycosyltransferases controlling initiation of O-glycosylation from Golgi to endoplasmic reticulum. Truncated O-glycans have been proposed to play functional roles for cancer-cell invasiveness, but our understanding of the biological functions of aberrant glycosylation in cancer is still highly limited. Here, we used exome sequencing of most glycosyltransferases in a large series of primary and metastatic pancreatic cancers to rule out somatic mutations as a cause of expression of truncated O-glycans. Instead, we found hypermethylation of core 1 β3-Gal-T-specific molecular chaperone, a key chaperone for O-glycan elongation, as the most prevalent cause. We next used gene editing to produce isogenic cell systems with and without homogenous truncated O-glycans that enabled, to our knowledge, the first polyomic and side-by-side evaluation of the cancer O-glycophenotype in an organotypic tissue model and in xenografts. The results strongly suggest that truncation of O-glycans directly induces oncogenic features of cell growth and invasion. The study provides support for targeting cancer-specific truncated O-glycans with immunotherapeutic measures.

  3. Immature truncated O-glycophenotype of cancer directly induces oncogenic features

    PubMed Central

    Radhakrishnan, Prakash; Dabelsteen, Sally; Madsen, Frey Brus; Francavilla, Chiara; Kopp, Katharina L.; Steentoft, Catharina; Vakhrushev, Sergey Y.; Olsen, Jesper V.; Hansen, Lars; Bennett, Eric P.; Woetmann, Anders; Yin, Guangliang; Chen, Longyun; Song, Haiyan; Bak, Mads; Hlady, Ryan A.; Peters, Staci L.; Opavsky, Rene; Thode, Christenze; Qvortrup, Klaus; Schjoldager, Katrine T.-B. G.; Clausen, Henrik; Hollingsworth, Michael A.; Wandall, Hans H.

    2014-01-01

    Aberrant expression of immature truncated O-glycans is a characteristic feature observed on virtually all epithelial cancer cells, and a very high frequency is observed in early epithelial premalignant lesions that precede the development of adenocarcinomas. Expression of the truncated O-glycan structures Tn and sialyl-Tn is strongly associated with poor prognosis and overall low survival. The genetic and biosynthetic mechanisms leading to accumulation of truncated O-glycans are not fully understood and include mutation or dysregulation of glycosyltransferases involved in elongation of O-glycans, as well as relocation of glycosyltransferases controlling initiation of O-glycosylation from Golgi to endoplasmic reticulum. Truncated O-glycans have been proposed to play functional roles for cancer-cell invasiveness, but our understanding of the biological functions of aberrant glycosylation in cancer is still highly limited. Here, we used exome sequencing of most glycosyltransferases in a large series of primary and metastatic pancreatic cancers to rule out somatic mutations as a cause of expression of truncated O-glycans. Instead, we found hypermethylation of core 1 β3-Gal-T-specific molecular chaperone, a key chaperone for O-glycan elongation, as the most prevalent cause. We next used gene editing to produce isogenic cell systems with and without homogenous truncated O-glycans that enabled, to our knowledge, the first polyomic and side-by-side evaluation of the cancer O-glycophenotype in an organotypic tissue model and in xenografts. The results strongly suggest that truncation of O-glycans directly induces oncogenic features of cell growth and invasion. The study provides support for targeting cancer-specific truncated O-glycans with immunotherapeutic measures. PMID:25118277

  4. Clinicopathologic features and molecular subtypes of breast cancer in young women (age ≤35).

    PubMed

    Goksu, Sema Sezgin; Tastekin, Didem; Arslan, Deniz; Gunduz, Seyda; Tatli, Ali Murat; Unal, Dilek; Salim, Derya; Guler, Tunc; Coskun, Hasan Senol

    2014-01-01

    Breast cancer in young women is a relatively rare disease; however it tends to be more aggressive and is the leading cause of cancer death in this population. The aim of this study is to investigate the clinical and biological features of breast cancer arising in young Turkish breast cancer patients. Patients with breast cancer aged 35 or less (≤35 years) were selected for the study. In total 211 cases were included. Pathologic features; histologic subtypes, grade, lymphovascular invasion, axillary involvement, and stage were recorded for each. The most common subtype was luminal B (36.5%), followed by luminal A (30.8%), triple negative (23.2%) and HER2+(9.5%) subtypes. Twelve percent of the patients had stage 4, 32.7% had stage 3, 46.4% had stage 2, and 6.2% had stage 1 disease at the time of diagnosis. Mean tumour diameter was 3.87 cm (range 0.3-13 cm). The axillary lymph nodes were positive in 74.4% of the patients, while lympho-vascular invasion was seen in 56.4%. Some 9.5% of patients had grade 1, 51.2% had grade 2, and 31.8% had grade 3 tumors. Young women with breast cancer in Turkey are more likely to present with luminal B subtype. Tumors in young women are more likely to present with advanced disease, to be high grade and and to have more lymphovascular invasion. Further research should focus on whether we need new treatment strategies for young patients with breast carcinoma.

  5. Clinicopathological Features of Cases with Primary Breast Cancer not Identified by 18F-FDG-PET.

    PubMed

    Fujii, Takaaki; Yajima, Reina; Tsuboi, Miki; Higuchi, Toru; Obayashi, Sayaka; Tokiniwa, Hideaki; Nagaoka, Rin; Takata, Daisuke; Horiguchi, Jun; Kuwano, Hiroyuki

    2016-06-01

    Several studies have reported that high F18-fluorodeoxyglucose (FDG) uptake is predictive of poor prognosis and aggressive features in patients with breast cancer. While these studies evaluated the prognostic value for cases with high FDG uptake, they did not elucidate the meaning of FDG negativity in primary breast cancer. In this study, we evaluated the clinicopathological features of breast cancer cases without FDG uptake. We retrospectively investigated the cases of 219 consecutive patients with primary breast cancer who underwent FDG-positron emission tomography (PET) preoperatively. Among the 219 patients, 25 (11.4%) did not have FDG uptake in the tumor. The 219 cases with breast cancer were divided into two groups based on the presence of FDG uptake in the primary tumor. The present univariate analysis revealed that histology, small invasive tumor size, high estrogen receptor (ER) or progesterone receptor (PgR) expression, low nuclear grade and absence of lymph node metastasis were significantly associated with negative FDG uptake in the primary tumor. On the other hand, the size of ductal spread was not significantly different between the two groups. Multivariate analysis revealed that small-size tumor invasion and lower nuclear grade were statistically significant. Among the 25 cases without FDG uptake, there was no recurrent disease in spite of there being no case that underwent chemotherapy, while 4 cases among the 194 cases with FDG uptake had disease recurrence. Our findings imply that preoperative FDG negativity in primary breast cancer is effective in predicting better prognosis, but is less effective in predicting ductal spread. Cases without FDG uptake in the primary tumor may have a lower risk of recurrent disease and may be able to safely avoid adjuvant chemotherapy. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  6. Assessment of two mammographic density related features in predicting near-term breast cancer risk

    NASA Astrophysics Data System (ADS)

    Zheng, Bin; Sumkin, Jules H.; Zuley, Margarita L.; Wang, Xingwei; Klym, Amy H.; Gur, David

    2012-02-01

    In order to establish a personalized breast cancer screening program, it is important to develop risk models that have high discriminatory power in predicting the likelihood of a woman developing an imaging detectable breast cancer in near-term (e.g., <3 years after a negative examination in question). In epidemiology-based breast cancer risk models, mammographic density is considered the second highest breast cancer risk factor (second to woman's age). In this study we explored a new feature, namely bilateral mammographic density asymmetry, and investigated the feasibility of predicting near-term screening outcome. The database consisted of 343 negative examinations, of which 187 depicted cancers that were detected during the subsequent screening examination and 155 that remained negative. We computed the average pixel value of the segmented breast areas depicted on each cranio-caudal view of the initial negative examinations. We then computed the mean and difference mammographic density for paired bilateral images. Using woman's age, subjectively rated density (BIRADS), and computed mammographic density related features we compared classification performance in estimating the likelihood of detecting cancer during the subsequent examination using areas under the ROC curves (AUC). The AUCs were 0.63+/-0.03, 0.54+/-0.04, 0.57+/-0.03, 0.68+/-0.03 when using woman's age, BIRADS rating, computed mean density and difference in computed bilateral mammographic density, respectively. Performance increased to 0.62+/-0.03 and 0.72+/-0.03 when we fused mean and difference in density with woman's age. The results suggest that, in this study, bilateral mammographic tissue density is a significantly stronger (p<0.01) risk indicator than both woman's age and mean breast density.

  7. Features of triple-negative breast cancer: Analysis of 38,813 cases from the national cancer database.

    PubMed

    Plasilova, Magdalena L; Hayse, Brandon; Killelea, Brigid K; Horowitz, Nina R; Chagpar, Anees B; Lannin, Donald R

    2016-08-01

    The aim of this study was to determine the features of triple-negative breast cancer (TNBC) using a large national database. TNBC is known to be an aggressive subtype, but national epidemiologic data are sparse. All patients with invasive breast cancer and known molecular subtype diagnosed in 2010 to 2011 were identified from the National Cancer Data Base (NCDB). Patients with and without TNBC were compared with respect to their sociodemographic and clinicopathologic features. TNBC was present in 38,628 of 295,801 (13%) female patients compared to 185 of 3136 (6%) male patients (P < 0.001). The incidence of TNBC varied by region from 10.8% in New England to 15.8% in the east south central US (P < 0.001), as well as by race with the highest rates in African-Americans (23.7%), and lowest in Filipino patients (8.9%). The incidence of TNBC also varied by histology, accounting for 76% of metaplastic cancers, but only 2% of infiltrating lobular carcinomas. TNBCs were significantly larger than non-TNBC (mean 2.8 cm vs 2.1 cm, P < 0.001), and more TNBC were poorly differentiated compared to other subtypes (79.7% vs 25.8%, P < 0.001). On univariate analysis, TNBC was no more likely than non-TNBC to have node-positive disease (32.0% vs 31.7%, respectively, P = 0.218) but in a multivariable analysis controlling for tumor size and grade, TNBC was associated with significantly less node-positivity (OR = 0.59; 95% confidence interval [CI]: 0.57-0.60). TNBC has distinct features regarding age, gender, geographic, and racial distribution. Compared to non-TNBC, TNBC is larger and higher grade, but less likely to have lymph node metastases.

  8. High quality machine-robust image features: identification in nonsmall cell lung cancer computed tomography images.

    PubMed

    Hunter, Luke A; Krafft, Shane; Stingo, Francesco; Choi, Haesun; Martel, Mary K; Kry, Stephen F; Court, Laurence E

    2013-12-01

    For nonsmall cell lung cancer (NSCLC) patients, quantitative image features extracted from computed tomography (CT) images can be used to improve tumor diagnosis, staging, and response assessment. For these findings to be clinically applied, image features need to have high intra and intermachine reproducibility. The objective of this study is to identify CT image features that are reproducible, nonredundant, and informative across multiple machines. Noncontrast-enhanced, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. Two machines ("M1" and "M2") used cine 4D-CT and one machine ("M3") used breath-hold helical 3D-CT. Gross tumor volumes (GTVs) were semiautonomously segmented then pruned by removing voxels with CT numbers less than a prescribed Hounsfield unit (HU) cutoff. Three hundred and twenty eight quantitative image features were extracted from each pruned GTV based on its geometry, intensity histogram, absolute gradient image, co-occurrence matrix, and run-length matrix. For each machine, features with concordance correlation coefficient values greater than 0.90 were considered reproducible. The Dice similarity coefficient (DSC) and the Jaccard index (JI) were used to quantify reproducible feature set agreement between machines. Multimachine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering based on the average correlation between features across multiple machines. For all image types, GTV pruning was found to negatively affect reproducibility (reported results use no HU cutoff). The reproducible feature percentage was highest for average images (M1 = 90.5%, M2 = 94.5%, M1∩M2 = 86.3%), intermediate for end-exhale images (M1 = 75.0%, M2 = 71.0%, M1∩M2 = 52.1%), and lowest for breath-hold images (M3 = 61.0%). Between M1 and M2, the reproducible feature sets

  9. High quality machine-robust image features: Identification in nonsmall cell lung cancer computed tomography images

    PubMed Central

    Hunter, Luke A.; Krafft, Shane; Stingo, Francesco; Choi, Haesun; Martel, Mary K.; Kry, Stephen F.; Court, Laurence E.

    2013-01-01

    Purpose: For nonsmall cell lung cancer (NSCLC) patients, quantitative image features extracted from computed tomography (CT) images can be used to improve tumor diagnosis, staging, and response assessment. For these findings to be clinically applied, image features need to have high intra and intermachine reproducibility. The objective of this study is to identify CT image features that are reproducible, nonredundant, and informative across multiple machines. Methods: Noncontrast-enhanced, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. Two machines (“M1” and “M2”) used cine 4D-CT and one machine (“M3”) used breath-hold helical 3D-CT. Gross tumor volumes (GTVs) were semiautonomously segmented then pruned by removing voxels with CT numbers less than a prescribed Hounsfield unit (HU) cutoff. Three hundred and twenty eight quantitative image features were extracted from each pruned GTV based on its geometry, intensity histogram, absolute gradient image, co-occurrence matrix, and run-length matrix. For each machine, features with concordance correlation coefficient values greater than 0.90 were considered reproducible. The Dice similarity coefficient (DSC) and the Jaccard index (JI) were used to quantify reproducible feature set agreement between machines. Multimachine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering based on the average correlation between features across multiple machines. Results: For all image types, GTV pruning was found to negatively affect reproducibility (reported results use no HU cutoff). The reproducible feature percentage was highest for average images (M1 = 90.5%, M2 = 94.5%, M1∩M2 = 86.3%), intermediate for end-exhale images (M1 = 75.0%, M2 = 71.0%, M1∩M2 = 52.1%), and lowest for breath-hold images (M3 = 61.0%). Between M1 and M2

  10. Clinicopathological features and prognosis of triple negative breast cancer in Kuwait: A comparative/perspective analysis☆

    PubMed Central

    Fayaz, Mohammed S.; El-Sherify, Mustafa S.; El-Basmy, Amany; Zlouf, Sadeq A.; Nazmy, Nashwa; George, Thomas; Samir, Susan; Attia, Gerges; Eissa, Heba

    2013-01-01

    Aim The aim of this study was to determine the incidence of TNBC in Kuwait, to analyze the clinicopathologic features and prognosis of this type of breast cancer, and compare it with reports from other regions of the world. Background Triple negative breast cancer (TNBC) is defined as a subtype that is negative for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2). There is a growing evidence of the heterogeneity of such entity on the molecular level that may cause discrete outcomes. Methods We analyzed the clinicopathologic features of 363 TNBC cases which were diagnosed in Kuwait from July 1999 to June 2009. The disease-free survival (DFS) and overall survival (OS) were analyzed by Kaplan–Meier method. Comparison was done with reports from USA, Europe, Middle and Far East. Results Among 2986 patients diagnosed with breast cancer in Kuwait, 363 patients (12.2%) were TNBC. The median age was 48 years, 57.2% had lymph nodes (LN) metastasis, 56.9% were of grade III tumor and 41.9% had stage II disease. 81% developed recurrences and 75% of deaths occurred by 2.5 years after treatment. There is marked variation of clinicopathologic features according to country of patients’ cohort. Conclusion The incidence of TNBC in our study is similar to other studies. TNBC patients showed an early major recurrence surge peaking at approximately year 2.5. Regional variation of clinicopathologic features indicates a need for molecular studies to define underlying molecular features and its impact on survival. PMID:24936335

  11. Novel mammographic image features differentiate between interval and screen-detected breast cancer: a case-case study.

    PubMed

    Strand, Fredrik; Humphreys, Keith; Cheddad, Abbas; Törnberg, Sven; Azavedo, Edward; Shepherd, John; Hall, Per; Czene, Kamila

    2016-10-05

    Interval breast cancers are often diagnosed at a more advanced stage than screen-detected cancers. Our aim was to identify features in screening mammograms of the normal breast that would differentiate between future interval cancers and screen-detected cancers, and to understand how each feature affects tumor detectability. From a population-based cohort of invasive breast cancer cases in Stockholm-Gotland, Sweden, diagnosed from 2001 to 2008, we analyzed the contralateral mammogram at the preceding negative screening of 394 interval cancer cases and 1009 screen-detected cancers. We examined 32 different image features in digitized film mammograms, based on three alternative dense area identification methods, by a set of logistic regression models adjusted for percent density with interval cancer versus screen-detected cancer as the outcome. Features were forward-selected into a multiple logistic regression model adjusted for mammographic percent density, age, BMI and use of hormone replacement therapy. The associations of the identified features were assessed also in a sample from an independent cohort. Two image features, 'skewness of the intensity gradient' and 'eccentricity', were associated with the risk of interval compared with screen-detected cancer. For the first feature, the per-standard deviation odds ratios were 1.32 (95 % CI: 1.12 to 1.56) and 1.21 (95 % CI: 1.04 to 1.41) in the primary and validation cohort respectively. For the second feature, they were 1.20 (95 % CI: 1.04 to 1.39) and 1.17 (95%CI: 0.98 to 1.39) respectively. The first feature was associated with the tumor size at screen detection, while the second feature was associated with the tumor size at interval detection. We identified two novel mammographic features in screening mammograms of the normal breast that differentiated between future interval cancers and screen-detected cancers. We present a starting point for further research into features beyond percent density that might be

  12. Association of multiparametric MRI quantitative imaging features with prostate cancer gene expression in MRI-targeted prostate biopsies

    PubMed Central

    Stoyanova, Radka; Pollack, Alan; Takhar, Mandeep; Lynne, Charles; Parra, Nestor; Lam, Lucia L.C.; Alshalalfa, Mohammed; Buerki, Christine; Castillo, Rosa; Jorda, Merce; Ashab, Hussam Al-deen; Kryvenko, Oleksandr N.; Punnen, Sanoj; Parekh, Dipen J.; Abramowitz, Matthew C.; Gillies, Robert J.; Davicioni, Elai; Erho, Nicholas; Ishkanian, Adrian

    2016-01-01

    Standard clinicopathological variables are inadequate for optimal management of prostate cancer patients. While genomic classifiers have improved patient risk classification, the multifocality and heterogeneity of prostate cancer can confound pre-treatment assessment. The objective was to investigate the association of multiparametric (mp)MRI quantitative features with prostate cancer risk gene expression profiles in mpMRI-guided biopsies tissues. Global gene expression profiles were generated from 17 mpMRI-directed diagnostic prostate biopsies using an Affimetrix platform. Spatially distinct imaging areas (‘habitats’) were identified on MRI/3D-Ultrasound fusion. Radiomic features were extracted from biopsy regions and normal appearing tissues. We correlated 49 radiomic features with three clinically available gene signatures associated with adverse outcome. The signatures contain genes that are over-expressed in aggressive prostate cancers and genes that are under-expressed in aggressive prostate cancers. There were significant correlations between these genes and quantitative imaging features, indicating the presence of prostate cancer prognostic signal in the radiomic features. Strong associations were also found between the radiomic features and significantly expressed genes. Gene ontology analysis identified specific radiomic features associated with immune/inflammatory response, metabolism, cell and biological adhesion. To our knowledge, this is the first study to correlate radiogenomic parameters with prostate cancer in men with MRI-guided biopsy. PMID:27438142

  13. Mammographic features in infertile women as a potential risk for breast cancer: a preliminary study.

    PubMed

    Meggiorini, M L; Cipolla, V; Rech, F; Labi, L; Vestri, A; de Felice, C

    2012-01-01

    The purpose of the present study was to evaluate breast mammographic features, particularly mammographic density in a selected population of infertile women and to assess if these women should be considered at higher risk for breast cancer. The prevalence of female infertility in Western countries is approximately 10-15% and since causes affecting the female are involved in 35-40%, concerns have developed about the future health of these women, specifically whether infertility could represent a risk factor for future cancer development. Moreover, infertility is now often treated with medication and procedures that could modify the hormonal environment and be cofactors in the cellular changes towards cancer development. Mammographic breast density is a useful marker for breast cancer risk and breast density is considered one of the strongest risk factors for breast cancer. Breast density is associated with known breast cancer risk factors such as reproductive and menstrual factors including serum estrogen and progesterone concentrations. In Italy the National Federation for Breast Cancer (FONCAM) guidelines suggest the usefulness of mammography from 35 years of age for women who undergo infertility hormone therapy (FONCAM Guidelines, 2005). According to this recommendation 294 women aged > or = 35, with primary infertility, sent to our breast service before joining an IVF program were recruited and then underwent clinical examination and X-ray mammography. Women were divided into two groups: dense breast (DB) and non-dense breast (NDB). Univariate analysis was employed to evaluate if there was an association between mammographic density and other risk factors. Evaluation of mammographic features showed the presence of BI-RADs C and D in the sample of 200 (68%) patients with DB and in 94 (32%) patients with NDB BI-RADS A and B. Univariate analysis showed that there were no statistically significant differences between the groups BD and NDB as regards age at

  14. Centrosome amplification induces high grade features and is prognostic of worse outcomes in breast cancer.

    PubMed

    Denu, Ryan A; Zasadil, Lauren M; Kanugh, Craig; Laffin, Jennifer; Weaver, Beth A; Burkard, Mark E

    2016-01-29

    Centrosome amplification (CA) has been reported in nearly all types of human cancer and is associated with deleterious clinical factors such as higher grade and stage. However, previous reports have not shown how CA affects cellular differentiation and clinical outcomes in breast cancer. We analyzed centrosomes by immunofluorescence and compared to ploidy and chromosomal instability (CIN) as assessed by 6-chromosome FISH in a cohort of 362 breast cancers with median clinical follow-up of 8.4 years. Centrosomes were recognized by immunofluorescence using antibodies for pericentriolar material (PCM; pericentrin) and centrioles (polyglutamylated tubulin). CA was experimentally induced in cell culture by overexpression of polo-like kinase 4 (PLK4). CA is associated with reduced all-cause and breast cancer-specific overall survival and recurrence-free survival. CA correlates strongly with high-risk subtypes (e.g. triple negative) and higher stage and grade, and the prognostic nature of CA can be explained largely by these factors. A strong correlation between CA and high tumor ploidy demonstrates that chromosome and centrosome doubling often occur in concert. CA is proposed to be a method of inducing CIN via aberrant mitotic cell divisions; consonant with this, we observed a strong correlation between CA and CIN in breast cancers. However, some CA tumors had low levels of CIN, indicating that protective mechanisms are at play, such as centrosome clustering during mitosis. Intriguingly, some high-risk tumors have more acentriolar centrosomes, suggesting PCM fragmentation as another mechanism of CA. In vitro induction of CA in two non-transformed human cell lines (MCF10A and RPE) demonstrated that CA induces a de-differentiated cellular state and features of high-grade malignancy, supporting the idea that CA intrinsically causes high-grade tumors. CA is associated with deleterious clinical factors and outcomes in breast cancer. Cell doubling events are the most prevalent

  15. Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features.

    PubMed

    Wang, Haibo; Cruz-Roa, Angel; Basavanhally, Ajay; Gilmore, Hannah; Shih, Natalie; Feldman, Mike; Tomaszewski, John; Gonzalez, Fabio; Madabhushi, Anant

    2014-10-01

    Breast cancer (BCa) grading plays an important role in predicting disease aggressiveness and patient outcome. A key component of BCa grade is the mitotic count, which involves quantifying the number of cells in the process of dividing (i.e., undergoing mitosis) at a specific point in time. Currently, mitosis counting is done manually by a pathologist looking at multiple high power fields (HPFs) on a glass slide under a microscope, an extremely laborious and time consuming process. The development of computerized systems for automated detection of mitotic nuclei, while highly desirable, is confounded by the highly variable shape and appearance of mitoses. Existing methods use either handcrafted features that capture certain morphological, statistical, or textural attributes of mitoses or features learned with convolutional neural networks (CNN). Although handcrafted features are inspired by the domain and the particular application, the data-driven CNN models tend to be domain agnostic and attempt to learn additional feature bases that cannot be represented through any of the handcrafted features. On the other hand, CNN is computationally more complex and needs a large number of labeled training instances. Since handcrafted features attempt to model domain pertinent attributes and CNN approaches are largely supervised feature generation methods, there is an appeal in attempting to combine these two distinct classes of feature generation strategies to create an integrated set of attributes that can potentially outperform either class of feature extraction strategies individually. We present a cascaded approach for mitosis detection that intelligently combines a CNN model and handcrafted features (morphology, color, and texture features). By employing a light CNN model, the proposed approach is far less demanding computationally, and the cascaded strategy of combining handcrafted features and CNN-derived features enables the possibility of maximizing the performance

  16. Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features

    PubMed Central

    Wang, Haibo; Cruz-Roa, Angel; Basavanhally, Ajay; Gilmore, Hannah; Shih, Natalie; Feldman, Mike; Tomaszewski, John; Gonzalez, Fabio; Madabhushi, Anant

    2014-01-01

    Abstract. Breast cancer (BCa) grading plays an important role in predicting disease aggressiveness and patient outcome. A key component of BCa grade is the mitotic count, which involves quantifying the number of cells in the process of dividing (i.e., undergoing mitosis) at a specific point in time. Currently, mitosis counting is done manually by a pathologist looking at multiple high power fields (HPFs) on a glass slide under a microscope, an extremely laborious and time consuming process. The development of computerized systems for automated detection of mitotic nuclei, while highly desirable, is confounded by the highly variable shape and appearance of mitoses. Existing methods use either handcrafted features that capture certain morphological, statistical, or textural attributes of mitoses or features learned with convolutional neural networks (CNN). Although handcrafted features are inspired by the domain and the particular application, the data-driven CNN models tend to be domain agnostic and attempt to learn additional feature bases that cannot be represented through any of the handcrafted features. On the other hand, CNN is computationally more complex and needs a large number of labeled training instances. Since handcrafted features attempt to model domain pertinent attributes and CNN approaches are largely supervised feature generation methods, there is an appeal in attempting to combine these two distinct classes of feature generation strategies to create an integrated set of attributes that can potentially outperform either class of feature extraction strategies individually. We present a cascaded approach for mitosis detection that intelligently combines a CNN model and handcrafted features (morphology, color, and texture features). By employing a light CNN model, the proposed approach is far less demanding computationally, and the cascaded strategy of combining handcrafted features and CNN-derived features enables the possibility of maximizing the

  17. Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis

    PubMed Central

    Galván-Tejada, Carlos E.; Zanella-Calzada, Laura A.; Galván-Tejada, Jorge I.; Celaya-Padilla, José M.; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L.

    2017-01-01

    Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions. PMID:28216571

  18. Joint analysis of histopathology image features and gene expression in breast cancer.

    PubMed

    Popovici, Vlad; Budinská, Eva; Čápková, Lenka; Schwarz, Daniel; Dušek, Ladislav; Feit, Josef; Jaggi, Rolf

    2016-05-11

    Genomics and proteomics are nowadays the dominant techniques for novel biomarker discovery. However, histopathology images contain a wealth of information related to the tumor histology, morphology and tumor-host interactions that is not accessible through these techniques. Thus, integrating the histopathology images in the biomarker discovery workflow could potentially lead to the identification of new image-based biomarkers and the refinement or even replacement of the existing genomic and proteomic signatures. However, extracting meaningful and robust image features to be mined jointly with genomic (and clinical, etc.) data represents a real challenge due to the complexity of the images. We developed a framework for integrating the histopathology images in the biomarker discovery workflow based on the bag-of-features approach - a method that has the advantage of being assumption-free and data-driven. The images were reduced to a set of salient patterns and additional measurements of their spatial distribution, with the resulting features being directly used in a standard biomarker discovery application. We demonstrated this framework in a search for prognostic biomarkers in breast cancer which resulted in the identification of several prognostic image features and a promising multimodal (imaging and genomic) prognostic signature. The source code for the image analysis procedures is freely available. The framework proposed allows for a joint analysis of images and gene expression data. Its application to a set of breast cancer cases resulted in image-based and combined (image and genomic) prognostic scores for relapse-free survival.

  19. Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis.

    PubMed

    Galván-Tejada, Carlos E; Zanella-Calzada, Laura A; Galván-Tejada, Jorge I; Celaya-Padilla, José M; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L

    2017-02-14

    Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions.

  20. Identifying ultrasound and clinical features of breast cancer molecular subtypes by ensemble decision

    PubMed Central

    Zhang, Lei; Li, Jing; Xiao, Yun; Cui, Hao; Du, Guoqing; Wang, Ying; Li, Ziyao; Wu, Tong; Li, Xia; Tian, Jiawei

    2015-01-01

    Breast cancer is molecularly heterogeneous and categorized into four molecular subtypes: Luminal-A, Luminal-B, HER2-amplified and Triple-negative. In this study, we aimed to apply an ensemble decision approach to identify the ultrasound and clinical features related to the molecular subtypes. We collected ultrasound and clinical features from 1,000 breast cancer patients and performed immunohistochemistry on these samples. We used the ensemble decision approach to select unique features and to construct decision models. The decision model for Luminal-A subtype was constructed based on the presence of an echogenic halo and post-acoustic shadowing or indifference. The decision model for Luminal-B subtype was constructed based on the absence of an echogenic halo and vascularity. The decision model for HER2-amplified subtype was constructed based on the presence of post-acoustic enhancement, calcification, vascularity and advanced age. The model for Triple-negative subtype followed two rules. One was based on irregular shape, lobulate margin contour, the absence of calcification and hypovascularity, whereas the other was based on oval shape, hypovascularity and micro-lobulate margin contour. The accuracies of the models were 83.8%, 77.4%, 87.9% and 92.7%, respectively. We identified specific features of each molecular subtype and expanded the scope of ultrasound for making diagnoses using these decision models. PMID:26046791

  1. Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction.

    PubMed

    Lian, Chunfeng; Ruan, Su; Denœux, Thierry; Jardin, Fabrice; Vera, Pierre

    2016-08-01

    As a vital task in cancer therapy, accurately predicting the treatment outcome is valuable for tailoring and adapting a treatment planning. To this end, multi-sources of information (radiomics, clinical characteristics, genomic expressions, etc) gathered before and during treatment are potentially profitable. In this paper, we propose such a prediction system primarily using radiomic features (e.g., texture features) extracted from FDG-PET images. The proposed system includes a feature selection method based on Dempster-Shafer theory, a powerful tool to deal with uncertain and imprecise information. It aims to improve the prediction accuracy, and reduce the imprecision and overlaps between different classes (treatment outcomes) in a selected feature subspace. Considering that training samples are often small-sized and imbalanced in our applications, a data balancing procedure and specified prior knowledge are taken into account to improve the reliability of the selected feature subsets. Finally, the Evidential K-NN (EK-NN) classifier is used with selected features to output prediction results. Our prediction system has been evaluated by synthetic and clinical datasets, consistently showing good performance. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Epigenetic alterations as a universal feature of cancer hallmarks and a promising target for personalized treatments.

    PubMed

    Schnekenburger, Michael; Florean, Cristina; Dicato, Mario; Diederich, Marc

    2016-01-01

    Despite considerable scientific progress, the burden of cancer in our society remains a major public health problem. Tumorigenesis is recognized as a complex and multistep process that involves the accumulation of successive transformational events with multi-factorial etiology. Nevertheless, such events result in the acquisition of key hallmark characteristics that are shared by all cancer cells. Accumulating evidence indicates that, besides genetic alterations, epigenetic mechanisms (heritable changes in gene expression caused by modifications in chromatin structure without alterations of DNA sequence) are implicated in the acquisition of malignant phenotype. The potential reversibility of epigenetic alterations linked to tumorigenesis offers a promising avenue for therapeutic intervention. This review focuses on the epigenetic regulation of the cancer hallmarks and the foreseeable use of epigenetic drugs to target these features as a promising strategy for anti-cancer therapy. Based on this body of evidence, we believe that epigenetic deregulations can affect virtually all cell functions and therefore therapeutic approaches with epigenetic drugs could allow multi-target approach against the hallmarks of cancer.

  3. Study on image feature extraction and classification for human colorectal cancer using optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Huang, Shu-Wei; Yang, Shan-Yi; Huang, Wei-Cheng; Chiu, Han-Mo; Lu, Chih-Wei

    2011-06-01

    Most of the colorectal cancer has grown from the adenomatous polyp. Adenomatous lesions have a well-documented relationship to colorectal cancer in previous studies. Thus, to detect the morphological changes between polyp and tumor can allow early diagnosis of colorectal cancer and simultaneous removal of lesions. OCT (Optical coherence tomography) has been several advantages including high resolution and non-invasive cross-sectional image in vivo. In this study, we investigated the relationship between the B-scan OCT image features and histology of malignant human colorectal tissues, also en-face OCT image and the endoscopic image pattern. The in-vitro experiments were performed by a swept-source optical coherence tomography (SS-OCT) system; the swept source has a center wavelength at 1310 nm and 160nm in wavelength scanning range which produced 6 um axial resolution. In the study, the en-face images were reconstructed by integrating the axial values in 3D OCT images. The reconstructed en-face images show the same roundish or gyrus-like pattern with endoscopy images. The pattern of en-face images relate to the stages of colon cancer. Endoscopic OCT technique would provide three-dimensional imaging and rapidly reconstruct en-face images which can increase the speed of colon cancer diagnosis. Our results indicate a great potential for early detection of colorectal adenomas by using the OCT imaging.

  4. Clinicopathologic features of breast cancer patients with type 2 diabetes mellitus in southwest of China.

    PubMed

    Wang, Rui-Jue; Lu, Lin-Jie; Jin, Liang-Bin; Li, Hong-Yuan; Ren, Guo-Sheng; Wu, Kai-Nan; Liu, Sheng-Chun; Kong, Ling-Quan

    2014-01-01

    The aim of this study was to study the prevalence and clinicopathologic features of breast cancer patients with type 2 diabetes mellitus in southwest of China for providing clinical guidance and prognosis appreciation for these patients. Through a case-control study of 3,381 primary breast cancer patients initially diagnosed from January 2007 to May 2013, one case group (164 female breast cancer patients with type 2 diabetes) and two control groups (first control group consists of 328 randomly selected nondiabetic breast cancer patients and second control group consists of 279 nondiabetic breast cancer patients without diabetes-related diseases such as cardiovascular or cerebrovascular diseases) were selected. The clinicopathological features between them were statistically analyzed. (1) Of 3,381 primary breast cancer patients with the average age of 50.5, ranging from 21 to 97 years of age, 164 (4.9 %) cases (with the average age of 60.7) suffered diabetes (previously diagnosed diabetes). (2) The differences of clinicopathologic features between the case group and first control group (with the average age of 61.5) were the ratio of hypertension (41.5 vs 26.1 %, P = 0.001) and axillary lymph node metastasis (51.1 vs 38.1 %, P = 0.046); and the differences of clinicopathologic features between the case group and second control group (with the average age of 64.3) were axillary lymph node metastasis (51.1 vs 35.8 %, P = 0.017), tumor size (≥ T2: 62.3 vs 53.1 %, P = 0.019) and p53 expression (51.0 vs 62.7 %, P = 0.018). No statistical significances (P > 0.05) of histological type, histological grade, or the expressions of estrogen receptor (ER), progesterone receptor, human epidermal growth factor 2 (HER2) and Ki67 were found between them. (3) The clinicopathologic features of ER-positive and ER-negative patients in each group were as follows: (1) In the case group, the ER-negative patients have more advanced tumor histological grade (G3, 19.0 vs 2.8 %, P = 0

  5. Clinicopathological features and surgical safety of gastric cancer in elderly patients.

    PubMed

    Lim, Joo Hyun; Lee, Dong Ho; Shin, Cheol Min; Kim, Nayoung; Park, Young Soo; Jung, Hyun Chae; Song, In Sung

    2014-12-01

    Gastric cancer is one of the most common cancers, especially among the elderly. However little is known about gastric cancer in elderly patients. This study was designed to evaluate the specific features of gastric cancer in elderly patients. Medical records of 1,107 patients who had radical gastrectomy for gastric cancer between June 2005 and December 2009 were reviewed. They were divided into young (<65 yr, n=676), young-old (65-74 yr, n=332), and old-old age group (≥75 yr, n=99). Increased CA 19-9 (5.6%, 13.4%, 14.6%, P=0.001), advanced diseases (42.5%, 47.0%, and 57.6, P=0.014), and node metastasis (37.6%, 38.9%, 51.5%, P=0.029) were more common in the young-old and old-old age groups. There were no significant differences in Helicobacter pylori status (63.6%, 56.7%, 61.2%, P=0.324) between the three groups. Surgery-related complication rates were similar in the three groups (5.3%, 5.1%, 8.1%, P=0.497). Microsatellite instability (P<0.001) and p53 overexpression (P<0.001) were more common among the elderly. The elderly group had more synchronous tumors (7.5%, 10.2%, 17.2%; P=0.006). Surgery can be applied to elderly gastric cancer without significant risk of complications. However, considering the more advanced disease and synchronous tumors among the elderly, care should be taken while deciding the extent of surgery for elderly gastric cancer.

  6. [Clinical and pathological features of breast cancer in a population of Mexico].

    PubMed

    Maffuz-Aziz, Antonio; Labastida-Almendaro, Sonia; Espejo-Fonseca, Aura; Rodríguez-Cuevas, Sergio

    Breast cancer is the most common among women in our country, and its treatment is based on prognostic factors to categorize patients into different risk groups. In this study, the clinical and pathological features that play a role as a prognostic factor in a representative population with breast cancer in México are described. A descriptive analysis of the clinical and pathological features of women diagnosed with breast cancer, in a period from June 2005 to May 2014; registered in a database and calculated by simple frequencies. A total of 4,411 patients were included, the average age at diagnosis was 53 years, 19.7% were diagnosed by mammography screening program and 80.3% derived from any signs or symptoms. Regarding the stages at diagnosis, 6.8% were carcinoma in situ, 36% at early stages (I and IIA), 45% locally advanced (IIB to IIIC), 7.7% metastatic and 3.9% unclassifiable. A 79% were ductal histology, lobular 7.8% and the rest, other types. Of ductal carcinomas, 9.1% were grade I, 54.1% grade II, and 34.6% grade III. Regarding the biological subtypes, 65.7% were luminal, 10.9% luminal Her positive, 8.7% pure Her 2 positive and 14.6% triple negative. In the present study, we described the clinical and pathologic features of a group of Mexican women with breast cancer that might reflect a national landscape, and represent the prognostic factors to determine groups of risk and treatment decisions. Copyright © 2016 Academia Mexicana de Cirugía A.C. Publicado por Masson Doyma México S.A. All rights reserved.

  7. Clinical features, anti-cancer treatments and outcomes of lung cancer patients with combined pulmonary fibrosis and emphysema.

    PubMed

    Minegishi, Yuji; Kokuho, Nariaki; Miura, Yukiko; Matsumoto, Masaru; Miyanaga, Akihiko; Noro, Rintaro; Saito, Yoshinobu; Seike, Masahiro; Kubota, Kaoru; Azuma, Arata; Kida, Kouzui; Gemma, Akihiko

    2014-08-01

    Combined pulmonary fibrosis and emphysema (CPFE) patients may be at significantly increased risk of lung cancer compared with either isolated emphysema or pulmonary fibrosis patients. Acute exacerbation (AE) of interstitial lung disease caused by anticancer treatment is the most common lethal complication in Japanese lung cancer patients. Nevertheless, the clinical significance of CPFE compared with isolated idiopathic interstitial pneumonias (IIPs) in patients with lung cancer is not well understood. A total of 1536 patients with lung cancer at Nippon Medical School Hospital between March 1998 and October 2011 were retrospectively reviewed. Patients with IIPs were categorized into two groups: (i) CPFE; IIP patients with definite emphysema and (ii) non-CPFE; isolated IIP patients without definite emphysema. The clinical features, anti-cancer treatments and outcomes of the CPFE group were compared with those of the non-CPFE group. CPFE and isolated IIPs were identified in 88 (5.7%) and 63 (4.1%) patients respectively, with lung cancer. AE associated with initial treatment occurred in 22 (25.0%) patients in the CPFE group and in 8 (12.7%) patients in the non-CPFE group, irrespective of treatment modality. Median overall survival (OS) of the CPFE group was 23.7 months and that of the non-CPFE group was 20.3 months (P=0.627). Chemotherapy was performed in a total of 83 patients. AE associated with chemotherapy for advanced lung cancer occurred in 6 (13.6%) patients in the CPFE group and 5 (12.8%) patients in the non-CPFE group. Median OS of the CPFE group was 14.9 months and that of the non-CPFE group was 21.6 months (P=0.679). CPFE was not an independent risk factor for AE and was not an independent prognosis factor in lung cancer patients with IIPs. Therefore, great care must be exercised with CPFE as well as IIP patients when performing anticancer treatment for patients with lung cancer. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  8. Cancer registries in Africa 2014: A survey of operational features and uses in cancer control planning.

    PubMed

    Gakunga, Robai; Parkin, D Maxwell

    2015-11-01

    A questionnaire survey of all active population based cancer registries in sub-Saharan Africa obtained information on their characteristics (size, staffing, funding), methods of working, the nature of any links between registries and their respective Health Authorities (national and/or local), and the use of their data in research or cancer control planning. 23/25 registries (92%) responded. Sources of direct funding and estimated amounts from each source were established, and suggest that it is approximately US$8-9 per case registered. Almost half of the funding is used for routine data collection, processing and analysis. Staffing levels vary, partly as a function of the registry size (approximately one FTE per 300 cases registered). Most data collection is active, using multiple sources (median 10 per registry), and is largely paper-based (abstraction onto paper forms), although all use the computer system CanReg© for data entry, storage and analysis. Most reporting by the registries is remarkably timely, and in general, their results are widely used by health authorities and other stakeholders in planning and evaluating services, while research output is much more variable. These registries are the source of almost all the existing information on cancer incidence and mortality in sub-Saharan Africa, as published in IARC's "Globocan".

  9. Clinicopathological features of young patients (<35 years of age) with breast cancer in a Japanese Breast Cancer Society supported study.

    PubMed

    Kataoka, Akemi; Tokunaga, Eriko; Masuda, Norikazu; Shien, Tadahiko; Kawabata, Kimiko; Miyashita, Mika

    2014-11-01

    To clarify the clinicopathological features of breast cancer in young females, surveillance data of the Registration Committee of the Japanese Breast Cancer Society were analyzed. The clinicopathological characteristics were compared between young (<35) patients and non-young (≥35) patients among 109,617 records registered between 2004 and 2009. The numbers of young and non-young patients were 2,982 (2.7 %) and 106,295 (97.0 %), respectively. The young patients had more cases of a familial history of breast cancer, more subjective symptoms, fewer bilateral tumors, lower BMIs, larger tumors, more positive lymph nodes, fewer instances of an ER-positive status, more instances of an HER2-positive status, more triple-negative tumors and more advanced TNM stages. The young patients more frequently received neoadjuvant chemotherapy and breast-conserving therapy (BCT) compared with the non-young patients. Eighty percent of all patients received adjuvant therapy. The young patients were more frequently treated with chemotherapy, molecular targeted therapy and radiation therapy than the non-young patients. In this study, young patients with breast cancer were diagnosed at more advanced stages and had more endocrine-unresponsive tumors than non-young patients. Further prognostic analyses should be conducted in this cohort.

  10. Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis.

    PubMed

    Sun, Wenqing; Zheng, Bin; Qian, Wei

    2017-04-13

    This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand-crafted features. All of the 1018 cases were acquired from Lung Image Database Consortium (LIDC) public lung cancer database. The nodules were segmented according to four radiologists' markings, and 13,668 samples were generated by rotating every slice of nodule images. Three multichannel ROI based deep structured algorithms were designed and implemented in this study: convolutional neural network (CNN), deep belief network (DBN), and stacked denoising autoencoder (SDAE). For the comparison purpose, we also implemented a CADx system using hand-crafted features including density features, texture features and morphological features. The performance of every scheme was evaluated by using a 10-fold cross-validation method and an assessment index of the area under the receiver operating characteristic curve (AUC). The observed highest area under the curve (AUC) was 0.899±0.018 achieved by CNN, which was significantly higher than traditional CADx with the AUC=0.848±0.026. The results from DBN was also slightly higher than CADx, while SDAE was slightly lower. By visualizing the automatic generated features, we found some meaningful detectors like curvy stroke detectors from deep structured schemes. The study results showed the deep structured algorithms with automatically generated features can achieve desirable performance in lung nodule diagnosis. With well-tuned parameters and large enough dataset, the deep learning algorithms can have better performance than current popular CADx. We believe the deep learning algorithms with similar data preprocessing procedure can be used in other medical image analysis areas as well. Copyright © 2017. Published by Elsevier Ltd.

  11. A new breast cancer risk analysis approach using features extracted from multiple sub-regions on bilateral mammograms

    NASA Astrophysics Data System (ADS)

    Sun, Wenqing; Tseng, Tzu-Liang B.; Zheng, Bin; Zhang, Jianying; Qian, Wei

    2015-03-01

    A novel breast cancer risk analysis approach is proposed for enhancing performance of computerized breast cancer risk analysis using bilateral mammograms. Based on the intensity of breast area, five different sub-regions were acquired from one mammogram, and bilateral features were extracted from every sub-region. Our dataset includes 180 bilateral mammograms from 180 women who underwent routine screening examinations, all interpreted as negative and not recalled by the radiologists during the original screening procedures. A computerized breast cancer risk analysis scheme using four image processing modules, including sub-region segmentation, bilateral feature extraction, feature selection, and classification was designed to detect and compute image feature asymmetry between the left and right breasts imaged on the mammograms. The highest computed area under the curve (AUC) is 0.763 ± 0.021 when applying the multiple sub-region features to our testing dataset. The positive predictive value and the negative predictive value were 0.60 and 0.73, respectively. The study demonstrates that (1) features extracted from multiple sub-regions can improve the performance of our scheme compared to using features from whole breast area only; (2) a classifier using asymmetry bilateral features can effectively predict breast cancer risk; (3) incorporating texture and morphological features with density features can boost the classification accuracy.

  12. Continuous wavelet transform-based feature selection applied to near-infrared spectral diagnosis of cancer.

    PubMed

    Chen, Hui; Lin, Zan; Mo, Lin; Wu, Hegang; Wu, Tong; Tan, Chao

    2015-01-01

    Spectrum is inherently local in nature since it can be thought of as a signal being composed of various frequency components. Wavelet transform (WT) is a powerful tool that partitions a signal into components with different frequency. The property of multi-resolution enables WT a very effective and natural tool for analyzing spectrum-like signal. In this study, a continuous wavelet transform (CWT)-based variable selection procedure was proposed to search for a set of informative wavelet coefficients for constructing a near-infrared (NIR) spectral diagnosis model of cancer. The CWT provided a fine multi-resolution feature space for selecting best predictors. A measure of discriminating power (DP) was defined to evaluate the coefficients. Partial least squares-discriminant analysis (PLS-DA) was used as the classification algorithm. A NIR spectral dataset associated to cancer diagnosis was used for experiment. The optimal results obtained correspond to the wavelet of db2. It revealed that on condition of having better performance on the training set, the optimal PLS-DA model using only 40 wavelet coefficients in 10 scales achieved the same performance as the one using all the variables in the original space on the test set: an overall accuracy of 93.8%, sensitivity of 92.5% and specificity of 96.3%. It confirms that the CWT-based feature selection coupled with PLS-DA is feasible and effective for constructing models of diagnostic cancer by NIR spectroscopy.

  13. Adjuvant Radiation Therapy Alone for HPV Related Oropharyngeal Cancers with High Risk Features

    PubMed Central

    Su, William; Liu, Jerry; Miles, Brett A.; Genden, Eric M.; Misiukiewicz, Krzysztof J.; Posner, Marshall; Gupta, Vishal; Bakst, Richard L.

    2016-01-01

    Background Current standard of care for oropharyngeal cancers with positive surgical margins and/or extracapsular extension is adjuvant chemoradiotherapy. It is unknown whether HPV+ oropharyngeal cancer benefits from this treatment intensification. Objective To investigate the outcomes of HPV+ patients treated with adjuvant radiotherapy alone when chemoradiotherapy was indicated based on high risk pathological features. They were compared with high risk HPV+ patients treated with adjuvant chemoradiotherapy. Methods All high risk HPV+ oropharyngeal cancer patients (9) who received radiotherapy alone were identified. We also identified 17 patients who received chemoradiotherapy as a comparison group. Median follow up time was 37.3 months. Results No local failures developed in adjuvant radiotherapy group. There was 1 distant recurrence in this cohort and 3 in CRT cohort. Regarding toxicity, 8 (47.1%) chemoradiotherapy patients had >10 lb. weight loss (p = 0.013), despite 75% of them having a percutaneous endoscopic gastrostomy tube placed. No individuals in radiotherapy group experienced a >10 lb. weight loss and none required a gastrostomy tube. Conclusions This series provides preliminary evidence suggesting that the omission of concurrent chemotherapy to adjuvant radiotherapy may offer comparative local control rates with a lower toxicity profile in the setting of HPV+ patients with traditional high risk features. PMID:27930732

  14. Novel histopathologic feature identified through image analysis augments stage II colorectal cancer clinical reporting

    PubMed Central

    Caie, Peter D.; Zhou, Ying; Turnbull, Arran K.; Oniscu, Anca; Harrison, David J.

    2016-01-01

    A number of candidate histopathologic factors show promise in identifying stage II colorectal cancer (CRC) patients at a high risk of disease-specific death, however they can suffer from low reproducibility and none have replaced classical pathologic staging. We developed an image analysis algorithm which standardized the quantification of specific histopathologic features and exported a multi-parametric feature-set captured without bias. The image analysis algorithm was executed across a training set (n = 50) and the resultant big data was distilled through decision tree modelling to identify the most informative parameters to sub-categorize stage II CRC patients. The most significant, and novel, parameter identified was the ‘sum area of poorly differentiated clusters’ (AreaPDC). This feature was validated across a second cohort of stage II CRC patients (n = 134) (HR = 4; 95% CI, 1.5– 11). Finally, the AreaPDC was integrated with the significant features within the clinical pathology report, pT stage and differentiation, into a novel prognostic index (HR = 7.5; 95% CI, 3–18.5) which improved upon current clinical staging (HR = 4.26; 95% CI, 1.7– 10.3). The identification of poorly differentiated clusters as being highly significant in disease progression presents evidence to suggest that these features could be the source of novel targets to decrease the risk of disease specific death. PMID:27322148

  15. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features.

    PubMed

    Magdy, Eman; Zayed, Nourhan; Fakhr, Mahmoud

    2015-01-01

    Computer-aided diagnostic (CAD) systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients' lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately. Amplitude-Modulation Frequency-Modulation (AM-FM) method thirdly, has been used to extract features for ROIs. Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR) for classification step. Finally, K-nearest neighbour (KNN), support vector machine (SVM), naïve Bayes, and linear classifiers have been used with the selected AM-FM features. The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated. The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier.

  16. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features

    PubMed Central

    Magdy, Eman; Zayed, Nourhan; Fakhr, Mahmoud

    2015-01-01

    Computer-aided diagnostic (CAD) systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients' lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately. Amplitude-Modulation Frequency-Modulation (AM-FM) method thirdly, has been used to extract features for ROIs. Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR) for classification step. Finally, K-nearest neighbour (KNN), support vector machine (SVM), naïve Bayes, and linear classifiers have been used with the selected AM-FM features. The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated. The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier. PMID:26451137

  17. Analysis of Mel-18 expression in prostate cancer tissues and correlation with clinicopathologic features.

    PubMed

    Wang, Wei; Lin, Tianxin; Huang, Jian; Hu, Weilie; Xu, Kewei; Liu, Jun

    2011-01-01

    Mel-18 is a member of the polycomb group (PcG) of proteins, which are chromatin regulatory factors that play an important role in development and oncogenesis. This study was designed to investigate the clinical and prognostic significance of Mel-18 in the patients with prostate cancer. Immunostaining with Mel-18 specific antibodies was performed on paraffin sections from 202 patients. Correlations between Mel-18 and the Gleason grading system, clinical stage, serum prostate-specific antigen (PSA) levels, and age were evaluated. PSA recurrence in 76 patients who underwent radical prostatectomy and survival in 59 patients with metastases at diagnosis were analyzed to evaluate the influence of Mel-18 expression in cancer progression using Kaplan-Meier analysis and multivariate Cox regression analysis. Staining was seen in all prostatic tissues. Mel-18 expression was significantly reduced in the prostate cancer patients with PSA levels over 100 ng/ml (P=0.009), advanced clinical stage (>T4, N1, or M1 disease, P=0.029), higher Gleason grade or with a higher Gleason score (P=0.018) than in those with other clinicopathologic features. Negative expression of Mel-18 was associated with significantly higher rates of PSA recurrence after radical prostatectomy than with positive expression of Mel-18 (P = 0.029), and was an independent predictor of PSA recurrence (P=0.034, HR=2.143) in multivariate analysis. Similarly, metastatic prostate cancer patients with negative expression of Mel-18 showed significantly worse survival compared with the positive expression of Mel-18 (P=0.025). In multivariate analysis, negative expression of Mel-18 was an independent predictor of cancer-specific survival (P=0.024, HR=2.365). Our study provides important evidence for the recognition of Mel-18 as a tumor suppressor. The expression of Mel-18 showed potential as a prognostic marker for human prostate cancer. Copyright © 2011 Elsevier Inc. All rights reserved.

  18. Identification of endometrial cancer methylation features using combined methylation analysis methods

    PubMed Central

    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

  19. Clinical features and overall survival among elderly cancer patients in a tertiary cancer center

    PubMed Central

    Antunes, Yuri Philippe Pimentel Vieira; Bugano, Diogo Diniz Gomes; del Giglio, Auro; Kaliks, Rafael Aliosha; Karnakis, Theodora; Pontes, Lucíola de Barros

    2015-01-01

    ABSTRACT Objective To evaluate the epidemiological profile and overall survival of a large population of elderly individuals diagnosed with solid tumors in a tertiary hospital. Methods This retrospective study included patients aged >65 years, diagnosed with solid tumors between January 2007 and December 2011, at Hospital Israelita Albert Einstein, São Paulo, Brazil. The medical records were reviewed to obtain information about clinical variables and overall survival. Results A total of 806 patients were identified, and 58.4% were male. Mean age was 74 years (65 to 99 years). The most common types were prostate (22%), colorectal (21%), breast (19%), and lung cancer (13%), followed by bladder (8%), pancreas (6%), and other types (11%). The majority of patients were diagnosed at early stage disease. After a median follow-up of 27 months (15 to 45 months), 29% of the patients (234/806) died, predominantly in the group older than 70 years. For the entire cohort, the median 2-year survival rate was 71%. Median overall survival was not reached within the study period. In a multivariate analysis, age (HR: 1.35; 95%CI: 1.25-1.45; p<0.001) and disease stage (HR: 1.93; 95%CI: 1.75-2.14; p<0.001) were independent negative predictors of poor survival. Conclusion The most prevalent tumors were prostate, colorectal, breast, and lung cancer, with the larger proportion diagnosed at initial stages, reflecting the great number of patients alive at last follow-up. PMID:26676269

  20. Delta-radiomics features for the prediction of patient outcomes in non-small cell lung cancer.

    PubMed

    Fave, Xenia; Zhang, Lifei; Yang, Jinzhong; Mackin, Dennis; Balter, Peter; Gomez, Daniel; Followill, David; Jones, Aaron Kyle; Stingo, Francesco; Liao, Zhongxing; Mohan, Radhe; Court, Laurence

    2017-04-03

    Radiomics is the use of quantitative imaging features extracted from medical images to characterize tumor pathology or heterogeneity. Features measured at pretreatment have successfully predicted patient outcomes in numerous cancer sites. This project was designed to determine whether radiomics features measured from non-small cell lung cancer (NSCLC) change during therapy and whether those features (delta-radiomics features) can improve prognostic models. Features were calculated from pretreatment and weekly intra-treatment computed tomography images for 107 patients with stage III NSCLC. Pretreatment images were used to determine feature-specific image preprocessing. Linear mixed-effects models were used to identify features that changed significantly with dose-fraction. Multivariate models were built for overall survival, distant metastases, and local recurrence using only clinical factors, clinical factors and pretreatment radiomics features, and clinical factors, pretreatment radiomics features, and delta-radiomics features. All of the radiomics features changed significantly during radiation therapy. For overall survival and distant metastases, pretreatment compactness improved the c-index. For local recurrence, pretreatment imaging features were not prognostic, while texture-strength measured at the end of treatment significantly stratified high- and low-risk patients. These results suggest radiomics features change due to radiation therapy and their values at the end of treatment may be indicators of tumor response.

  1. Clinicopathological features and prognostic factors of young breast cancers in Eastern Guangdong of China

    PubMed Central

    Wei, Jin-Tao; Huang, Wen-He; Du, Cai-Wen; Qiu, Si-Qi; Wei, Xiao-Long; Liu, Jing; Zhang, Guo-Jun

    2014-01-01

    Breast cancer in young women is typically with higher proportion of adverse pathological features. Breast cancer with BRCA1 mutation is often early-onset, and is usually associated with triple negative phenotpe. In this study, we aim to analyze the clinicopathological characteristics and prognosis in young breast cancer patients (≤35 years old) comparing to non-young patients (>35 years old). A total of 1913 cases of primary breast carcinoma with stage I–III were enrolled, with 283 cases diagnosed as young patients. No significant difference was observed in tumor size, TNM staging, lymph node metastasis, ER, HER-2 or histological grade between young and non-young patients. Multivariate analysis demonstrated that age was an independent prognostic factor for overall survival (OS). In 70 samples of young patients available, BRCA1 was immunohistochemically positive 85.7% in cytoplasm and 41.4% in nuclear. BRCA1 nuclear expression is not significantly associated with clinicopathological characteristics in young breast cancer patients. PMID:24942640

  2. Hypoxia-inducible factor 1–mediated characteristic features of cancer cells for tumor radioresistance

    PubMed Central

    Harada, Hiroshi

    2016-01-01

    Tumor hypoxia has been attracting increasing attention in the fields of radiation biology and oncology since Thomlinson and Gray detected hypoxic cells in malignant solid tumors and showed that they exert a negative impact on the outcome of radiation therapy. This unfavorable influence has, at least partly, been attributed to cancer cells acquiring a radioresistant phenotype through the activation of the transcription factor, hypoxia-inducible factor 1 (HIF-1). On the other hand, accumulating evidence has recently revealed that, even though HIF-1 is recognized as an important regulator of cellular adaptive responses to hypoxia, it may not become active and induce tumor radioresistance under hypoxic conditions only. The mechanisms by which HIF-1 is activated in cancer cells not only under hypoxic conditions, but also under normoxic conditions, through cancer-specific genetic alterations and the resultant imbalance in intermediate metabolites have been summarized herein. The relevance of the HIF-1–mediated characteristic features of cancer cells, such as the production of antioxidants through reprogramming of the glucose metabolic pathway and cell cycle regulation, for tumor radioresistance has also been reviewed. PMID:26983985

  3. MtDNA depleted PC3 cells exhibit Warburg effect and cancer stem cell features

    PubMed Central

    Li, Xiaoran; Zhong, Yali; Lu, Jie; Axcrona, Karol; Eide, Lars; Syljuåsen, Randi G.; Peng, Qian; Wang, Junbai; Zhang, Hongquan; Goscinski, Mariusz Adam; Kvalheim, Gunnar; Nesland, Jahn M.; Suo, Zhenhe

    2016-01-01

    Reducing mtDNA content was considered as a critical step in the metabolism restructuring for cell stemness restoration and further neoplastic development. However, the connections between mtDNA depletion and metabolism reprograming-based cancer cell stemness in prostate cancers are still lack of studies. Here, we demonstrated that human CRPC cell line PC3 tolerated high concentration of the mtDNA replication inhibitor ethidium bromide (EtBr) and the mtDNA depletion triggered a universal metabolic remodeling process. Failure in completing that process caused lethal consequences. The mtDNA depleted (MtDP) PC3 cells could be steadily maintained in the special medium in slow cycling status. The MtDP PC3 cells contained immature mitochondria and exhibited Warburg effect. Furthermore, the MtDP PC3 cells were resistant to therapeutic treatments and contained greater cancer stem cell-like subpopulations: CD44+, ABCG2+, side-population and ALDHbright. In conclusion, these results highlight the association of mtDNA content, mitochondrial function and cancer cell stemness features. PMID:27248169

  4. Identification of Prognostic Molecular Features in the Reactive Stroma of Human Breast and Prostate Cancer

    PubMed Central

    Provero, Paolo; Fusco, Carlo; Delorenzi, Mauro; Stehle, Jean-Christophe; Stamenkovic, Ivan

    2011-01-01

    Primary tumor growth induces host tissue responses that are believed to support and promote tumor progression. Identification of the molecular characteristics of the tumor microenvironment and elucidation of its crosstalk with tumor cells may therefore be crucial for improving our understanding of the processes implicated in cancer progression, identifying potential therapeutic targets, and uncovering stromal gene expression signatures that may predict clinical outcome. A key issue to resolve, therefore, is whether the stromal response to tumor growth is largely a generic phenomenon, irrespective of the tumor type or whether the response reflects tumor-specific properties. To address similarity or distinction of stromal gene expression changes during cancer progression, oligonucleotide-based Affymetrix microarray technology was used to compare the transcriptomes of laser-microdissected stromal cells derived from invasive human breast and prostate carcinoma. Invasive breast and prostate cancer-associated stroma was observed to display distinct transcriptomes, with a limited number of shared genes. Interestingly, both breast and prostate tumor-specific dysregulated stromal genes were observed to cluster breast and prostate cancer patients, respectively, into two distinct groups with statistically different clinical outcomes. By contrast, a gene signature that was common to the reactive stroma of both tumor types did not have survival predictive value. Univariate Cox analysis identified genes whose expression level was most strongly associated with patient survival. Taken together, these observations suggest that the tumor microenvironment displays distinct features according to the tumor type that provides survival-predictive value. PMID:21611158

  5. Prediction of breast cancer by profiling of urinary RNA metabolites using Support Vector Machine-based feature selection.

    PubMed

    Henneges, Carsten; Bullinger, Dino; Fux, Richard; Friese, Natascha; Seeger, Harald; Neubauer, Hans; Laufer, Stefan; Gleiter, Christoph H; Schwab, Matthias; Zell, Andreas; Kammerer, Bernd

    2009-04-05

    Breast cancer belongs to the most frequent and severe cancer types in human. Since excretion of modified nucleosides from increased RNA metabolism has been proposed as a potential target in pathogenesis of breast cancer, the aim of the present study was to elucidate the predictability of breast cancer by means of urinary excreted nucleosides. We analyzed urine samples from 85 breast cancer women and respective healthy controls to assess the metabolic profiles of nucleosides by a comprehensive bioinformatic approach. All included nucleosides/ribosylated metabolites were isolated by cis-diol specific affinity chromatography and measured with liquid chromatography ion trap mass spectrometry (LC-ITMS). A valid set of urinary metabolites was selected by exclusion of all candidates with poor linearity and/or reproducibility in the analytical setting. The bioinformatic tool of Oscillating Search Algorithm for Feature Selection (OSAF) was applied to iteratively improve features for training of Support Vector Machines (SVM) to better predict breast cancer. After identification of 51 nucleosides/ribosylated metabolites in the urine of breast cancer women and/or controls by LC- ITMS coupling, a valid set of 35 candidates was selected for subsequent computational analyses. OSAF resulted in 44 pairwise ratios of metabolite features by iterative optimization. Based on this approach ultimately estimates for sensitivity and specificity of 83.5% and 90.6% were obtained for best prediction of breast cancer. The classification performance was dominated by metabolite pairs with SAH which highlights its importance for RNA methylation in cancer pathogenesis. Extensive RNA-pathway analysis based on mass spectrometric analysis of metabolites and subsequent bioinformatic feature selection allowed for the identification of significant metabolic features related to breast cancer pathogenesis. The combination of mass spectrometric analysis and subsequent SVM-based feature selection represents

  6. Clinical and Molecular Features of Laron Syndrome, A Genetic Disorder Protecting from Cancer.

    PubMed

    Janecka, Anna; Kołodziej-Rzepa, Marta; Biesaga, Beata

    2016-01-01

    Laron syndrome (LS) is a rare, genetic disorder inherited in an autosomal recessive manner. The disease is caused by mutations of the growth hormone (GH) gene, leading to GH/insulin-like growth factor type 1 (IGF1) signalling pathway defect. Patients with LS have characteristic biochemical features, such as a high serum level of GH and low IGF1 concentration. Laron syndrome was first described by the Israeli physician Zvi Laron in 1966. Globally, around 350 people are affected by this syndrome and there are two large groups living in separate geographic regions: Israel (69 individuals) and Ecuador (90 individuals). They are all characterized by typical appearance such as dwarfism, facial phenotype, obesity and hypogenitalism. Additionally, they suffer from hypoglycemia, hypercholesterolemia and sleep disorders, but surprisingly have a very low cancer risk. Therefore, studies on LS offer a unique opportunity to better understand carcinogenesis and develop new strategies of cancer treatment.

  7. Inflammation, autophagy, and obesity: common features in the pathogenesis of pancreatitis and pancreatic cancer.

    PubMed

    Gukovsky, Ilya; Li, Ning; Todoric, Jelena; Gukovskaya, Anna; Karin, Michael

    2013-06-01

    Inflammation and autophagy are cellular defense mechanisms. When these processes are deregulated (deficient or overactivated) they produce pathologic effects, such as oxidative stress, metabolic impairments, and cell death. Unresolved inflammation and disrupted regulation of autophagy are common features of pancreatitis and pancreatic cancer. Furthermore, obesity, a risk factor for pancreatitis and pancreatic cancer, promotes inflammation and inhibits or deregulates autophagy, creating an environment that facilitates the induction and progression of pancreatic diseases. However, little is known about how inflammation, autophagy, and obesity interact to promote exocrine pancreatic disorders. We review the roles of inflammation and autophagy, and their deregulation by obesity, in pancreatic diseases. We discuss the connections among disordered pathways and important areas for future research. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.

  8. Correlation between three-dimensional ultrasound features and pathological prognostic factors in breast cancer.

    PubMed

    Jiang, Jun; Chen, Ya-qing; Xu, Yi-zhuan; Chen, Ming-li; Zhu, Yun-kai; Guan, Wen-bin; Wang, Xiao-jin

    2014-06-01

    To investigate the correlation of three-dimensional (3D) ultrasound features with prognostic factors in invasive ductal carcinoma. Surgical resection specimens of 85 invasive ductal carcinomas of 85 women who had undergone 3D ultrasound were included. Morphology features and vascularization perfusion on 3D ultrasound were evaluated. Pathologic prognostic factors, including tumour size, histological grade, lymph node status, oestrogen and progesterone receptor status (ER, PR), c-erbB-2 and p53 expression, and microvessel density (MVD) were determined. Correlations of 3D ultrasound features and prognostic factors were analysed. The retraction pattern in the coronal plane had a significant value as an independent predictor of a small tumour size (P = 0.014), a lower histological grade (P = 0.009) and positive ER or PR expression status (P = 0.001, 0.044). The retraction pattern with a hyperechoic ring only existed in low-grade and ER-positive tumours. The presence of the hyperechoic ring strengthened the ability of the retraction pattern to predict a good prognosis of breast cancer. The increased intra-tumour vascularization index (VI, the mean tumour vascularity) reflected a higher histological grade (P = 0.025) and had a positive correlation with MVD (r = 0.530, P = 0.001). The retraction pattern and histogram indices of VI provided by 3D ultrasound may be useful in predicting prognostic information about breast cancer. Three-dimensional ultrasound can potentially provide prognostic evaluation of breast cancer. The retraction pattern and hyperechoic ring in the coronal plane suggest good prognosis. The increased intra-tumour vascularization index reflects a higher histological grade. The intra-tumour vascularization index is positively correlated with microvessel density.

  9. Evaluation of insulin like growth facror-1 genetic polymorphism with gastric cancer susceptibility and clinicopathological features.

    PubMed

    Farahani, Roya Kishani; Azimzadeh, Pedram; Rostami, Elham; Malekpour, Habib; Aghdae, Hamid Asadzadeh; Pourhoseingholi, Mohamad Amin; Nazemalhosseini Mojarad, Ehsan; Zali, Mohammad Reza

    2015-01-01

    Gastric cancer (GC) is one of the most common malignancies in the world. It is the first cause of cancer deaths in both sexes In Iranian population. Circulating insulin-like growth factor-one (IGF-1) levels have been associated for gastric cancer. IGF-1 protein has central roles involved in the regulation of epithelial cell growth, proliferation, transformation, apoptosis and metastasis. Single nucleotide polymorphism in IGF-1 regulatory elements may lead to alter in IGF-1 expression level and GC susceptibility. The aim of this study was to investigate the influence of IGF-1 gene polymorphism (rs5742612) on risk of GC and clinicopathological features for the first time in Iranian population. In total, 241 subjects including 100 patients with GC and 141 healthy controls were recruited in our study. Genotypes were analyzed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay with DNA from peripheral blood. The polymorphism was statistically analyzed to investigate the relationship with the risk of GC and clinicopathological properties. Logistic regression analysis revealed that there was no significant association between rs5742612 and the risk of GC. In addition, no significant association between genotypes and clinicopathological features was observed (p value>0.05). The frequencies of the CC, CT, and TT genotypes were 97%, 3%, and 0%, respectively, among the cases, and 97.9%, 2.1%, and 0%, respectively, among the controls. CC genotype was more frequent in cases and controls. The frequencies of C and T alleles were 98.9% and 1.1% in controls and 98.5% and 1.5% in patient respectively. Our results provide the first evidence that this variant is rare in Iranian population and it may not be a powerful genetic predisposing biomarker for prediction GC clinicopathological features in an Iranian population.

  10. Breast cancer features in women under the age of 40 years.

    PubMed

    Eugênio, Deise Santiago Girão; Souza, Juliana A; Chojniak, Rubens; Bitencourt, Almir G V; Graziano, Luciana; Souza, Elvira F

    2016-11-01

    To describe the clinical features, imaging findings and pathological aspects of breast cancer diagnosed in women under the age of 40 years. A retrospective, descriptive study was performed through analysis of medical records between November 2008 and August 2012. One hundred and twenty (120) patients were included, of whom 112 underwent mammography, 113 underwent ultrasonography, and 105 underwent magnetic resonance imaging (MRI). The histopathological data was obtained in most cases from post-surgical analysis, which was available for 113 patients. The mean age at diagnosis of primary breast cancer was 34 years. Only 11 patients (9.0%) had a family history of breast or ovarian cancer in first-degree relative. Ninety-two (92) patients sought medical attention after showing breast symptoms, and the presence of a palpable nodule was the main complaint. One hundred and twenty-two (122) primary tumors were diagnosed, of which 112 were invasive (95%). The most common histological type was invasive ductal carcinoma (73.8%). Luminal B was the predominant molecular subtype (42.6%). Ultrasonography was positive in 94.5% of the cases and the most common finding were nodules (94.8%). At mammography, the malignancy was observed in 92.8% and the presence of suggestive calcifications was the dominant feature. The MRI was positive in 98% of patients, and mass lesions were the most common. Most cases of breast cancer diagnosed in patients under the age of 40 years, in our population, had symptoms at diagnosis and tumor with more aggressive biological behavior. Despite the ultrasound has been the most widely used method, we found improved characterization of breast lesions when also used mammography and MRI.

  11. Beyond breast cancer: mammographic features and mortality risk in a population of healthy women.

    PubMed

    Murphy, Rachel A; Schairer, Catherine; Gierach, Gretchen L; Byrne, Celia; Sherman, Mark E; Register, Thomas C; Ding, Jingzhong; Kritchevsky, Stephen B; Harris, Tamara B

    2013-01-01

    Breast fibroglandular (dense) tissue is a risk factor for breast cancer. Beyond breast cancer, little is known regarding the prognostic significance of mammographic features. We evaluated relationships between nondense (fatty) breast area and dense area with all-cause mortality in 4,245 initially healthy women from the Breast Cancer Detection Demonstration Project; 1,361 died during a mean follow-up of 28.2 years. Dense area and total breast area were assessed using planimeter measurements from screening mammograms. Percent density reflects dense area relative to breast area and nondense area was calculated as the difference between total breast area and dense area. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated by Cox proportional hazards regression. In age-adjusted models, greater nondense and total breast area were associated with increased risk of death (HR 1.17, 95% CI 1.10-1.24 and HR 1.13, 95% CI 1.06-1.19, per SD difference) while greater dense area and percent density were associated with lower risk of death (HR 0.91, 95% CI 0.86-0.95 and HR 0.87, 95% CI 0.83-0.92, per SD difference). Associations were not attenuated with adjustment for race, education, mammogram type (x-ray or xerogram), smoking status, diabetes and heart disease. With additional adjustment for body mass index, associations were diminished for all features but remained statistically significant for dense area (HR 0.94, 95% CI 0.89-0.99, per SD difference) and percent density (HR 0.93, 95% CI 0.87-0.98, per SD difference). These data indicate that dense area and percent density may relate to survival in healthy women and suggest the potential utility of mammograms beyond prediction of breast cancer risk.

  12. Evaluating stability of histomorphometric features across scanner and staining variations: predicting biochemical recurrence from prostate cancer whole slide images

    NASA Astrophysics Data System (ADS)

    Leo, Patrick; Lee, George; Madabhushi, Anant

    2016-03-01

    Quantitative histomorphometry (QH) is the process of computerized extraction of features from digitized tissue slide images. Typically these features are used in machine learning classifiers to predict disease presence, behavior and outcome. Successful robust classifiers require features that both discriminate between classes of interest and are stable across data from multiple sites. Feature stability may be compromised by variation in slide staining and scanning procedures. These laboratory specific variables include dye batch, slice thickness and the whole slide scanner used to digitize the slide. The key therefore is to be able to identify features that are not only discriminating between the classes of interest (e.g. cancer and non-cancer or biochemical recurrence and non- recurrence) but also features that will not wildly fluctuate on slides representing the same tissue class but from across multiple different labs and sites. While there has been some recent efforts at understanding feature stability in the context of radiomics applications (i.e. feature analysis of radiographic images), relatively few attempts have been made at studying the trade-off between feature stability and discriminability for histomorphometric and digital pathology applications. In this paper we present two new measures, preparation-induced instability score (PI) and latent instability score (LI), to quantify feature instability across and within datasets. Dividing PI by LI yields a ratio for how often a feature for a specific tissue class (e.g. low grade prostate cancer) is different between datasets from different sites versus what would be expected from random chance alone. Using this ratio we seek to quantify feature vulnerability to variations in slide preparation and digitization. Since our goal is to identify stable QH features we evaluate these features for their stability and thus inclusion in machine learning based classifiers in a use case involving prostate cancer

  13. Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to Chemotherapy.

    PubMed

    Danala, Gopichandh; Thai, Theresa; Gunderson, Camille C; Moxley, Katherine M; Moore, Kathleen; Mannel, Robert S; Liu, Hong; Zheng, Bin; Qiu, Yuchen

    2017-10-01

    The study aimed to investigate the role of applying quantitative image features computed from computed tomography (CT) images for early prediction of tumor response to chemotherapy in the clinical trials for treating ovarian cancer patients. A dataset involving 91 patients was retrospectively assembled. Each patient had two sets of pre- and post-therapy CT images. A computer-aided detection scheme was applied to segment metastatic tumors previously tracked by radiologists on CT images and computed image features. Two initial feature pools were built using image features computed from pre-therapy CT images only and image feature difference computed from both pre- and post-therapy images. A feature selection method was applied to select optimal features, and an equal-weighted fusion method was used to generate a new quantitative imaging marker from each pool to predict 6-month progression-free survival. The prediction accuracy between quantitative imaging markers and the Response Evaluation Criteria in Solid Tumors (RECIST) criteria was also compared. The highest areas under the receiver operating characteristic curve are 0.684 ± 0.056 and 0.771 ± 0.050 when using a single image feature computed from pre-therapy CT images and feature difference computed from pre- and post-therapy CT images, respectively. Using two corresponding fusion-based image markers, the areas under the receiver operating characteristic curve significantly increased to 0.810 ± 0.045 and 0.829 ± 0.043 (P < 0.05), respectively. Overall prediction accuracy levels are 71.4%, 80.2%, and 74.7% when using two imaging markers and RECIST, respectively. This study demonstrated the feasibility of predicting patients' response to chemotherapy using quantitative imaging markers computed from pre-therapy CT images. However, using image feature difference computed between pre- and post-therapy CT images yielded higher prediction accuracy. Copyright © 2017 The Association of University

  14. Colon adenoma features and their impact on risk of future advanced adenomas and colorectal cancer

    PubMed Central

    Calderwood, Audrey H; Lasser, Karen E; Roy, Hemant K

    2016-01-01

    AIM To review the evidence on the association between specific colon adenoma features and the risk of future colonic neoplasia [adenomas and colorectal cancer (CRC)]. METHODS We performed a literature search using the National Library of Medicine through PubMed from 1/1/2003 to 5/30/2015. Specific Medical Subject Headings terms (colon, colon polyps, adenomatous polyps, epidemiology, natural history, growth, cancer screening, colonoscopy, CRC) were used in conjunction with subject headings/key words (surveillance, adenoma surveillance, polypectomy surveillance, and serrated adenoma). We defined non-advanced adenomas as 1-2 adenomas each < 10 mm in size and advanced adenomas as any adenoma ≥ 10 mm size or with > 25% villous histology or high-grade dysplasia. A combined endpoint of advanced neoplasia included advanced adenomas and invasive CRC. RESULTS Our search strategy identified 592 candidate articles of which 8 met inclusion criteria and were relevant for assessment of histology (low grade vs high grade dysplasia, villous features) and adenoma size. Six of these studies met the accepted quality indicator threshold for overall adenoma detection rate > 25% among study patients. We found 254 articles of which 7 met inclusion criteria for the evaluation of multiple adenomas. Lastly, our search revealed 222 candidate articles of which 6 met inclusion criteria for evaluation of serrated polyps. Our review found that villous features, high grade dysplasia, larger adenoma size, and having ≥ 3 adenomas at baseline are associated with an increased risk of future colonic neoplasia in some but not all studies. Serrated polyps in the proximal colon are associated with an increased risk of future colonic neoplasia, comparable to having a baseline advanced adenoma. CONCLUSION Data on adenoma features and risk of future adenomas and CRC are compelling yet modest in absolute effect size. Future research should refine this risk stratification. PMID:28035253

  15. A comparative analysis of swarm intelligence techniques for feature selection in cancer classification.

    PubMed

    Gunavathi, Chellamuthu; Premalatha, Kandasamy

    2014-01-01

    Feature selection in cancer classification is a central area of research in the field of bioinformatics and used to select the informative genes from thousands of genes of the microarray. The genes are ranked based on T-statistics, signal-to-noise ratio (SNR), and F-test values. The swarm intelligence (SI) technique finds the informative genes from the top-m ranked genes. These selected genes are used for classification. In this paper the shuffled frog leaping with Lévy flight (SFLLF) is proposed for feature selection. In SFLLF, the Lévy flight is included to avoid premature convergence of shuffled frog leaping (SFL) algorithm. The SI techniques such as particle swarm optimization (PSO), cuckoo search (CS), SFL, and SFLLF are used for feature selection which identifies informative genes for classification. The k-nearest neighbour (k-NN) technique is used to classify the samples. The proposed work is applied on 10 different benchmark datasets and examined with SI techniques. The experimental results show that the results obtained from k-NN classifier through SFLLF feature selection method outperform PSO, CS, and SFL.

  16. Breast cancer subtype intertumor heterogeneity: MRI-based features predict results of a genomic assay.

    PubMed

    Sutton, Elizabeth J; Oh, Jung Hun; Dashevsky, Brittany Z; Veeraraghavan, Harini; Apte, Aditya P; Thakur, Sunitha B; Deasy, Joseph O; Morris, Elizabeth A

    2015-11-01

    To investigate the association between a validated, gene-expression-based, aggressiveness assay, Oncotype Dx RS, and morphological and texture-based image features extracted from magnetic resonance imaging (MRI). This retrospective study received Internal Review Board approval and need for informed consent was waived. Between 2006-2012, we identified breast cancer patients with: 1) ER+, PR+, and HER2- invasive ductal carcinoma (IDC); 2) preoperative breast MRI; and 3) Oncotype Dx RS test results. Extracted features included morphological, histogram, and gray-scale correlation matrix (GLCM)-based texture features computed from tumors contoured on pre- and three postcontrast MR images. Linear regression analysis was performed to investigate the association between Oncotype Dx RS and different clinical, pathologic, and imaging features. P < 0.05 was considered statistically significant. Ninety-five patients with IDC were included with a median Oncotype Dx RS of 16 (range: 0-45). Using stepwise multiple linear regression modeling, two MR-derived image features, kurtosis in the first and third postcontrast images and histologic nuclear grade, were found to be significantly correlated with the Oncotype Dx RS with P = 0.0056, 0.0005, and 0.0105, respectively. The overall model resulted in statistically significant correlation with Oncotype Dx RS with an R-squared value of 0.23 (adjusted R-squared = 0.20; P = 0.0002) and a Spearman's rank correlation coefficient of 0.49 (P < 0.0001). A model for IDC using imaging and pathology information correlates with Oncotype Dx RS scores, suggesting that image-based features could also predict the likelihood of recurrence and magnitude of chemotherapy benefit. © 2015 Wiley Periodicals, Inc.

  17. Short-term and long-term survival of interval breast cancers taking into account prognostic features.

    PubMed

    Delacour-Billon, Solenne; Mathieu-Wacquant, Anne Laure; Campone, Mario; Auffret, Nathalie; Amossé, Sophie; Allioux, Corinne; Cowppli-Bony, Anne; Molinié, Florence

    2017-01-01

    The aim of this population-based study was to estimate short-term and long-term survival of interval breast cancers and to compare them to clinically detected cancers, taking into account prognostic features. This study included all interval cancers and clinically detected cancers diagnosed in the Loire-Atlantique population-based cancer registry from 2000 to 2010 in women aged 50-76 years. We used the Pohar-Perme method to estimate 5- and 10 year net survival rates and a flexible parametric model to compare interval cancer and clinically detected cancer prognosis with and without adjustment for the main prognostic factors (age, stage, histological grade, and phenotype). This study included 813 interval cancers and 1,354 clinically detected cancers. Interval cancers were diagnosed at a significantly less advanced stage than clinically detected cancers, but more often with a triple-negative phenotype. Interval cancer age-standardised net survival was 88.0% at 5 years (95% CI 84.9-91.2) and 81.7% at 10 years (95% CI 76.9-86.9), whereas clinically detected cancer age-standardised net survival was 77.8% (95% CI 75.1-80.6) and 64.6% (95% CI 60.7-68.7), respectively. After adjustment for covariates, survival no longer differed between interval cancers and clinically detected cancers at 5 and 10 years. Although the interval cancer net survival rate was higher, interval cancers had a similar short-term and long-term prognosis than clinically detected cancers after taking into account the main prognostic factors.

  18. [Clinical features of osteonecrosis of jaws after bisphosphonates therapy for bone metastasis of breast cancer].

    PubMed

    Guo, Yu-xing; Wang, Dian-can; Wang, Yang; Peng, Xin; Mao, Chi; Guo, Chuan-bin

    2016-02-18

    To understand the clinical features of osteonecrosis of the jaw after bisphosphonates use for therapy of breast cancer patients with bone metastasis. The cases diagnosed as bisphosphonates-related osteonecrosis of the jaws (BRONJ) were retrospectively analyzed from January 2011 to August 2015 in the Peking University School and Hospital of Stomatology, and those breast cancer patients with bone metastasis were selected. The clinical symptoms, imaging characteristics and treatment results were summarized. A total of 14 cases of breast cancer patients with bone metastasis were selected, with an average age of 60.21 years. The average time of suffering from breast cancer was 9.77 years, and the average time of bone metastasis and bisphosphonates drugs use was 5.67 and 3.29 years individually. There was no patient with systemic application history of hormone therapy, and no history of diabetes. There were 9 patients with tooth extractions history, and the mean time of bone necrosis symptoms was 8.58 months. There were 10 cases with bone necrosis occurring on mandible, 3 cases on maxilla, and one case with both upper and lower jaws involved. Among the 10 patients with surgical treatment, there were 3 cases cured, and 6 cases improved. However, the clinical symptoms of 2 cases with conservative treatment were significantly aggravated. The medication time between the bisphosphonates use beginning and the occurrence of BRONJ is relatively long. The history of diabetes and long-time hormone use did not exist in this group. Tooth extraction itself does not determine the severity of BRONJ. Mandible is the most common site involved by BRONJ. Surgical treatment can alleviate the clinical symptoms of BRONJ with breast cancer to some extent.

  19. Clinical features of colorectal cancer patients in advanced age: a population-based approach.

    PubMed

    Maffei, Stefania; Colantoni, Alessandra; Kaleci, Shaniko; Benatti, Piero; Tesini, Ester; de Leon, Maurizio Ponz

    2016-03-01

    In the immediate future, the number of geriatric patients will continue to rise; consequently we should expect an increase of colorectal cancer, a disease of the elderly population. Through the data of a Cancer Registry, we examined (a) the effect of ageing on the main features of colorectal cancer; (b) changes in management, especially for individuals older than 80 years; and (c) changes in prognosis and survival in subgroups of patients with different age. The Registry provided information on colorectal cancer up to 2010 (27 years). A total of 5293 patients were registered; these were divided into three groups: A (0-64 years), B (65-79) and C (80 or more). Three periods of observation were chosen: 1 (1984-1992), 2 (1993-2001) and 3 (2001-2010). Group A included 1571 patients (29 %), Group B 2539 (48 %) and Group C 1183 (22.3 %). The fraction of old individuals increased during the 27 years of the investigation. In these patients, tumours were predominantly localized to the right colon (42.6 %). The rate of surgery and ratio between curative and palliative approaches were similar among the three groups (p < 0.38). There was disparity (p < 0.002) in the administration of chemotherapy (5.8 % of the elderly vs 34.4 % in remaining patients). Survival increased over time in all three groups. In the elderly, average 5-year survival was 31 % in period 1 and 55 % in period 3. These data show that in Western countries, the standard of care for colorectal cancer diagnosed in geriatric patients has improved over the last 30 years.

  20. Bloodstream infections in adult patients with cancer: clinical features and pathogenic significance of Staphylococcus aureus bacteremia.

    PubMed

    Kang, Cheol-In; Song, Jae-Hoon; Chung, Doo Ryeon; Peck, Kyong Ran; Yeom, Joon-Sup; Son, Jun Seong; Wi, Yu Mi

    2012-10-01

    The aim of this study was to more precisely delineate the characteristics and outcomes of bloodstream infections in adult cancer patients. Using a database for nationwide surveillance of bacteremia, we analyzed data related to bacteremia in adult patients with cancer in order to evaluate clinical features and outcomes and to define predictive factors for mortality. Of 1,246 patients, 896 (71.9%) had solid tumors, 328 (26.3%) had hematologic malignancies, and 22 (1.8%) had both. The following conditions were more common in the neutropenic group than in the non-neutropenic group: nosocomial acquisition, hematologic malignancy, corticosteroid use, immunosuppressant use, primary bacteremia, and pneumonia (all P < 0.05). The infections were caused by Gram-negative bacilli in 55.6% and by Gram-positive cocci in 32.7%. Gram-negative pathogens were more frequently isolated from neutropenic patients than from non-neutropenic patients (61.9% vs. 53.5%, P = 0.010), with a significant predominance of Escherichia coli and Klebsiella pneumoniae. Among 1,001 patients whose outcomes could be evaluated, the overall 30-day mortality rate was 24.1%, and multivariate analysis showed that Staphylococcus aureus bacteremia was a significant factor associated with mortality (odds ratio (OR), 1.80; 95% confidence interval (CI), 1.03-3.15), along with nosocomial acquisition, pneumonia, severe sepsis or septic shock, and higher Pitt bacteremia score (all P values <0.05). This study represents the comprehensive assessment of bloodstream infections in neutropenic versus non-neutropenic cancer patients. Given the pathogenic significance of S. aureus bacteremia in adult patients with cancer, additional strategies for the management of S. aureus bacteremia in cancer patients are needed to improve outcomes.

  1. Isolated pachymeningeal metastasis from breast cancer: Clinical features and prognostic factors.

    PubMed

    Heo, Mi Hwa; Cho, Yoo Jin; Kim, Hee Kyung; Kim, Ji-Yeon; Park, Yeon Hee

    2017-10-01

    To evaluate the clinical features and prognoses of patients with isolated pachymeningeal metastasis (IPM) from breast cancer. We reviewed the medical records of all patients with metastatic breast cancer (MBC) treated from January 2009 to August 2016. Eligibility criteria included diagnosis of pachymeningeal metastasis based on brain magnetic resonance imaging and histologic diagnosis of primary breast cancer. We excluded patients with concomitant parenchymal or leptomeningeal metastases. Thirty-eight patients who matched our inclusion criteria were included in this study. The incidence of IPM in breast cancer was 1.5% of all patients with MBC. The molecular subtype distribution was: triple negative, 29.0%; ER+/HER2-, 44.7%; ER+/HER2+, 18.4%; and ER-/HER2+, 7.9%. All isolated pachymeningeal involvement resulted from the direct extension of skull metastases. The median time to IPM from systemic metastasis was 28.6 (95% CI: 23.6-33.6) months. The median time to IPM from skull metastasis was 5.2 (95% CI: 0-10.9) months. The median overall survival (OS) from IPM was 4.0 (95% CI: 2.5-5.5) months. In patients who received chemotherapy the OS was longer than for those who received radiotherapy or supportive care only [median OS 8.9 (95% CI: 0.0-18.4), 2.8 (95% CI: 0.5-5.0), and 0.8 (95% CI: 0.6-1.1) months, respectively (p = 0.006)]. Multivariate analysis revealed that good performance status and chemotherapy were associated with better survival outcomes. Stratified evaluation is required for patients with skull metastasis from breast cancer, as pachymeningeal involvement can develop and be associated with unsuspected outcomes. Copyright © 2017. Published by Elsevier Ltd.

  2. Phenotypic feature quantification of patient derived 3D cancer spheroids in fluorescence microscopy image

    NASA Astrophysics Data System (ADS)

    Kang, Mi-Sun; Rhee, Seon-Min; Seo, Ji-Hyun; Kim, Myoung-Hee

    2017-03-01

    Patients' responses to a drug differ at the cellular level. Here, we present an image-based cell phenotypic feature quantification method for predicting the responses of patient-derived glioblastoma cells to a particular drug. We used high-content imaging to understand the features of patient-derived cancer cells. A 3D spheroid culture formation resembles the in vivo environment more closely than 2D adherent cultures do, and it allows for the observation of cellular aggregate characteristics. However, cell analysis at the individual level is more challenging. In this paper, we demonstrate image-based phenotypic screening of the nuclei of patient-derived cancer cells. We first stitched the images of each well of the 384-well plate with the same state. We then used intensity information to detect the colonies. The nuclear intensity and morphological characteristics were used for the segmentation of individual nuclei. Next, we calculated the position of each nucleus that is appeal of the spatial pattern of cells in the well environment. Finally, we compared the results obtained using 3D spheroid culture cells with those obtained using 2D adherent culture cells from the same patient being treated with the same drugs. This technique could be applied for image-based phenotypic screening of cells to determine the patient's response to the drug.

  3. Tumor apelin, not serum apelin, is associated with the clinical features and prognosis of gastric cancer.

    PubMed

    Feng, Meiyan; Yao, Guodong; Yu, Hongwei; Qing, Yu; Wang, Kuan

    2016-10-12

    To study the association between Apelin expression and the clinical features and postoperative prognosis in patients with gastric cancer (Int J Cancer 136:2388-2401, 2015). Tumor samples and matched adjacent normal tissues were collected from 270 patients with GC receiving surgical resection. The tumor and serum Apelin levels were determined by immunohistochemistry and ELISA methods, respectively. GC cell lines were cultured for migration and invasive assays. Our data showed that tumor Apelin expression status, instead of serum Apelin level, was closely associated with more advance clinical features including tumor differentiation, lymph node and distant metastases. Moreover, patients with high tumor Apelin level had a significantly shorter overall survival period compared to those with low Apelin expression and those with or negative Apelin staining. Our in vitro study revealed that the Apelin regulated the migration and invasion abilities of GC cell lines, accompanied by up-regulations of a variety of cytokines associated with tumor invasiveness. Our data suggest that tumor Apelin can be used as a marker to evaluate clinical characteristics and predict prognosis in GC patients.

  4. Relationship between reticuloendothelial systems' FDG uptake level and clinicopathological features in patient with invasive ductal breast cancer.

    PubMed

    Şahin, Ertan; Elboğa, Umut

    2017-06-09

    The reticuloendothelial system (RES) is a part of the immune system and plays a major role in the protection of against diseases. We thought that FDG-PET/CT may show the degree of systemic immune response induced with malignancy in the organs with the high RES activity. Our objective is to investigate FDG uptake levels of high RES activity organs (liver, spleen, bone marrow) in invasive ductal breast cancer and to evaluate the association with the clinicopathological features. In the present study, 193 patients with invasive ductal breast cancer who performed FDG-PET/CT were categorized according to the clinicopathological features including age, tumor size, axillary nodal status, histological grade, the presence of lymphavascular invasion, receptor status, Ki-67 proliferation index and biological subgroup. Also, a control group of 100 subjects were identified for comparison with breast cancer patients. We analyzed the relation of FDG uptake levels in high RES activity organs and clinicopathological features in patients. There was a statistically significant difference of SUVmax of the liver, spleen, and bone marrow between cancer and control groups (P < 0.0001). We found that high SUVmax in liver, spleen and bone marrow were significantly correlated with worse prognostic clinicopathological features in patient with invasive ductal breast cancer. FDG uptake level in high RES activity organs is associated with the presence of tumor, and also directly relating clinicopathological features for patients with invasive ductal breast cancer.

  5. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine.

    PubMed

    Xi, Maolong; Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

    2016-01-01

    This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV). Finally, the BQPSO coupling SVM (BQPSO/SVM), binary PSO coupling SVM (BPSO/SVM), and genetic algorithm coupling SVM (GA/SVM) are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms.

  6. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

    PubMed Central

    Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

    2016-01-01

    This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV). Finally, the BQPSO coupling SVM (BQPSO/SVM), binary PSO coupling SVM (BPSO/SVM), and genetic algorithm coupling SVM (GA/SVM) are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms. PMID:27642363

  7. Clinical features and evolution of oral cancer: A study of 274 cases in Buenos Aires, Argentina.

    PubMed

    Brandizzi, Daniel; Gandolfo, Mariana; Velazco, María Lucia; Cabrini, Rómulo Luis; Lanfranchi, Hector Eduardo

    2008-09-01

    Oral Squamous Cell Carcinoma has a low survival rate, 34 to 66% five-year survival after initial diagnosis, due to late diagnosis. The aim of the present study was to examine the clinical features and evolution of oral cancer in the University of Buenos Aires. 274 patients with primary oral carcinoma, over the 1992-2000 period were included in the study. The survival rate of this population was 80% at 12 months, 60% at 24 months, 46% at 36 months, 40% at 48 months, and 39% at 60 months (5 years). The tumor localizations with worse prognosis were floor of mouth and tongue, with survival rates of 19% and 27% respectively. Sixty-five percent of the oral carcinomas evaluated were diagnosed at advanced stages (III and IV). The patients under study exhibited the lowest survival rate described for oral cancer (34% five-year survival after initial diagnosis). The population included in this study can be considered representative of the Argentine population. This bad prognosis would be mainly due to the large number of oral cancer cases that were diagnosed at advanced stages.

  8. Severe reaction to radiotherapy for breast cancer as the presenting feature of ataxia telangiectasia

    PubMed Central

    Byrd, P J; Srinivasan, V; Last, J I; Smith, A; Biggs, P; Carney, E F; Exley, A; Abson, C; Stewart, G S; Izatt, L; Taylor, A M

    2012-01-01

    Background: Severe early and late radiation reaction to radiotherapy is extremely rare in breast cancer patients. Such a reaction prompted an investigation into a 44-year-old mother (patient A-T213). Methods: A neurological examination was performed and blood lymphocytes and skin fibroblasts were assessed for radiosensitivity chromosomally and by colony-forming assay. The ATM gene was sequenced and ATM mutations modelled by site-directed mutagenesis. The ATM kinase activity was also assessed. Results: Patient A-T213 was normally ambulant with no ataxia and minimal other neurological features. T lymphocytes and skin fibroblasts were unusually radiosensitive, although less sensitive than in classical ataxia telangiectasia (A-T). A lymphoblastoid cell line and skin fibroblasts expressed ATM protein with some retained kinase activity. One missense ATM mutation c.8672G>A (p.Gly2891Asp) and a c.1A>G substitution were identified. In the modelling system, the p.Gly2891Asp mutant protein was expressed and shown to have residual ATM kinase activity. Conclusion: Patient A-T213 has a milder form of A-T with biallelic ATM mutations, which may have contributed to breast cancer development, and certainly caused the severe radiation reaction. Ataxia telangiectasia should be investigated as a potential cause of untoward severe early and late radiation reactions in breast cancer patients. PMID:22146522

  9. Multiple Adaptive Neuro-Fuzzy Inference System with Automatic Features Extraction Algorithm for Cervical Cancer Recognition

    PubMed Central

    Subhi Al-batah, Mohammad; Mat Isa, Nor Ashidi; Klaib, Mohammad Fadel; Al-Betar, Mohammed Azmi

    2014-01-01

    To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women worldwide. The current methods (i.e., Pap smear and liquid-based cytology (LBC)) to screen for cervical cancer are time-consuming and dependent on the skill of the cytopathologist and thus are rather subjective. Therefore, this paper presents an intelligent computer vision system to assist pathologists in overcoming these problems and, consequently, produce more accurate results. The developed system consists of two stages. In the first stage, the automatic features extraction (AFE) algorithm is performed. In the second stage, a neuro-fuzzy model called multiple adaptive neuro-fuzzy inference system (MANFIS) is proposed for recognition process. The MANFIS contains a set of ANFIS models which are arranged in parallel combination to produce a model with multi-input-multioutput structure. The system is capable of classifying cervical cell image into three groups, namely, normal, low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL). The experimental results prove the capability of the AFE algorithm to be as effective as the manual extraction by human experts, while the proposed MANFIS produces a good classification performance with 94.2% accuracy. PMID:24707316

  10. Severe reaction to radiotherapy for breast cancer as the presenting feature of ataxia telangiectasia.

    PubMed

    Byrd, P J; Srinivasan, V; Last, J I; Smith, A; Biggs, P; Carney, E F; Exley, A; Abson, C; Stewart, G S; Izatt, L; Taylor, A M

    2012-01-17

    Severe early and late radiation reaction to radiotherapy is extremely rare in breast cancer patients. Such a reaction prompted an investigation into a 44-year-old mother (patient A-T213). A neurological examination was performed and blood lymphocytes and skin fibroblasts were assessed for radiosensitivity chromosomally and by colony-forming assay. The ATM gene was sequenced and ATM mutations modelled by site-directed mutagenesis. The ATM kinase activity was also assessed. Patient A-T213 was normally ambulant with no ataxia and minimal other neurological features. T lymphocytes and skin fibroblasts were unusually radiosensitive, although less sensitive than in classical ataxia telangiectasia (A-T). A lymphoblastoid cell line and skin fibroblasts expressed ATM protein with some retained kinase activity. One missense ATM mutation c.8672G>A (p.Gly2891Asp) and a c.1A>G substitution were identified. In the modelling system, the p.Gly2891Asp mutant protein was expressed and shown to have residual ATM kinase activity. Patient A-T213 has a milder form of A-T with biallelic ATM mutations, which may have contributed to breast cancer development, and certainly caused the severe radiation reaction. Ataxia telangiectasia should be investigated as a potential cause of untoward severe early and late radiation reactions in breast cancer patients.

  11. STAT3 Expression, Molecular Features, Inflammation Patterns and Prognosis in a Database of 724 Colorectal Cancers

    PubMed Central

    Morikawa, Teppei; Baba, Yoshifumi; Yamauchi, Mai; Kuchiba, Aya; Nosho, Katsuhiko; Shima, Kaori; Tanaka, Noriko; Huttenhower, Curtis; Frank, David A.; Fuchs, Charles S.; Ogino, Shuji

    2010-01-01

    Purpose STAT3 (signal transducer and activator of transcription 3) is a transcription factor that is constitutively activated in some cancers. STAT3 appears to play crucial roles in cell proliferation and survival, angiogenesis, tumor-promoting inflammation and suppression of anti-tumor host immune response in the tumor microenvironment. Although the STAT3 signaling pathway is a potential drug target, clinical, pathologic, molecular or prognostic features of STAT3-activated colorectal cancer remain uncertain. Experimental Design Utilizing a database of 724 colon and rectal cancer cases, we evaluated phosphorylated STAT3 (p-STAT3) expression by immunohistochemistry. Cox proportional hazards model was used to compute mortality hazard ratio (HR), adjusting for clinical, pathologic and molecular features, including microsatellite instability (MSI), the CpG island methylator phenotype (CIMP), LINE-1 methylation, 18q loss of heterozygosity, TP53 (p53), CTNNB1 (β-catenin), JC virus T-antigen, and KRAS, BRAF, and PIK3CA mutations. Results Among the 724 tumors, 131 (18%) showed high-level p-STAT3 expression (p-STAT3-high), 244 (34%) showed low-level expression (p-STAT3-low), and the remaining 349 (48%) were negative for p-STAT3. p-STAT3 overexpression was associated with significantly higher colorectal cancer-specific mortality [log-rank p=0.0020; univariate HR (p-STAT3-high vs. p-STAT3-negative) 1.85, 95% confidence interval (CI) 1.30–2.63, Ptrend =0.0005; multivariate HR, 1.61, 95% CI 1.11–2.34, Ptrend =0.015). p-STAT3 expression was positively associated with peritumoral lymphocytic reaction (multivariate odds ratio 3.23; 95% CI, 1.89–5.53; p<0.0001). p-STAT3 expression was not associated with MSI, CIMP, or LINE-1 hypomethylation. Conclusions STAT3 activation in colorectal cancer is associated with adverse clinical outcome, supporting its potential roles as a prognostic biomarker and a chemoprevention and/or therapeutic target. PMID:21310826

  12. Comparison of prognosis and clinical features between synchronous bilateral and unilateral breast cancers.

    PubMed

    Karakas, Yusuf; Kertmen, Neyran; Lacin, Sahin; Aslan, Alma; Demir, Metin; Ates, Ozturk; Aksoy, Sercan; Altundag, Kadri

    2017-01-01

    The clinical significance of synchronous bilateral breast cancer (SBBC) is unclear and its influence on prognosis is controversial. Our study objective was to determine the epidemiological features, tumor characteristics, and prognosis of SBBC in comparison with those of unilateral breast cancer (UBC). A total of 3675 breast cancer patients diagnosed and treated between 2000 and 2014 were evaluated. Of these patients, 132 (3.6%) had bilateral breast cancer, including 55 patients (1.5%) with SBBC and 77 (2.1%) with metachronous bilateral breast cancer (MBBC). The patient demographic characteristics, including survival data and clinicopathological tumor characteristics, were obtained from medical charts and compared between the patients with SBBC and those with UBC. The median age in the SBBC group was 51 years (range 32-77). The mastectomy rate was higher in the SBBC group (72.7%) than in the UBC group (66.6%) (p=0.08). In both the SBBC and UBC groups, the baseline clinicopathological features and the history of treatment with radiotherapy and chemotherapy were similar. Infiltrating ductal carcinoma was the most common histology in both groups. Lobular histology was more frequent in the SBBC group (36.3%) than in the UBC group (17.1%; p<0.001). Stage IV disease at initial presentation was more frequent in the SBBC group than in the UBC group (34.5 vs 8.7%, p<0.001). The 5-year disease-free survival (DFS) rates were 90% and 82% in the SBBC and UBC groups, respectively (p=0.99). The 5-year overall survival (OS) rates were 83% and 88%, respectively (p=0.357). The multivariate Cox regression analysis, including stage, hormone receptor status, grade, and SBBC, revealed that the presence of SBBC was not associated with OS (hazard ratio 0.929; 95% confidence interval, 0.455-0.1894, p=0.839). Despite the differences in histology, initial stage, and other characteristics, the prognoses of UBC and SBBC were similar.

  13. Accelerated whole breast irradiation in early breast cancer patients with adverse prognostic features

    PubMed Central

    Lee, Sea-Won; Shin, Kyung Hwan; Chie, Eui Kyu; Kim, Jin Ho; Im, Seock-Ah; Han, Wonshik; Noh, Dong-Young; Lim, Hyeon Woo; Kim, Tae Hyun; Lee, Keun Seok; Lee, Eun Sook; Sung, Soo Yoon; Kim, Kyubo

    2016-01-01

    Purpose Accelerated whole breast irradiation (AWBI) and conventional whole breast irradiation (CWBI) were compared to determine whether AWBI is as effective as CWBI in patients with early breast cancer and adverse prognostic features. Patients and methods We included 330 patients who underwent breast-conserving surgery (BCS) and post-operative radiation therapy (RT) using AWBI for pT1-2 and pN0-1a breast cancer from 2007 to 2010. These patients were matched with 330 patients who received CWBI according to stage, age (±3 years), and the year of BCS. AWBI of 39 Gy and CWBI of 50.4 Gy were given in 13 and 28 fractions, respectively. Results Median follow-up time was 81.9 months. There were no statistically significant differences between the AWBI and CWBI groups in terms of age, stage, tumor grade, or molecular subtype. More patients with Ki-67 index ≥ 14% were present in the AWBI group (AWBI 47.0% vs. CWBI 10.3%; P<0.01). The 5-year ipsilateral breast tumor relapse (IBTR) rates for the AWBI and CWBI groups were 0.8% and 1.8%, respectively (P=0.54). High tumor grade was a statistically significant risk factor for IBTR (5-year IBTR rate: 2.9%; P=0.01). Ki-67 ≥ 14% was marginally related to IBTR (5-year IBTR rate: 2.2%; P=0.07). There were no statistically significant differences in the hazard ratios between the AWBI and CWBI groups according to any of the risk factors. There were no acute grade 3 toxicities in the AWBI group. There were no late grade 3 toxicities in either group. Conclusions AWBI is comparable to CWBI in early breast cancer with adverse prognostic features. PMID:27588485

  14. When fear of cancer recurrence becomes a clinical issue: a qualitative analysis of features associated with clinical fear of cancer recurrence.

    PubMed

    Mutsaers, Brittany; Jones, Georden; Rutkowski, Nicole; Tomei, Christina; Séguin Leclair, Caroline; Petricone-Westwood, Danielle; Simard, Sébastien; Lebel, Sophie

    2016-10-01

    Fear of cancer recurrence (FCR) is a common experience for cancer survivors. However, it remains unclear what characteristics differentiate non-clinical from clinical levels of FCR. The goal of this study was to investigate the potential hallmarks of clinical FCR. A convenience sample of 40 participants (n = 19 female) was drawn from another study (Lebel et al. in Qual Life Res 25:311-321. doi: 10.1007/s11136-015-1088-2 , 2016). The semi-structured interview for fear of cancer recurrence (Simard and Savard in J Cancer Surviv 9:481-491. doi: 10.1007/s11764-015-0424-4 , 2015) was used to identify participants with non-clinical and clinical FCR and qualitative analysis of these interviews was performed. Individuals with clinical FCR reported the following features: death-related thoughts, feeling alone, belief that the cancer would return, experiencing intolerance of uncertainty, having cancer-related thoughts and imagery that were difficult to control, daily and recurrent, lasted 30 minutes or more, increased over time, caused distress and impacted their daily life. Triggers of FCR and coping strategies did not appear to be features of clinical FCR as they were reported by participants with a range of FCR scores. While features of clinical FCR found in this analysis such as intrusive thoughts, distress and impact on functioning confirmed previous FCR research, other features spontaneously emerged from the interviews including "death-related thoughts," "feeling alone," and "belief that the cancer will return." The participants' descriptions of cancer-specific fear and worry suggest that FCR is a distinct phenomenon related to cancer survivorship, despite similarities with psychological disorders (e.g., Anxiety Disorders). Future research investigating the construct of FCR, and the distinguishing features of clinical FCR across a range of cancer types and gender is required.

  15. Patient feature based dosimetric Pareto front prediction in esophageal cancer radiotherapy

    SciTech Connect

    Wang, Jiazhou; Zhao, Kuaike; Peng, Jiayuan; Xie, Jiang; Chen, Junchao; Zhang, Zhen; Hu, Weigang; Jin, Xiance; Studenski, Matthew

    2015-02-15

    Purpose: To investigate the feasibility of the dosimetric Pareto front (PF) prediction based on patient’s anatomic and dosimetric parameters for esophageal cancer patients. Methods: Eighty esophagus patients in the authors’ institution were enrolled in this study. A total of 2928 intensity-modulated radiotherapy plans were obtained and used to generate PF for each patient. On average, each patient had 36.6 plans. The anatomic and dosimetric features were extracted from these plans. The mean lung dose (MLD), mean heart dose (MHD), spinal cord max dose, and PTV homogeneity index were recorded for each plan. Principal component analysis was used to extract overlap volume histogram (OVH) features between PTV and other organs at risk. The full dataset was separated into two parts; a training dataset and a validation dataset. The prediction outcomes were the MHD and MLD. The spearman’s rank correlation coefficient was used to evaluate the correlation between the anatomical features and dosimetric features. The stepwise multiple regression method was used to fit the PF. The cross validation method was used to evaluate the model. Results: With 1000 repetitions, the mean prediction error of the MHD was 469 cGy. The most correlated factor was the first principal components of the OVH between heart and PTV and the overlap between heart and PTV in Z-axis. The mean prediction error of the MLD was 284 cGy. The most correlated factors were the first principal components of the OVH between heart and PTV and the overlap between lung and PTV in Z-axis. Conclusions: It is feasible to use patients’ anatomic and dosimetric features to generate a predicted Pareto front. Additional samples and further studies are required improve the prediction model.

  16. Focal Lymphocytic Thyroiditis Nodules Share the Features of Papillary Thyroid Cancer on Ultrasound

    PubMed Central

    Hwang, Sena; Shin, Dong Yeob; Kim, Eun Kyung; Yang, Woo Ick; Byun, Jung Woo; Lee, Su Jin; Kim, Gyuri; Im, Soo Jung

    2015-01-01

    Purpose It is often difficult to discriminate focal lymphocytic thyroiditis (FLT) or adenomatous hyperplasia (AH) from thyroid cancer if they both have suspicious ultrasound (US) findings. We aimed to make a predictive model of FLT from papillary thyroid cancer (PTC) in suspicious nodules with benign cytologic results. Materials and Methods We evaluated 214 patients who had undergone fine-needle aspiration biopsy (FNAB) and had shown thyroid nodules with suspicious US features. PTC was confirmed by surgical pathology. FLT and AH were confirmed through more than two separate FNABs. Clinical and biochemical findings, as well as US features, were evaluated. Results Of 214 patients, 100 patients were diagnosed with PTC, 55 patients with FLT, and 59 patients with AH. The proportion of elevated thyrotropin (TSH) levels (p=0.014) and thyroglobulin antibody (Tg-Ab) or thyroid peroxidase antibody (TPO-Ab) positivity (p<0.001) in the FLT group was significantly higher than that in the PTC group. Regarding US features, absence of calcification (p=0.006) and "diffuse thyroid disease" (DTD) pattern on US (p<0.001) were frequently seen in the FLT group. On multivariate analysis, Tg-Ab positivity, presence of a DTD pattern on US, and absence of calcification in nodules were associated with FLT with the best specificity of 99% and positive predictive value of 96%. In contrast, a taller than wide shape of nodules was the only variable significant for differentiating AH from PTC. Conclusion Suspicious thyroid nodules with cytologic benign results could be followed up with US rather than repeat FNAB, if patients exhibit Tg-Ab positivity, no calcifications in nodules, and a DTD pattern on US. PMID:26256977

  17. Curcumin effectively inhibits oncogenic NF-kB signaling and restrains stemness features in liver cancer

    PubMed Central

    Marquardt, Jens U.; Gomez-Quiroz, Luis; Camacho, Lucrecia O. Arreguin; Pinna, Federico; Lee, Yun-Han; Kitade, Mitsuteru; Domínguez, Mayrel Palestino; Castven, Darko; Breuhahn, Kai; Conner, Elizabeth A.; Galle, Peter R.; Andersen, Jesper B.; Factor, Valentina M.; Thorgeirsson, Snorri S.

    2015-01-01

    Background & Aims The cancer stem cells (CSCs) have important therapeutic implications for multi-resistant cancers including hepatocellular carcinoma (HCC). Among the key pathways frequently activated in liver CSCs is NF-kB signaling. Methods We evaluated the CSCs-depleting potential of NF-kB inhibition in liver cancer achieved by the IKK inhibitor curcumin, RNAi and specific peptide SN50. The effects on CSCs were assessed by analysis of Side Population (SP), sphere formation and tumorigenicity. Molecular changes were determined by RT-qPCR, global gene expression microarray, EMSA, and Western blotting. Results HCC cell lines exposed to curcumin exhibited differential responses to curcumin and were classified as sensitive and resistant. In sensitive lines, curcumin-mediated induction of cell death was directly related to the extent of NF-kB inhibition. The treatment also led to a selective CSC-depletion as evidenced by a reduced SP size, decreased sphere formation, down-regulation of CSC markers and suppressed tumorigenicity. Similarly, NF-kB inhibition by SN50 and siRNA against p65 suppressed tumor cell growth. In contrast, curcumin-resistant cells displayed a paradoxical increase in proliferation and expression of CSC markers. Mechanistically, an important component of the CSC-depleting activity of curcumin could be attributed to a NF-kB-mediated HDAC inhibition. Co-administration of the class I/II HDAC inhibitor trichostatine sensitized resistant cells to curcumin. Further, integration of a predictive signature of curcumin sensitivity with human HCC database indicated that HCCs with poor prognosis and progenitor features are most likely to benefit from NF-kB inhibition. Conclusions These results demonstrate that blocking NF-kB can specifically target CSC populations and suggest a potential for combined inhibition of NF-kB and HDAC signaling for treatment of liver cancer patients with poor prognosis. PMID:25937435

  18. Clinical and pathologic features of young endometrial cancer patients with loss of mismatch repair expression.

    PubMed

    Grzankowski, Kassondra S; Shimizu, David M; Kimata, Chieko; Black, Michael; Terada, Keith Y

    2012-09-01

    This study examines premenopausal and early menopause patients in a unique population with endometrial cancer and loss of mismatch repair (MMR) gene expression. The purpose is to compare clinical and pathologic differences in patients with loss of expression (LOE) to those with normal expression (NE). Endometrial cancer patients under age 60 in-between 1998 and 2008 were identified from a single tumor registry. Clinical and pathologic data were abstracted from records. Staining for expression of MSH6, MSH2, MLH1, and PMS2 were performed on archived tissue blocks. Statistical analysis was performed. 158 patients were analyzed; 58% Asian, 34% Pacific Islander, and 8% Caucasian. 31 demonstrated LOE of at least one MMR gene; 127 retained NE. 50% Caucasian, 21.9% Asian, and 12.5% Pacific Island populations had LOE of one or more MMR genes. LOE was found to have a higher incidence of Grade III (p=0.0013) and stage 3-4 tumors (p=0.0079), mean depth of myometrial invasion (p=0.0019), lymphovascular space invasion (p=0.0020), nodal metastases (p=0.0157), and a lower incidence of Grade I (p=0.0020) and stage 1A tumors (p=0.0085). LOE had a significantly lower mean BMI (p=0.0001). 35% of patients in the NE vs zero in the LOE group had a BMI greater than 40. Younger patients with LOE endometrial cancer appear to represent a clinically significant subgroup of patients without features characteristically found in classic type 1 endometrial cancer generally demonstrating lower BMI and tumors associated with poor prognostic characteristics. It is unclear if the distinctive ethnicity found in Hawaii has a significant impact on outcome. Further investigation is necessary to identify appropriate treatment strategies. Copyright © 2012 Elsevier Inc. All rights reserved.

  19. Identifying Cancer Biomarkers From Microarray Data Using Feature Selection and Semisupervised Learning

    PubMed Central

    Maulik, Ujjwal

    2014-01-01

    Microarrays have now gone from obscurity to being almost ubiquitous in biological research. At the same time, the statistical methodology for microarray analysis has progressed from simple visual assessments of results to novel algorithms for analyzing changes in expression profiles. In a micro-RNA (miRNA) or gene-expression profiling experiment, the expression levels of thousands of genes/miRNAs are simultaneously monitored to study the effects of certain treatments, diseases, and developmental stages on their expressions. Microarray-based gene expression profiling can be used to identify genes, whose expressions are changed in response to pathogens or other organisms by comparing gene expression in infected to that in uninfected cells or tissues. Recent studies have revealed that patterns of altered microarray expression profiles in cancer can serve as molecular biomarkers for tumor diagnosis, prognosis of disease-specific outcomes, and prediction of therapeutic responses. Microarray data sets containing expression profiles of a number of miRNAs or genes are used to identify biomarkers, which have dysregulation in normal and malignant tissues. However, small sample size remains a bottleneck to design successful classification methods. On the other hand, adequate number of microarray data that do not have clinical knowledge can be employed as additional source of information. In this paper, a combination of kernelized fuzzy rough set (KFRS) and semisupervised support vector machine (S3VM) is proposed for predicting cancer biomarkers from one miRNA and three gene expression data sets. Biomarkers are discovered employing three feature selection methods, including KFRS. The effectiveness of the proposed KFRS and S3VM combination on the microarray data sets is demonstrated, and the cancer biomarkers identified from miRNA data are reported. Furthermore, biological significance tests are conducted for miRNA cancer biomarkers. PMID:27170887

  20. Clinical Features of Male Breast Cancer: Experiences from Seven Institutions Over 20 Years.

    PubMed

    Hong, Ji Hyung; Ha, Kyung Sun; Jung, Yun Hwa; Won, Hye Sung; An, Ho Jung; Lee, Guk Jin; Kang, Donghoon; Park, Ji Chan; Park, Sarah; Byun, Jae Ho; Suh, Young Jin; Kim, Jeong Soo; Park, Woo Chan; Jung, Sang Seol; Park, Il Young; Chung, Su-Mi; Woo, In Sook

    2016-10-01

    Breast cancer treatment has progressed significantly over the past 20 years. However, knowledge regarding male breast cancer (MBC) is sparse because of its rarity. This study is an investigation of the clinicopathologic features, treatments, and clinical outcomes of MBC. Clinical records of 59 MBC patients diagnosed during 1995-2014 from seven institutions in Korea were reviewed retrospectively. Over a 20-year period, MBC patients accounted for 0.98% among total breast cancer patients, and increased every 5 years. The median age of MBC patientswas 66 years (range, 24 to 87 years). Forty-three patients (73%) complained of a palpable breast mass initially. The median symptom duration was 5 months (range, 1 to 36 months). Mastectomy was performed in 96% of the patients. The most frequent histology was infiltrating ductal carcinoma (75%). Ninety-one percent of tumors (38/43) were estrogen receptor-positive, and 28% (11/40) showed epidermal growth factor receptor 2 (HER-2) overexpression. After curative surgery, 42% of patients (19/45) received adjuvant chemotherapy; 77% (27/35) received hormone therapy. Five out of ten patients with HER-2 overexpressing tumors did not receive adjuvant anti-HER-2 therapy, while two out of four patients with HER-2 overexpressing tumors received palliative trastuzumab for recurrent and metastatic disease. Letrozole was used for one patient in the palliative setting. The median overall survival durations were 7.2 years (range, 0.6 to 17.0 years) in patients with localized disease and 2.9 years (range, 0.6 to 4.3 years) in those with recurrent or metastatic disease. Anti-HER-2 and hormonal therapy, except tamoxifen, have been underutilized in Korean MBC patients compared to female breast cancer patients. With the development of precision medicine, active treatment with targeted agents should be applied. Further investigation of the unique pathobiology of MBC is clinically warranted.

  1. Identifying Cancer Biomarkers From Microarray Data Using Feature Selection and Semisupervised Learning.

    PubMed

    Chakraborty, Debasis; Maulik, Ujjwal

    2014-01-01

    Microarrays have now gone from obscurity to being almost ubiquitous in biological research. At the same time, the statistical methodology for microarray analysis has progressed from simple visual assessments of results to novel algorithms for analyzing changes in expression profiles. In a micro-RNA (miRNA) or gene-expression profiling experiment, the expression levels of thousands of genes/miRNAs are simultaneously monitored to study the effects of certain treatments, diseases, and developmental stages on their expressions. Microarray-based gene expression profiling can be used to identify genes, whose expressions are changed in response to pathogens or other organisms by comparing gene expression in infected to that in uninfected cells or tissues. Recent studies have revealed that patterns of altered microarray expression profiles in cancer can serve as molecular biomarkers for tumor diagnosis, prognosis of disease-specific outcomes, and prediction of therapeutic responses. Microarray data sets containing expression profiles of a number of miRNAs or genes are used to identify biomarkers, which have dysregulation in normal and malignant tissues. However, small sample size remains a bottleneck to design successful classification methods. On the other hand, adequate number of microarray data that do not have clinical knowledge can be employed as additional source of information. In this paper, a combination of kernelized fuzzy rough set (KFRS) and semisupervised support vector machine (S(3)VM) is proposed for predicting cancer biomarkers from one miRNA and three gene expression data sets. Biomarkers are discovered employing three feature selection methods, including KFRS. The effectiveness of the proposed KFRS and S(3)VM combination on the microarray data sets is demonstrated, and the cancer biomarkers identified from miRNA data are reported. Furthermore, biological significance tests are conducted for miRNA cancer biomarkers.

  2. Imaging features of automated breast volume scanner: Correlation with molecular subtypes of breast cancer.

    PubMed

    Zheng, Feng-Yang; Lu, Qing; Huang, Bei-Jian; Xia, Han-Sheng; Yan, Li-Xia; Wang, Xi; Yuan, Wei; Wang, Wen-Ping

    2017-01-01

    To investigate the correlation between the imaging features obtained by an automated breast volume scanner (ABVS) and molecular subtypes of breast cancer. We examined 303 malignant breast tumours by ABVS for specific imaging features and by immunohistochemical analysis to determine the molecular subtype. ABVS imaging features, including retraction phenomenon, shape, margins, echogenicity, post-acoustic features, echogenic halo, and calcifications were analysed by univariate and multivariate logistic regression analyses to determine the significant predictive factors of the molecular subtypes. By univariate logistic regression analysis, the predictive factors of the Luminal-A subtype (n=128) were retraction phenomenon (odds ratio [OR]=10.188), post-acoustic shadowing (OR=5.112), and echogenic halo (OR=3.263, P<0.001). The predictive factors of the Human-epidermal-growth-factor-receptor-2-amplified subtype (n=39) were calcifications (OR=6.210), absence of retraction phenomenon (OR=4.375), non-mass lesions (OR=4.286, P<0.001), absence of echogenic halo (OR=3.851, P=0.035), and post-acoustic enhancement (OR=3.641, P=0.008). The predictors for the Triple-Negative subtype (n=47) were absence of retraction phenomenon (OR=5.884), post-acoustic enhancement (OR=5.255, P<0.001), absence of echogenic halo (OR=4.138, P=0.002), and absence of calcifications (OR=3.363, P=0.001). Predictors for the Luminal-B subtype (n=89) had a relatively lower association (OR≤2.328). By multivariate logistic regression analysis, retraction phenomenon was the strongest independent predictor for the Luminal-A subtype (OR=9.063, P<0.001) when present and for the Triple-Negative subtype (OR=4.875, P<0.001) when absent. ABVS imaging features, especially retraction phenomenon, have a strong correlation with the molecular subtypes, expanding the scope of ultrasound in identifying breast cancer subtypes with confidence. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  3. Multi-channels statistical and morphological features based mitosis detection in breast cancer histopathology.

    PubMed

    Irshad, Humayun; Roux, Ludovic; Racoceanu, Daniel

    2013-01-01

    Accurate counting of mitosis in breast cancer histopathology plays a critical role in the grading process. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. This work aims at improving the accuracy of mitosis detection by selecting the color channels that better capture the statistical and morphological features having mitosis discrimination from other objects. The proposed framework includes comprehensive analysis of first and second order statistical features together with morphological features in selected color channels and a study on balancing the skewed dataset using SMOTE method for increasing the predictive accuracy of mitosis classification. The proposed framework has been evaluated on MITOS data set during an ICPR 2012 contest and ranked second from 17 finalists. The proposed framework achieved 74% detection rate, 70% precision and 72% F-Measure. In future work, we plan to apply our mitosis detection tool to images produced by different types of slide scanners, including multi-spectral and multi-focal microscopy.

  4. A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets.

    PubMed

    Antropova, Natalia; Huynh, Benjamin Q; Giger, Maryellen L

    2017-07-06

    Deep learning methods for radiomics/computer-aided diagnosis (CADx) are often prohibited by small datasets, long computation time, and the need for extensive image preprocessing. We aim to develop a breast CADx methodology that addresses the aforementioned issues by exploiting the efficiency of pre-trained convolutional neural networks (CNNs) and using pre-existing handcrafted CADx features. We present a methodology that extracts and pools low- to mid-level features using a pretrained CNN and fuses them with handcrafted radiomic features computed using conventional CADx methods. Our methodology is tested on three different clinical imaging modalities (dynamic contrast enhanced-MRI [690 cases], full-field digital mammography [245 cases], and ultrasound [1125 cases]). From ROC analysis, our fusion-based method demonstrates, on all three imaging modalities, statistically significant improvements in terms of AUC as compared to previous breast cancer CADx methods in the task of distinguishing between malignant and benign lesions. (DCE-MRI [AUC = 0.89 (se = 0.01)], FFDM [AUC = 0.86 (se = 0.01)], and ultrasound [AUC = 0.90 (se = 0.01)]). We proposed a novel breast CADx methodology that can be used to more effectively characterize breast lesions in comparison to existing methods. Furthermore, our proposed methodology is computationally efficient and circumvents the need for image preprocessing. © 2017 American Association of Physicists in Medicine.

  5. Profiling of Discrete Gynecological Cancers Reveals Novel Transcriptional Modules and Common Features Shared by Other Cancer Types and Embryonic Stem Cells

    PubMed Central

    Jacob-Hirsch, Jasmine; Amariglio, Ninette; Vlachos, George D.; Loutradis, Dimitrios; Anagnou, Nicholas P.

    2015-01-01

    Studies on individual types of gynecological cancers (GCs), utilizing novel expression technologies, have revealed specific pathogenetic patterns and gene markers for cervical (CC), endometrial (EC) and vulvar cancer (VC). Although the clinical phenotypes of the three types of gynecological cancers are discrete, the fact they originate from a common embryological origin, has led to the hypothesis that they might share common features reflecting regression to early embryogenesis. To address this question, we performed a comprehensive comparative analysis of their profiles. Our data identified both common features (pathways and networks) and novel distinct modules controlling the same deregulated biological processes in all three types. Specifically, four novel transcriptional modules were discovered regulating cell cycle and apoptosis. Integration and comparison of our data with other databases, led to the identification of common features among cancer types, embryonic stem (ES) cells and the newly discovered cell population of squamocolumnar (SC) junction of the cervix, considered to host the early cancer events. Conclusively, these data lead us to propose the presence of common features among gynecological cancers, other types of cancers, ES cells and the pre-malignant SC junction cells, where the novel E2F/NFY and MAX/CEBP modules play an important role for the pathogenesis of gynecological carcinomas. PMID:26559525

  6. Breast cancer with brain metastases: clinicopathologic features, survival, and paired biomarker analysis.

    PubMed

    Shen, Qi; Sahin, Aysegul A; Hess, Kenneth R; Suki, Dima; Aldape, Kenneth D; Sawaya, Raymond; Ibrahim, Nuhad K

    2015-05-01

    The aim of this study was to describe clinicopathologic features of patients with breast cancer brain metastasis (BCBM); to evaluate survival after diagnosis of BCBM; and to compare estrogen receptor (ER), progesterone receptor (PR), and HER2 expression in the paired primary and brain tumors. We identified 140 consecutive patients who underwent craniotomy for BCBM (either for diagnostic purpose or with therapeutic intent) at the University of Texas MD Anderson Cancer Center between 2002 and 2009. Most patients had invasive ductal histology (91%), grade 3 tumors (67%), and positive axillary lymph node (64%). Of the tumors, 56% were ER-negative, 62% were PR-negative, 44% were HER2-positive, and 28% were triple negative (TN). Brain metastasis (BM) was solitary in 51% of patients. Median interval from breast cancer diagnosis to BM was 46 months; median survival after BM was 14.1 months. In the univariate analysis, younger age, solitary brain metastasis, and ER or PR positivity in the breast tumors were associated with longer survival. There was a statistical trend toward increased survival in HER2-positive patients compared with HER2-negative patients (18 vs. 11 months). In the multivariate analysis, predictors for longer survival included younger age, solitary brain lesion, and HER2 positivity in the breast cancer. Biomarkers were evaluated in paired primary and brain tumors in 35 patients for ER status, 34 for PR status, and 36 for HER2 status. Discordant rates were 28% for ER, 20% for PR, and 3% for HER2. Compared with unselected breast cancer patients at the same institution, patients with breast cancer who had brain metastases had a higher proportion of hormone receptor-negative, HER2-positive, and TN tumors. Younger age, solitary brain lesion, and HER2 expression were independent predictors of better survival in patients with BCBM. HER2 status was highly concordant between the paired primary and brain tumors, whereas changes of ER and PR status occurred in a

  7. [Association of serum albumin level with clinicopathologic features and prognosis in colon cancer].

    PubMed

    Jiang, Zhiqiang; Li, Yalan; Han, Guangsen; Zhang, Jian; Li, Zhi; Wang, Daohai; Liu, Yingjun

    2016-01-01

    To evaluate the clinical significance of preoperative serum albumin level and its association with survival in colon cancer patients. Clinicopathological data of 621 consecutive patients with colon cancer admitted in Henan Cancer Hospital between January 2000 and December 2008 were retrospectively analyzed. These patients were divided into hypoalbuminemic and normal groups according to the definition of hypoalbuminemia (serum albumin < 35 g/L). Clinicopathological features were compared between two groups. The association of preoperative serum albumin level and the prognosis was analyzed by Kaplan-Meier and Log-rank test. Multivariate Cox model was used to evaluate the survival. Sixty-seven(10.8%) patients were defined as preoperative hypoalbuminemia and were mostly found in those with right hemicolon cancer. Preoperative serum albumin level was associated with depth of tumor (χ(2)=35.609, P=0.000), lymph node metastasis (χ(2)=8.110, P=0.004), distant metastasis (χ(2)=9.064, P=0.003), advanced TNM T staging (χ(2)=23.070, P=0.000), and not associated with age, gender, tumor gross type, histological type, and degree of tumor differentiation (all P>0.05). 5-year survival rate of hypoalbuminemia group and normal group was 55.2% and 66.1% respectively (P=0.032). Univariate analysis revealed age (P=0.000), tumor gross type (P=0.014), degree of tumor differentiation (P=0.014), depth of tumor (P=0.000), lymph node metastasis (P=0.001), distant metastasis (P=0.000), advanced TNM T staging (P=0.000), operative method (P=0.000) and preoperative serum albumin level (P=0.032) were associated with survival. Cox multivariate analysis revealed the albumin level was the independent prognostic factor of the 5-year overall survival (HR:0.694, 95% CI: 0.492-0.980, P=0.038). The patients with higher albumin level had better survival outcome. Preoperative serum albumin level is an independent prognostic factor for colon cancer. Colon cancer patients with hypoalbuminemia have worse

  8. Breast Cancer With Brain Metastases: Clinicopathologic Features, Survival, and Paired Biomarker Analysis

    PubMed Central

    Shen, Qi; Hess, Kenneth R.; Suki, Dima; Aldape, Kenneth D.; Sawaya, Raymond; Ibrahim, Nuhad K.

    2015-01-01

    Background. The aim of this study was to describe clinicopathologic features of patients with breast cancer brain metastasis (BCBM); to evaluate survival after diagnosis of BCBM; and to compare estrogen receptor (ER), progesterone receptor (PR), and HER2 expression in the paired primary and brain tumors. Materials and Methods. We identified 140 consecutive patients who underwent craniotomy for BCBM (either for diagnostic purpose or with therapeutic intent) at the University of Texas MD Anderson Cancer Center between 2002 and 2009. Results. Most patients had invasive ductal histology (91%), grade 3 tumors (67%), and positive axillary lymph node (64%). Of the tumors, 56% were ER-negative, 62% were PR-negative, 44% were HER2-positive, and 28% were triple negative (TN). Brain metastasis (BM) was solitary in 51% of patients. Median interval from breast cancer diagnosis to BM was 46 months; median survival after BM was 14.1 months. In the univariate analysis, younger age, solitary brain metastasis, and ER or PR positivity in the breast tumors were associated with longer survival. There was a statistical trend toward increased survival in HER2-positive patients compared with HER2-negative patients (18 vs. 11 months). In the multivariate analysis, predictors for longer survival included younger age, solitary brain lesion, and HER2 positivity in the breast cancer. Biomarkers were evaluated in paired primary and brain tumors in 35 patients for ER status, 34 for PR status, and 36 for HER2 status. Discordant rates were 28% for ER, 20% for PR, and 3% for HER2. Conclusion. Compared with unselected breast cancer patients at the same institution, patients with breast cancer who had brain metastases had a higher proportion of hormone receptor-negative, HER2-positive, and TN tumors. Younger age, solitary brain lesion, and HER2 expression were independent predictors of better survival in patients with BCBM. HER2 status was highly concordant between the paired primary and brain tumors

  9. Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer: association with histopathological features and subtypes.

    PubMed

    Kim, Yunju; Ko, Kyounglan; Kim, Daehong; Min, Changki; Kim, Sungheon G; Joo, Jungnam; Park, Boram

    2016-07-01

    To evaluate the associations between intravoxel incoherent motion (IVIM)-derived parameters and histopathological features and subtypes of breast cancer. Pre-operative MRI from 275 patients with unilateral breast cancer was analyzed. The apparent diffusion coefficient (ADC) and IVIM parameters [tissue diffusion coefficient (Dt), perfusion fraction (fp) and pseudodiffusion coefficient] were obtained from cancer and normal tissue using diffusion-weighted imaging with b-values of 0, 30, 70, 100, 150, 200, 300, 400, 500 and 800 s mm(-2). We then compared the IVIM parameters of tumours with different histopathological features and subtypes. The ADC and Dt were lower and fp was higher in cancers than in normal tissues (p < 0.001). The Dt was lower in high Ki-67 cancer than in low Ki-67 cancer (p = 0.019), whereas ADC showed no significant difference (p = 0.309). Luminal B [human epidermal growth factor receptor 2 (HER2)-negative] cancer showed lower ADC (p = 0.003) and Dt (p = 0.001) than other types. We found low tissue diffusivity in high Ki-67 cancer and luminal B (HER2-negative) cancer using IVIM imaging. Low tissue diffusivity is more clearly shown in high Ki-67 tumours and luminal B (HER2-negative) tumours with the IVIM model.

  10. Hypertension is the primary component of metabolic syndrome associated with pathologic features of kidney cancer.

    PubMed

    Kocher, Neil J; Rjepaj, Chris; Robyak, Haley; Lehman, Erik; Raman, Jay D

    2017-01-01

    To determine whether individual and/or cumulative components of metabolic syndrome (obesity, hypertension, dyslipidemia, and hyperglycemia) are associated with pathologic features of kidney cancer. A review of our kidney tumor database identified 462 patients who underwent partial or radical nephrectomy for renal cell carcinoma. The NCEP ATP-III criteria were used to define metabolic syndrome (MetS). Linear fixed effects modeling and ordinal logistic regression examined the relationship between MetS (individual and cumulative components) and pathologic characteristics. Two hundred and seventy-eight men and 184 women with a median age of 58 years, BMI of 31 kg/m(2), tumor size of 3.7 cm, and nephrometry score of 6 were included. Ninety-seven (21 %) patients met NCEP ATP-III criteria for MetS. Hypertension was the only individual component of MetS associated with pathologic features of kidney cancer including increased tumor size [geometric mean ratio 1.17 (1.05-1.32), P = 0.03], higher tumor grade [OR 1.49 (1.03-2.17), P = 0.04], increasing nephrometry score [OR 1.77 (1.28-2.48), P = 0.001], and non-clear cell histology [OR 1.42 (1.01-2.02), P = 0.05]. Furthermore, combinations of MetS components were associated with increased tumor grade (P = 0.02), tumor stage (P = 0.02), nephrometry score (P ≤ 0.001), and non-clear cell histology (P = 0.02), only when hypertension was included. MetS is composed of four risk factors each implicated in carcinogenesis. We identified hypertension as the primary component associated with specific pathologic features of kidney cancer. Further studies are necessary to elucidate whether the effect of hypertension is a function of severity and/or chronicity.

  11. Radiogenomic analysis of breast cancer: dynamic contrast enhanced - magnetic resonance imaging based features are associated with molecular subtypes

    NASA Astrophysics Data System (ADS)

    Wang, Shijian; Fan, Ming; Zhang, Juan; Zheng, Bin; Wang, Xiaojia; Li, Lihua

    2016-03-01

    Breast cancer is one of the most common malignant tumor with upgrading incidence in females. The key to decrease the mortality is early diagnosis and reasonable treatment. Molecular classification could provide better insights into patient-directed therapy and prognosis prediction of breast cancer. It is known that different molecular subtypes have different characteristics in magnetic resonance imaging (MRI) examination. Therefore, we assumed that imaging features can reflect molecular information in breast cancer. In this study, we investigated associations between dynamic contrasts enhanced MRI (DCE-MRI) features and molecular subtypes in breast cancer. Sixty patients with breast cancer were enrolled and the MR images were pre-processed for noise reduction, registration and segmentation. Sixty-five dimensional imaging features including statistical characteristics, morphology, texture and dynamic enhancement in breast lesion and background regions were semiautomatically extracted. The associations between imaging features and molecular subtypes were assessed by using statistical analyses, including univariate logistic regression and multivariate logistic regression. The results of multivariate regression showed that imaging features are significantly associated with molecular subtypes of Luminal A (p=0.00473), HER2-enriched (p=0.00277) and Basal like (p=0.0117), respectively. The results indicated that three molecular subtypes are correlated with DCE-MRI features in breast cancer. Specifically, patients with a higher level of compactness or lower level of skewness in breast lesion are more likely to be Luminal A subtype. Besides, the higher value of the dynamic enhancement at T1 time in normal side reflect higher possibility of HER2-enriched subtype in breast cancer.

  12. Two-step feature selection for predicting survival time of patients with metastatic castrate resistant prostate cancer

    PubMed Central

    Shiga, Motoki

    2016-01-01

    Metastatic castrate resistant prostate cancer (mCRPC) is the major cause of death in prostate cancer patients. Even though some options for treatment of mCRPC have been developed, the most effective therapies remain unclear. Thus finding key patient clinical variables related with mCRPC is an important issue for understanding the disease progression mechanism of mCRPC and clinical decision making for these patients. The Prostate Cancer DREAM Challenge is a crowd-based competition to tackle this essential challenge using new large clinical datasets. This paper proposes an effective procedure for predicting global risks and survival times of these patients, aimed at sub-challenge 1a and 1b of the Prostate Cancer DREAM challenge. The procedure implements a two-step feature selection procedure, which first implements sparse feature selection for numerical clinical variables and statistical hypothesis testing of differences between survival curves caused by categorical clinical variables, and then implements a forward feature selection to narrow the list of informative features. Using Cox’s proportional hazards model with these selected features, this method predicted global risk and survival time of patients using a linear model whose input is a median time computed from the hazard model. The challenge results demonstrated that the proposed procedure outperforms the state of the art model by correctly selecting more informative features on both the global risk prediction and the survival time prediction. PMID:27990267

  13. Triple negative breast cancer in North of Morocco: clinicopathologic and prognostic features.

    PubMed

    Derkaoui, Touria; Bakkach, Joaira; Mansouri, Mohamed; Loudiyi, Ali; Fihri, Mohamed; Alaoui, Fatima Zahra; Barakat, Amina; El Yemlahi, Bouchra; Bihri, Hassan; Nourouti, Naima Ghailani; Mechita, Mohcine Bennani

    2016-10-22

    Triple Negative Breast Cancer (TNBC) is defined by a lack of estrogen and progesterone receptor gene expression and by the absence of overexpression on HER2. It is associated to a poor prognosis. We propose to analyze the clinicopathologic and prognostic characteristics of this breast cancer subtype in a Mediterranean population originated or resident in the North of Morocco. We conducted a retrospective study of 279 patients diagnosed with breast cancer between January 2010 and January 2015. Clinicopathologic and prognostic features have been analyzed. Disease-Free Survival (DFS) and Overall Survival (OS) have been estimated. Of all cases, forty-nine (17.6 %) were identified as having triple negative breast cancer with a median age of 46 years. The average tumor size was 3.6 cm. The majority of patients have had invasive ductal carcinoma (91.8 %) and 40.4 % of them were grade III SBR. Nodal metastasis was detected in 38.9 % of the patients and vascular invasion was found in 36.6 % of them. About half of the patients had an early disease (53.1 %) and 46.9 % were diagnosed at an advanced stage. Patients with operable tumors (61.2 %) underwent primary surgery and adjuvant chemotherapy. Patients with no operable tumors (26.5 %) received neoadjuvant chemotherapy followed by surgery, and patients with metastatic disease (12.2 %) were treated by palliative chemotherapy. DFS and OS at 5 years were respectively 83.7 and 71.4 %. Among 49, twelve had recurrences, found either when diagnosing them or after a follow-up. Local relapse was 6.1 %. Lung and liver metastases accounted consecutively for 8.2 and 10.2 %. Bone metastases were found in 4.1 % and brain metastases in 2.1 % of the cases. Our results are in accordance with literature data, particularly what concerning young age and poor prognosis among TNBC phenotype. Therefore, the identification of BRCA mutations in our population seems to be essential in order to better adapt management options for this aggressive form

  14. Clinicopathological features and outcomes in advanced nonsmall cell lung cancer with tailored therapy

    PubMed Central

    Bala, Stalin; Gundeti, Sadashivudu; Linga, Vijay Gandhi; Maddali, Lakshmi Srinivas; Digumarti, Raghunadha Rao; Uppin, Shantveer G.

    2016-01-01

    Context: Lung cancer is an important cause of cancer-related deaths worldwide. There is an increasing incidence of lung cancer in never smokers and a shift of histology from squamous cell to adenocarcinoma globally in the recent past. Data on treatment outcomes with newer platinum doublets is scant from India. Aims: To study the clinicopathological features, response rates (RRs), progression-free survival (PFS), overall survival (OS), and the 1, 2, and 3 years survival, in patients with advanced nonsmall cell lung cancer (NSCLC). Materials and Methods: Data of all patients who received chemotherapy for Stage IIIB and IV NSCLC between January 2010 and June 2014 were retrospectively analyzed. Statistical Analysis Used: Univariate analysis for OS was done by plotting Kaplan–Meier curves and the log-rank test was used to calculate P values. Logistic regression analysis for OS was carried out using MedCalc statistical software. Results: A total of 353 patients received chemotherapy. Of these, 256 were evaluable for outcome parameters. The median age at presentation was 58 years with a male:female ratio of 2.53:1. The smoker:nonsmoker ratio was 1:1. Adenocarcinomatous histology was the most common both in smokers and nonsmokers reported in 70.8% patients. Epidermal growth factor receptor (EGFR) mutation and echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase translocation were seen in 35% and 3% of patients, respectively. The RR, median PFS, OS, 1, 2, and 3 years survival were 80%, 8 months, 12.1 months, 51.5%, 12.7%, and 4.2%, respectively. There was no significant survival difference among the treatment regimen used but the response to I line chemotherapy impacted survival. Female gender, performance status, and nonsquamous histology were significant predictors of OS (P = 0.0443, P = 0.0003, P = 0.048, respectively). Conclusions: There was an increase in the incidence of nonsmokers. Adenocarcinoma was the most common histology in both smokers

  15. Somatic molecular changes and histo-pathological features of colorectal cancer in Tunisia

    PubMed Central

    Aissi, Sana; Buisine, Marie Pierre; Zerimech, Farid; Kourda, Nadia; Moussa, Amel; Manai, Mohamed; Porchet, Nicole

    2013-01-01

    AIM: To determine correlations between family history, clinical features and mutational status of genes involved in the progression of colorectal cancer (CRC). METHODS: Histo-pathological features and molecular changes [KRAS, BRAF and CTNNB1 genes mutations, microsatellite instability (MSI) phenotype, expression of mismatch repair (MMR) and mucin (MUC) 5AC proteins, mutation and expression analysis of TP53, MLH1 promoter hypermethylation analysis] were examined in a series of 51 unselected Tunisian CRC patients, 10 of them had a proven or probable hereditary disease, on the track of new tumoral markers for CRC susceptibility in Tunisian patients. RESULTS: As expected, MSI and MMR expression loss were associated to the presence of familial CRC (75% vs 9%, P < 0.001). However, no significant associations have been detected between personal or familial cancer history and KRAS (codons 12 and 13) or TP53 (exons 4-9) alterations. A significant inverse relationship has been observed between the presence of MSI and TP53 accumulation (10.0% vs 48.8%, P = 0.0335) in CRC tumors, suggesting different molecular pathways to CRC that in turn may reflect different environmental exposures. Interestingly, MUC5AC expression was significantly associated to the presence of MSI (46.7% vs 8.3%, P = 0.0039), MMR expression loss (46.7% vs 8.3%, P = 0.0039) and the presence of familial CRC (63% vs 23%, P = 0.039). CONCLUSION: These findings suggest that MUC5AC expression analysis may be useful in the screening of Tunisian patients with high risk of CRC. PMID:23983431

  16. Assessment of pathological prostate cancer characteristics in men with favorable biopsy features on predominantly sextant biopsy.

    PubMed

    Chun, Felix K-H; Suardi, Nazareno; Capitanio, Umberto; Jeldres, Claudio; Ahyai, Sascha; Graefen, Markus; Haese, Alexander; Steuber, Thomas; Erbersdobler, Andreas; Montorsi, Francesco; Huland, Hartwig; Karakiewicz, Pierre I

    2009-03-01

    The rate of insignificant prostate cancer (IPCa) is increasing. To examine three end points in patients with a single, positive core and no high-grade prostate cancer (PCa) at biopsy, namely (1) rate of clinical IPCa at radical prostatectomy (RP), defined as organ-confined PCa with a Gleason score of 6 or lower and tumor volume<0.5 cc; (2) rate of pathologically unfavorable PCa at RP (Gleason 7-10 or non-organ-confined disease); and (3) ability to predict either insignificant or unfavorable PCa at RP. Retrospective analysis of 209 men with one positive biopsy core showing Gleason 6 or lower. : Detailed clinical and RP data were used in multivariable logistic regression models. Their bias-corrected accuracy estimates were quantified using the area under the curve (AUC) method. At RP, IPCa was present in 28 patients (13.4%) and pathologically unfavorable PCa, defined as Gleason 7 or higher or non-organ-confined PCa, was reported in 70 (33.5%) of 209 men; when Gleason 8 or higher or non-organ-confined PCa was considered, the proportion fell to 11%. Our multivariable models predicting different categories of pathologically unfavorable PCa at RP had an accuracy rate between 56% and 68% for predicting IPCa at RP versus 65.1% to 66.1% and 61.7% for the IPCa nomograms of Kattan et al and Nakanishi et al, respectively. Our data are not applicable to screening because they originate from a referral population. Despite highly favorable biopsy features, between 11% and 33% of men had unfavorable PCa at RP and only a minority (13.4%) had pathologically confirmed IPCa. Neither clinically insignificant nor pathologically unfavorable features could be predicted with sufficient accuracy for clinical decision making.

  17. A model of study for human cancer: Spontaneous occurring tumors in dogs. Biological features and translation for new anticancer therapies.

    PubMed

    Ranieri, G; Gadaleta, C D; Patruno, R; Zizzo, N; Daidone, M G; Hansson, M G; Paradiso, A; Ribatti, D

    2013-10-01

    Murine cancer models have been extremely useful for analyzing the biology of pathways involved in cancer initiation, promotion, and progression. Interestingly, several murine cancer models also exhibit heterogeneity, genomic instability and an intact immune system. However, they do not adequately represent several features that define cancer in humans, including long periods of latency, the complex biology of cancer recurrence and metastasis and outcomes to novel therapies. Therefore, additional models that better investigate the human disease are needed. In the pet population, with special references to the dog, cancer is a spontaneous disease and dogs naturally develop cancers that share many characteristics with human malignancies. More than 40 years ago, optimization of bone marrow transplantation protocols was undertaken in dogs and recently novel targeted therapies such as liposomal muramyl tripeptide phosphatidylethanolamine and several tyrosine kinase inhibitors, namely masitinib (AB1010) and toceranib phosphate (SU11654), have been developed to treat dog tumors which have then been translated to human clinical trials. In this review article, we will analyze biological data from dog tumors and comparative features with human tumors, and new therapeutic approaches translated from dog to human cancer.

  18. Risk factors and histopathological features of breast cancer among women with different menopausal status and age at diagnosis.

    PubMed

    Unlu, Ozan; Kiyak, Dilara; Caka, Canan; Yagmur, Merve; Yavas, Huseyin G; Erdogan, Fadime; Sener, Nazli; Oguz, Bahar; Babacan, Taner; Altundag, Kadri

    2017-01-01

    Although there are studies that investigate different risk factors and clinicopathological features of breast cancer in women at different age groups and menopausal status, there is a need for studies with larger study populations due to controversial findings. We conducted this study to identify demographic parameters in breast cancer patients and histopathological features of the tumors for different age groups and compare them to demonstrate significant differences, if any. 3325 women diagnosed with breast cancer in Hacettepe University Oncology Hospital Outpatient Clinic between January 1994 and March 2014 were included in this study. Postmenopausal women who were older than 65 were found to have higher number of children, higher rates of oral contraceptive use, greater age at menarche, and have higher rates of first full-time pregnancy before the age of 30. On the other hand, higher rates of grade 3 tumors, advanced lymph node stage, lymphovascular invasion, and triple negative breast cancers were more frequently seen in premenopausal women below the age of 35. Since earlier age at the time of diagnosis is associated with bad prognosis, early diagnosis of breast cancer gains importance in younger women. Implementing targeted screening programs of breast cancer for younger women may become a need in the future. Meanwhile, well-education on risks of breast cancer and regular self-examination for early diagnosis need to be emphasized for the prevention of breast cancer and related diseases in young ages.

  19. Nuclei-Based Features for Uterine Cervical Cancer Histology Image Analysis With Fusion-Based Classification.

    PubMed

    Guo, Peng; Banerjee, Koyel; Joe Stanley, R; Long, Rodney; Antani, Sameer; Thoma, George; Zuna, Rosemary; Frazier, Shelliane R; Moss, Randy H; Stoecker, William V

    2016-11-01

    Cervical cancer, which has been affecting women worldwide as the second most common cancer, can be cured if detected early and treated well. Routinely, expert pathologists visually examine histology slides for cervix tissue abnormality assessment. In previous research, we investigated an automated, localized, fusion-based approach for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on image analysis of 61 digitized histology images. This paper introduces novel acellular and atypical cell concentration features computed from vertical segment partitions of the epithelium region within digitized histology images to quantize the relative increase in nuclei numbers as the CIN grade increases. Based on the CIN grade assessments from two expert pathologists, image-based epithelium classification is investigated with voting fusion of vertical segments using support vector machine and linear discriminant analysis approaches. Leave-one-out is used for the training and testing for CIN classification, achieving an exact grade labeling accuracy as high as 88.5%.

  20. Predicting the pathological features of the mesorectum before the laparoscopic approach to rectal cancer.

    PubMed

    Fernández Ananín, Sonia; Targarona, Eduardo M; Martinez, Carmen; Pernas, Juan Carlos; Hernández, Diana; Gich, Ignasi; Sancho, Francesc J; Trias, Manuel

    2014-12-01

    Pelvic anatomy and tumour features play a role in the difficulty of the laparoscopic approach to total mesorectal excision in rectal cancer. The aim of the study was to analyse whether these characteristics also influence the quality of the surgical specimen. We performed a prospective study in consecutive patients with rectal cancer located less than 12 cm from the anal verge who underwent laparoscopic surgery between January 2010 and July 2013. Exclusion criteria were T1 and T4 tumours, abdominoperineal resections, obstructive and perforated tumours, or any major contraindication for laparoscopic surgery. Dependent variables were the circumferential resection margin (CMR) and the quality of the mesorectum. Sixty-four patients underwent laparoscopic sphincter-preserving total mesorectal excision. Resection was complete in 79.1% of specimens and CMR was positive in 9.7%. Univariate analysis showed tumour depth (T status) (P = 0.04) and promontorium-subsacrum angle (P = 0.02) independently predicted CRM (circumferential resection margin) positivity. Tumour depth (P < 0.05) and promontorium-subsacrum axis (P < 0.05) independently predicted mesorectum quality. Multivariate analysis identified the promontorium-subsacrum angle (P = 0.012) as the only independent predictor of CRM. Bony pelvis dimensions influenced the quality of the specimen obtained by laparoscopy. These measurements may be useful to predict which patients will benefit most from laparoscopic surgery and also to select patients in accordance with the learning curve of trainee surgeons.

  1. SBRT for prostate cancer: Challenges and features from a physicist prospective.

    PubMed

    Mancosu, Pietro; Clemente, Stefania; Landoni, Valeria; Ruggieri, Ruggero; Alongi, Filippo; Scorsetti, Marta; Stasi, Michele

    2016-03-01

    Emerging data are showing the safety and the efficacy of Stereotactic Body Radiation Therapy (SBRT) in prostate cancer management. In this context, the medical physicists are regularly involved to review the appropriateness of the adopted technology and to proactively study new solutions. From the physics point of view there are two major challenges in prostate SBRT: (1) mitigation of geometrical uncertainty and (2) generation of highly conformal dose distributions that maximally spare the OARs. Geometrical uncertainties have to be limited as much as possible in order to avoid the use of large PTV margins. Furthermore, advanced planning and delivery techniques are needed to generate maximally conformal dose distributions. In this non-systematic review the technology and the physics aspects of SBRT for prostate cancer were analyzed. In details, the aims were: (i) to describe the rationale of reducing the number of fractions (i.e. increasing the dose per fraction), (ii) to analyze the features to be accounted for performing an extreme hypo-fractionation scheme (>6-7Gy), and (iii) to describe technological solutions for treating in a safe way. The analysis of outcomes, toxicities, and other clinical aspects are not object of the present evaluation. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  2. Patterns and Biologic Features of p53 Mutation Types in Korean Breast Cancer Patients

    PubMed Central

    Kim, Hyung Won; Lee, Hak Min; Hwang, Seung Hyun; Ahn, Sung Gwe; Lee, Kyung-A

    2014-01-01

    Purpose The p53 gene is one of the most frequently mutated genes in breast cancer. We investigated the patterns and biologic features of p53 gene mutation and evaluated their clinical significance in Korean breast cancer patients. Methods Patients who underwent p53 gene sequencing were included. Mutational analysis of exon 5 to exon 9 of the p53 gene was carried out using polymerase chain reaction-denaturing high performance liquid chromatography and direct sequencing. Results A total of 497 patients were eligible for the present study and p53 gene mutations were detected in 71 cases (14.3%). Mutation of p53 was significantly associated with histologic grading (p<0.001), estrogen receptor and progesterone receptor status (p<0.001), HER2 status (p<0.001), Ki-67 (p=0.028), and tumor size (p=0.004). The most frequent location of p53 mutations was exon 7 and missense mutation was the most common type of mutation. Compared with patients without mutation, there was a statistically significant difference in relapse-free survival of patients with p53 gene mutation and missense mutation (p=0.020, p=0.006, respectively). Only p53 missense mutation was an independent prognostic factor for relapse-free survival in multivariate analysis, with an adjusted hazard ratio of 2.29 (95% confidence interval, 1.08-4.89, p=0.031). Conclusion Mutation of the p53 gene was associated with more aggressive clinicopathologic characteristics and p53 missense mutation was an independent negative prognostic factor in Korean breast cancer patients. PMID:24744791

  3. Clinicopathologic features of breast cancers that develop in women with previous benign breast disease.

    PubMed

    Visscher, Daniel W; Frost, Marlene H; Hartmann, Lynn C; Frank, Ryan D; Vierkant, Robert A; McCullough, Ann E; Winham, Stacey J; Vachon, Celine M; Ghosh, Karthik; Brandt, Kathleen R; Farrell, Ann M; Tarabishy, Yaman; Hieken, Tina J; Haddad, Tufia C; Kraft, Ruth A; Radisky, Derek C; Degnim, Amy C

    2016-02-01

    Women with benign breast disease (BBD) have an increased risk of developing breast cancer (BC). Nearly 30% of all BCs develop in women with prior BBD. Information regarding features of the expected number of BCs after BBD would enhance individualized surveillance and prevention strategies for these women. In the current study, the authors sought to characterize BCs developing in a large cohort of women with BBD. The current study cohort included 13,485 women who underwent breast biopsy for mammographic or palpable concerns between 1967 and 2001. Biopsy slides were reviewed and classified as nonproliferative disease, proliferative disease without atypia, or atypical hyperplasia. BCs were identified by follow-up questionnaires, medical records, and Tumor Registry data. BC tissues were obtained and reviewed. With median follow-up of 15.8 years, 1273 women developed BC. The majority of BCs were invasive (81%), of which 61% were ductal, 13% were mixed ductal/lobular, and 14% were lobular. Approximately two-thirds of the BC cases were intermediate or high grade, and 29% were lymph node positive. Cancer characteristics were similar across the 3 histologic categories of BBD, with a similar frequency of ductal carcinoma in situ, invasive disease, tumor size, time to invasive BC, histologic type of BC, lymph node positivity, and human epidermal growth factor receptor 2 positivity. Women with atypical hyperplasia were found to have a higher frequency of estrogen receptor-positive BC (91%) compared with women with proliferative disease without atypia (80%) or nonproliferative disease (85%) (P = .02). A substantial percentage of all BCs develop in women with prior BBD. The majority of BCs after BBD are invasive tumors of ductal type, with a substantial number demonstrating lymph node positivity. Of all the BCs in the current study, 84% were estrogen receptor positive. Prevention therapy should be strongly encouraged in higher-risk women with BBD. © 2015 American Cancer Society.

  4. A Comparison of the Biological Features of Prostate Cancer with (PSA+, PSMA+) Profile according to RKIP

    PubMed Central

    Ben Jemaa, Awatef; Bouraoui, Yosra; Sallami, Sataa; Nouira, Yassine; Oueslati, Ridha

    2013-01-01

    Purpose. To investigate differences in the biological features of the most immunoexpressed prostate cancer (PC) profiles (PSA+, PSMA+) according to the RKIP. Methods. 19 PC with dominant Gleason grade ≥8 were studied. Expression of PSA, PSMA, RKIP, Raf-1, MEK-1, ERK-1, ERK-2, p-Akt (T308), p-Akt (S473), NF-κB p50, and NF-κBp65 were detected immunohistochemically. Results. Loss of RKIP in the most immunoexpressed PC (PSA+, PSMA+) profile was associated with increased levels of PSA and PSMA expression. Intensities of immunoreactions to PSA and PSMA were higher in cancer cells negative for RKIP (12.51 ± 1.6 and 34.95 ± 1.92) compared to those positive for RKIP (4.68 ± 1.11 and 28.56 ± 0.91). In parallel, missing RKIP expression in PC patients with PSA+, PSMA+ profile was connected with increased components of both Raf-1/MEK/ERK and NF-κB (p65/p50), whereas Akt is activated independently of RKIP. Conclusions. Although characterized by the same (PSA+, PSMA+) profile, PC phenotype missing the RKIP related to invasive potential and greater biological aggressiveness reflected in overexpression of components of Raf-1/MEK/ERK and NF-κB (p65/p50) in which Akt is activated independently of RKIP. Taking into account the PC phenotypes according to RKIP among PSA-PSMA profiles may improve distinguishing them from cancers that will become more aggressive and therefore adapt the therapeutic strategies in those patients. PMID:23991415

  5. Current composite-feature classification methods do not outperform simple single-genes classifiers in breast cancer prognosis.

    PubMed

    Staiger, Christine; Cadot, Sidney; Györffy, Balázs; Wessels, Lodewyk F A; Klau, Gunnar W

    2013-01-01

    Integrating gene expression data with secondary data such as pathway or protein-protein interaction data has been proposed as a promising approach for improved outcome prediction of cancer patients. Methods employing this approach usually aggregate the expression of genes into new composite features, while the secondary data guide this aggregation. Previous studies were limited to few data sets with a small number of patients. Moreover, each study used different data and evaluation procedures. This makes it difficult to objectively assess the gain in classification performance. Here we introduce the Amsterdam Classification Evaluation Suite (ACES). ACES is a Python package to objectively evaluate classification and feature-selection methods and contains methods for pooling and normalizing Affymetrix microarrays from different studies. It is simple to use and therefore facilitates the comparison of new approaches to best-in-class approaches. In addition to the methods described in our earlier study (Staiger et al., 2012), we have included two prominent prognostic gene signatures specific for breast cancer outcome, one more composite feature selection method and two network-based gene ranking methods. Employing the evaluation pipeline we show that current composite-feature classification methods do not outperform simple single-genes classifiers in predicting outcome in breast cancer. Furthermore, we find that also the stability of features across different data sets is not higher for composite features. Most stunningly, we observe that prediction performances are not affected when extracting features from randomized PPI networks.

  6. A study of T2-weighted MR image texture features and diffusion-weighted MR image features for computer-aided diagnosis of prostate cancer

    NASA Astrophysics Data System (ADS)

    Peng, Yahui; Jiang, Yulei; Antic, Tatjana; Giger, Maryellen L.; Eggener, Scott; Oto, Aytekin

    2013-02-01

    The purpose of this study was to study T2-weighted magnetic resonance (MR) image texture features and diffusionweighted (DW) MR image features in distinguishing prostate cancer (PCa) from normal tissue. We collected two image datasets: 23 PCa patients (25 PCa and 23 normal tissue regions of interest [ROIs]) imaged with Philips MR scanners, and 30 PCa patients (41 PCa and 26 normal tissue ROIs) imaged with GE MR scanners. A radiologist drew ROIs manually via consensus histology-MR correlation conference with a pathologist. A number of T2-weighted texture features and apparent diffusion coefficient (ADC) features were investigated, and linear discriminant analysis (LDA) was used to combine select strong image features. Area under the receiver operating characteristic (ROC) curve (AUC) was used to characterize feature effectiveness in distinguishing PCa from normal tissue ROIs. Of the features studied, ADC 10th percentile, ADC average, and T2-weighted sum average yielded AUC values (+/-standard error) of 0.95+/-0.03, 0.94+/-0.03, and 0.85+/-0.05 on the Phillips images, and 0.91+/-0.04, 0.89+/-0.04, and 0.70+/-0.06 on the GE images, respectively. The three-feature combination yielded AUC values of 0.94+/-0.03 and 0.89+/-0.04 on the Phillips and GE images, respectively. ADC 10th percentile, ADC average, and T2-weighted sum average, are effective in distinguishing PCa from normal tissue, and appear robust in images acquired from Phillips and GE MR scanners.

  7. A CBR framework with gradient boosting based feature selection for lung cancer subtype classification.

    PubMed

    Ramos-González, Juan; López-Sánchez, Daniel; Castellanos-Garzón, Jose A; de Paz, Juan F; Corchado, Juan M

    2017-07-01

    Molecular subtype classification represents a challenging field in lung cancer diagnosis. Although different methods have been proposed for biomarker selection, efficient discrimination between adenocarcinoma and squamous cell carcinoma in clinical practice presents several difficulties, especially when the latter is poorly differentiated. This is an area of growing importance, since certain treatments and other medical decisions are based on molecular and histological features. An urgent need exists for a system and a set of biomarkers that provide an accurate diagnosis. In this paper, a novel Case Based Reasoning framework with gradient boosting based feature selection is proposed and applied to the task of squamous cell carcinoma and adenocarcinoma discrimination, aiming to provide accurate diagnosis with a reduced set of genes. The proposed method was trained and evaluated on two independent datasets to validate its generalization capability. Furthermore, it achieved accuracy rates greater than those of traditional microarray analysis techniques, incorporating the advantages inherent to the Case Based Reasoning methodology (e.g. learning over time, adaptability, interpretability of solutions, etc.). Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Investigation of automated feature extraction techniques for applications in cancer detection from multispectral histopathology images

    NASA Astrophysics Data System (ADS)

    Harvey, Neal R.; Levenson, Richard M.; Rimm, David L.

    2003-05-01

    Recent developments in imaging technology mean that it is now possible to obtain high-resolution histological image data at multiple wavelengths. This allows pathologists to image specimens over a full spectrum, thereby revealing (often subtle) distinctions between different types of tissue. With this type of data, the spectral content of the specimens, combined with quantitative spatial feature characterization may make it possible not only to identify the presence of an abnormality, but also to classify it accurately. However, such are the quantities and complexities of these data, that without new automated techniques to assist in the data analysis, the information contained in the data will remain inaccessible to those who need it. We investigate the application of a recently developed system for the automated analysis of multi-/hyper-spectral satellite image data to the problem of cancer detection from multispectral histopathology image data. The system provides a means for a human expert to provide training data simply by highlighting regions in an image using a computer mouse. Application of these feature extraction techniques to examples of both training and out-of-training-sample data demonstrate that these, as yet unoptimized, techniques already show promise in the discrimination between benign and malignant cells from a variety of samples.

  9. Gastric adenocarcinoma in common variable immunodeficiency: features of cancer and associated gastritis may be characteristic of the condition.

    PubMed

    De Petris, Giovanni; Dhungel, Bal M; Chen, Longwen; Chang, Yu-Hui H

    2014-10-01

    Common variable immunodeficiency (CVID) is associated with an increased risk of gastric cancer. The aim of the study was to determine the morphological features of CVID-associated gastric adenocarcinoma (CAGA) and of the background gastritis. The population of gastric cancer patients with CVID of Mayo Clinic in the period 2000-2010 was studied; 6 cases of CVID (2 males, 4 females, average age 47 years, age range 26-71 years) were found in 5793 patients with gastric cancer in the study period. Each patient underwent gastric resection for which histology slides were reviewed. Chronic gastritis variables, CVID-related findings, and features of the adenocarcinoma were recorded. CAGA was of intestinal type, with high number of intratumoral lymphocytes (ITLs). Cancer was diagnosed in younger patients than in the overall population of gastric cancer. Severe atrophic metaplastic pangastritis with extensive dysplasia was present in the background in 4 cases, with features of lymphocytic gastritis in 2 cases. Features of CVID (plasma cells paucity in 4 of 6 cases, lymphoid nodules prominent in four cases) could be detected. In summary, gastric adenocarcinoma at young age with ITLs, accompanied by atrophic metaplastic pangastritis, should alert the pathologist of the possibility of CAGA. It follows that, in presence of those characteristics, the search of CVID-associated abnormalities should be undertaken in the nonneoplastic tissues.

  10. Evaluation of correlation between CT image features and ERCC1 protein expression in assessing lung cancer prognosis

    NASA Astrophysics Data System (ADS)

    Tan, Maxine; Emaminejad, Nastaran; Qian, Wei; Sun, Shenshen; Kang, Yan; Guan, Yubao; Lure, Fleming; Zheng, Bin

    2014-03-01

    Stage I non-small-cell lung cancers (NSCLC) usually have favorable prognosis. However, high percentage of NSCLC patients have cancer relapse after surgery. Accurately predicting cancer prognosis is important to optimally treat and manage the patients to minimize the risk of cancer relapse. Studies have shown that an excision repair crosscomplementing 1 (ERCC1) gene was a potentially useful genetic biomarker to predict prognosis of NSCLC patients. Meanwhile, studies also found that chronic obstructive pulmonary disease (COPD) was highly associated with lung cancer prognosis. In this study, we investigated and evaluated the correlations between COPD image features and ERCC1 gene expression. A database involving 106 NSCLC patients was used. Each patient had a thoracic CT examination and ERCC1 genetic test. We applied a computer-aided detection scheme to segment and quantify COPD image features. A logistic regression method and a multilayer perceptron network were applied to analyze the correlation between the computed COPD image features and ERCC1 protein expression. A multilayer perceptron network (MPN) was also developed to test performance of using COPD-related image features to predict ERCC1 protein expression. A nine feature based logistic regression analysis showed the average COPD feature values in the low and high ERCC1 protein expression groups are significantly different (p < 0.01). Using a five-fold cross validation method, the MPN yielded an area under ROC curve (AUC = 0.669±0.053) in classifying between the low and high ERCC1 expression cases. The study indicates that CT phenotype features are associated with the genetic tests, which may provide supplementary information to help improve accuracy in assessing prognosis of NSCLC patients.

  11. Clinico-morphological features of BRAF inhibition-induced proliferative skin lesions in cancer patients.

    PubMed

    Belum, Viswanath Reddy; Rosen, Alyx C; Jaimes, Natalia; Dranitsaris, George; Pulitzer, Melissa P; Busam, Klaus J; Marghoob, Ashfaq A; Carvajal, Richard D; Chapman, Paul B; Lacouture, Mario E

    2015-01-01

    The use of BRAF inhibitors may lead to the development of cutaneous toxicities such as rashes, photosensitivity, alopecia, palmoplantar erythrodysesthesia, and proliferative skin lesions, including keratoacanthomas (KAs) and cutaneous squamous cell carcinomas (cuSCCs). The latter are noteworthy for their potential to exhibit malignant features, and they may necessitate invasive treatment. Their prompt identification is of primary importance for directing supportive care efforts and maintaining dose intensity while minimizing the morbidity associated with supportive care interventions. Because such lesions are less familiar to oncologists, this study was designed to characterize their clinico-morphological features, which have not been hitherto described. The clinical and dermoscopic characteristics and risk factors of new-onset proliferative skin lesions (benign verrucous lesions and KAs/cuSCCs) developing after the initiation of treatment with vemurafenib, dabrafenib, and XL281 were analyzed; the histopathological diagnoses were ascertained. The majority of the lesions were benign verrucous lesions (78%, n = 87), whereas KAs/cuSCCs represented 22% (n = 25). The median times to biopsy for the initial verrucous lesions and KAs/cuSCCs were 4.8 and 10.5 weeks, respectively. The clinico-morphological features significant for KAs/cuSCCs included a larger size (P < .001), a nodular appearance (P < .001), a central keratin plug (P < .001), a central ulceration or crust (P = .04), an adherent scale (P = .02), an erythematous halo (P = .03), and a scaly ring (collarette; P < .001) at the periphery. Our findings represent the first detailed description of the clinico-morphological characteristics that permit distinction between the benign and malignant skin lesions induced by BRAF inhibitors. They are valuable for the recognition of lesions that require intervention and/or a dermatology referral versus those that permit provisional

  12. Color edges extraction using statistical features and automatic threshold technique: application to the breast cancer cells

    PubMed Central

    2014-01-01

    Background Color image segmentation has been so far applied in many areas; hence, recently many different techniques have been developed and proposed. In the medical imaging area, the image segmentation may be helpful to provide assistance to doctor in order to follow-up the disease of a certain patient from the breast cancer processed images. The main objective of this work is to rebuild and also to enhance each cell from the three component images provided by an input image. Indeed, from an initial segmentation obtained using the statistical features and histogram threshold techniques, the resulting segmentation may represent accurately the non complete and pasted cells and enhance them. This allows real help to doctors, and consequently, these cells become clear and easy to be counted. Methods A novel method for color edges extraction based on statistical features and automatic threshold is presented. The traditional edge detector, based on the first and the second order neighborhood, describing the relationship between the current pixel and its neighbors, is extended to the statistical domain. Hence, color edges in an image are obtained by combining the statistical features and the automatic threshold techniques. Finally, on the obtained color edges with specific primitive color, a combination rule is used to integrate the edge results over the three color components. Results Breast cancer cell images were used to evaluate the performance of the proposed method both quantitatively and qualitatively. Hence, a visual and a numerical assessment based on the probability of correct classification (P C ), the false classification (P f ), and the classification accuracy (Sens(%)) are presented and compared with existing techniques. The proposed method shows its superiority in the detection of points which really belong to the cells, and also the facility of counting the number of the processed cells. Conclusions Computer simulations highlight that the proposed method

  13. mtDNA germ line variation mediated ROS generates retrograde signaling and induces pro-cancerous metabolic features

    PubMed Central

    Singh, Rajnish Kumar; Srivastava, Archita; Kalaiarasan, Ponnusamy; Manvati, Siddharth; Chopra, Rupali; Bamezai, Rameshwar N. K.

    2014-01-01

    mtDNA non-synonymous germ line variation (G10398A; p.A114T) has remained equivocal with least mechanistic understanding in showing an association with cancer. This has necessitated showing in-vitro how an over-expression within mitochondria of either of the variants produces higher intracellular ROS, resulting in differential anchorage dependent and independent growth. Both these features were observed to be relatively higher in ND3:114T variant. An elevated amount of intracellular carbonylated proteins and a reduced activity of a key glycolytic enzyme, Pyruvate kinase M2, along with high glucose uptake and lactate production were other pro-cancerous features observed. The retrograde signaling through surplus ROS was generated by post-ND3 over-expression regulated nuclear gene expression epigenetically, involving selectively the apoptotic-DDR-pathways. The feature of ND3 over-expression, inducing ROS mediated pro-cancerous features in the cells in in vitro, was replicated in a pilot study in a limited number of sporadic breast tumors, suggesting the importance of mitochondrial germ-line variant(s) in enabling the cells to acquire pro-cancerous features. PMID:25300428

  14. Skin cancer texture analysis of OCT images based on Haralick, fractal dimension, Markov random field features, and the complex directional field features

    NASA Astrophysics Data System (ADS)

    Raupov, Dmitry S.; Myakinin, Oleg O.; Bratchenko, Ivan A.; Zakharov, Valery P.; Khramov, Alexander G.

    2016-10-01

    In this paper, we propose a report about our examining of the validity of OCT in identifying changes using a skin cancer texture analysis compiled from Haralick texture features, fractal dimension, Markov random field method and the complex directional features from different tissues. Described features have been used to detect specific spatial characteristics, which can differentiate healthy tissue from diverse skin cancers in cross-section OCT images (B- and/or C-scans). In this work, we used an interval type-II fuzzy anisotropic diffusion algorithm for speckle noise reduction in OCT images. The Haralick texture features as contrast, correlation, energy, and homogeneity have been calculated in various directions. A box-counting method is performed to evaluate fractal dimension of skin probes. Markov random field have been used for the quality enhancing of the classifying. Additionally, we used the complex directional field calculated by the local gradient methodology to increase of the assessment quality of the diagnosis method. Our results demonstrate that these texture features may present helpful information to discriminate tumor from healthy tissue. The experimental data set contains 488 OCT-images with normal skin and tumors as Basal Cell Carcinoma (BCC), Malignant Melanoma (MM) and Nevus. All images were acquired from our laboratory SD-OCT setup based on broadband light source, delivering an output power of 20 mW at the central wavelength of 840 nm with a bandwidth of 25 nm. We obtained sensitivity about 97% and specificity about 73% for a task of discrimination between MM and Nevus.

  15. Regression-Based Approach For Feature Selection In Classification Issues. Application To Breast Cancer Detection And Recurrence

    NASA Astrophysics Data System (ADS)

    Belciug, Smaranda; Serbanescu, Mircea-Sebastian

    2015-09-01

    Feature selection is considered a key factor in classifications/decision problems. It is currently used in designing intelligent decision systems to choose the best features which allow the best performance. This paper proposes a regression-based approach to select the most important predictors to significantly increase the classification performance. Application to breast cancer detection and recurrence using publically available datasets proved the efficiency of this technique.

  16. Prediction of near-term breast cancer risk using local region-based bilateral asymmetry features in mammography

    NASA Astrophysics Data System (ADS)

    Li, Yane; Fan, Ming; Li, Lihua; Zheng, Bin

    2017-03-01

    This study proposed a near-term breast cancer risk assessment model based on local region bilateral asymmetry features in Mammography. The database includes 566 cases who underwent at least two sequential FFDM examinations. The `prior' examination in the two series all interpreted as negative (not recalled). In the "current" examination, 283 women were diagnosed cancers and 283 remained negative. Age of cancers and negative cases completely matched. These cases were divided into three subgroups according to age: 152 cases among the 37-49 age-bracket, 220 cases in the age-bracket 50- 60, and 194 cases with the 61-86 age-bracket. For each image, two local regions including strip-based regions and difference-of-Gaussian basic element regions were segmented. After that, structural variation features among pixel values and structural similarity features were computed for strip regions. Meanwhile, positional features were extracted for basic element regions. The absolute subtraction value was computed between each feature of the left and right local-regions. Next, a multi-layer perception classifier was implemented to assess performance of features for prediction. Features were then selected according stepwise regression analysis. The AUC achieved 0.72, 0.75 and 0.71 for these 3 age-based subgroups, respectively. The maximum adjustable odds ratios were 12.4, 20.56 and 4.91 for these three groups, respectively. This study demonstrate that the local region-based bilateral asymmetry features extracted from CC-view mammography could provide useful information to predict near-term breast cancer risk.

  17. Prediction of pathologic femoral fractures in patients with lung cancer using machine learning algorithms: Comparison of computed tomography-based radiological features with clinical features versus without clinical features.

    PubMed

    Oh, Eunsun; Seo, Sung Wook; Yoon, Young Cheol; Kim, Dong Wook; Kwon, Sunyoung; Yoon, Sungroh

    2017-01-01

    The purpose of this article is to compare the predictive power of two models trained with computed tomography (CT)-based radiological features and both CT-based radiological and clinical features for pathologic femoral fractures in patients with lung cancer using machine learning algorithms. Between January 2010 and December 2014, 315 lung cancer patients with metastasis to the femur were included. Among them, 84 patients who underwent CT scan and were followed up for more than 3 months were enrolled. We examined clinical and radiological risk factors affecting pathologic fracture through logistic regression. Predictive analysis was performed using five different supervised learning algorithms. The power of predictive model trained with CT-based radiological features was compared to those trained with both CT-based radiological and clinical features. In multivariate logistic regression, female sex (odds ratio = 0.25, p = 0.0126), osteolysis (odds ratio = 7.62, p = 0.0239), and absence of radiation therapy (odds ratio = 10.25, p = 0.0258) significantly increased the risk of pathologic fracture in proximal femur. The predictive model trained with both CT-based radiological and clinical features showed the highest area under the receiver operating characteristic curve (0.80 ± 0.14, p < 0.0001) through gradient boosting algorithm. We believe that machine learning algorithms may be useful in the prediction of pathologic femoral fracture, which are multifactorial problem.

  18. Unsupervised feature construction and knowledge extraction from genome-wide assays of breast cancer with denoising autoencoders.

    PubMed

    Tan, Jie; Ung, Matthew; Cheng, Chao; Greene, Casey S

    2015-01-01

    Big data bring new opportunities for methods that efficiently summarize and automatically extract knowledge from such compendia. While both supervised learning algorithms and unsupervised clustering algorithms have been successfully applied to biological data, they are either dependent on known biology or limited to discerning the most significant signals in the data. Here we present denoising autoencoders (DAs), which employ a data-defined learning objective independent of known biology, as a method to identify and extract complex patterns from genomic data. We evaluate the performance of DAs by applying them to a large collection of breast cancer gene expression data. Results show that DAs successfully construct features that contain both clinical and molecular information. There are features that represent tumor or normal samples, estrogen receptor (ER) status, and molecular subtypes. Features constructed by the autoencoder generalize to an independent dataset collected using a distinct experimental platform. By integrating data from ENCODE for feature interpretation, we discover a feature representing ER status through association with key transcription factors in breast cancer. We also identify a feature highly predictive of patient survival and it is enriched by FOXM1 signaling pathway. The features constructed by DAs are often bimodally distributed with one peak near zero and another near one, which facilitates discretization. In summary, we demonstrate that DAs effectively extract key biological principles from gene expression data and summarize them into constructed features with convenient properties.

  19. [Comparison of clinicopathological features and prognosis between left-sided colon cancer and right-sided colon cancer].

    PubMed

    Gao, Xianhua; Yu, Guanyu; Liu, Peng; Hao, Liqiang; Liu, Lianjie; Zhang, Wei

    2017-06-25

    To compare the clinicopathological features and prognosis between left-sided colon cancer (LC) and right-sided colon cancer (RC). Clinicopathological and follow-up data of 2 174 colon carcinoma cases undergoing resection at Shanghai Changhai Hospital of The Second Military Medical University from January 2000 to December 2010 were retrospectively analyzed. Patients with transverse colon cancer, overlapping position, unknown location, recurrent cancer, multiple primary cancer, concomitant malignant tumors, preoperative chemotherapy, local resection, incomplete clinical data and missed follow up were excluded. Finally, a total of 1 036 patients, whose primary tumors were radically removed, were enrolled, with 563 patients in LC group (including carcinoma in cecum, ascending colon and hepatic flexure) and 473 in RC group (including carcinoma in splenic flexure, descending colon and sigmoid colon). The clinicopathological features and survival, including median overall survival, 5-year overall survival rate, tumor specific median overall survival, cancer specific 5-year overall survival rate, were compared between LC and RC groups. Tumor specific overall survival was defined as the period between operation date to the date of death caused by cancer progression. Multivariate Cox regression analysis was used to analyze the influencing factors of survival. Propensity score matching was carried out to balance the clinicopathological factors between the two groups with the SAS 9.3, taking the following parameters into consideration (age, gender, gross appearance, tumor diameter, invasion depth, lymph node metastasis, distant metastasis, TNM stages, differentiation, CEA and CA199-9). Patients in RC group and LC group were matched according to the propensity scores and the clinicopathological characteristics and prognosis of two groups were compared again. No significant differences were identified between the two groups in age, distant metastasis and serum CEA level

  20. βIII-tubulin overexpression is linked to aggressive tumor features and genetic instability in urinary bladder cancer.

    PubMed

    Hinsch, Andrea; Chaker, Aref; Burdelski, Christian; Koop, Christina; Tsourlakis, Maria Christina; Steurer, Stefan; Rink, Michael; Eichenauer, Till Simon; Wilczak, Waldemar; Wittmer, Corinna; Fisch, Margit; Simon, Ronald; Sauter, Guido; Büschek, Franziska; Clauditz, Till; Minner, Sarah; Jacobsen, Frank

    2017-03-01

    Development of genetic instability is a hallmark of tumor progression. Type III β-tubulin (TUBB3) is a component of microtubules involved in chromosome segregation. Its overexpression has been linked to adverse features of urinary bladder cancer. To investigate the role of TUBB3 for development of genetic instability, we compared TUBB3 expression with histopathological features and surrogate markers of genetic instability and tumor aggressiveness; copy number changes of HER2, TOP2A, CCND1, RAF1, and FGFR1; nuclear accumulation of p53, and cell proliferation in a tissue microarray (TMA) with more than 700 bladder cancers. TUBB3 expression was linked to high-grade and advanced-stage cancers (P<.0001), rapid cell proliferation (P<.0001), presence of multiple gene copy number alterations (P=.0008), and nuclear accumulation of p53 (P=.0008). Strong TUBB3 staining was found in 43% of urothelial cancers harboring copy number alterations as compared with 28% of genetically stable cancers, and in 50% of p53-positive cancers as compared with 30% of p53-negative tumors. The fraction of tumors with concomitant TUBB3 and p53 positivity increased with tumor stage and grade: 2% in pTaG1-2, 11% in pTaG3, 17% in pT1G2, 23% in pT1G3, and 32% in pT2-4 cancers (P<.0001). Importantly, strong TUBB3 overexpression was detectable in about 20% of low-grade, noninvasive cancers. In summary, our study demonstrates that TUBB3 overexpression is linked to an aggressive subtype of urinary bladder cancers, which is characterized by increased genetic instability, p53 alterations, and rapid cell proliferation. Detection of TUBB3 overexpression in genetically stable, low-grade, and noninvasive bladder cancers may be clinically useful to identify patients requiring particular close monitoring.

  1. Molecular profiles of thyroid cancer subtypes: Classification based on features of tissue revealed by mass spectrometry imaging.

    PubMed

    Pietrowska, Monika; Diehl, Hanna C; Mrukwa, Grzegorz; Kalinowska-Herok, Magdalena; Gawin, Marta; Chekan, Mykola; Elm, Julian; Drazek, Grzegorz; Krawczyk, Anna; Lange, Dariusz; Meyer, Helmut E; Polanska, Joanna; Henkel, Corinna; Widlak, Piotr

    2017-07-01

    Determination of the specific type of thyroid cancer is crucial for the prognosis and selection of treatment of this malignancy. However, in some cases appropriate classification is not possible based on histopathological features only, and it might be supported by molecular biomarkers. Here we aimed to characterize molecular profiles of different thyroid malignancies using mass spectrometry imaging (MSI) which enables the direct annotation of molecular features with morphological pictures of an analyzed tissue. Fifteen formalin-fixed paraffin-embedded tissue specimens corresponding to five major types of thyroid cancer were analyzed by MALDI-MSI after in-situ trypsin digestion, and the possibility of classification based on the results of unsupervised segmentation of MALDI images was tested. Novel method of semi-supervised detection of the cancer region of interest (ROI) was implemented. We found strong separation of medullary cancer from malignancies derived from thyroid epithelium, and separation of anaplastic cancer from differentiated cancers. Reliable classification of medullary and anaplastic cancers using an approach based on automated detection of cancer ROI was validated with independent samples. Moreover, extraction of spectra from tumor areas allowed the detection of molecular components that differentiated follicular cancer and two variants of papillary cancer (classical and follicular). We concluded that MALDI-MSI approach is a promising strategy in the search for biomarkers supporting classification of thyroid malignant tumors. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  2. Mammographic features and subsequent risk of breast cancer: a comparison of qualitative and quantitative evaluations in the Guernsey prospective studies.

    PubMed

    Torres-Mejía, Gabriela; De Stavola, Bianca; Allen, Diane S; Pérez-Gavilán, Juan J; Ferreira, Jorge M; Fentiman, Ian S; Dos Santos Silva, Isabel

    2005-05-01

    Mammographic features are known to be associated with breast cancer but the magnitude of the effect differs markedly from study to study. Methods to assess mammographic features range from subjective qualitative classifications to computer-automated quantitative measures. We used data from the UK Guernsey prospective studies to examine the relative value of these methods in predicting breast cancer risk. In all, 3,211 women ages > or =35 years who had a mammogram taken in 1986 to 1989 were followed-up to the end of October 2003, with 111 developing breast cancer during this period. Mammograms were classified using the subjective qualitative Wolfe classification and several quantitative mammographic features measured using computer-based techniques. Breast cancer risk was positively associated with high-grade Wolfe classification, percent breast density and area of dense tissue, and negatively associated with area of lucent tissue, fractal dimension, and lacunarity. Inclusion of the quantitative measures in the same model identified area of dense tissue and lacunarity as the best predictors of breast cancer, with risk increasing by 59% [95% confidence interval (95% CI), 29-94%] per SD increase in total area of dense tissue but declining by 39% (95% CI, 53-22%) per SD increase in lacunarity, after adjusting for each other and for other confounders. Comparison of models that included both the qualitative Wolfe classification and these two quantitative measures to models that included either the qualitative or the two quantitative variables showed that they all made significant contributions to prediction of breast cancer risk. These findings indicate that breast cancer risk is affected not only by the amount of mammographic density but also by the degree of heterogeneity of the parenchymal pattern and, presumably, by other features captured by the Wolfe classification.

  3. Estrogen switches pure mucinous breast cancer to invasive lobular carcinoma with mucinous features.

    PubMed

    Jambal, Purevsuren; Badtke, Melanie M; Harrell, J Chuck; Borges, Virginia F; Post, Miriam D; Sollender, Grace E; Spillman, Monique A; Horwitz, Kathryn B; Jacobsen, Britta M

    2013-01-01

    Mucinous breast cancer (MBC) is mainly a disease of postmenopausal women. Pure MBC is rare and augurs a good prognosis. In contrast, MBC mixed with other histological subtypes of invasive disease loses the more favorable prognosis. Because of the relative rarity of pure MBC, little is known about its cell and tumor biology and relationship to invasive disease of other subtypes. We have now developed a human breast cancer cell line called BCK4, in which we can control the behavior of MBC. BCK4 cells were derived from a patient whose poorly differentiated primary tumor was treated with chemotherapy, radiation and tamoxifen. Malignant cells from a recurrent pleural effusion were xenografted in mammary glands of a nude mouse. Cells from the solid tumor xenograft were propagated in culture to generate the BCK4 cell line. Multiple marker and chromosome analyses demonstrate that BCK4 cells are human, near diploid and luminal, expressing functional estrogen, androgen, and progesterone receptors. When xenografted back into immunocompromised cycling mice, BCK4 cells grow into small pure MBC. However, if mice are supplemented with continuous estradiol, tumors switch to invasive lobular carcinoma (ILC) with mucinous features (mixed MBC), and growth is markedly accelerated. Tamoxifen prevents the expansion of this more invasive component. The unexpected ability of estrogens to convert pure MBC into mixed MBC with ILC may explain the rarity of the pure disease in premenopausal women. These studies show that MBC can be derived from lobular precursors and that BCK4 cells are new, unique models to study the phenotypic plasticity, hormonal regulation, optimal therapeutic interventions, and metastatic patterns of MBC.

  4. Surgical treatment of microinvasive cervical cancer: analysis of pathologic features with implications on radicality.

    PubMed

    Yoneda, Juliana Yoko; Braganca, Joana Froes; Sarian, Luis Otavio; Borba, Patrícia Patury; Conceição, Jose Carlos J; Zeferino, Luiz Carlos

    2015-05-01

    To evaluate pathologic features with implications on surgical radicality in women treated with radical hysterectomy and pelvic lymphadenectomy for cervical cancer stage IA1 with lymph vascular space invasion (LVSI) and stage IA2 by correlating findings in conization and hysterectomy specimens. Women with cervical cancer stage IA1 with LVSI and stage IA2 diagnosed by loop electrosurgical excisional procedure or cold knife conization were treated with radical hysterectomy and pelvic lymphadenectomy from January 1999 to December 2011 in 2 institutions. Fifty patients were enrolled: 40 with stage IA2 and 10 with stage IA1 with LVSI. Median age was 43 (30-67) years. All patients underwent cervical conization for diagnosis (45 loop electrosurgical excisional procedure, 5 cold knife). Lymph vascular space invasion was detected in 15 patients (30%). Two patients had positive pelvic nodes. No parametrial involvement was detected in the entire cohort. Positive margins were present in 35 patients, and residual disease was detected in 22 patients (44%). Positive margins predicted residual disease at radical hysterectomy (P = 0.02). Medium follow-up time was 51 months. One patient developed a pelvic recurrence, and there were no disease-related deaths. Patients with positive margins in cone biopsy specimens have an increased risk of residual disease at radical hysterectomy and require careful evaluation before conservative surgery. Pelvic lymph node evaluation is essential because lymph node metastasis may occur even in early stages. The lack of parametrial invasion in this study reinforces the knowledge that the select group of patients with microinvasive cervical carcinoma stages IA1 LVSI and stage IA2 have a very low risk of parametrial infiltration. Less radical surgery can be carefully considered for these patients.

  5. Variability of Image Features Computed from Conventional and Respiratory-Gated PET/CT Images of Lung Cancer

    PubMed Central

    Oliver, Jasmine A.; Budzevich, Mikalai; Zhang, Geoffrey G.; Dilling, Thomas J.; Latifi, Kujtim; Moros, Eduardo G.

    2015-01-01

    Radiomics is being explored for potential applications in radiation therapy. How various imaging protocols affect quantitative image features is currently a highly active area of research. To assess the variability of image features derived from conventional [three-dimensional (3D)] and respiratory-gated (RG) positron emission tomography (PET)/computed tomography (CT) images of lung cancer patients, image features were computed from 23 lung cancer patients. Both protocols for each patient were acquired during the same imaging session. PET tumor volumes were segmented using an adaptive technique which accounted for background. CT tumor volumes were delineated with a commercial segmentation tool. Using RG PET images, the tumor center of mass motion, length, and rotation were calculated. Fifty-six image features were extracted from all images consisting of shape descriptors, first-order features, and second-order texture features. Overall, 26.6% and 26.2% of total features demonstrated less than 5% difference between 3D and RG protocols for CT and PET, respectively. Between 10 RG phases in PET, 53.4% of features demonstrated percent differences less than 5%. The features with least variability for PET were sphericity, spherical disproportion, entropy (first and second order), sum entropy, information measure of correlation 2, Short Run Emphasis (SRE), Long Run Emphasis (LRE), and Run Percentage (RPC); and those for CT were minimum intensity, mean intensity, Root Mean Square (RMS), Short Run Emphasis (SRE), and RPC. Quantitative analysis using a 3D acquisition versus RG acquisition (to reduce the effects of motion) provided notably different image feature values. This study suggests that the variability between 3D and RG features is mainly due to the impact of respiratory motion. PMID:26692535

  6. Flow cytometric DNA hypertetraploidy is associated with unfavourable prognostic features in breast cancer.

    PubMed Central

    Pinto, A E; André, S; Nogueira, M; Mendonça, E; Soares, J

    1997-01-01

    AIM: Breast tumours with a DNA content higher than 4N (hypertetraploidy) are not well characterised. The aim of this study was to evaluate the clinical and biological characteristics of 51 hypertetraploid breast carcinomas selected from a series of 860 consecutive cases analysed by flow cytometry. METHODS: The clinicopathological characteristics of the hypertetraploid group were compared with those of a control group of 138 non-hypertetraploid breast carcinomas. Breast tumours from patients submitted to surgery as primary therapeutic approach (15 hypertetraploid and the 138 non-hypertetraploid) were TNM staged and classified according to the histological type and grade. The remaining 36 patients had advanced neoplastic disease at presentation and were classified by cytological criteria only. DNA flow cytometric analysis was performed on fresh-frozen samples stained with propidium iodide. Hormone receptors were analysed by immunocytochemistry. RESULTS: The incidence of hypertetraploid breast tumours was 5.9% (51 of 860). All the patients were women and the mean age at diagnosis was 65 years. There was a family history of breast cancer in 21.6% of cases. In the group of operated patients, 33.3% had pT3 tumours and 53.3% had axillary lymph node metastases. All but one tumour were invasive ductal carcinomas; the remaining was an invasive papillary carcinoma. Ten (66.7%) tumours were classified as poorly differentiated carcinomas. Oestrogen and progesterone receptors were negative in 33 (64.7%) and 38 (74.5%) tumours, respectively. At last follow up, 35 (72.9%) patients were alive, while 13 (27.1%) died of disease within three years of diagnosis. Statistical comparison of the clinicopathological features of hypertetraploid v non-hypertetraploid breast carcinomas yielded a significant difference in tumour size (p < 0.001), histological grade (p < 0.001), hormone receptor status (p < 0.001), and overall survival (p < 0.001) between the two groups. CONCLUSION: Flow

  7. Clinicopathological features and outcomes in patients undergoing radical resection for early gastric cancer with signet ring cell histology.

    PubMed

    Wang, Z; Zhang, X; Hu, J; Zeng, W; Zhou, Z

    2015-12-01

    The signet ring cell histology is regarded as an independent predictor of poor prognosis in advanced gastric adenocarcinomas, but its biologic behavior in early gastric cancer remains highly controversial. Our objective was to compare the clinicopathological features and outcomes in patients undergoing curative resection between SRCs and non-SRCs histologic types of early gastric cancer. Clinicopathologic features and the overall survival rates of 334 patients with early gastric cancer undergoing D2 curative resection from January 1994 to December 2008 were retrospectively reviewed and compared according to the histologic type. Clinicopathologic features were comparable between two groups, except age, ulcer findings and the presence of lymph node metastasis. The incidence of recurrence for SRCs group was significantly lower than that for non-SRCs group (10.4% vs. 19.6%; P<0.05). The overall 5-year survival rate was 88.6% in all cases. The overall survival rate of patients in SRCs group was significantly better than that of patients in non-SRCs group (5-year survival, 93.9% vs. 85.8%; P=0.027). Multivariable analysis revealed that SRCs subtype, lymphovascular invasion, and lymph node metastasis were independent prognostic factors. Our analysis revealed that the biological behavior of SRCs was different from other undifferentiated cancer histologic subtypes in early stage. Early gastric cancer with signet ring cell histology had low incidence of lymph node metastasis and a relatively favorable prognosis. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  8. Predicting and replacing the pathological Gleason grade with automated gland ring morphometric features from immunofluorescent prostate cancer images.

    PubMed

    Khan, Faisal M; Scott, Richard; Donovan, Michael; Fernandez, Gerardo

    2017-04-01

    The Gleason grade is the most common architectural and morphological assessment of prostate cancer severity and prognosis. There have been numerous algorithms developed to approximate and duplicate the Gleason scoring system, mostly developed in standard H&E brightfield microscopy. Immunofluorescence (IF) image analysis of tissue pathology has recently been proven to be robust in developing prognostic assessments of disease, particularly in prostate cancer. We leverage a method of segmenting gland rings in IF images for predicting the pathological Gleason, both the clinical and the image specific grades, which may not necessarily be the same. We combine these measures with nuclear specific characteristics. In 324 images from 324 patients, our individual features correlate well univariately with the Gleason grades and in a multivariate setting have an accuracy of 85% in predicting the Gleason grade. Additionally, these features correlate strongly with clinical progression outcomes [concordance index (CI) of 0.89], significantly outperforming the clinical Gleason grades (CI of 0.78). Finally, in multivariate models for multiple prostate cancer progression endpoints, replacing the Gleason with these features results in equivalent or improved performances. This work presents the first assessment of morphological gland unit features from IF images for predicting the Gleason grade, and even replacing it in prostate cancer prognostics.

  9. Long-term exposure of MCF-7 breast cancer cells to ethanol stimulates oncogenic features

    PubMed Central

    Gelfand, Robert; Vernet, Dolores; Bruhn, Kevin W.; Sarkissyan, Suren; Heber, David; Vadgama, Jaydutt V.; Gonzalez-Cadavid, Nestor F.

    2017-01-01

    Alcohol consumption is a risk factor for breast cancer. Little is known regarding the mechanism, although it is assumed that acetaldehyde or estrogen mediated pathways play a role. We previously showed that long-term exposure to 2.5 mM ethanol (blood alcohol ~0.012%) of MCF-12A, a human normal epithelial breast cell line, induced epithelial mesenchymal transition (EMT) and oncogenic transformation. In this study, we investigated in the human breast cancer cell line MCF-7, whether a similar exposure to ethanol at concentrations ranging up to peak blood levels in heavy drinkers would increase malignant progression. Short-term (1-week) incubation to ethanol at as low as 1–5 mM (corresponding to blood alcohol concentration of ~0.0048–0.024%) upregulated the stem cell related proteins Oct4 and Nanog, but they were reduced after exposure at 25 mM. Long-term (4-week) exposure to 25 mM ethanol upregulated the Oct4 and Nanog proteins, as well as the malignancy marker Ceacam6. DNA microarray analysis in cells exposed for 1 week showed upregulated expression of metallothionein genes, particularly MT1X. Long-term exposure upregulated expression of some malignancy related genes (STEAP4, SERPINA3, SAMD9, GDF15, KRT15, ITGB6, TP63, and PGR, as well as the CEACAM, interferon related, and HLA gene families). Some of these findings were validated by RT-PCR. A similar treatment also modulated numerous microRNAs (miRs) including one regulator of Oct4 as well as miRs involved in oncogenesis and/or malignancy, with only a few estrogen-induced miRs. Long-term 25 mM ethanol also induced a 5.6-fold upregulation of anchorage-independent growth, an indicator of malignant-like features. Exposure to acetaldehyde resulted in little or no effect comparable to that of ethanol. The previously shown alcohol induction of oncogenic transformation of normal breast cells is now complemented by the current results suggesting alcohol's potential involvement in malignant progression of breast cancer

  10. Postoperative oligo-recurrence of non-small-cell lung cancer: clinical features and survival†.

    PubMed

    Hishida, Tomoyuki; Yoshida, Junji; Aokage, Keiju; Nagai, Kanji; Tsuboi, Masahiro

    2016-03-01

    Postoperative recurrences of non-small-cell lung cancer (NSCLC) are usually disseminated and systemic. Recently, the concept of oligo-recurrence, which is theoretically curable by definitive local therapy (DLT), has been proposed in several cancers. The aim of this study was to clarify clinical features and outcomes of patients with postoperative oligo-recurrence of NSCLC. From 3275 patients with resected pathological stage IA-IIIB NSCLC between 1993 and 2011, a total of 768 patients who developed recurrence were included in this study. Oligo-recurrence was defined as 1-3 loco-regional or distant recurrent lesions restricted to a single organ. Other recurrences were classified as poly-recurrence. Second primary lung cancers and suspected lesions were excluded. DLT included surgery, stereotactic radiotherapy and radiotherapy with a 45 Gy or higher dose, performed with curative intent. Oligo-recurrence was identified in 162 (21%) patients, mainly as a solitary recurrence (n = 129, 80%) in regional lymph nodes, brain, lung, bone and adrenal gland, and the proportion of patients with oligo-recurrence increased gradually year by year. The patients with oligo-recurrence had more early-staged disease at initial surgery and a longer time to recurrence than those with poly-recurrence. The entire population of oligo-recurrence patients had better post-recurrence survival (PRS) than those with poly-recurrence (5-year PRS: 32.9 vs 9.9%, P < 0.001). For oligo-recurrence, DLT was totally conducted in 105 (65%) patients as initial treatment. Multivariate analyses revealed that the initial DLT was associated with improved PRS [odds ratio (OR) 0.44; 95% confidence interval (CI) 0.29-0.68]. The recurrence location and initial pathological stage did not affect PRS. The 5-year PRS and postoperative progression-free survival rates after DLT were 38.6 and 22.3%, respectively. Of the 10 long-term (≥5-year) progression-free survivors, 9 were those with a solitary recurrence. Initial DLT

  11. Long-term exposure of MCF-7 breast cancer cells to ethanol stimulates oncogenic features.

    PubMed

    Gelfand, Robert; Vernet, Dolores; Bruhn, Kevin W; Sarkissyan, Suren; Heber, David; Vadgama, Jaydutt V; Gonzalez-Cadavid, Nestor F

    2017-01-01

    Alcohol consumption is a risk factor for breast cancer. Little is known regarding the mechanism, although it is assumed that acetaldehyde or estrogen mediated pathways play a role. We previously showed that long-term exposure to 2.5 mM ethanol (blood alcohol ~0.012%) of MCF-12A, a human normal epithelial breast cell line, induced epithelial mesenchymal transition (EMT) and oncogenic transformation. In this study, we investigated in the human breast cancer cell line MCF-7, whether a similar exposure to ethanol at concentrations ranging up to peak blood levels in heavy drinkers would increase malignant progression. Short-term (1-week) incubation to ethanol at as low as 1-5 mM (corresponding to blood alcohol concentration of ~0.0048-0.024%) upregulated the stem cell related proteins Oct4 and Nanog, but they were reduced after exposure at 25 mM. Long-term (4-week) exposure to 25 mM ethanol upregulated the Oct4 and Nanog proteins, as well as the malignancy marker Ceacam6. DNA microarray analysis in cells exposed for 1 week showed upregulated expression of metallothionein genes, particularly MT1X. Long-term exposure upregulated expression of some malignancy related genes (STEAP4, SERPINA3, SAMD9, GDF15, KRT15, ITGB6, TP63, and PGR, as well as the CEACAM, interferon related, and HLA gene families). Some of these findings were validated by RT-PCR. A similar treatment also modulated numerous microRNAs (miRs) including one regulator of Oct4 as well as miRs involved in oncogenesis and/or malignancy, with only a few estrogen-induced miRs. Long-term 25 mM ethanol also induced a 5.6-fold upregulation of anchorage-independent growth, an indicator of malignant-like features. Exposure to acetaldehyde resulted in little or no effect comparable to that of ethanol. The previously shown alcohol induction of oncogenic transformation of normal breast cells is now complemented by the current results suggesting alcohol's potential involvement in malignant progression of breast cancer.

  12. Clinical presentation features of testicular cancer in public hospitals in the Autonomous Community of Madrid, Spain.

    PubMed

    Moreno, A; Domínguez, A; Alpuente, C; Hernándo, A; Torres, J; Cabrera, J A

    2015-01-01

    To study the clinical features of the patients with germ cell tumor of testis in the Autonomous Community of Madrid, emphasizing on the different treatments used. Retrospective analysis of 536 patients with testicular cancer who were obtained from the Community of Madrid cancer registry, during a follow-up period of 15 years (1991-2010). Data analysis has been performed using SPSS 15.0 for Windows. Chi-square test has been used to determine possible relationships among variables. The level of significance was p ≤ 0.05 RESULTS: An increase in the incidence rate has been detected along study period. Mean age was 33.6±13.6 years. 89.7% of cases were germ cells tumors (46% seminoma and 43.6% nonseminomatous germ cell tumor [NSGCT]) and other histologic subtypes the remaining 10.3% of cases. 74% of patients were diagnosed with stage I disease, 8.2% with stage II and 16.2% with stage III; 54.3% of patients were treated with surgery plus adjuvant chemotherapy and in 5.6% of patients the treatment was surgery plus adjuvant radiotherapy. Surgery alone was used in 27.4% of cases: in 32.7% of stage I tumors, 13.6% of stage II and 9.2% of stage III. Radiotherapy was prescribed in 10% of stage I tumors, in 9% of stage II and in 3.4% of stage III. For the seminomas: the surgery-chemotherapy association was used in 49.8 of cases, surgery alone in 30% and surgery plus radiotherapy in 16.6% of cases. For the NSGCT, surgery plus chemotherapy was used in 70.5% of patients, surgery alone in 23.5% and surgery-radiotherapy association in 0.8% of cases. Testicular cancer incidence is increasing. Adjuvant chemotherapy is the treatment used most frequently in the more advanced stages of both seminomas and NSGCT. The tendency to reduce the use of radiotherapy in the treatment of seminoma was confirmed. Copyright © 2014 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

  13. Unique metabolic features of pancreatic cancer stroma: relevance to the tumor compartment, prognosis, and invasive potential

    PubMed Central

    Knudsen, Erik S.; Balaji, Uthra; Freinkman, Elizaveta; McCue, Peter; Witkiewicz, Agnieszka K.

    2016-01-01

    Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis. The aggressiveness and therapeutic recalcitrance of this malignancy has been attributed to multiple factors including the influence of an active desmoplastic stroma. How the stromal microenvironment of PDAC contributes to the fatal nature of this disease is not well defined. In the analysis of clinical specimens, we observed diverse expression of the hypoxic marker carbonic anhydrase IX and the lactate transporter MCT4 in the stromal compartment. These stromal features were associated with the epithelial to mesenchymal phenotype in PDAC tumor cells, and with shorter patient survival. Cultured cancer-associated fibroblasts (CAFs) derived from primary PDAC exhibited a high basal level of hypoxia inducible factor 1a (HIF1α) that was both required and sufficient to modulate the expression of MCT4. This event was associated with increased transcription and protein synthesis of HIF1α in CAFs relative to PDAC cell lines, while surprisingly the protein turnover rate was equivalent. CAFs utilized glucose predominantly for glycolytic intermediates, whereas glutamine was the preferred metabolite for the TCA cycle. Unlike PDAC cell lines, CAFs were resistant to glucose withdrawal but sensitive to glutamine depletion. Consistent with the lack of reliance on glucose, CAFs could survive the acute depletion of MCT4. In co-culture and xenograft studies CAFs stimulated the invasive potential and metastatic spread of PDAC cell lines through a mechanism dependent on HIF1α and MCT4. Together, these data indicate that stromal metabolic features influence PDAC tumor cells to promote invasiveness and metastatic potential and associate with poor outcome in patients with PDAC. PMID:27623078

  14. Mutation spectrum of TP53 gene predicts clinicopathological features and survival of gastric cancer

    PubMed Central

    Tahara, Tomomitsu; Shibata, Tomoyuki; Okamoto, Yasuyuki; Yamazaki, Jumpei; Kawamura, Tomohiko; Horiguchi, Noriyuki; Okubo, Masaaki; Nakano, Naoko; Ishizuka, Takamitsu; Nagasaka, Mitsuo; Nakagawa, Yoshihito; Ohmiya, Naoki

    2016-01-01

    Background and aim TP53 gene is frequently mutated in gastric cancer (GC), but the relationship with clinicopathological features and prognosis is conflicting. Here, we screened TP53 mutation spectrum of 214 GC patients in relation to their clinicopathological features and prognosis. Results TP53 nonsilent mutations were detected in 80 cases (37.4%), being frequently occurred as C:G to T:A single nucleotide transitions at 5′-CpG-3′ sites. TP53 mutations occurred more frequently in differentiated histologic type than in undifferentiated type in the early stage (48.6% vs. 7%, P=0.0006), while the mutations correlated with venous invasion among advanced stage (47.7% vs. 20.7%, P=0.04). Subset of GC with TP53 hot spot mutations (R175, G245, R248, R273, R282) presented significantly worse overall survival and recurrence free survival compared to others (both P=0.001). Methods Matched biopsies from GC and adjacent tissues from 214 patients were used for the experiment. All coding regions of TP53 gene (exon2 to exon11) were examined using Sanger sequencing. Conclusion Our data suggest that GC with TP53 mutations seems to develop as differentiated histologic type and show aggressive biological behavior such as venous invasion. Moreover, our data emphasizes the importance of discriminating TP53 hot spot mutations (R175, G245, R248, R273, R282) to predict worse overall survival and recurrence free survival of GC patients. PMID:27323394

  15. Pathologic features of breast cancer associated with complete response to neoadjuvant chemotherapy: importance of tumor necrosis.

    PubMed

    Pu, Robert T; Schott, Anne F; Sturtz, David E; Griffith, Kent A; Kleer, Celina G

    2005-03-01

    Breast cancer patients with a complete pathologic response after neoadjuvant chemotherapy have a better prognosis than incomplete responders. The predictive value of the histologic characteristics of the tumor prior to neoadjuvant treatment has not been well defined, and there are no guidelines for reporting tumor characteristics in the core biopsy report. Histologic and nuclear grades, presence of tumor necrosis and angiolymphatic invasion (ALI), and estrogen receptor (ER), progesterone receptor (PR), and HER-2/neu expression were assessed in core biopsies of 55 patients with invasive carcinomas. Patients were then uniformly treated with four cycles of doxorubicin/docetaxel followed by excisions and lymph node dissections. Complete pathologic response (pCR) was defined as having no invasive carcinoma at excision. Noncomplete pathologic response was defined as having invasive carcinoma at excision. Five of the 55 patients (9%) achieved pCR. Of the 5 complete responders, 4 (80%) had tumor necrosis in the core biopsy specimens, while only 8 of the 46 (17%) noncomplete responders (pNR) had this feature (P = 0.0086). Higher histologic and nuclear grades, ER, PR status, and HER-2/neu overexpression were not associated with pCR. The presence of ALI in the core biopsy, post-therapy excision, or both was associated with axillary lymph node metastases (P = 0.0062, P = 0.0249, and P = 0.0021, respectively). Although preliminary, our study suggests that the presence of tumor necrosis and ALI in the core biopsy may be important features to be included in the standard report.

  16. Epidermal growth factor receptor gene polymorphisms are associated with prognostic features of breast cancer

    PubMed Central

    2014-01-01

    Background The epidermal growth factor receptor (EGFR) is differently expressed in breast cancer, and its presence may favor cancer progression. We hypothesized that two EGFR functional polymorphisms, a (CA)n repeat in intron 1, and a single nucleotide polymorphism, R497K, may affect EGFR expression and breast cancer clinical profile. Methods The study population consisted of 508 Brazilian women with unilateral breast cancer, and no distant metastases. Patients were genotyped for the (CA)n and R497K polymorphisms, and the associations between (CA)n polymorphism and EGFR transcript levels (n = 129), or between either polymorphism and histopathological features (n = 505) were evaluated. The REMARK criteria of tumor marker evaluation were followed. Results (CA)n lengths ranged from 14 to 24 repeats, comprehending 11 alleles and 37 genotypes. The most frequent allele was (CA)16 (0.43; 95% CI = 0.40–0.46), which was set as the cut-off length to define the Short allele. Variant (CA)n genotypes had no significant effect in tumoral EGFR mRNA levels, but patients with two (CA)n Long alleles showed lower chances of being negative for progesterone receptor (ORadjusted = 0.42; 95% CI = 0.19–0.91). The evaluation of R497K polymorphism indicated a frequency of 0.21 (95% CI = 0.19 – 0.24) for the variant (Lys) allele. Patients with variant R497K genotypes presented lower proportion of worse lymph node status (pN2 or pN3) when compared to the reference genotype Arg/Arg (ORadjusted = 0.32; 95% CI = 0.17–0.59), which resulted in lower tumor staging (ORadjusted = 0.34; 95% CI = 0.19-0.63), and lower estimated recurrence risk (OR = 0.50; 95% CI = 0.30-0.81). The combined presence of both EGFR polymorphisms (Lys allele of R497K and Long/Long (CA)n) resulted in lower TNM status (ORadjusted = 0.22; 95% CI = 0.07-0.75) and lower ERR (OR = 0.25; 95% CI = 0.09-0.71). When tumors were stratified according to biological

  17. Clinical features of kidney cancer in primary care: a case-control study using primary care records

    PubMed Central

    Shephard, Elizabeth; Neal, Richard; Rose, Peter; Walter, Fiona; Hamilton, William T

    2013-01-01

    Background Kidney cancer accounts for over 4000 UK deaths annually, and is one of the cancer sites with a poor mortality record compared with Europe. Aim To identify and quantify all clinical features of kidney cancer in primary care. Design Case-control study, using General Practice Research Database records. Method A total of 3149 patients aged ≥40 years, diagnosed with kidney cancer between 2000 and 2009, and 14 091 age, sex and practice-matched controls, were selected. Clinical features associated with kidney cancer were identified, and analysed using conditional logistic regression. Positive predictive values for features of kidney cancer were estimated. Results Cases consulted more frequently than controls in the year before diagnosis: median 16 consultations (interquartile range 10–25) versus 8 (4–15): P<0.001. Fifteen features were independently associated with kidney cancer: visible haematuria, odds ratio 37 (95% confidence interval [CI] = 28 to 49), abdominal pain 2.8 (95% CI = 2.4 to 3.4), microcytosis 2.6 (95% CI = 1.9 to 3.4), raised inflammatory markers 2.4 (95% CI = 2.1 to 2.8), thrombocytosis 2.2 (95% CI = 1.7 to 2.7), low haemoglobin 1.9 (95% CI = 1.6 to 2.2), urinary tract infection 1.8 (95% CI = 1.5 to 2.1), nausea 1.8 (95% CI = 1.4 to 2.3), raised creatinine 1.7 (95% CI = 1.5 to 2.0), leukocytosis 1.5 (95% CI = 1.2 to 1.9), fatigue 1.5 (95% CI = 1.2 to 1.9), constipation 1.4 (95% CI = 1.1 to 1.7), back pain 1.4 (95% CI = 1.2 to 1.7), abnormal liver function 1.3 (95% CI = 1.2 to 1.5), and raised blood sugar 1.2 (95% CI = 1.1 to 1.4). The positive predictive value for visible haematuria in patients aged ≥60 years was 1.0% (95% CI = 0.8 to 1.3). Conclusion Visible haematuria is the commonest and most powerful single predictor of kidney cancer, and the risk rises when additional symptoms are present. When considered alongside the risk of bladder cancer, the overall risk of urinary tract cancer from haematuria warrants referral. PMID:23540481

  18. Induction of CaSR expression circumvents the molecular features of malignant CaSR null colon cancer cells.

    PubMed

    Singh, Navneet; Chakrabarty, Subhas

    2013-11-15

    We recently reported on the isolation and characterization of calcium sensing receptor (CaSR) null human colon cancer cells (Singh et al., Int J Cancer 2013; 132: 1996-2005). CaSR null cells possess a myriad of molecular features that are linked to a highly malignant and drug resistant phenotype of colon cancer. The CaSR null phenotype can be maintained in defined human embryonic stem cell culture medium. We now show that the CaSR null cells can be induced to differentiate in conventional culture medium, regained the expression of CaSR with a concurrent reversal of the cellular and molecular features associated with the null phenotype. These features include cellular morphology, expression of colon cancer stem cell markers, expression of survivin and thymidylate synthase and sensitivity to fluorouracil. Other features include the expression of epithelial mesenchymal transition linked molecules and transcription factors, oncogenic miRNAs and tumor suppressive molecule and miRNA. With the exception of cancer stem cell markers, the reversal of molecular features, upon the induction of CaSR expression, is directly linked to the expression and function of CaSR because blocking CaSR induction by shRNA circumvented such reversal. We further report that methylation and demethylation of the CaSR gene promoter underlie CaSR expression. Due to the malignant nature of the CaSR null cells, inclusion of the CaSR null phenotype in disease management may improve on the mortality of this disease. Because CaSR is a robust promoter of differentiation and mediates its action through diverse mechanisms and pathways, inactivation of CaSR may serve as a new paradigm in colon carcinogenesis.

  19. Reproducibility of quantitative high-throughput BI-RADS features extracted from ultrasound images of breast cancer.

    PubMed

    Hu, Yuzhou; Qiao, Mengyun; Guo, Yi; Wang, Yuanyuan; Yu, Jinhua; Li, Jiawei; Chang, Cai

    2017-07-01

    Digital Breast Imaging Reporting and Data System (BI-RADS) features extracted from ultrasound images are essential in computer-aided diagnosis, prediction, and prognosis of breast cancer. This study focuses on the reproducibility of quantitative high-throughput BI-RADS features in the presence of variations due to different segmentation results, various ultrasound machine models, and multiple ultrasound machine settings. Dataset 1 consists of 399 patients with invasive breast cancer and is used as the training set to measure the reproducibility of features, while dataset 2 consists of 138 other patients and is a validation set used to evaluate the diagnosis performances of the final reproducible features. Four hundred and sixty high-throughput BI-RADS features are designed and quantized according to BI-RADS lexicon. Concordance Correlation Coefficient (CCC) and Deviation (Dev) are used to assess the effect of the segmentation methods and Between-class Distance (BD) is used to study the influences of the machine models. In addition, the features jointly shared by two methodologies are further investigated on their effects with multiple machine settings. Subsequently, the absolute value of Pearson Correlation Coefficient (Rabs ) is applied for redundancy elimination. Finally, the features that are reproducible and not redundant are preserved as the stable feature set. A 10-fold Support Vector Machine (SVM) classifier is employed to verify the diagnostic ability. One hundred and fifty-three features were found to have high reproducibility (CCC > 0.9 & Dev < 0.1) within the manual and automatic segmentation. Three hundred and thirty-nine features were stable (BD < 0.2) at different machine models. Two feature sets shared the same 102 features, in which nine features were highly sensitive to the machine settings. Forty-six features were finally preserved after redundancy elimination. For the validation in dataset 2, the area under curve (AUC) of the 10-fold SVM

  20. Computed tomographic features predictive of local recurrence in patients with early stage lung cancer treated with stereotactic body radiation therapy.

    PubMed

    Halpenny, Darragh; Ridge, Carole A; Hayes, Sara; Zheng, Junting; Moskowitz, Chaya S; Rimner, Andreas; Ginsberg, Michelle S

    2015-01-01

    The objective of this study is to identify computed tomography (CT) features of local recurrence (LR) after stereotactic body radiation therapy (SBRT) for lung cancer. Two hundred eighteen patients underwent SBRT for lung cancer from January 1st, 2006 to March 1st, 2011. Signs of LR recorded: opacity with new bulging margin, opacification of air bronchograms, enlarging pleural effusion, new or enlarging mass, and increased lung density at the treatment site. A new bulging margin at the treatment site was the only feature significantly associated with LR (P<.005). Most CT features classically associated with LR following conventional radiation therapy are unreliable for predicting LR following SBRT. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Comparative Analysis of Clinicopathologic Features of, Treatment in, and Survival of Americans with Lung or Bronchial Cancer

    PubMed Central

    Li, Dan; Du, Xianglin L.; Ren, Yinghong; Liu, Peijun; Li, Shuting; Yang, Jiao; Lv, Meng; Chen, Ling; Wang, Xin; Li, Enxiao; Yang, Jin; Yi, Min

    2016-01-01

    Ethnic disparities in lung and bronchial cancer diagnoses and disease-specific survival (DSS) rates in the United States are well known. However, few studies have specifically assessed these differences in Asian subgroups. The primary objectives of the retrospective analysis described herein were to identify any significant differences in clinicopathologic features, treatment, and survival rate between Asian lung cancer patients and lung cancer patients in other broad ethnic groups in the United States and to determine the reasons for these differences among subgroups of Asian patients with lung or bronchial cancer. We searched the Surveillance, Epidemiology, and End Results Program database to identify patients diagnosed with lung or bronchial cancer from 1990 to 2012. Differences in clinicopathologic features, treatment, and DSS rate in four broad ethnic groups and eight Asian subgroups were compared. The study population consisted of 849,088 patients, 5.2% of whom were of Asian descent. Female Asian patients had the lowest lung and bronchial cancer incidence rates, whereas male black patients had the highest rates. Asian patients had the best 5-year DSS rate. In our Asian subgroup analysis, Indian/Pakistani patients had the best 5-year DSS rate, whereas Hawaiian/Pacific Islander patients had the worst 5-year DSS rates. We found the differences in DSS rate among the four broad ethnic groups and eight Asian subgroups when we grouped patients by age and disease stage, as well. Asian patients had better DSS rates than those in the other three broad ethnic groups in almost every age and disease-stage group, especially in older patients and those with advanced-stage disease. In conclusion, we found that clinicopathologic features and treatment of lung and bronchial cancer differ by ethnicity in the United States, and the differences impact survival in each ethnic group. PMID:27244238

  2. Transcriptional coexpression network reveals the involvement of varying stem cell features with different dysregulations in different gastric cancer subtypes.

    PubMed

    Kalamohan, Kalaivani; Periasamy, Jayaprakash; Bhaskar Rao, Divya; Barnabas, Georgina D; Ponnaiyan, Srigayatri; Ganesan, Kumaresan

    2014-10-01

    Despite the advancements in the cancer therapeutics, gastric cancer ranks as the second most common cancers with high global mortality rate. Integrative functional genomic investigation is a powerful approach to understand the major dysregulations and to identify the potential targets toward the development of targeted therapeutics for various cancers. Intestinal and diffuse type gastric tumors remain the major subtypes and the molecular determinants and drivers of these distinct subtypes remain unidentified. In this investigation, by exploring the network of gene coexpression association in gastric tumors, mRNA expressions of 20,318 genes across 200 gastric tumors were categorized into 21 modules. The genes and the hub genes of the modules show gastric cancer subtype specific expression. The expression patterns of the modules were correlated with intestinal and diffuse subtypes as well as with the differentiation status of gastric tumors. Among these, G1 module has been identified as a major driving force of diffuse type gastric tumors with the features of (i) enriched mesenchymal, mesenchymal stem cell like, and mesenchymal derived multiple lineages, (ii) elevated OCT1 mediated transcription, (iii) involvement of Notch activation, and (iv) reduced polycomb mediated epigenetic repression. G13 module has been identified as key factor in intestinal type gastric tumors and found to have the characteristic features of (i) involvement of embryonic stem cell like properties, (ii) Wnt, MYC and E2F mediated transcription programs, and (iii) involvement of polycomb mediated repression. Thus the differential transcription programs, differential epigenetic regulation and varying stem cell features involved in two major subtypes of gastric cancer were delineated by exploring the gene coexpression network. The identified subtype specific dysregulations could be optimally employed in developing subtype specific therapeutic targeting strategies for gastric cancer.

  3. Bilateral image subtraction features for multivariate automated classification of breast cancer risk

    NASA Astrophysics Data System (ADS)

    Celaya-Padilla, Jose M.; Rodriguez-Rojas, Juan; Galván-Tejada, Jorge I.; Martínez-Torteya, Antonio; Treviño, Victor; Tamez-Peña, José G.

    2014-03-01

    Early tumor detection is key in reducing breast cancer deaths and screening mammography is the most widely available method for early detection. However, mammogram interpretation is based on human radiologist, whose radiological skills, experience and workload makes radiological interpretation inconsistent. In an attempt to make mammographic interpretation more consistent, computer aided diagnosis (CADx) systems has been introduced. This paper presents an CADx system aimed to automatically triage normal mammograms form suspicious mammograms. The CADx system co-reregister the left and breast images, then extracts image features from the co-registered mammographic bilateral sets. Finally, an optimal logistic multivariate model is generated by means of an evolutionary search engine. In this study, 440 subjects form the DDSM public data sets were used: 44 normal mammograms, 201 malignant mass mammograms, and 195 mammograms with malignant calci cations. The results showed a cross validation accuracy of 0.88 and an area under receiver operating characteristic (AUC) of 0.89 for the calci cations vs. normal mammograms. The optimal mass vs. normal mammograms model obtained an accuracy of 0.85 and an AUC of 0.88.

  4. BioCAST/IFCT-1002: epidemiological and molecular features of lung cancer in never-smokers.

    PubMed

    Couraud, Sébastien; Souquet, Pierre-Jean; Paris, Christophe; Dô, Pascal; Doubre, Hélène; Pichon, Eric; Dixmier, Adrien; Monnet, Isabelle; Etienne-Mastroianni, Bénédicte; Vincent, Michel; Trédaniel, Jean; Perrichon, Marielle; Foucher, Pascal; Coudert, Bruno; Moro-Sibilot, Denis; Dansin, Eric; Labonne, Stéphanie; Missy, Pascale; Morin, Franck; Blanché, Hélène; Zalcman, Gérard

    2015-05-01

    Lung cancer in never-smokers (LCINS) (fewer than 100 cigarettes in lifetime) is considered as a distinct entity and harbours an original molecular profile. However, the epidemiological and molecular features of LCINS in Europe remain poorly understood. All consecutive newly diagnosed LCINS patients were included in this prospective observational study by 75 participating centres during a 14-month period. Each patient completed a detailed questionnaire about risk factor exposure. Biomarker and pathological analyses were also collected. We report the main descriptive overall results with a focus on sex differences. 384 patients were included: 65 men and 319 women. 66% had been exposed to passive smoking (significantly higher among women). Definite exposure to main occupational carcinogens was significantly higher in men (35% versus 8% in women). A targetable molecular alteration was found in 73% of patients (without any significant sex difference): EGFR in 51%, ALK in 8%, KRAS in 6%, HER2 in 3%, BRAF in 3%, PI3KCA in less than 1%, and multiple in 2%. We present the largest and most comprehensive LCINS analysis in a European population. Physicians should track occupational exposure in men (35%), and a somatic molecular alteration in both sexes (73%). Copyright ©ERS 2015.

  5. Do mammographic tumor features in breast cancer relate to breast density and invasiveness, tumor size, and axillary lymph node involvement?

    PubMed

    Sartor, Hanna; Borgquist, Signe; Hartman, Linda; Olsson, Åsa; Jawdat, Faith; Zackrisson, Sophia

    2015-05-01

    Breast density and mammographic tumor features of breast cancer may carry prognostic information. The potential benefit of using the combined information obtained from breast density, mammographic tumor features, and pathological tumor characteristics has not been extensively studied. To investigate how mammographic tumor features relate to breast density and pathological tumor characteristics. This retrospective study was carried out within the Malmö Diet and Cancer Study: a population-based cohort study recruiting 17,035 women during 1991-1996. A total of 826 incident breast cancers were identified during follow-up. Mammography images were collected and analyzed according to breast density and tumor features at diagnosis. Pathological data were retrieved from medical reports. Mammographic tumor features in relation to invasiveness, tumor size, and axillary lymph node involvement were analyzed using logistic regression yielding odds ratios (OR) with 95% confidence intervals (CI) and adjusted for age at diagnosis, mode of detection, and breast density. Tumors presenting as an ill-defined mass or calcifications were more common in dense breasts than tumors presenting as a distinct mass or with spiculated appearance. Invasive cancer was more common in tumors with spiculated appearance than tumors presenting as a distinct mass (adjusted OR, 5.68 [1.81-17.84]). Among invasive tumors, an ill-defined mass was more often large (>20 mm) compared with a distinct mass, (adjusted OR, 3.16 [1.80-5.55]). Tumors presenting as an ill-defined mass or calcifications were more common in dense breasts. Spiculated appearance was related to invasiveness, and ill-defined mass to larger tumor size, regardless of mode of detection and breast density. The potential role of mammographic tumor features in clinical decision-making warrants further investigation. © The Foundation Acta Radiologica 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  6. Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods

    PubMed Central

    2013-01-01

    Background Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. Results In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. Conclusions The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies. PMID:23725313

  7. Annual Report to the Nation on the Status of Cancer, 1975-2012, featuring the increasing incidence of liver cancer.

    PubMed

    Ryerson, A Blythe; Eheman, Christie R; Altekruse, Sean F; Ward, John W; Jemal, Ahmedin; Sherman, Recinda L; Henley, S Jane; Holtzman, Deborah; Lake, Andrew; Noone, Anne-Michelle; Anderson, Robert N; Ma, Jiemin; Ly, Kathleen N; Cronin, Kathleen A; Penberthy, Lynne; Kohler, Betsy A

    2016-05-01

    Annual updates on cancer occurrence and trends in the United States are provided through an ongoing collaboration among the American Cancer Society (ACS), the Centers for Disease Control and Prevention (CDC), the National Cancer Institute (NCI), and the North American Association of Central Cancer Registries (NAACCR). This annual report highlights the increasing burden of liver and intrahepatic bile duct (liver) cancers. Cancer incidence data were obtained from the CDC, NCI, and NAACCR; data about cancer deaths were obtained from the CDC's National Center for Health Statistics (NCHS). Annual percent changes in incidence and death rates (age-adjusted to the 2000 US Standard Population) for all cancers combined and for the leading cancers among men and women were estimated by joinpoint analysis of long-term trends (incidence for 1992-2012 and mortality for 1975-2012) and short-term trends (2008-2012). In-depth analysis of liver cancer incidence included an age-period-cohort analysis and an incidence-based estimation of person-years of life lost because of the disease. By using NCHS multiple causes of death data, hepatitis C virus (HCV) and liver cancer-associated death rates were examined from 1999 through 2013. Among men and women of all major racial and ethnic groups, death rates continued to decline for all cancers combined and for most cancer sites; the overall cancer death rate (for both sexes combined) decreased by 1.5% per year from 2003 to 2012. Overall, incidence rates decreased among men and remained stable among women from 2003 to 2012. Among both men and women, deaths from liver cancer increased at the highest rate of all cancer sites, and liver cancer incidence rates increased sharply, second only to thyroid cancer. Men had more than twice the incidence rate of liver cancer than women, and rates increased with age for both sexes. Among non-Hispanic (NH) white, NH black, and Hispanic men and women, liver cancer incidence rates were higher for persons born

  8. Examination of autoantibody status and clinical features that associate with cancer risk and cancer-associated scleroderma

    PubMed Central

    Shah, Ami A.; Hummers, Laura K.; Casciola-Rosen, Livia; Visvanathan, Kala; Rosen, Antony; Wigley, Fredrick M.

    2015-01-01

    Introduction We previously reported a contemporaneous onset of cancer and scleroderma in patients with RNA polymerase III (pol) antibodies and identified a biological link between cancer and scleroderma. This investigation was designed to further evaluate whether autoantibody status and other characteristics associate with cancer and a clustering of cancer with scleroderma onset. Methods Logistic regression analysis was performed to assess the relationship between two outcomes, cancer (model-1) and a close (±2 years) cancer-scleroderma interval (model-2), as a function of autoantibody status and scleroderma covariates. Results Of 1044 scleroderma patients, 168 (16.1%) had cancer. In the adjusted model-1, only older age at scleroderma onset (OR 1.04, 95% CI 1.02,1.05) and white race (OR 2.71, 95% CI 1.22,6.04) were significantly associated with cancer risk overall. In the adjusted model-2, only pol positivity (OR 5.08; 95% CI 1.60,16.1) and older age at scleroderma onset (OR 1.04; 95% CI 1.00,1.08) were significantly associated with a close cancer-scleroderma interval. While pol was associated with a short cancer-scleroderma interval independent of age of scleroderma onset, the cancer-scleroderma interval shortened with older age at scleroderma onset in other antibody groups (Spearman’s p<0.05), particularly among patients with anti-topoisomerase-1 (topo) and patients negative for centromere, topoisomerase-1 and pol antibodies. Conclusions Increased age at scleroderma onset is strongly associated with cancer risk overall. While pol status is an independent marker of coincident cancer and scleroderma at any age, a clustering of cancer with scleroderma is also seen in patients developing scleroderma at older ages with topo and other autoantibody specificities. PMID:25605296

  9. Interaction-Based Feature Selection for Uncovering Cancer Driver Genes Through Copy Number-Driven Expression Level.

    PubMed

    Park, Heewon; Niida, Atsushi; Imoto, Seiya; Miyano, Satoru

    2017-02-01

    Driver gene selection is crucial to understand the heterogeneous system of cancer. To identity cancer driver genes, various statistical strategies have been proposed, especially the L1-type regularization methods have drawn a large amount of attention. However, the statistical approaches have been developed purely from algorithmic and statistical point, and the existing studies have applied the statistical approaches to genomic data analysis without consideration of biological knowledge. We consider a statistical strategy incorporating biological knowledge to identify cancer driver gene. The alterations of copy number have been considered to driver cancer pathogenesis processes, and the region of strong interaction of copy number alterations and expression levels was known as a tumor-related symptom. We incorporate the influence of copy number alterations on expression levels to cancer driver gene-selection processes. To quantify the dependence of copy number alterations on expression levels, we consider [Formula: see text] and [Formula: see text] effects of copy number alterations on expression levels of genes, and incorporate the symptom of tumor pathogenesis to gene-selection procedures. We then proposed an interaction-based feature-selection strategy based on the adaptive L1-type regularization and random lasso procedures. The proposed method imposes a large amount of penalty on genes corresponding to a low dependency of the two features, thus the coefficients of the genes are estimated to be small or exactly 0. It implies that the proposed method can provide biologically relevant results in cancer driver gene selection. Monte Carlo simulations and analysis of the Cancer Genome Atlas (TCGA) data show that the proposed strategy is effective for high-dimensional genomic data analysis. Furthermore, the proposed method provides reliable and biologically relevant results for cancer driver gene selection in TCGA data analysis.

  10. Annual Report to the Nation on the Status of Cancer, 1975–2012, Featuring the Increasing Incidence of Liver Cancer

    PubMed Central

    Ryerson, A. Blythe; Eheman, Christie R.; Altekruse, Sean F.; Ward, John W.; Jemal, Ahmedin; Sherman, Recinda L.; Henley, S. Jane; Holtzman, Deborah; Lake, Andrew; Noone, Anne-Michelle; Anderson, Robert N.; Ma, Jiemin; Ly, Kathleen N.; Cronin, Kathleen A.; Penberthy, Lynne; Kohler, Betsy A.

    2016-01-01

    BACKGROUND Annual updates on cancer occurrence and trends in the United States are provided through an ongoing collaboration among the American Cancer Society (ACS), the Centers for Disease Control and Prevention (CDC), the National Cancer Institute (NCI), and the North American Association of Central Cancer Registries (NAACCR). This annual report highlights the increasing burden of liver and intrahepatic bile duct (liver) cancers. METHODS Cancer incidence data were obtained from the CDC, NCI, and NAACCR; data about cancer deaths were obtained from the CDC’s National Center for Health Statistics (NCHS). Annual percent changes in incidence and death rates (age-adjusted to the 2000 US Standard Population) for all cancers combined and for the leading cancers among men and women were estimated by joinpoint analysis of long-term trends (incidence for 1992–2012 and mortality for 1975–2012) and short-term trends (2008–2012). In-depth analysis of liver cancer incidence included an age-period-cohort analysis and an incidence-based estimation of person-years of life lost because of the disease. By using NCHS multiple causes of death data, hepatitis C virus (HCV) and liver cancer-associated death rates were examined from 1999 through 2013. RESULTS Among men and women of all major racial and ethnic groups, death rates continued to decline for all cancers combined and for most cancer sites; the overall cancer death rate (for both sexes combined) decreased by 1.5% per year from 2003 to 2012. Overall, incidence rates decreased among men and remained stable among women from 2003 to 2012. Among both men and women, deaths from liver cancer increased at the highest rate of all cancer sites, and liver cancer incidence rates increased sharply, second only to thyroid cancer. Men had more than twice the incidence rate of liver cancer than women, and rates increased with age for both sexes. Among non-Hispanic (NH) white, NH black, and Hispanic men and women, liver cancer incidence

  11. Altered glycometabolism affects both clinical features and prognosis of triple-negative and neoadjuvant chemotherapy-treated breast cancer.

    PubMed

    Dong, Tieying; Kang, Xinmei; Liu, Zhaoliang; Zhao, Shu; Ma, Wenjie; Xuan, Qijia; Liu, Hang; Wang, Zhipeng; Zhang, Qingyuan

    2016-06-01

    Glycometabolism is a distinctive aspect of energy metabolism in breast cancer, and key glycometabolism enzymes/pathways (glycolysis, hexosamine biosynthetic pathway, and pentose phosphate pathway) may directly or indirectly affect the clinical features. In this study, we analyzed the particular correlation between the altered glycometabolism and clinical features of breast cancer to instruct research and clinical treatment. Tissue microarrays containing 189 hollow needle aspiration samples and 295 triple-negative breast cancer tissues were used to test the expression of M2 isoform of pyruvate kinase (PKM2), glutamine-fructose-6-phosphate transaminase 1 (GFPT1), glucose-6-phosphate dehydrogenase (G6PD), and p53 by immunohistochemistry and the intensity of these glycometabolism-related protein was evaluated. Chi-square test, Kaplan-Meier estimates, and Cox proportional hazards model were used to analyze the relationship between the expression of these factors and major clinical features. PKM2, GFPT1, and G6PD affect the pathologic complete response rate of neoadjuvant chemotherapy patients in different ways; pyruvate kinase muscle isozyme 2 (PKM2) and G6PD are closely associated with the molecular subtypes, whereas GFPT1 is correlated with cancer size. All these three factors as well as p53 have impacts on the progression-free survival and overall survival of triple-negative breast cancer patients. Cancer size shows significant association with PKM2 and GFPT1 expression, while the pN stage and grade are associated with PKM2 and G6PD expression. Our study support that clinical characteristics are reflections of specific glycometabolism pathways, so their relationships may shed light on the orientation of research or clinical treatment. The expression of PKM2, GFPT1, and G6PD are hazardous factors for prognosis: high expression of these proteins predict worse progression-free survival and overall survival in triple-negative breast cancer, as well as worse pathologic

  12. Radiological characteristics, histological features and clinical outcomes of lung cancer patients with coexistent idiopathic pulmonary fibrosis.

    PubMed

    Khan, K A; Kennedy, M P; Moore, E; Crush, L; Prendeville, S; Maher, M M; Burke, L; Henry, M T

    2015-02-01

    Despite advances in diagnosis and management, the outcomes for both lung cancer and idiopathic pulmonary fibrosis (IPF) are still unfavourable. The pathophysiology and outcomes for patients with concomitant lung cancer and IPF remains unclear. A retrospective analysis was performed of all patients presenting with concomitant IPF and lung cancer to our centre over a 3-year period. Patients with connective tissue disease, asbestos exposure, sarcoidosis, previous thoracic radiation, radiological evidence of fibrosis but no histological confirmation of lung cancer, or the use of medications known to cause pulmonary fibrosis were excluded. We describe clinical, radiological and pathological characteristics of this group. We also report the response to standardized lung cancer therapy in this cohort. Of 637 lung cancer patients, 34 were identified with concomitant IPF (5.3 %) and all were smokers. 85 % had non-small cell lung cancer, 41 % were squamous cell cancers. The majority of tumours were located in the lower lobes, peripheral and present in an area of honeycombing. Despite the fact that approximately 2/3rds of the patients had localised or locally advanced lung cancer, the outcome of therapy for lung cancer was extremely poor regardless of tumour stage or severity of IPF. At our centre, 1/20 patients with lung cancer have concomitant IPF. The majority of these tumours are small in size, peripheral in location and squamous cell carcinoma; in an area of honey combing. The outcome for concomitant lung cancer and IPF regardless of stage or therapy is poor.

  13. Frequency of breast cancer with hereditary risk features in Spain: Analysis from GEICAM "El Álamo III" retrospective study.

    PubMed

    Márquez-Rodas, Iván; Pollán, Marina; Escudero, María José; Ruiz, Amparo; Martín, Miguel; Santaballa, Ana; Martínez Del Prado, Purificación; Batista, Norberto; Andrés, Raquel; Antón, Antonio; Llombart, Antonio; Fernandez Aramburu, Antonio; Adrover, Encarnación; González, Sonia; Seguí, Miguel Angel; Calvo, Lourdes; Lizón, José; Rodríguez Lescure, Álvaro; Ramón Y Cajal, Teresa; Llort, Gemma; Jara, Carlos; Carrasco, Eva; López-Tarruella, Sara

    2017-01-01

    To determine the frequency of breast cancer (BC) patients with hereditary risk features in a wide retrospective cohort of patients in Spain. a retrospective analysis was conducted from 10,638 BC patients diagnosed between 1998 and 2001 in the GEICAM registry "El Álamo III", dividing them into four groups according to modified ESMO and SEOM hereditary cancer risk criteria: Sporadic breast cancer group (R0); Individual risk group (IR); Familial risk group (FR); Individual and familial risk group (IFR) with both individual and familial risk criteria. 7,641 patients were evaluable. Of them, 2,252 patients (29.5%) had at least one hereditary risk criteria, being subclassified in: FR 1.105 (14.5%), IR 970 (12.7%), IFR 177 (2.3%). There was a higher frequency of newly diagnosed metastatic patients in the IR group (5.1% vs 3.2%, p = 0.02). In contrast, in RO were lower proportion of big tumors (> T2) (43.8% vs 47.4%, p = 0.023), nodal involvement (43.4% vs 48.1%, p = 0.004) and lower histological grades (20.9% G3 for the R0 vs 29.8%) when compared to patients with any risk criteria. Almost three out of ten BC patients have at least one hereditary risk cancer feature that would warrant further genetic counseling. Patients with hereditary cancer risk seems to be diagnosed with worse prognosis factors.

  14. An improved survivability prognosis of breast cancer by using sampling and feature selection technique to solve imbalanced patient classification data

    PubMed Central

    2013-01-01

    Background Breast cancer is one of the most critical cancers and is a major cause of cancer death among women. It is essential to know the survivability of the patients in order to ease the decision making process regarding medical treatment and financial preparation. Recently, the breast cancer data sets have been imbalanced (i.e., the number of survival patients outnumbers the number of non-survival patients) whereas the standard classifiers are not applicable for the imbalanced data sets. The methods to improve survivability prognosis of breast cancer need for study. Methods Two well-known five-year prognosis models/classifiers [i.e., logistic regression (LR) and decision tree (DT)] are constructed by combining synthetic minority over-sampling technique (SMOTE) ,cost-sensitive classifier technique (CSC), under-sampling, bagging, and boosting. The feature selection method is used to select relevant variables, while the pruning technique is applied to obtain low information-burden models. These methods are applied on data obtained from the Surveillance, Epidemiology, and End Results database. The improvements of survivability prognosis of breast cancer are investigated based on the experimental results. Results Experimental results confirm that the DT and LR models combined with SMOTE, CSC, and under-sampling generate higher predictive performance consecutively than the original ones. Most of the time, DT and LR models combined with SMOTE and CSC use less informative burden/features when a feature selection method and a pruning technique are applied. Conclusions LR is found to have better statistical power than DT in predicting five-year survivability. CSC is superior to SMOTE, under-sampling, bagging, and boosting to improve the prognostic performance of DT and LR. PMID:24207108

  15. An improved survivability prognosis of breast cancer by using sampling and feature selection technique to solve imbalanced patient classification data.

    PubMed

    Wang, Kung-Jeng; Makond, Bunjira; Wang, Kung-Min

    2013-11-09

    Breast cancer is one of the most critical cancers and is a major cause of cancer death among women. It is essential to know the survivability of the patients in order to ease the decision making process regarding medical treatment and financial preparation. Recently, the breast cancer data sets have been imbalanced (i.e., the number of survival patients outnumbers the number of non-survival patients) whereas the standard classifiers are not applicable for the imbalanced data sets. The methods to improve survivability prognosis of breast cancer need for study. Two well-known five-year prognosis models/classifiers [i.e., logistic regression (LR) and decision tree (DT)] are constructed by combining synthetic minority over-sampling technique (SMOTE), cost-sensitive classifier technique (CSC), under-sampling, bagging, and boosting. The feature selection method is used to select relevant variables, while the pruning technique is applied to obtain low information-burden models. These methods are applied on data obtained from the Surveillance, Epidemiology, and End Results database. The improvements of survivability prognosis of breast cancer are investigated based on the experimental results. Experimental results confirm that the DT and LR models combined with SMOTE, CSC, and under-sampling generate higher predictive performance consecutively than the original ones. Most of the time, DT and LR models combined with SMOTE and CSC use less informative burden/features when a feature selection method and a pruning technique are applied. LR is found to have better statistical power than DT in predicting five-year survivability. CSC is superior to SMOTE, under-sampling, bagging, and boosting to improve the prognostic performance of DT and LR.

  16. Features of Undiagnosed Breast Cancers at Screening Breast MR Imaging and Potential Utility of Computer-Aided Evaluation.

    PubMed

    Seo, Mirinae; Cho, Nariya; Bae, Min Sun; Koo, Hye Ryoung; Kim, Won Hwa; Lee, Su Hyun; Chu, Ajung

    2016-01-01

    To retrospectively evaluate the features of undiagnosed breast cancers on prior screening breast magnetic resonance (MR) images in patients who were subsequently diagnosed with breast cancer, as well as the potential utility of MR-computer-aided evaluation (CAE). Between March 2004 and May 2013, of the 72 consecutive pairs of prior negative MR images and subsequent MR images with diagnosed cancers (median interval, 32.8 months; range, 5.4-104.6 months), 36 (50%) had visible findings (mean size, 1.0 cm; range, 0.3-5.2 cm). The visible findings were divided into either actionable or underthreshold groups by the blinded review by 5 radiologists. MR imaging features, reasons for missed cancer, and MR-CAE features according to actionability were evaluated. Of the 36 visible findings on prior MR images, 33.3% (12 of 36) of the lesions were determined to be actionable and 66.7% (24 of 36) were underthreshold; 85.7% (6 of 7) of masses and 31.6% (6 of 19) of non-mass enhancements were classified as actionable lesions. Mimicking physiologic enhancements (27.8%, 10 of 36) and small lesion size (27.8%, 10 of 36) were the most common reasons for missed cancer. Actionable findings tended to show more washout or plateau kinetic patterns on MR-CAE than underthreshold findings, as the 100% of actionable findings and 46.7% of underthreshold findings showed washout or plateau (p = 0.008). MR-CAE has the potential for reducing the number of undiagnosed breast cancers on screening breast MR images, the majority of which are caused by mimicking physiologic enhancements or small lesion size.

  17. Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties

    PubMed Central

    Wang, Yongcui; Fang, Jianwen; Chen, Shilong

    2016-01-01

    Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell ‘A549_LUNG’ and compound ‘Topotecan’. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails. PMID:27645580

  18. Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties

    NASA Astrophysics Data System (ADS)

    Wang, Yongcui; Fang, Jianwen; Chen, Shilong

    2016-09-01

    Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell ‘A549_LUNG’ and compound ‘Topotecan’. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails.

  19. The role of leptin in gastric cancer: Clinicopathologic features and molecular mechanisms

    SciTech Connect

    Lee, Kang Nyeong; Choi, Ho Soon; Yang, Sun Young; Park, Hyun Ki; Lee, Young Yiul; Lee, Oh Young; Yoon, Byung Chul; Hahm, Joon Soo; Paik, Seung Sam

    2014-04-18

    Highlights: • Leptin and Ob-R are expressed in gastric adenoma and early and advanced cancer. • Leptin is more likely associated with differentiated gastric cancer or cardia cancer. • Leptin proliferates gastric cancer cells via activating the STAT3 and ERK1/2 pathways. - Abstract: Obesity is associated with certain types of cancer, including gastric cancer. However, it is still unclear whether obesity-related cytokine, leptin, is implicated in gastric cancer. Therefore, we aimed to investigate the role of leptin in gastric cancer. The expression of leptin and its receptor, Ob-R, was assessed by immunohistochemical staining and was compared in patients with gastric adenoma (n = 38), early gastric cancer (EGC) (n = 38), and advanced gastric cancer (AGC) (n = 38), as a function of their clinicopathological characteristics. Gastric cancer cell lines were studied to investigate the effects of leptin on the signal transducer and activator of transcription-3 (STAT3) and extracellular receptor kinase 1/2 (ERK1/2) signaling pathways using MTT assays, immunoblotting, and inhibition studies. Leptin was expressed in gastric adenomas (42.1%), EGCs (47.4%), and AGCs (43.4%). Ob-R expression tended to increase from gastric adenoma (2%), through EGC (8%), to AGC (18%). Leptin induced the proliferation of gastric cancer cells by activating STAT3 and ERK1/2 and up-regulating the expression of vascular endothelial growth factor (VEGF). Blocking Ob-R with pharmacological inhibitors and by RNAi decreased both the leptin-induced activation of STAT3 and ERK1/2 and the leptin-induced expression of VEGF. Leptin plays a role in gastric cancer by stimulating the proliferation of gastric cancer cells via activating the STAT3 and ERK1/2 pathways.

  20. Association of DW/DCE-MRI features with prognostic factors in breast cancer.

    PubMed

    Shao, Guoliang; Fan, Linyin; Zhang, Juan; Dai, Gang; Xie, Tieming

    2017-03-02

    Through analyzing apparent diffusion coefficient (ADC) values and morphological evaluations, this research aimed to study how magnetic resonance imaging (MRI)-based breast lesion characteristics can enhance the diagnosis and prognosis of breast cancer. A total of 118 breast lesions, including 50 benign and 68 malignant lesions, from 106 patients were analyzed. All lesions were measured with both diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI. The average ADC of breast lesions was analyzed at b values of 600, 800 and 1,000 s/mm2. Lesion margins, lesion enhancement patterns, and dynamic curves were also investigated. The relations between MRI-based features and molecular prognostic factors were evaluated using Spearman's rank correlation analysis. A b value of 800 s/mm2 was used to distinguish malignant from benign breast lesions, with an ADC cutoff value of 1.365 × 10-3 mm2/s. The average ADC value between invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS) was significantly different. Malignant lesions were more likely to have spiculated margins, heterogeneous enhancement and washout curves. On the other hand, DCIS was more likely to have spiculated margins, heterogeneous/rim enhancement and plateau/washout dynamic curves. A significant negative correlation was found between progesterone receptor (PR) status and dynamic imaging (p = 0.027), while a significant positive correlation was found between Ki-67 status and lesion enhancement (p = 0.045). Both ADC values and MRI morphological assessment could be used to distinguish malignant breast lesions from benign ones.

  1. Clinical, pathological and biological features associated with BRAF mutations in non-small cell lung cancer

    PubMed Central

    Cardarella, Stephanie; Ogino, Atsuko; Nishino, Mizuki; Butaney, Mohit; Shen, Jeanne; Lydon, Christine; Yeap, Beow Y.; Sholl, Lynette M.; Johnson, Bruce E.; Jänne, Pasi A.

    2013-01-01

    Purpose BRAF mutations are found in a subset of non-small cell lung cancers (NSCLCs). We examined the clinical characteristics and treatment outcomes of patients with NSCLC harboring BRAF mutations. Experimental Design Using DNA sequencing, we successfully screened 883 NSCLC patients for BRAF mutations between 7/1/09 and 7/16/12. Baseline characteristics and treatment outcomes were compared between patients with and without BRAF mutations. Wild type controls consisted of NSCLC patients without a somatic alteration in BRAF, KRAS, EGFR, and ALK. In vitro studies assessed the biological properties of selected non-V600E BRAF mutations identified from NSCLC patients. Results Of 883 tumors screened, 36 (4%) harbored BRAF mutations (V600E: 18; non-V600E: 18) and 257 were wild type for BRAF, EGFR, KRAS, and ALK negative. Twenty-nine of the 36 BRAF mutant patients were smokers. There were no distinguishing clinical features between BRAF mutant and wild type patients. Advanced NSCLC patients with BRAF mutations and wild type tumors showed similar response rates and progression-free survival (PFS) to platinum-based combination chemotherapy and no difference in overall survival. Within the BRAF cohort, patients with V600E mutated tumors had a shorter PFS to platinum-based chemotherapy compared to those with non-V600E mutations, although this did not reach statistical significance (4.1 versus 8.9 months; P=0.297). We identified five BRAF mutations not previously reported in NSCLC; two of the five were associated with increased BRAF kinase activity. Conclusions BRAF mutations occur in 4% of NSCLCs and half are non-V600E. Prospective trials are ongoing to validate BRAF as a therapeutic target in NSCLC. PMID:23833300

  2. Lumpectomy with or without postoperative radiotherapy for breast cancer with favourable prognostic features: results of a randomized study

    PubMed Central

    Holli, K; Saaristo, R; Isola, J; Joensuu, H; Hakama, M

    2001-01-01

    The aim of this trial was to study the value of adding post-operative radiotherapy to lumpectomy in a subgroup of breast cancer patients with favourable patient-, tumour-, and treatment-related prognostic features. 152 women aged over 40 with unifocal breast cancer seen in preoperative mammography were randomly assigned to lumpectomy alone (no-XRT group) or to lumpectomy followed by radiotherapy to the ipsilateral breast (50 Gy given within 5 weeks, XRT group). All cancers were required to be invasive node-negative, smaller than 2 cm in diameter and well or moderately differentiated, to contain no extensive intraductal component, to be progesterone receptor-positive, DNA diploid, have S-phase fraction ≤7 and be excised with at least 1 cm margin. During a mean follow-up time of 6.7 years, 13 (18.1%) cancers recurred locally in the no-XRT and 6 (7.5%) in the XRT group (P = 0.03). There was no difference between the groups in the ultimate breast preservation rate (95.0% vs. 94.4% in XRT and no-XRT, respectively, P = 0.88), distant metastasis-free survival (P = 0.36), or 5-year cancer-specific survival (97.1% in XRT and 98.6 in no-XRT). Radiation therapy given after lumpectomy reduces the frequency of ipsilateral breast recurrences even in women with small breast cancer with several favourable clinical and biological features. However, the breast preservation rate may not increase due to more frequent use of salvage mastectomies in patients treated with postoperative radiotherapy. © 2001 Cancer Research Campaign http://www.bjcancer.com PMID:11161371

  3. Improved biochemical outcome with adjuvant radiotherapy after radical prostatectomy for prostate cancer with poor pathologic features

    SciTech Connect

    Vargas, Carlos; Kestin, Larry L. . E-mail: lkestin@beaumont.edu; Weed, Dan W.; Krauss, Daniel; Vicini, Frank A.; Martinez, Alvaro A.

    2005-03-01

    Purpose: The indications for adjuvant external beam radiotherapy (EBRT) after radical prostatectomy (RP) are poorly defined. We performed a retrospective comparison of our institution's experience treating prostate cancer with RP vs. RP followed by adjuvant EBRT. Methods and materials: Between 1987 and 1998, 617 patients with clinical Stage T1-T2N0M0 prostate cancer underwent RP. Patients who underwent preoperative androgen deprivation and those with positive lymph nodes were excluded. Of the 617 patients, 34 (5.5%) with an undetectable postoperative prostate-specific antigen (PSA) level underwent adjuvant prostatic fossa RT at a median of 0.25 year (range, 0.1-0.6) postoperatively because of poor pathologic features. The median total dose was 59.4 Gy (range, 50.4-66.6 Gy) in 1.8-2.0-Gy fractions. These 34 RP+RT patients were compared with the remaining 583 RP patients. Biochemical failure was defined as any postoperative PSA level {>=}0.1 ng/mL and any postoperative PSA level {>=}0.3 ng/mL (at least 30 days after surgery). Administration of androgen deprivation was also scored as biochemical failure when applying either definition. The median clinical follow-up was 8.2 years (range, 0.1-11.2 years) for RP and 8.4 years (range, 0.3-13.8 years) for RP+RT. Results: Radical prostatectomy + radiation therapy patients had a greater pathologic Gleason score (mean, 7.3 vs. 6.5; p < 0.01) and pathologic T stage (median, T3a vs. T2c; p < 0.01). Age (median, 65.7 years) and pretreatment PSA level (median, 7.9 ng/mL) were similar between the treatment groups. Extracapsular extension was present in 72% of RP+RT patients vs. 27% of RP patients (p < 0.01). The RP+RT patients were more likely to have seminal vesicle invasion (29% vs. 9%, p < 0.01) and positive margins (73% vs. 36%, p < 0.01). Despite these poor pathologic features, the 5-year biochemical control (BC) rate (PSA < 0.1 ng/mL) was 57% for RP+RT and 47% for RP (p = 0.28). For patients with extracapsular extension, the

  4. Association of mammographic image feature change and an increasing risk trend of developing breast cancer: an assessment

    NASA Astrophysics Data System (ADS)

    Tan, Maxine; Leader, Joseph K.; Liu, Hong; Zheng, Bin

    2015-03-01

    We recently investigated a new mammographic image feature based risk factor to predict near-term breast cancer risk after a woman has a negative mammographic screening. We hypothesized that unlike the conventional epidemiology-based long-term (or lifetime) risk factors, the mammographic image feature based risk factor value will increase as the time lag between the negative and positive mammography screening decreases. The purpose of this study is to test this hypothesis. From a large and diverse full-field digital mammography (FFDM) image database with 1278 cases, we collected all available sequential FFDM examinations for each case including the "current" and 1 to 3 most recently "prior" examinations. All "prior" examinations were interpreted negative, and "current" ones were either malignant or recalled negative/benign. We computed 92 global mammographic texture and density based features, and included three clinical risk factors (woman's age, family history and subjective breast density BIRADS ratings). On this initial feature set, we applied a fast and accurate Sequential Forward Floating Selection (SFFS) feature selection algorithm to reduce feature dimensionality. The features computed on both mammographic views were individually/ separately trained using two artificial neural network (ANN) classifiers. The classification scores of the two ANNs were then merged with a sequential ANN. The results show that the maximum adjusted odds ratios were 5.59, 7.98, and 15.77 for using the 3rd, 2nd, and 1st "prior" FFDM examinations, respectively, which demonstrates a higher association of mammographic image feature change and an increasing risk trend of developing breast cancer in the near-term after a negative screening.

  5. Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

    PubMed Central

    Nissan, Noam; Furman-Haran, Edna; Feinberg-Shapiro, Myra; Grobgeld, Dov; Eyal, Erez; Zehavi, Tania; Degani, Hadassa

    2014-01-01

    Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection. PMID:25549209

  6. Tracking the mammary architectural features and detecting breast cancer with magnetic resonance diffusion tensor imaging.

    PubMed

    Nissan, Noam; Furman-Haran, Edna; Feinberg-Shapiro, Myra; Grobgeld, Dov; Eyal, Erez; Zehavi, Tania; Degani, Hadassa

    2014-12-15

    Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.

  7. A computational study on convolutional feature combination strategies for grade classification in colon cancer using fluorescence microscopy data

    NASA Astrophysics Data System (ADS)

    Chowdhury, Aritra; Sevinsky, Christopher J.; Santamaria-Pang, Alberto; Yener, Bülent

    2017-03-01

    The cancer diagnostic workflow is typically performed by highly specialized and trained pathologists, for which analysis is expensive both in terms of time and money. This work focuses on grade classification in colon cancer. The analysis is performed over 3 protein markers; namely E-cadherin, beta actin and colagenIV. In addition, we also use a virtual Hematoxylin and Eosin (HE) stain. This study involves a comparison of various ways in which we can manipulate the information over the 4 different images of the tissue samples and come up with a coherent and unified response based on the data at our disposal. Pre- trained convolutional neural networks (CNNs) is the method of choice for feature extraction. The AlexNet architecture trained on the ImageNet database is used for this purpose. We extract a 4096 dimensional feature vector corresponding to the 6th layer in the network. Linear SVM is used to classify the data. The information from the 4 different images pertaining to a particular tissue sample; are combined using the following techniques: soft voting, hard voting, multiplication, addition, linear combination, concatenation and multi-channel feature extraction. We observe that we obtain better results in general than when we use a linear combination of the feature representations. We use 5-fold cross validation to perform the experiments. The best results are obtained when the various features are linearly combined together resulting in a mean accuracy of 91.27%.

  8. Hanging by a thread: exploring the features of nonresponse in an online young adult cancer survivorship support community.

    PubMed

    Crook, Brittani; Glowacki, Elizabeth M; Love, Brad; Jones, Barbara L; Macpherson, Catherine Fiona; Johnson, Rebecca H

    2016-02-01

    Finding helpful information can be challenging for young adult (YA) cancer survivors; thus, it is critical to examine features of online posts that successfully solicit responses and assess how these differ from posts that do not solicit responses. Using posts from an online YA cancer support community, we analyzed initial posts that did and did not receive replies utilizing Linguistic Inquiry Word Count (LIWC). Independent t tests revealed significant differences between the sets of posts regarding content, emotions, cognitive processes, pronoun use, and linguistic complexity. More specifically, posts with replies contained fewer words per sentence, had more first-person pronouns, had more expressions of negative emotions, and contained more present tense and past tense verbs. The findings of this study can help improve peer-exchanged support in online communities so that YA cancer survivors can more effectively receive digital support. This research also provides communication researchers, health educators, and care providers a lens for understanding the YA cancer survivorship experience. This research helps survivors be strategic in how they use online forums to seek advice and support. More complete understanding of what kinds of prompts produce responses allows those in need to craft messages in ways that are most likely to elicit support from fellow cancer survivors. These implications for message design extend beyond blogging and can be applicable for text message and email exchanges between cancer patients and their care providers.

  9. Prognostic features of 51 colorectal and 130 appendiceal cancer patients with peritoneal carcinomatosis treated by cytoreductive surgery and intraperitoneal chemotherapy.

    PubMed Central

    Sugarbaker, P H; Jablonski, K A

    1995-01-01

    OBJECTIVE: A treatment plan to be used in patients with peritoneal carcinomatosis was devised and tested as a Phase II study. BACKGROUND: Peritoneal carcinomatosis from appendical or colorectal cancer has been regarded as a fatal clinical entity. Treatment protocols have not been reported previously. METHODS: The authors used cytoreductive surgery and intraperitoneal chemotherapy to treat 181 consecutive patients with peritoneal carcinomatosis. There were 51 patients with colorectal cancer and 130 patients with appendiceal cancer. Mean follow-up is 24 months, with a range of 0 to 149 months. RESULTS: Clinical features that showed prognostic significance included appendiceal versus colorectal primary tumors (p = 0.0001), grade 1 versus grades 2 and 3 histopathology (p = 0.0003), complete versus incomplete cytoreductions (p = 0.0001), lymph node-negative versus lymph node-positive primary tumors (p = 0.0001), and volume of peritoneal carcinomatosis present preoperatively for colon cancer (p = 0.0006). Features with no statistical prognostic significance included preoperative tumor volume for appendiceal cancer, age, sex, number of cycles of chemotherapy, operative time, complications, blood loss, and institution providing treatment. From these prognostic features, four prognostic groups were identified, and 3-year survival was estimated by the product-limit survival method. Group I patients (n = 76) were those with grade 1 histology, no lymph node metastases, and complete cytoreductions (survival at 3 years = 99%). Group II patients (n = 23) were those with grade 2 or 3 histology, no lymph node metastases, and complete cytoreductions (65%). Group III patients (n = 24) had any histology, lymph node metastases, and complete cytoreductions (66%). Group IV patients (n = 58) had incomplete cytoreductions (20%). PMID:7857141

  10. A statistical feature selection method for lung cancer classification in CT scans

    NASA Astrophysics Data System (ADS)

    Al-Absi, Hamada R. H.; Samir, Brahim Belhaouari

    2013-10-01

    This paper presents a computer aided diagnosis for lung nodules in CT images. The system consists of feature extraction, feature selection and classification. A two-step feature selection process is introduced to reduce the number of coefficients produced in the feature extraction step. This helps in enhancing the classification performance as it removes unneeded and redundant information. The classification rate of the system reached 98.10 % with minimum false negatives and zero false positives.

  11. Computer-Aided Renal Cancer Quantification and Classification from Contrast-enhanced CT via Histograms of Curvature-Related Features

    PubMed Central

    Linguraru, Marius George; Wang, Shijun; Shah, Furhawn; Gautam, Rabindra; Peterson, James; Linehan, W. Marston; Summers, Ronald M.

    2009-01-01

    In clinical practice, renal cancer diagnosis is performed by manual quantifications of tumor size and enhancement, which are time consuming and show high variability. We propose a computer-assisted clinical tool to assess and classify renal tumors in contrast-enhanced CT for the management and classification of kidney tumors. The quantification of lesions used level-sets and a statistical refinement step to adapt to the shape of the lesions. Intra-patient and inter-phase registration facilitated the study of lesion enhancement. From the segmented lesions, the histograms of curvature-related features were used to classify the lesion types via random sampling. The clinical tool allows the accurate quantification and classification of cysts and cancer from clinical data. Cancer types are further classified into four categories. Computer-assisted image analysis shows great potential for tumor diagnosis and monitoring. PMID:19964705

  12. Computer extracted texture features on T2w MRI to predict biochemical recurrence following radiation therapy for prostate cancer

    NASA Astrophysics Data System (ADS)

    Ginsburg, Shoshana B.; Rusu, Mirabela; Kurhanewicz, John; Madabhushi, Anant

    2014-03-01

    In this study we explore the ability of a novel machine learning approach, in conjunction with computer-extracted features describing prostate cancer morphology on pre-treatment MRI, to predict whether a patient will develop biochemical recurrence within ten years of radiation therapy. Biochemical recurrence, which is characterized by a rise in serum prostate-specific antigen (PSA) of at least 2 ng/mL above the nadir PSA, is associated with increased risk of metastasis and prostate cancer-related mortality. Currently, risk of biochemical recurrence is predicted by the Kattan nomogram, which incorporates several clinical factors to predict the probability of recurrence-free survival following radiation therapy (but has limited prediction accuracy). Semantic attributes on T2w MRI, such as the presence of extracapsular extension and seminal vesicle invasion and surrogate measure- ments of tumor size, have also been shown to be predictive of biochemical recurrence risk. While the correlation between biochemical recurrence and factors like tumor stage, Gleason grade, and extracapsular spread are well- documented, it is less clear how to predict biochemical recurrence in the absence of extracapsular spread and for small tumors fully contained in the capsule. Computer{extracted texture features, which quantitatively de- scribe tumor micro-architecture and morphology on MRI, have been shown to provide clues about a tumor's aggressiveness. However, while computer{extracted features have been employed for predicting cancer presence and grade, they have not been evaluated in the context of predicting risk of biochemical recurrence. This work seeks to evaluate the role of computer-extracted texture features in predicting risk of biochemical recurrence on a cohort of sixteen patients who underwent pre{treatment 1.5 Tesla (T) T2w MRI. We extract a combination of first-order statistical, gradient, co-occurrence, and Gabor wavelet features from T2w MRI. To identify which of these

  13. Automated diagnosis of mammogram images of breast cancer using discrete wavelet transform and spherical wavelet transform features: a comparative study.

    PubMed

    Ganesan, Karthikeyan; Acharya, U Rajendra; Chua, Chua Kuang; Min, Lim Choo; Abraham, Thomas K

    2014-12-01

    Mammograms are one of the most widely used techniques for preliminary screening of breast cancers. There is great demand for early detection and diagnosis of breast cancer using mammograms. Texture based feature extraction techniques are widely used for mammographic image analysis. In specific, wavelets are a popular choice for texture analysis of these images. Though discrete wavelets have been used extensively for this purpose, spherical wavelets have rarely been used for Computer-Aided Diagnosis (CAD) of breast cancer using mammograms. In this work, a comparison of the performance between the features of Discrete Wavelet Transform (DWT) and Spherical Wavelet Transform (SWT) based on the classification results of normal, benign and malignant stage was studied. Classification was performed using Linear Discriminant Classifier (LDC), Quadratic Discriminant Classifier (QDC), Nearest Mean Classifier (NMC), Support Vector Machines (SVM) and Parzen Classifier (ParzenC). We have obtained a maximum classification accuracy of 81.73% for DWT and 88.80% for SWT features using SVM classifier.

  14. Immortalizing the Complexity of Cancer Metastasis Genetic Features of Lethal Metastatic Pancreatic Cancer Obtained from Rapid Autopsy

    PubMed Central

    Embuscado, Erlinda E.; Laheru, Daniel; Ricci, Francesca; Yun, Ki Jung; de Boom Witzel, Sten; Seigel, Allison; Flickinger, Katie; Hidalgo, Manuel; Bova, G. Steven; Iacobuzio-Donahue, Christine A.

    2009-01-01

    The virtual lack of well-characterized metastatic pancreatic cancer tissues for study has limited systematic studies of the metastatic process of this deadly disease. To address this important issue, we have instituted a rapid autopsy protocol for the collection of high quality tissues from patients with metastatic pancreatic cancer, called the Gastrointestinal Cancer Rapid Medical Donation Program (GICRMDP). At the time of preparation of this manuscript, 20 patients with metastatic pancreatic cancer and one patient with metastatic colon cancer have undergone a rapid autopsy in association with the GICRMDP. The average time interval achieved for these 21 patients was 8.0 hours, with more than 500 individual samples of matched high quality primary and metastatic pancreatic cancer tissues, peritoneal/pleural fluid and blood obtained so far. For the first four patients in which the autopsy was performed in <6 hours, we have successfully xenografted the primary tumor and/or two to four independent matched metastases from a variety of target organ sites, with a take rate of almost 60% for the first 26 xenografted tumors attempted. In an initial survey of KRAS2, TP53 and DPC4 genetic status in lethal metastatic pancreatic cancers, activating KRAS2 mutations were detected in 82% of cases and inactivating TP53 mutations in 55% of cases, consistent with rates of genetic alteration of these genes in early stage pancreatic cancers. However, DPC4 inactivation was found in 75% of patients analyzed, suggesting that genetic inactivation of the DPC4 tumor suppressor gene continues to be selected for with growth at the primary site and metastatic spread to other organs. The invaluable tissue resources generated by the success of the GICRMDP will provide an unparalleled resource for study of metastatic pancreatic cancer and of the metastatic process in general. PMID:15846069

  15. Endoscopic features of submucosal deeply invasive colorectal cancer with NBI characteristics : S Saito et al. Endoscopic images of early colorectal cancer.

    PubMed

    Saito, Shoichi; Tajiri, Hisao; Ikegami, Masahiro

    2015-12-01

    In this review, we discuss the features of conventional endoscopy, magnified endoscopy involving image enhanced endoscopy and endoscopic ultrasonography (EUS) using illustrations for submucosal deeply invasive colorectal cancer (SM-Ca). First, the typical features of SM-Ca were observed, including fold convergence, stiffness, depression (ulceration) and elevated lesions in depressed areas. Magnified endoscopic findings using NBI showed dilated, irregularly shaped micro-capillary vessels. In addition, VI and VN pits were clearly visible using crystal violet staining. In contrast, using EUS, at the third layer we found a layer that was thin compared to the surrounding normal mucosa, which suggested the existence of SM-Ca.

  16. Unique Features of Germline Variation in Five Egyptian Familial Breast Cancer Families Revealed by Exome Sequencing

    PubMed Central

    Kim, Yeong C.; Soliman, Amr S.; Cui, Jian; Ramadan, Mohamed; Hablas, Ahmed; Abouelhoda, Mohamed; Hussien, Nehal; Ahmed, Ola; Zekri, Abdel-Rahman Nabawy; Seifeldin, Ibrahim A.

    2017-01-01

    Genetic predisposition increases the risk of familial breast cancer. Recent studies indicate that genetic predisposition for familial breast cancer can be ethnic-specific. However, current knowledge of genetic predisposition for the disease is predominantly derived from Western populations. Using this existing information as the sole reference to judge the predisposition in non-Western populations is not adequate and can potentially lead to misdiagnosis. Efforts are required to collect genetic predisposition from non-Western populations. The Egyptian population has high genetic variations in reflecting its divergent ethnic origins, and incident rate of familial breast cancer in Egypt is also higher than the rate in many other populations. Using whole exome sequencing, we investigated genetic predisposition in five Egyptian familial breast cancer families. No pathogenic variants in BRCA1, BRCA2 and other classical breast cancer-predisposition genes were present in these five families. Comparison of the genetic variants with those in Caucasian familial breast cancer showed that variants in the Egyptian families were more variable and heterogeneous than the variants in Caucasian families. Multiple damaging variants in genes of different functional categories were identified either in a single family or shared between families. Our study demonstrates that genetic predisposition in Egyptian breast cancer families may differ from those in other disease populations, and supports a comprehensive screening of local disease families to determine the genetic predisposition in Egyptian familial breast cancer. PMID:28076423

  17. FAP, gastric cancer, and genetic counseling featuring children and young adults: a family study and review.

    PubMed

    Lynch, Henry T; Snyder, Carrie; Davies, Janine M; Lanspa, Stephen; Lynch, Jane; Gatalica, Zoran; Graeve, Victoria; Foster, Jason

    2010-12-01

    Familial adenomatous polyposis is a highly complex and multifaceted colorectal cancer prone disorder which is often significantly confounded by extracolonic cancers inclusive of gastric cancer, a significant problem in the Orient. Gastric cancer in familial adenomatous polyposis is heavily influenced by fundic gland polyps which are often so voluminous as to defy effective endoscopic surveillance. This study involves more than two decades of investigation of an attenuated familial adenomatous polyposis family where gastric cancer posed an early diagnostic problem because it was obscured by multiple fundic gland polyps. Fundic gland polyps are common in familial adenomatous polyposis and attenuated familial adenomatous polyposis and, if voluminous, may interfere with effective endoscopic gastric cancer surveillance. This family is believed to be the first of its type reported with focus upon education and genetic counseling in the setting of a family information service. Cancer control in familial adenomatous polyposis may be partially resolved through use of familial colorectal cancer registries, with greater attention to family history and its interpretation, genetic counseling, and clinical translation for diagnosis and management.

  18. Unique Features of Germline Variation in Five Egyptian Familial Breast Cancer Families Revealed by Exome Sequencing.

    PubMed

    Kim, Yeong C; Soliman, Amr S; Cui, Jian; Ramadan, Mohamed; Hablas, Ahmed; Abouelhoda, Mohamed; Hussien, Nehal; Ahmed, Ola; Zekri, Abdel-Rahman Nabawy; Seifeldin, Ibrahim A; Wang, San Ming

    2017-01-01

    Genetic predisposition increases the risk of familial breast cancer. Recent studies indicate that genetic predisposition for familial breast cancer can be ethnic-specific. However, current knowledge of genetic predisposition for the disease is predominantly derived from Western populations. Using this existing information as the sole reference to judge the predisposition in non-Western populations is not adequate and can potentially lead to misdiagnosis. Efforts are required to collect genetic predisposition from non-Western populations. The Egyptian population has high genetic variations in reflecting its divergent ethnic origins, and incident rate of familial breast cancer in Egypt is also higher than the rate in many other populations. Using whole exome sequencing, we investigated genetic predisposition in five Egyptian familial breast cancer families. No pathogenic variants in BRCA1, BRCA2 and other classical breast cancer-predisposition genes were present in these five families. Comparison of the genetic variants with those in Caucasian familial breast cancer showed that variants in the Egyptian families were more variable and heterogeneous than the variants in Caucasian families. Multiple damaging variants in genes of different functional categories were identified either in a single family or shared between families. Our study demonstrates that genetic predisposition in Egyptian breast cancer families may differ from those in other disease populations, and supports a comprehensive screening of local disease families to determine the genetic predisposition in Egyptian familial breast cancer.

  19. Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer.

    PubMed

    Roudier, Martine P; Winters, Brian R; Coleman, Ilsa; Lam, Hung-Ming; Zhang, Xiaotun; Coleman, Roger; Chéry, Lisly; True, Lawrence D; Higano, Celestia S; Montgomery, Bruce; Lange, Paul H; Snyder, Linda A; Srivastava, Shiv; Corey, Eva; Vessella, Robert L; Nelson, Peter S; Üren, Aykut; Morrissey, Colm

    2016-06-01

    The TMPRSS2-ERG gene fusion is detected in approximately half of primary prostate cancers (PCa) yet the prognostic significance remains unclear. We hypothesized that ERG promotes the expression of common genes in primary PCa and metastatic castration-resistant PCa (CRPC), with the objective of identifying ERG-associated pathways, which may promote the transition from primary PCa to CRPC. We constructed tissue microarrays (TMA) from 127 radical prostatectomy specimens, 20 LuCaP patient-derived xenografts (PDX), and 152 CRPC metastases obtained immediately at time of death. Nuclear ERG was assessed by immunohistochemistry (IHC). To characterize the molecular features of ERG-expressing PCa, a subset of IHC confirmed ERG+ or ERG- specimens including 11 radical prostatectomies, 20 LuCaP PDXs, and 45 CRPC metastases underwent gene expression analysis. Genes were ranked based on expression in primary PCa and CRPC. Common genes of interest were targeted for IHC analysis and expression compared with biochemical recurrence (BCR) status. IHC revealed that 43% of primary PCa, 35% of the LuCaP PDXs, and 18% of the CRPC metastases were ERG+ (12 of 48 patients [25%] had at least one ERG+ metastasis). Based on gene expression data and previous literature, two proteins involved in calcium signaling (NCALD, CACNA1D), a protein involved in inflammation (HLA-DMB), CD3 positive immune cells, and a novel ERG-associated protein, DCLK1 were evaluated in primary PCa and CRPC metastases. In ERG+ primary PCa, a weak association was seen with NCALD and CACNA1D protein expression. HLA-DMB association with ERG was decreased and CD3 cell number association with ERG was changed from positive to negative in CRPC metastases compared to primary PCa. DCLK1 was upregulated at the protein level in unpaired ERG+ primary PCa and CRPC metastases (P = 0.0013 and P < 0.0001, respectively). In primary PCa, ERG status or expression of targeted proteins was not associated with BCR-free survival

  20. Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?

    PubMed Central

    Fave, Xenia; Mackin, Dennis; Zhang, Joy; Fried, David; Balter, Peter; Followill, David; Gomez, Daniel; Kyle Jones, A.; Stingo, Francesco; Fontenot, Jonas; Court, Laurence

    2015-01-01

    Purpose: Increasing evidence suggests radiomics features extracted from computed tomography (CT) images may be useful in prognostic models for patients with nonsmall cell lung cancer (NSCLC). This study was designed to determine whether such features can be reproducibly obtained from cone-beam CT (CBCT) images taken using medical Linac onboard-imaging systems in order to track them through treatment. Methods: Test-retest CBCT images of ten patients previously enrolled in a clinical trial were retrospectively obtained and used to determine the concordance correlation coefficient (CCC) for 68 different texture features. The volume dependence of each feature was also measured using the Spearman rank correlation coefficient. Features with a high reproducibility (CCC > 0.9) that were not due to volume dependence in the patient test-retest set were further examined for their sensitivity to differences in imaging protocol, level of scatter, and amount of motion by using two phantoms. The first phantom was a texture phantom composed of rectangular cartridges to represent different textures. Features were measured from two cartridges, shredded rubber and dense cork, in this study. The texture phantom was scanned with 19 different CBCT imagers to establish the features’ interscanner variability. The effect of scatter on these features was studied by surrounding the same texture phantom with scattering material (rice and solid water). The effect of respiratory motion on these features was studied using a dynamic-motion thoracic phantom and a specially designed tumor texture insert of the shredded rubber material. The differences between scans acquired with different Linacs and protocols, varying amounts of scatter, and with different levels of motion were compared to the mean intrapatient difference from the test-retest image set. Results: Of the original 68 features, 37 had a CCC >0.9 that was not due to volume dependence. When the Linac manufacturer and imaging protocol

  1. Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?

    SciTech Connect

    Fave, Xenia Fried, David; Mackin, Dennis; Yang, Jinzhong; Zhang, Joy; Balter, Peter; Followill, David; Gomez, Daniel; Kyle Jones, A.; Stingo, Francesco; Fontenot, Jonas; Court, Laurence

    2015-12-15

    Purpose: Increasing evidence suggests radiomics features extracted from computed tomography (CT) images may be useful in prognostic models for patients with nonsmall cell lung cancer (NSCLC). This study was designed to determine whether such features can be reproducibly obtained from cone-beam CT (CBCT) images taken using medical Linac onboard-imaging systems in order to track them through treatment. Methods: Test-retest CBCT images of ten patients previously enrolled in a clinical trial were retrospectively obtained and used to determine the concordance correlation coefficient (CCC) for 68 different texture features. The volume dependence of each feature was also measured using the Spearman rank correlation coefficient. Features with a high reproducibility (CCC > 0.9) that were not due to volume dependence in the patient test-retest set were further examined for their sensitivity to differences in imaging protocol, level of scatter, and amount of motion by using two phantoms. The first phantom was a texture phantom composed of rectangular cartridges to represent different textures. Features were measured from two cartridges, shredded rubber and dense cork, in this study. The texture phantom was scanned with 19 different CBCT imagers to establish the features’ interscanner variability. The effect of scatter on these features was studied by surrounding the same texture phantom with scattering material (rice and solid water). The effect of respiratory motion on these features was studied using a dynamic-motion thoracic phantom and a specially designed tumor texture insert of the shredded rubber material. The differences between scans acquired with different Linacs and protocols, varying amounts of scatter, and with different levels of motion were compared to the mean intrapatient difference from the test-retest image set. Results: Of the original 68 features, 37 had a CCC >0.9 that was not due to volume dependence. When the Linac manufacturer and imaging protocol

  2. The role of leptin in gastric cancer: clinicopathologic features and molecular mechanisms.

    PubMed

    Lee, Kang Nyeong; Choi, Ho Soon; Yang, Sun Young; Park, Hyun Ki; Lee, Young Yiul; Lee, Oh Young; Yoon, Byung Chul; Hahm, Joon Soo; Paik, Seung Sam

    2014-04-18

    Obesity is associated with certain types of cancer, including gastric cancer. However, it is still unclear whether obesity-related cytokine, leptin, is implicated in gastric cancer. Therefore, we aimed to investigate the role of leptin in gastric cancer. The expression of leptin and its receptor, Ob-R, was assessed by immunohistochemical staining and was compared in patients with gastric adenoma (n=38), early gastric cancer (EGC) (n=38), and advanced gastric cancer (AGC) (n=38), as a function of their clinicopathological characteristics. Gastric cancer cell lines were studied to investigate the effects of leptin on the signal transducer and activator of transcription-3 (STAT3) and extracellular receptor kinase 1/2 (ERK1/2) signaling pathways using MTT assays, immunoblotting, and inhibition studies. Leptin was expressed in gastric adenomas (42.1%), EGCs (47.4%), and AGCs (43.4%). Ob-R expression tended to increase from gastric adenoma (2%), through EGC (8%), to AGC (18%). Leptin induced the proliferation of gastric cancer cells by activating STAT3 and ERK1/2 and up-regulating the expression of vascular endothelial growth factor (VEGF). Blocking Ob-R with pharmacological inhibitors and by RNAi decreased both the leptin-induced activation of STAT3 and ERK1/2 and the leptin-induced expression of VEGF. Leptin plays a role in gastric cancer by stimulating the proliferation of gastric cancer cells via activating the STAT3 and ERK1/2 pathways. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. Clinical, Molecular and Geographical Features of Hereditary Breast/Ovarian Cancer in Latvia

    PubMed Central

    2005-01-01

    Introduction The aim of the study is to evaluate the incidence and phenotype-genotype characteristics of hereditary breast and ovarian cancer syndromes in Latvia in order to develop the basis of clinical management for patients and their relatives affected by this syndrome. Materials and methods In 2002-2004 in two Latvian oncology hospitals (Liepãja Oncology Hospital and Daugavpils Oncology Hospital) cancer family histories were collected from 287 consecutive patients with breast and ovarian cancer. In all cases, when it was possible to obtain the blood sample, DNA testing for founder mutations in the BRCA1 gene was performed. Results Among 287 family cancer histories analysed in 8 (2.8%) cases criteria of hereditary breast cancer (HBC) were fulfilled and in 5 (1.7%) cases hereditary breast and ovarian cancer (HBOC) was diagnosed. In 50 (17.4%) cases we have suspicion of hereditary breast cancer (HBC susp.) and in 8 (2.8%) cases - suspicion of hereditary breast and ovarian cancer (HBOC susp.). We have one (0.3%) case with hereditary ovarian cancer (HOC). DNA testing of founder mutations in the BRCA1 gene (exon 20 (5382 insC) exon 5 (300T/G), exon 11, 17 (4153delA)) for 178/287 (62%) patients was performed. In 9/287 (4.9%) cases we found a mutation in the BRCA1 gene. 4 mutations were detected in exon 11, 17 (4153delA) and 4 mutations in exon 20 (5382 insC) and 1 in exon 5. Conclusions Existing pedigree/clinical data suggest that in Latvia the clinical frequency of hereditary breast and ovarian cancer is around 5% of consecutive breast and ovarian cancer patients and suspicion of the syndrome is observed in another 20% of cases. Frequency of BRCA1 founder mutations is 5% of all consecutive breast and ovarian cancers. Considerable geographical differences in the clinical and molecular frequency of hereditary breast ovarian cancer have been observed in Latvia. PMID:20223033

  4. [Clinicopathological features and prognosis of HER2-negative luminal-type breast cancer patients with early and late recurrence].

    PubMed

    Chen, X L; Fan, Y; Xu, B H

    2016-06-23

    To compare the clinicopathological features and prognosis of HER2-negative luminal-type breast cancer patients with early and late recurrence. We reviewed the records of recurrent breast cancer patients who previously underwent surgery at the Cancer Hospital, Chinese Academy of Medical Sciences between 2003 and 2009. A total of 390 cases were identified as eligible recurrent patients with HER2-negative luminal-type breast cancer. Among them, 279 cases had early recurrence (DFS<5 years) and 111 cases had late recurrence (DFS≥5 years). The clinicopathological features, sites of initial metastasis and survival after recurrence in the two groups were compared and analyzed. Patients with vascular invasion or and ≥4 lymph node metastases were found more common in the early recurrence group (P<0.05), while positive status of both hormone receptors and non-standardized hormone therapy were more frequently seen in the late recurrence group (P<0.05). In the late recurrence group, initial lung metastasis was seen in 47.7% of patients, significantly higher than that (25.1%) in the early recurrence group (P<0.001). Although initial multiple organ metastases were more common in the late recurrence group (P<0.05), its median overall survival (OS) after recurrence was 66 months, significantly longer than that of the early recurrence group (39 months) (HR=1.6, P=0.003). The two groups of HER2-negative luminal-type breast cancer patients with early and late recurrence show some differences in clinicopathological features and prognosis. Both vascular invasion and ≥4 lymph node metastases are important factors affecting the DFS in HER-2-negative luminal-type breast cancer patients, and early recurrence is more frequently seen in this group. Late recurrence is the more frequent recurrence pattern in the HER-2 negative luminal type breast cancer patients, especially, in the double hormone receptor-positive patients who received non-standardized hormone therapy. The prognosis for

  5. Molecular Features and Methylation Status in Early Onset (≤40 Years) Colorectal Cancer: A Population Based, Case-Control Study

    PubMed Central

    Magnani, Giulia; Furlan, Daniela; Sahnane, Nora; Reggiani Bonetti, Luca; Domati, Federica; Pedroni, Monica

    2015-01-01

    Colorectal cancer is usually considered a disease of the elderly. However, a small fraction of patients develops colorectal cancer earlier. The aim of our study was to define the frequency of known hereditary colorectal syndromes and to characterise genetic and epigenetic features of early nonhereditary tumors. Thirty-three patients ≤40 years with diagnosis of colorectal cancer and 41 patients with disease at >60 years of age were investigated for MSI, Mismatch Repair proteins expression, KRAS and BRAF mutations, hypermethylation, and LINE-1 hypomethylation. Detection of germline mutations was performed in Mismatch Repair, APC and MUTYH genes. Early onset colorectal cancer showed a high incidence of hereditary forms (18%). KRAS mutations were detected in 36% of early nonhereditary tumors. Early onset colorectal cancer disclosed an average number of methylated genes significantly lower when compared to the controls (p = 0.02). Finally both of the two groups were highly methylated in ESR1, GATA5, and WT1 genes and were similar for LINE-1 hypomethylation. The genetic make-up of carcinomas differs from young to elderly patients. Early onset tumors showed more frequently a constitutional defective of Mismatch Repair System and a minor number of methylated genes. Hypermethylation of ESR1, GATA5, and WT1 genes suggests possible markers in the earlier diagnosis of colorectal tumorigenesis. PMID:26557847

  6. Extramural venous invasion detected by MDCT as an adverse imaging feature for predicting synchronous metastases in T4 gastric cancer.

    PubMed

    Cheng, Jin; Wu, Jing; Ye, Yingjiang; Zhang, Chunfang; Zhang, Yinli; Wang, Yi

    2017-04-01

    Background Extramural venous invasion (EMVI) is defined histologically as the active invasion of tumor cells to the lumens of mesenteric vessels beyond the muscularis propria in advanced gastrointestinal cancer, resulting in distant metastases. Purpose To determine the association between synchronous metastatic disease in patients with T4 gastric cancer and EMVI detected on contrast-enhanced multiple-row detector computed tomography (MDCT). Material and Methods A total of 152 patients with T4 gastric carcinoma were retrospectively reviewed and divided into EMVI-positive and EMVI-negative groups where EMVI, as detected on MDCT, was defined as a tubular or nodular soft tissue thickening extending from the tumor along the vessels of the mesentery. Synchronous metastases were detected by MDCT and/or confirmed by postoperative diagnosis. Logistic regression analyses were performed to analyze the predictive factors of synchronous metastases in gastric cancer. Results Synchronous metastases were found in 47 of 152 (30.9%) patients with T4 gastric cancer. Thirty-one of 77 (40.3%) patients in the EMVI-positive group had evidence of metastases compared to 16 (21.3%) of 75 patients in the EMVI-negative group ( P = 0.019). Synchronous metastases were significantly associated with EMVI with an odds ratio (OR) of 2.250 (95% CI, 1.072-4.724). Conclusion EMVI-positive tumors, as an adverse imaging feature, were significantly associated with synchronous metastases in patients with T4 gastric cancer.

  7. Annual Report to the Nation on the Status of Cancer, 1975–2014, Featuring Survival

    PubMed Central

    Ward, Elizabeth M.; Johnson, Christopher J.; Cronin, Kathleen A.; Ma, Jiemin; Ryerson, A. Blythe; Mariotto, Angela; Lake, Andrew J.; Wilson, Reda; Sherman, Recinda L.; Anderson, Robert N.; Henley, S. Jane; Kohler, Betsy A.; Penberthy, Lynne; Feuer, Eric J.; Weir, Hannah K.

    2017-01-01

    Abstract Background: The American Cancer Society (ACS), the Centers for Disease Control and Prevention (CDC), the National Cancer Institute (NCI), and the North American Association of Central Cancer Registries (NAACCR) collaborate to provide annual updates on cancer occurrence and trends in the United States. This Annual Report highlights survival rates. Methods: Data were from the CDC- and NCI-funded population-based cancer registry programs and compiled by NAACCR. Trends in age-standardized incidence and death rates for all cancers combined and for the leading cancer types by sex were estimated by joinpoint analysis and expressed as annual percent change. We used relative survival ratios and adjusted relative risk of death after a diagnosis of cancer (hazard ratios [HRs]) using Cox regression model to examine changes or differences in survival over time and by sociodemographic factors. Results: Overall cancer death rates from 2010 to 2014 decreased by 1.8% (95% confidence interval [CI] = –1.8 to –1.8) per year in men, by 1.4% (95% CI = –1.4 to –1.3) per year in women, and by 1.6% (95% CI = –2.0 to –1.3) per year in children. Death rates decreased for 11 of the 16 most common cancer types in men and for 13 of the 18 most common cancer types in women, including lung, colorectal, female breast, and prostate, whereas death rates increased for liver (men and women), pancreas (men), brain (men), and uterine cancers. In contrast, overall incidence rates from 2009 to 2013 decreased by 2.3% (95% CI = –3.1 to –1.4) per year in men but stabilized in women. For several but not all cancer types, survival statistically significantly improved over time for both early and late-stage diseases. Between 1975 and 1977, and 2006 and 2012, for example, five-year relative survival for distant-stage disease statistically significantly increased from 18.7% (95% CI = 16.9% to 20.6%) to 33.6% (95% CI = 32.2% to 35.0%) for female breast cancer but not for liver

  8. Identifying master regulators of cancer and their downstream targets by integrating genomic and epigenomic features.

    PubMed

    Gevaert, Olivier; Plevritis, Sylvia

    2013-01-01

    Vast amounts of molecular data characterizing the genome, epigenome and transcriptome are becoming available for a variety of cancers. The current challenge is to integrate these diverse layers of molecular biology information to create a more comprehensive view of key biological processes underlying cancer. We developed a biocomputational algorithm that integrates copy number, DNA methylation, and gene expression data to study master regulators of cancer and identify their targets. Our algorithm starts by generating a list of candidate driver genes based on the rationale that genes that are driven by multiple genomic events in a subset of samples are unlikely to be randomly deregulated. We then select the master regulators from the candidate driver and identify their targets by inferring the underlying regulatory network of gene expression. We applied our biocomputational algorithm to identify master regulators and their targets in glioblastoma multiforme (GBM) and serous ovarian cancer. Our results suggest that the expression of candidate drivers is more likely to be influenced by copy number variations than DNA methylation. Next, we selected the master regulators and identified their downstream targets using module networks analysis. As a proof-of-concept, we show that the GBM and ovarian cancer module networks recapitulate known processes in these cancers. In addition, we identify master regulators that have not been previously reported and suggest their likely role. In summary, focusing on genes whose expression can be explained by their genomic and epigenomic aberrations is a promising strategy to identify master regulators of cancer.

  9. Prostate cancer early detection, version 1.2014. Featured updates to the NCCN Guidelines.

    PubMed

    Carroll, Peter R; Parsons, J Kellogg; Andriole, Gerald; Bahnson, Robert R; Barocas, Daniel A; Catalona, William J; Dahl, Douglas M; Davis, John W; Epstein, Jonathan I; Etzioni, Ruth B; Giri, Veda N; Hemstreet, George P; Kawachi, Mark H; Lange, Paul H; Loughlin, Kevin R; Lowrance, William; Maroni, Paul; Mohler, James; Morgan, Todd M; Nadler, Robert B; Poch, Michael; Scales, Chuck; Shanefelt, Terrence M; Vickers, Andrew J; Wake, Robert; Shead, Dorothy A; Ho, Maria

    2014-09-01

    The NCCN Guidelines for Prostate Cancer Early Detection provide recommendations for men choosing to participate in an early detection program for prostate cancer. These NCCN Guidelines Insights highlight notable recent updates. Overall, the 2014 update represents a more streamlined and concise set of recommendations. The panel stratified the age ranges at which initiating testing for prostate cancer should be considered. Indications for biopsy include both a cutpoint and the use of multiple risk variables in combination. In addition to other biomarkers of specificity, the Prostate Health Index has been included to aid biopsy decisions in certain men, given recent FDA approvals.

  10. The Demographic Features, Clinicopathological Characteristics and Cancer-specific Outcomes for Patients with Microinvasive Breast Cancer: A SEER Database Analysis

    PubMed Central

    Wang, Wenna; Zhu, Wenjie; Du, Feng; Luo, Yang; Xu, Binghe

    2017-01-01

    To investigate the clinicopathological characteristics and survival outcomes of microinvasive breast cancer, we conducted an observational study of female diagnosed with DCIS or DCIS with microinvasion (DCISM) from 1990 to 2012 using the Surveillance, Epidemiology, and End Results (SEER) database. There were 87695 DCIS and 8863 DCISM identified. In DCISM group, patients appeared to be younger and more black patients were identified in comparison with DCIS group. Furthermore, DCISM was associated with more aggressive tumor characteristics like higher rates of oestrogen receptor (ER) and progesterone receptor (PR) negativity, HER2 positivity, and lymph node metastasis. With a median follow-up of 91 months, patients with DCISM had worse cancer-specific survival (CSS) (hazard ratio [HR], 2.475; P < 0.001) and overall survival (OS) (HR, 1.263; P < 0.001). In the multivariable analysis, microinvasion was an independent prognostic factor for worse CSS (HR, 1.919; P < 0.001) and OS (HR, 1.184; P < 0.001). The 10-year cancer-specific mortality rate was 1.49% in DCIS and 4.08% in DCISM (HR, 2.771; P < 0.001). The 20-year cancer-specific mortality rate was 4.00% in DCIS and 9.65% in DCISM (HR, 2.482; P < 0.001). Deepening understanding of the nature of microinvasive breast cancer will be valuable for clinical treatment recommendations. PMID:28165014

  11. Clinicopathological features and prognostic roles of KRAS, BRAF, PIK3CA and NRAS mutations in advanced gastric cancer

    PubMed Central

    2014-01-01

    Background RAS-RAF-MEK-ERK and PI3K-AKT pathways form a significant cascade for potential molecular target therapy in advanced cancer. The clinical significance of mutations in these genes in advanced gastric cancer (AGC) is uncertain. Methods We collected formalin-fixed, paraffin-embedded and fresh frozen tumor samples from AGC patients and analyzed the KRAS, NRAS, BRAF and PIK3CA mutations by direct-sequencing. We retrospectively investigated the clinicopathological features of these mutations in AGC patients, and selected patients with metastatic gastric cancer. Results Among 167 AGC patients, mutations of KRAS codons 12/13 (N = 8/164, 4.9%), PIK3CA (N = 9/163, 5.5%), and NRAS codon 12/13(N = 3/159, 1.9%) were detected. Comparison of the clinicopathological features of the mutated KRAS, PIK3CA, NRAS genes with an all-wild type of these genes showed that the frequency of the intestinal type was significantly higher in patients whose tumor tissue contained KRAS mutations (P = 0.014). Among 125 patients with metastatic gastric cancer, patients with NRAS codon 12/13 mutations in their tumors had shorter overall survival compared with NRAS wild-type patients (MST: 14.7 vs 8.8 months, P = 0.011). By multivariate analyses, NRAS codon 12/13 mutation was an indicator for poor prognosis in patients with metastatic gastric cancer (adjusted HR 5.607, 95% CI: 1.637-19.203). Conclusions Our study indicated that mutations of KRAS, PIK3CA and NRAS were rare in AGC. NRAS mutations were likely to associate with poor prognosis in metastatic state of AGC patients, but further validation of other research is required. PMID:24774510

  12. Tracking the Correlation Between CpG Island Methylator Phenotype and Other Molecular Features and Clinicopathological Features in Human Colorectal Cancers: A Systematic Review and Meta-Analysis

    PubMed Central

    Zong, Liang; Abe, Masanobu; Ji, Jiafu; Zhu, Wei-Guo; Yu, Duonan

    2016-01-01

    Objectives: The controversy of CpG island methylator phenotype (CIMP) in colorectal cancers (CRCs) persists, despite many studies that have been conducted on its correlation with molecular and clinicopathological features. To drive a more precise estimate of the strength of this postulated relationship, a meta-analysis was performed. Methods: A comprehensive search for studies reporting molecular and clinicopathological features of CRCs stratified by CIMP was performed within the PubMed, EMBASE, and Cochrane Library. CIMP was defined by either one of the three panels of gene-specific CIMP markers (Weisenberger panel, classic panel, or a mixture panel of the previous two) or the genome-wide DNA methylation profile. The associations of CIMP with outcome parameters were estimated using odds ratio (OR) or weighted mean difference (WMD) or hazard ratios (HRs) with 95% confidence interval (CI) for each study using a fixed effects or random effects model. Results: A total of 29 studies involving 9,393 CRC patients were included for analysis. We observed more BRAF mutations (OR 34.87; 95% CI, 22.49–54.06) and microsatellite instability (MSI) (OR 12.85 95% CI, 8.84–18.68) in CIMP-positive vs. -negative CRCs, whereas KRAS mutations were less frequent (OR 0.47; 95% CI, 0.30–0.75). Subgroup analysis showed that only the genome-wide methylation profile-defined CIMP subset encompassed all BRAF-mutated CRCs. As expected, CIMP-positive CRCs displayed significant associations with female (OR 0.64; 95% CI, 0.56–0.72), older age at diagnosis (WMD 2.77; 95% CI, 1.15–4.38), proximal location (OR 6.91; 95% CI, 5.17–9.23), mucinous histology (OR 3.81; 95% CI, 2.93–4.95), and poor differentiation (OR 4.22; 95% CI, 2.52–7.08). Although CIMP did not show a correlation with tumor stage (OR 1.10; 95% CI, 0.82–1.46), it was associated with shorter overall survival (HR 1.73; 95% CI, 1.27–2.37). Conclusions: The meta-analysis highlights that CIMP-positive CRCs take their own

  13. BRAF-Mutated Colorectal Cancer Exhibits Distinct Clinicopathological Features from Wild-Type BRAF-Expressing Cancer Independent of the Microsatellite Instability Status

    PubMed Central

    2017-01-01

    In patients with colorectal cancer (CRC), the BRAF V600E mutation has been reported to be associated with several clinicopathological features and poor survival. However, the prognostic implications of BRAF V600E mutation and the associated clinicopathological characteristics in CRCs remain controversial. Therefore, we reviewed various clinicopathological features, including BRAF status, in 349 primary CRCs and analyzed the relationship between BRAF status and various clinicopathological factors, including overall survival. Similar to previous studies conducted in Eastern countries, the incidence of the BRAF V600E mutation in the current study was relatively low (5.7%). BRAF-mutated CRC exhibits distinct clinicopathological features from wild-type BRAF-expressing cancer independent of the microsatellite instability (MSI) status. This mutation was significantly associated with a proximal tumor location (P = 0.002); mucinous, signet ring cell, and serrated tumor components (P < 0.001, P = 0.003, and P = 0.008, respectively); lymphovascular invasion (P = 0.004); a peritumoral lymphoid reaction (P = 0.009); tumor budding (P = 0.046); and peritoneal seeding (P = 0.012). In conclusion, the incidence of the BRAF V600E mutation was relatively low in this study. BRAF-mutated CRCs exhibited some clinicopathological features which were also frequently observed in MSI-H CRCs, such as a proximal location; mucinous, signet ring cell, and serrated components; and marked peritumoral lymphoid reactions. PMID:27914130

  14. [Prostate cancer in Guadeloupe (French West Indies): incidence, mortality and clinicopathological features].

    PubMed

    Brureau, L; Multigner, L; Wallois, A; Verhoest, G; Ndong, J-R; Fofana, M; Blanchet, P

    2009-02-01

    In mainland France, as in most Western countries, prostate cancer is the most frequent cancer in men. However, the incidence of this cancer is highly variable, depending on the region of the world. This variability is largely accounted for by differences in access to care, but also by environmental conditions and the ethnogeographic origins of the populations. The French West Indies--the archipelago of Guadeloupe and the island of Martinique--are unique in terms of their geography, environment and the lifestyle and origins of their populations. We report the incidence and mortality rates for prostate cancer in the French West Indies and also provide the first description of the major clinical and anatomical characteristics of this disease in this region.

  15. HPV-Associated Head and Neck Cancer: Unique Features of Epidemiology and Clinical Management.

    PubMed

    Maxwell, Jessica H; Grandis, Jennifer R; Ferris, Robert L

    2016-01-01

    Human papillomavirus (HPV) is a recently identified causative agent for a subset of head and neck cancers, primarily in the oropharynx, and is largely responsible for the rising worldwide incidence of oropharyngeal cancer (OPC). Patients with HPV-positive OPC have distinct risk factor profiles and generally have a better prognosis than patients with traditional, HPV-negative, head and neck cancer. Concurrent chemotherapy and radiation is a widely accepted primary treatment modality for many patients with HPV-positive OPC. However, recent advances in surgical modalities, including transoral laser and robotic surgery, have led to the reemergence of primary surgical treatment for HPV-positive patients. Clinical trials are under way to determine optimal treatment strategies for the growing subset of patients with HPV-positive OPC. Similarly, identifying those patients with HPV-positive cancer who are at risk for recurrence and poor survival is critical in order to tailor individual treatment regimens and avoid potential undertreatment.

  16. HPV-Associated Head and Neck Cancer: Unique Features of Epidemiology and Clinical Management

    PubMed Central

    Maxwell, Jessica H.; Grandis, Jennifer R.; Ferris, Robert L.

    2017-01-01

    Human papillomavirus (HPV) is a recently identified causative agent for a subset of head and neck cancers, primarily in the oropharynx, and is largely responsible for the rising worldwide incidence of oropharyngeal cancer (OPC). Patients with HPV-positive OPC have distinct risk factor profiles and generally have a better prognosis than patients with traditional, HPV-negative, head and neck cancer. Concurrent chemotherapy and radiation is a widely accepted primary treatment modality for many patients with HPV-positive OPC. However, recent advances in surgical modalities, including transoral laser and robotic surgery, have led to the reemergence of primary surgical treatment for HPV-positive patients. Clinical trials are under way to determine optimal treatment strategies for the growing subset of patients with HPV-positive OPC. Similarly, identifying those patients with HPV-positive cancer who are at risk for recurrence and poor survival is critical in order to tailor individual treatment regimens and avoid potential undertreatment. PMID:26332002

  17. Clinical features and survival of lung cancer patients with pleural effusions.

    PubMed

    Porcel, Jose M; Gasol, Ariadna; Bielsa, Silvia; Civit, Carme; Light, Richard W; Salud, Antonieta

    2015-05-01

    The clinical relevance of pleural effusions in lung cancer has seldom been approached systematically. The aim of this study was to determine the prevalence, causes and natural history of lung cancer-associated pleural effusions, as well as their influence on survival. Retrospective review of clinical records and imaging of 556 consecutive patients with a newly diagnosed lung cancer over a 4-year period at our institution. Lung cancer comprised 490 non-small cell and 66 small cell types. About 40% of patients with lung cancer developed pleural effusions at some time during the course of their disease. In half the patients, the effusions were too small to be tapped. These effusions did not progress to require a pleural intervention. Patients with minimal effusions had a worse prognosis compared to patients without pleural effusions (median survival of 7.49 vs 12.65 months, P < 0.001). Less than 20% of the 113 patients subjected to a diagnostic thoracentesis had benign causes for their effusions. Palliative pleural procedures (like therapeutic thoracenteses, pleurodesis or tunnelled pleural catheters) were conducted in 79 (84%) of the 94 malignant effusions. An effusion's size equal to or greater than half of the hemithorax was a strong predictor of the need for a palliative procedure. Overall survival of patients with malignant effusions was 5.49 months. Malignant pleural effusions are a poor prognostic factor in the setting of lung cancer, which includes minimal effusions not amenable to tapping. © 2015 Asian Pacific Society of Respirology.

  18. Features of the immunohistochemical characteristics of primary tumors and recurrences of breast cancer after radical treatment.

    PubMed

    Prystash, Yurij Y

    Appearance of Recurrence (RC) of breast cancer (BC) is associated with a high risk of distant metastases, needs re-treatment and indicates the tumor aggressiveness. It has been remained unclear the molecular characteristics both of the RC and primary tumors in patients with invasive forms of breast cancer after mastectomy by Madden. To explore the changing of the receptor status of the primary tumor and local RC in patients with breast cancer. Immunohistochemical study were conducted on 262 patients with invasive breast cancer. Patients were divided into two groups: only local RC - 131 women and primary tumors of patients without local RC - also 131 persons. The difference of the receptor status of the tumors is presented. In the group of patients with recurrent "triplet negative" cancer and patients with positive reaction of epidermal growth factor (HER2neo) is more than 15.2%. In patients where RC (control group in the study) was not observed we have the mass greater proportion of tumors with positive hormone receptors in various combinations. Relapses are accompanied by lower levels of hormone receptors and increasing the frequency of "triplet negative" cancer as well as increasing of epidermal growth factor.

  19. Utilizing spatial and spectral features of photoacoustic imaging for ovarian cancer detection and diagnosis

    NASA Astrophysics Data System (ADS)

    Li, Hai; Kumavor, Patrick; Salman Alqasemi, Umar; Zhu, Quing

    2015-01-01

    A composite set of ovarian tissue features extracted from photoacoustic spectral data, beam envelope, and co-registered ultrasound and photoacoustic images are used to characterize malignant and normal ovaries using logistic and support vector machine (SVM) classifiers. Normalized power spectra were calculated from the Fourier transform of the photoacoustic beamformed data, from which the spectral slopes and 0-MHz intercepts were extracted. Five features were extracted from the beam envelope and another 10 features were extracted from the photoacoustic images. These 17 features were ranked by their p-values from t-tests on which a filter type of feature selection method was used to determine the optimal feature number for final classification. A total of 169 samples from 19 ex vivo ovaries were randomly distributed into training and testing groups. Both classifiers achieved a minimum value of the mean misclassification error when the seven features with lowest p-values were selected. Using these seven features, the logistic and SVM classifiers obtained sensitivities of 96.39±3.35% and 97.82±2.26%, and specificities of 98.92±1.39% and 100%, respectively, for the training group. For the testing group, logistic and SVM classifiers achieved sensitivities of 92.71±3.55% and 92.64±3.27%, and specificities of 87.52±8.78% and 98.49±2.05%, respectively.

  20. Meta-Analysis of the Relationship between NM23 Expression to Gastric Cancer Risk and Clinical Features

    PubMed Central

    Liu, Zhimin; Huang, Hao; Lao, Min; Huang, Lingsha

    2017-01-01

    The prognostic value of reduced NM23 expression for gastric cancer (GC) patients is still contradictory. Thus, we conducted a meta-analysis to quantitatively evaluate the association of NM23 expression with GC risk and clinical features by analyzing 27 publications. The result of our meta-analysis indicated that NM23 expression is markedly reduced in gastric cancer tissues (OR = 3.15; 95% CI = 1.97–5.03; P < 0.001). Furthermore, NM23 expression was negatively correlated with N stage, TNM stage, and histological grade. However, NM23 expression was not correlated with T stage, lymphatic invasion, vascular invasion, and 5-year overall survival rate. In conclusion, reduced NM23 expression correlated with gastric cancer risk, but its association with GC clinical features remains inconclusive. Therefore, large-scale and well-designed studies, which use uniform antibody and criterion of NM23 positive expression, are required to further validate the role of the NM23 in predicting GC progression. PMID:28401162

  1. Assessment of a Four-View Mammographic Image Feature Based Fusion Model to Predict Near-Term Breast Cancer Risk.

    PubMed

    Tan, Maxine; Pu, Jiantao; Cheng, Samuel; Liu, Hong; Zheng, Bin

    2015-10-01

    The purpose of this study was to develop and assess a new quantitative four-view mammographic image feature based fusion model to predict the near-term breast cancer risk of the individual women after a negative screening mammography examination of interest. The dataset included fully-anonymized mammograms acquired on 870 women with two sequential full-field digital mammography examinations. For each woman, the first "prior" examination in the series was interpreted as negative (not recalled) during the original image reading. In the second "current" examination, 430 women were diagnosed with pathology verified cancers and 440 remained negative ("cancer-free"). For each of four bilateral craniocaudal and mediolateral oblique view images of left and right breasts, we computed and analyzed eight groups of global mammographic texture and tissue density image features. A risk prediction model based on three artificial neural networks was developed to fuse image features computed from two bilateral views of four images. The risk model performance was tested using a ten-fold cross-validation method and a number of performance evaluation indices including the area under the receiver operating characteristic curve (AUC) and odds ratio (OR). The highest AUC = 0.725 ± 0.026 was obtained when the model was trained by gray-level run length statistics texture features computed on dense breast regions, which was significantly higher than the AUC values achieved using the model trained by only two bilateral one-view images (p < 0.02). The adjustable OR values monotonically increased from 1.0 to 11.8 as model-generated risk score increased. The regression analysis of OR values also showed a significant increase trend in slope (p < 0.01). As a result, this preliminary study demonstrated that a new four-view mammographic image feature based risk model could provide useful and supplementary image information to help predict the near-term breast cancer risk.

  2. Can BI-RADS features on mammography be used as a surrogate for expensive genomic testing in breast cancer patients?

    NASA Astrophysics Data System (ADS)

    Harowicz, Michael R.; Marks, Jeffrey R.; Marcom, P. Kelly; Mazurowski, Maciej A.

    2017-03-01

    Medical oncologists increasingly rely on expensive genomic analysis to stratify patients for different treatment. The genomic markers are able to divide patients into groups that behave differently in terms of tumor presentation, likelihood of metastatic spread, and response to chemotherapy and radiation therapy. In recent years there has been a rapid increase in the number of genomic tests available, like the Oncotype DX test, which provides the risk of cancer recurrence for a subset of patients. Radiogenomics, a new field that investigates the relationship between imaging phenotypes and genomic characteristics, may offer a less expensive and less invasive imaging surrogate for molecular subtype and Oncotype DX recurrence score (ODRS). This retrospective study analyzes the relationship between Breast Imaging-Reporting and Data System (BI-RADS) features as assessed by radiologists on mammograms with molecular subtype and ODRS. We used data from patients with BI-RADS features (shape or margin) and a genomic feature (subtype or ODRS) for the following cohort: shape vs. subtype (n=69), margin vs. subtype (n=78), shape vs. ODRS (n=20), and margin vs. ODRS (n=18). The association between features was assessed using a Fisher's exact test. Our results show that shape assessed by radiologists according to the BI-RADS lexicon is associated with molecular subtype (p=0.0171), while BI-RADS features of shape and margin were not significantly associated with ODRS (p=0.7839, p=0.6047 respectively).

  3. The clinicopathological and prognostic features of Chinese and Japanese inpatients with lung cancer

    PubMed Central

    Li, Qing-chang; Liu, Jia-jie; Liu, Li-li; Yang, Xue-feng; Jiang, Hua-mao; Zheng, Hua-chuan

    2016-01-01

    Here, we retrospectively compared the differences in clinicopathological behaviors and prognosis of lung cancer from the First Affiliated Hospital (CMU1, n=513), Shengjing Hospital (CMUS, n=1021), Tumor Hospital (CMUT, n=5378) of China Medical University, the First Affiliated Hospital of Dalian (DMU, n=2251) and Jinzhou (JMU, n=630) Medical University, Takaoka Kouseiren Hospital (Takaoka, n=163) of Japan. Japanese lung cancer patients showed smaller tumor size, lower TNM staging, lower ratio of squamous cell carcinoma and higher ratio of small and large cell carcinomas than Chinese patients (p<0.05). Survival analysis showed that tumor size was employed as a prognostic factor for the Japanese and Chinese cancer patients (p<0.05). In DMU and CMUS, the ratios of female patients or adenocarcinoma were higher than other hospitals (p<0.05), while the patients from CMUT and CMU1 were younger than the others (p<0.05). The ratios of squamous cell carcinoma from CMUT, CMU1 and JMU were higher than the others, while it was the same for the ratio of large and small cell carcinoma in Takaoka and CMU1 (p<0.05). TNM staging was higher in CMUT than JMU and Takaoka (p<0.05). The female patients of lung cancer showed young prone, large tumor size, a high ratio of adenocarcinoma and advanced TNM staging in comparison to the counterpart (p<0.05). The younger patients of lung cancer displayed smaller tumor size, higher ratio of adenocarcinoma, lower TNM staging than the elder in Takaoka (p<0.05). There were more aggressive behaviors and shorter survival time for Chinese than Japanese lung cancer patients. The prevention of lung cancer should be strengthened by establishing a systematic and effective screening strategy, especially for the young and female patients. PMID:27608841

  4. Aberrant Keap1 methylation in breast cancer and association with clinicopathological features

    PubMed Central

    Barbano, Raffaela; Muscarella, Lucia Anna; Pasculli, Barbara; Valori, Vanna Maria; Fontana, Andrea; Coco, Michelina; la Torre, Annamaria; Balsamo, Teresa; Poeta, Maria Luana; Marangi, Giovanni Francesco; Maiello, Evaristo; Castelvetere, Marina; Pellegrini, Fabio; Murgo, Roberto; Fazio, Vito Michele; Parrella, Paola

    2013-01-01

    Keap1 (Kelch-like ECH-associated protein 1) is an adaptor protein that mediates the ubiquitination/degradation of genes regulating cell survival and apoptosis under oxidative stress conditions. We determined methylation status of the KEAP1 promoter in 102 primary breast cancers, 14 pre-invasive lesions, 38 paired normal breast tissues and 6 normal breast from reductive mammoplasty by quantitative methylation specific PCR (QMSP). Aberrant promoter methylation was detected in 52 out of the 102 primary breast cancer cases (51%) and 10 out of 14 pre-invasive lesions (71%). No mutations of the KEAP1 gene were identified in the 20 breast cancer cases analyzed by fluorescence based direct sequencing. Methylation was more frequent in the subgroup of patients identified as ER positive-HER2 negative tumors (66.7%) as compared with triple-negative breast cancers (35%) (p = 0.05, Chi-square test). The impact of the interactions between Er, PgR, Her2 expression and KEAP1 methylation on mortality was investigated by RECPAM multivariable statistical analysis, identifying four prognostic classes at different mortality risks. Triple-negative breast cancer patients with KEAP1 methylation had higher mortality risk than patients without triple-negative breast cancer (HR = 14.73, 95%CI: 3.65–59.37). Both univariable and multivariable COX regressions analyses showed that KEAP1 methylation was associated with a better progression free survival in patients treated with epirubicin/cyclophosfamide and docetaxel as sequential chemotherapy (HR = 0.082; 95%CI: 0.007–0.934). These results indicate that aberrant promoter methylation of the KEAP1 gene is involved in breast cancerogenesis. In addition, identifying patients with KEAP1 epigenetic abnormalities may contribute to disease progression prediction in breast cancer patients. PMID:23249627

  5. Deletion of 18q is a strong and independent prognostic feature in prostate cancer.

    PubMed

    Kluth, Martina; Graunke, Maximilian; Möller-Koop, Christina; Hube-Magg, Claudia; Minner, Sarah; Michl, Uwe; Graefen, Markus; Huland, Hartwig; Pompe, Raisa; Jacobsen, Frank; Hinsch, Andrea; Wittmer, Corinna; Lebok, Patrick; Steurer, Stefan; Büscheck, Franziska; Clauditz, Till; Wilczak, Waldemar; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald

    2016-12-27

    Deletion of 18q recurrently occurs in prostate cancer. To evaluate its clinical relevance, dual labeling fluorescence in-situ hybridization (FISH) using probes for 18q21 and centromere 18 was performed on a prostate cancer tissue microarray (TMA). An 18q deletion was found in 517 of 6,881 successfully analyzed cancers (7.5%). 18q deletion was linked to unfavorable tumor phenotype. An 18q deletion was seen in 6.4% of 4,360 pT2, 8.0% of 1,559 pT3a and 11.8% of 930 pT3b-pT4 cancers (P < 0.0001). Deletions of 18q were detected in 6.9% of 1,636 Gleason ≤ 3 + 3, 6.8% of 3,804 Gleason 3 + 4, 10.1% of 1,058 Gleason 4+3, and 9.9% of 344 Gleason ≥ 4 + 4 tumors (P = 0.0013). Deletions of 18q were slightly more frequent in ERG-fusion negative (8.2%) than in ERG-fusion positive cancers (6.4%, P = 0.0063). 18q deletions were also linked to biochemical recurrence (BCR, P < 0.0001). This was independent from established pre- and postoperative prognostic factors (P ≤ 0.0004). In summary, the results of our study identify 18q deletion as an independent prognostic parameter in prostate cancer. As it is easy to measure, 18q deletion may be a suitable component for multiparametric molecular prostate cancer prognosis tests.

  6. Deletion of 18q is a strong and independent prognostic feature in prostate cancer

    PubMed Central

    Möller-Koop, Christina; Hube-Magg, Claudia; Minner, Sarah; Michl, Uwe; Graefen, Markus; Huland, Hartwig; Pompe, Raisa; Jacobsen, Frank; Hinsch, Andrea; Wittmer, Corinna; Lebok, Patrick; Steurer, Stefan; Büscheck, Franziska; Clauditz, Till; Wilczak, Waldemar; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald

    2016-01-01

    Deletion of 18q recurrently occurs in prostate cancer. To evaluate its clinical relevance, dual labeling fluorescence in-situ hybridization (FISH) using probes for 18q21 and centromere 18 was performed on a prostate cancer tissue microarray (TMA). An 18q deletion was found in 517 of 6,881 successfully analyzed cancers (7.5%). 18q deletion was linked to unfavorable tumor phenotype. An 18q deletion was seen in 6.4% of 4,360 pT2, 8.0% of 1,559 pT3a and 11.8% of 930 pT3b-pT4 cancers (P < 0.0001). Deletions of 18q were detected in 6.9% of 1,636 Gleason ≤ 3 + 3, 6.8% of 3,804 Gleason 3 + 4, 10.1% of 1,058 Gleason 4+3, and 9.9% of 344 Gleason ≥ 4 + 4 tumors (P = 0.0013). Deletions of 18q were slightly more frequent in ERG-fusion negative (8.2%) than in ERG-fusion positive cancers (6.4%, P = 0.0063). 18q deletions were also linked to biochemical recurrence (BCR, P < 0.0001). This was independent from established pre- and postoperative prognostic factors (P ≤ 0.0004). In summary, the results of our study identify 18q deletion as an independent prognostic parameter in prostate cancer. As it is easy to measure, 18q deletion may be a suitable component for multiparametric molecular prostate cancer prognosis tests. PMID:27861151

  7. Aberrant Keap1 methylation in breast cancer and association with clinicopathological features.

    PubMed

    Barbano, Raffaela; Muscarella, Lucia Anna; Pasculli, Barbara; Valori, Vanna Maria; Fontana, Andrea; Coco, Michelina; la Torre, Annamaria; Balsamo, Teresa; Poeta, Maria Luana; Marangi, Giovanni Francesco; Maiello, Evaristo; Castelvetere, Marina; Pellegrini, Fabio; Murgo, Roberto; Fazio, Vito Michele; Parrella, Paola

    2013-01-01

    Keap1 (Kelch-like ECH-associated protein 1) is an adaptor protein that mediates the ubiquitination/degradation of genes regulating cell survival and apoptosis under oxidative stress conditions. We determined methylation status of the KEAP1 promoter in 102 primary breast cancers, 14 pre-invasive lesions, 38 paired normal breast tissues and 6 normal breast from reductive mammoplasty by quantitative methylation specific PCR (QMSP). Aberrant promoter methylation was detected in 52 out of the 102 primary breast cancer cases (51%) and 10 out of 14 pre-invasive lesions (71%). No mutations of the KEAP1 gene were identified in the 20 breast cancer cases analyzed by fluorescence based direct sequencing. Methylation was more frequent in the subgroup of patients identified as ER positive-HER2 negative tumors (66.7%) as compared with triple-negative breast cancers (35%) (p = 0.05, Chi-square test). The impact of the interactions between Er, PgR, Her2 expression and KEAP1 methylation on mortality was investigated by RECPAM multivariable statistical analysis, identifying four prognostic classes at different mortality risks. Triple-negative breast cancer patients with KEAP1 methylation had higher mortality risk than patients without triple-negative breast cancer (HR = 14.73, 95%CI: 3.65-59.37). Both univariable and multivariable COX regressions analyses showed that KEAP1 methylation was associated with a better progression free survival in patients treated with epirubicin/cyclophosfamide and docetaxel as sequential chemotherapy (HR = 0.082; 95%CI: 0.007-0.934). These results indicate that aberrant promoter methylation of the KEAP1 gene is involved in breast cancerogenesis. In addition, identifying patients with KEAP1 epigenetic abnormalities may contribute to disease progression prediction in breast cancer patients.

  8. Cancers in BRCA1 and BRCA2 carriers and in women at high risk for breast cancer: MR imaging and mammographic features.

    PubMed

    Gilbert, Fiona J; Warren, Ruth M L; Kwan-Lim, Gek; Thompson, Deborah J; Eeles, Ros A; Evans, D Gareth; Leach, Martin O

    2009-08-01

    To review imaging features of screening-detected cancers on images from diagnostic and prior examinations to identify specific abnormalities to aid earlier detection of or facilitate differentiation of cancers in BRCA1 and BRCA2 carriers and in women with a high risk for breast cancer. Informed consent and multicenter and local research ethics committee approval were obtained. Women (mean age, 40.1 years; range, 27-55 years) who had at least a 50% risk of being a BRCA1, BRCA2, or TP53 gene mutation carrier were recruited from August 1997 to March 2003 into the United Kingdom Magnetic Resonance Imaging in Breast Screening Study Group trial and were offered annual magnetic resonance (MR) imaging and two-view mammography (total number of screenings, 2065 and 1973; mean, 2.38 and 2.36, respectively). Images in all 39 cancer cases were reread in consensus to document the morphologic and enhancement imaging features on MR and mammographic images in screening and prior examinations. Cases were grouped into genetic subtypes. With MR imaging, there was no difference in morphologic or enhancement characteristics between the genetic subgroups. Cancers on images from prior examinations were of smaller size, showed less enhancement, and were more likely to have a type 1 enhancement curve compared with those cancers in the subsequent diagnostic screening examinations. The tumor sizes detected by using MR imaging and mammography were not significantly different (P = .46). The cancers in BRCA1 carriers found by using MR imaging tended to be smaller than those detected by using mammography (median, 17 mm vs 30 mm; P = .37), whereas the opposite was true for cancers found in BRCA2 carriers (MR imaging median size = 12.5 mm vs mammographic median size = 6 mm; P = .067); the difference was not significant. Tumors with prior MR imaging abnormalities grew at an average of 5.1 mm/y. When undertaking MR imaging surveillance in high-risk women, small enhancing lesions should be regarded

  9. Pathological features and survival outcomes of very young patients with early breast cancer: how much is "very young"?

    PubMed

    Cancello, Giuseppe; Maisonneuve, Patrick; Mazza, Manuelita; Montagna, Emilia; Rotmensz, Nicole; Viale, Giuseppe; Pruneri, Giancarlo; Veronesi, Paolo; Luini, Alberto; Gentilini, Oreste; Goldhirsch, Aron; Colleoni, Marco

    2013-12-01

    We collected information on 497 consecutive breast cancer patients aged less than 35 years operated at the European Institute of Oncology. The main aim of the study is to compare biological and clinical features dividing the population by age: <25 years, 25-29 and 30-34 years old. Pattern of recurrence and survival were also analyzed. Patients aged <25 years had 81.8% poorly differentiated tumors compared with 66.7% and 56.5% in the 25-29 and 30-34 groups, respectively; no other significant difference were found in the distribution of clinical and immunohistochemical features The distribution of Luminal A and B, Triple Negative and HER2 subtypes (immunohistochemically defined) was not statistically different among the three age groups. No difference was found in the incidence of loco-regional relapses, distant metastases, disease-free survival (p = 0.79) and overall survival (p = 0.99) between the three age groups. This latter findings was confirmed using age as a continuous variable assuming a linear association between age and the outcomes considered, too. In conclusion, our data indicate that the group of patients with breast cancer below 35 years is essentially a homogenous group when classical clinical and immunohistochemical features were considered. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Comparison of Clinicopathological Features and Prognosis in Triple-Negative and Non-Triple Negative Breast Cancer

    PubMed Central

    Qiu, Jingdan; Xue, Xinying; Hu, Chao; Xu, Hu; Kou, Deqiang; Li, Rong; Li, Ming

    2016-01-01

    Purpose: Triple-negative breast cancer (TNBC) has attracted more attention both clinically and experimentally because of its high-risk biological characteristics and lacking of effective treatment method. The purpose of this retrospective study was to find out the incidence of triple-negative breast cancer (TNBC) in all kinds of breast cancers and to compare and analyze the clinicopathological features, recurrence, metastasis and prognosis of patients with TNBC and non-triple negative breast cancer (non-TNBC). Methods: A total of 1578 female patients with primary breast cancer were diagnosed and treated at the department of General Surgery, the Chinese PLA General Hospital, China, from Jan. 2004 to Jun. 2009. The 1578 breast cancer patients were divided into two groups: the TNBC group and the non-TNBC group. The clinical features and prognosis of the two groups were compared. Results: The incidence of TNBC was 20.41%. Compared with the non-TNBC, the TNBC were characterized as younger age, higher histological grade, higher rate of positive lymph node, bigger tumor size, higher clinical stage at diagnosis, higher histological grade, quicker and easier recurrence and metastasis and lower 5-year DFS rate and 5-year OS rate. The metastasis of TNBC had obvious organic tendency. The lungs, liver and brain were the first three most common sites of metastases. The information of age, the tumor size, lymph node status, clinical stage, histological grade, pathological types and operation method, especially the age and lymph node status play the important roles in judging the prognosis of TNBC. Conclusions: According to this study we found that TNBC was a distinct subgroup of breast cancer with particular clinicopathologic behavior. Compared with the non-TNBC, TNBC was characterized by more aggressive behavior, and lower DFS and OS rate. The metastasis of TNBC had obvious organic tendency. The information of age, the maximum diameter of the tumor, lymph node status, clinical

  11. Clinicopathological features and outcome of gastric metastases from primary lung cancer: A case report and systematic review

    PubMed Central

    HUANG, QINGYUAN; SU, XIAODONG; BELLA, AMOS ELA; LUO, KONGJIA; JIN, JIETIAN; ZHANG, SHUISHEN; LUO, GUANGYU; RONG, TIEHUA; FU, JIANHUA

    2015-01-01

    Primary lung cancer is the fourth most frequently diagnosed cancer, but gastric metastasis from lung cancer is extremely rare. Little is known about its clinicopathological features, prognosis and optimal treatment strategy. The present study reports a case of primary lung cancer that metastasized to the stomach and to the best of our knowledge, is the first to identify discordance in epidermal growth factor receptor (EGFR) mutation status between the primary tumor and gastric metastasis. The study also systematically searched the Medline database for similar cases to provide a literature review. Data concerning the clinicopathological features, treatment strategies and outcomes were extracted and analyzed. In total, 22 eligible cases were identified from 16 studies. The average age at presentation was 67.3 years and there was a male predominance of 90.9%. Epigastric pain (45.5%) was the most common chief complaint, followed by melena (22.7%), nausea/vomiting (13.6%) and hematemesis (9.1%). Three patients were asymptomatic. Five patients sought the initial consultation for gastrointestinal symptoms. The median time between the primary lung cancer diagnosis and the confirmation of gastric metastasis was five months. Endoscopically, gastric lesions were described as polypoid masses or volcano-like ulcers, mostly involving the gastric corpus, which were identified in 62.5% of the 16 cases in which information regarding the site of metastasis was available. Gastric metastases were reported from adenocarcinoma, squamous cell carcinoma, small cell lung cancer and pleomorphic carcinoma of the lung. The median survival following comprehensive treatment strategies was four months, and the one-year post-metastasis survival rate was 35.3%. In conclusion, although primary lung cancer metastasis to the stomach is rare, clinicians should be aware of the possibility of its occurrence. Comprehensive and personalized treatment may be beneficial to patients. EGFR tyrosine

  12. DNA methylation and breast tumor clinicopathological features: The Western New York Exposures and Breast Cancer (WEB) study.

    PubMed

    Callahan, Catherine L; Wang, Youjin; Marian, Catalin; Weng, Daniel Y; Eng, Kevin H; Tao, Meng-Hua; Ambrosone, Christine B; Nie, Jing; Trevisan, Maurizio; Smiraglia, Dominic; Edge, Stephen B; Shields, Peter G; Freudenheim, Jo L

    2016-09-01

    We evaluated the association between methylation of 9 genes, SCGB3A1, GSTP1, RARB, SYK, FHIT, CDKN2A, CCND2, BRCA1, and SFN in tumor samples from 720 breast cancer cases with clinicopathological features of the tumors and survival. Logistic regression was used to estimate odds ratios (OR) of methylation and Cox proportional hazards models to estimate hazard ratios (HR) between methylation and breast cancer related mortality. Estrogen receptor (ER) and progesterone receptor (PR) positivity were associated with increased SCGB3A1 methylation among pre- and post-menopausal cases. Among premenopausal women, compared with Stage 0 cases, cases of invasive cancer were more likely to have increased methylation of RARB (Stage I OR = 4.7, 95% CI: 1.1-19.0; Stage IIA/IIB OR = 9.7, 95% CI: 2.4-39.9; Stage III/IV OR = 5.6, 95% CI: 1.1-29.4) and lower methylation of FHIT (Stage I OR = 0.2, 95% CI: 0.1-0.9; Stage IIA/IIB OR = 0.2, 95% CI: 0.1-0.8; Stage III/IV OR = 0.6, 95% CI: 0.1-3.4). Among postmenopausal women, methylation of SYK was associated with increased tumor size (OR = 1.7, 95% CI: 1.0-2.7) and higher nuclear grade (OR = 2.0, 95% CI 1.2-3.6). Associations between methylation and breast cancer related mortality were observed among pre- but not post-menopausal women. Methylation of SCGB3A1 was associated with reduced risk of death from breast cancer (HR = 0.41, 95% CI: 0.17-0.99) as was BRCA1 (HR = 0.41, 95% CI: 0.16-0.97). CCND2 methylation was associated with increased risk of breast cancer mortality (HR = 3.4, 95% CI: 1.1-10.5). We observed differences in methylation associated with tumor characteristics; methylation of these genes was also associated with breast cancer survival among premenopausal cases. Understanding of the associations of DNA methylation with other clinicopathological features may have implications for prevention and treatment.

  13. Expression profile of SIX family members correlates with clinic-pathological features and prognosis of breast cancer

    PubMed Central

    Xu, Han-Xiao; Wu, Kong-Ju; Tian, Yi-Jun; Liu, Qian; Han, Na; He, Xue-Lian; Yuan, Xun; Wu, Gen Sheng; Wu, Kong-Ming

    2016-01-01

    Abstract Sineoculis homeobox homolog (SIX) family proteins, including SIX1, SIX2, SIX3, SIX4, SIX5, and SIX6, have been implicated in the initiation and progression of breast cancer, but the role of each member in breast tumor is not fully understood. We conducted a systematic review and meta-analysis to evaluate the association between the mRNA levels of all 6 members and clinic-pathological characteristics and clinical outcome of breast cancer patients based on the PRISMA statement criteria. ArrayExpress and Oncomine were searched for eligible databases published up to December 10, 2015. The association between the mRNA expression of SIX family members and clinic-pathological features and prognosis was measured by the odds ratio (OR), hazard ratio (HR), and the corresponding 95% confidence interval (CI), respectively. All statistical analyses were performed using STATA software. In total, 20 published Gene Expression Omnibus (GEO) databases with 3555 patients were analyzed. Our analysis revealed that patients with SIX1 overexpression had worse overall survival (OS) (HR: 1.28, 95% CI: 1.03–1.58) and shorter relapse-free survival (RFS) (HR: 1.28, 95% CI: 1.05–1.56), and much worse prognosis for luminal breast cancer patients with SIX1 overexpression (OS: HR: 1.64, 95% CI: 1.13–2.39; RFS: HR: 1.43, 95% CI: 1.06–1.93). We found that patients with higher SIX2 level had shorter time to both relapse and metastasis. However, high SIX3 mRNA level was a protective factor for OS and RFS of basal-like breast cancer patients. Our study suggested that members of SIX family played distinct roles in breast cancer. Detailed analysis of the expression of the SIX family members might provide useful information to predict breast cancer progression and prognosis. PMID:27399099

  14. Mutational load of the mitochondrial genome predicts pathological features and biochemical recurrence in prostate cancer

    PubMed Central

    Kalsbeek, Anton M.F.; Chan, Eva F.K.; Grogan, Judith; Petersen, Desiree C.; Jaratlerdsiri, Weerachai; Gupta, Ruta; Lyons, Ruth J.; Haynes, Anne Maree; Horvath, Lisa G.; Kench, James G.; Stricker, Phillip D.; Hayes, Vanessa M.

    2016-01-01

    Prostate cancer management is complicated by extreme disease heterogeneity, which is further limited by availability of prognostic biomarkers. Recognition of prostate cancer as a genetic disease has prompted a focus on the nuclear genome for biomarker discovery, with little attention given to the mitochondrial genome. While it is evident that mitochondrial DNA (mtDNA) mutations are acquired during prostate tumorigenesis, no study has evaluated the prognostic value of mtDNA variation. Here we used next-generation sequencing to interrogate the mitochondrial genomes from prostate tissue biopsies and matched blood of 115 men having undergone a radical prostatectomy for which there was a mean of 107 months clinical follow-up. We identified 74 unique prostate cancer specific somatic mtDNA variants in 50 patients, providing significant expansion to the growing catalog of prostate cancer mtDNA mutations. While no single variant or variant cluster showed recurrence across multiple patients, we observe a significant positive correlation between the total burden of acquired mtDNA variation and elevated Gleason Score at diagnosis and biochemical relapse. We add to accumulating evidence that total acquired genomic burden, rather than specific mtDNA mutations, has diagnostic value. This is the first study to demonstrate the prognostic potential of mtDNA mutational burden in prostate cancer. PMID:27705925

  15. A standardised protocol for texture feature analysis of endoscopic images in gynaecological cancer

    PubMed Central

    Neofytou, Marios S; Tanos, Vasilis; Pattichis, Marios S; Pattichis, Constantinos S; Kyriacou, Efthyvoulos C; Koutsouris, Dimitris D

    2007-01-01

    Background In the development of tissue classification methods, classifiers rely on significant differences between texture features extracted from normal and abnormal regions. Yet, significant differences can arise due to variations in the image acquisition method. For endoscopic imaging of the endometrium, we propose a standardized image acquisition protocol to eliminate significant statistical differences due to variations in: (i) the distance from the tissue (panoramic vs close up), (ii) difference in viewing angles and (iii) color correction. Methods We investigate texture feature variability for a variety of targets encountered in clinical endoscopy. All images were captured at clinically optimum illumination and focus using 720 × 576 pixels and 24 bits color for: (i) a variety of testing targets from a color palette with a known color distribution, (ii) different viewing angles, (iv) two different distances from a calf endometrial and from a chicken cavity. Also, human images from the endometrium were captured and analysed. For texture feature analysis, three different sets were considered: (i) Statistical Features (SF), (ii) Spatial Gray Level Dependence Matrices (SGLDM), and (iii) Gray Level Difference Statistics (GLDS). All images were gamma corrected and the extracted texture feature values were compared against the texture feature values extracted from the uncorrected images. Statistical tests were applied to compare images from different viewing conditions so as to determine any significant differences. Results For the proposed acquisition procedure, results indicate that there is no significant difference in texture features between the panoramic and close up views and between angles. For a calibrated target image, gamma correction provided an acquired image that was a significantly better approximation to the original target image. In turn, this implies that the texture features extracted from the corrected images provided for better approximations

  16. Long Noncoding RNA H19 in Digestive System Cancers: A Meta-Analysis of Its Association with Pathological Features.

    PubMed

    Lin, Yang; Xu, Lijian; Wei, Wei; Zhang, Xiaohui; Ying, Rongchao

    2016-01-01

    Long noncoding RNA (lncRNA) H19 has been reported to be upregulated in malignant digestive tumors, but its clinical relevance is not yet established. The meta-analysis was to investigate the association between H19 expression and pathological features of digestive system cancers. The databases of PubMed, EMBase, Web of Science, CNKI, and WanFang were searched for the related studies. A total of 478 patients from 6 studies were finally included. The meta-analysis showed that the patient group of high H19 expression had a higher risk of poorly differentiated grade, deep tumor invasion (T2 stage or more), lymph node metastasis, and advanced TNM stage than the group of low H19 expression, although there was no difference between them in terms of distant metastasis. Therefore, the high expression of lncRNA H19 might predict poor oncological outcomes of patients with digestive system cancers.

  17. SOX2 promotes dedifferentiation and imparts stem cell-like features to pancreatic cancer cells

    PubMed Central

    Herreros-Villanueva, M; Zhang, J-S; Koenig, A; Abel, E V; Smyrk, T C; Bamlet, W R; de Narvajas, A A-M; Gomez, T S; Simeone, D M; Bujanda, L; Billadeau, D D

    2013-01-01

    SOX2 (Sex-determining region Y (SRY)-Box2) has important functions during embryonic development and is involved in cancer stem cell (CSC) maintenance, in which it impairs cell growth and tumorigenicity. However, the function of SOX2 in pancreatic cancer cells is unclear. The objective of this study was to analyze SOX2 expression in human pancreatic tumors and determine the role of SOX2 in pancreatic cancer cells regulating CSC properties. In this report, we show that SOX2 is not expressed in normal pancreatic acinar or ductal cells. However, ectopic expression of SOX2 is observed in 19.3% of human pancreatic tumors. SOX2 knockdown in pancreatic cancer cells results in cell growth inhibition via cell cycle arrest associated with p21Cip1 and p27Kip1 induction, whereas SOX2 overexpression promotes S-phase entry and cell proliferation associated with cyclin D3 induction. SOX2 expression is associated with increased levels of the pancreatic CSC markers ALDH1, ESA and CD44. Importantly, we show that SOX2 is enriched in the ESA+/CD44+ CSC population from two different patient samples. Moreover, we show that SOX2 directly binds to the Snail, Slug and Twist promoters, leading to a loss of E-Cadherin and ZO-1 expression. Taken together, our findings show that SOX2 is aberrantly expressed in pancreatic cancer and contributes to cell proliferation and stemness/dedifferentiation through the regulation of a set of genes controlling G1/S transition and epithelial-to-mesenchymal transition (EMT) phenotype, suggesting that targeting SOX2-positive cancer cells could be a promising therapeutic strategy. PMID:23917223

  18. Body mass index (BMI) and breast cancer: impact on tumor histopathologic features, cancer subtypes and recurrence rate in pre and postmenopausal women.

    PubMed

    Biglia, Nicoletta; Peano, Elisa; Sgandurra, Paola; Moggio, Giulia; Pecchio, Silvia; Maggiorotto, Furio; Sismondi, Piero

    2013-03-01

    The study aims to analyze the association between body mass index (BMI) at time of diagnosis, breast cancer histopathologic features (tumor size, nuclear grade, estrogen and progesterone receptor (ER and PgR) and HER-2/neu expression, histological subtypes, Ki-67 index, lymphatic/vascular invasion, axillary nodes involvement) and incidence of different subtypes defined using hormone receptors and HER2/neu expression, according to menopausal status; to evaluate the impact of BMI on disease free survival (DFS) at multivariate analysis. A total of 2148 patients (592 premenopausal, 1556 postmenopausal) were classified into subgroups according to BMI distribution. High BMI was significantly associated with larger size tumor both in pre (p = 0.01) and postmenopausal women (p = 0.00). Obese premenopausal women showed worse histopathologic features (more metastatic axillary lymphnodes, p = 0.017 and presence of vascular invasion, p = 0.006) compared to under/normal weight group. Postmenopausal patients with BMI > 25 developed more frequently ER/PgR positive cancers (87% versus 75%, p 0.017), while no association was found in premenopausal women. We could not found any statistically significant correlation between breast cancer subtypes (luminal A, B, HER-2 and basal-like) and BMI both in pre and postmenopause. Higher BMI was significantly associated with a shorter DR-FS in postmenopausal women but the independent prognostic role of obesity was not confirmed in our analysis.

  19. A comparison of clinicopathological features and prognosis in prostate cancer between atomic bomb survivors and control patients.

    PubMed

    Shoji, Koichi; Teishima, Jun; Hayashi, Tetsutaro; Shinmei, Shunsuke; Akita, Tomoyuki; Sentani, Kazuhiro; Takeshima, Yukio; Arihiro, Koji; Tanaka, Junko; Yasui, Wataru; Matsubara, Akio

    2017-07-01

    An atomic bomb (A-bomb) was dropped on Hiroshima on 6th August 1945. Although numerous studies have investigated cancer incidence and mortality among A-bomb survivors, only a small number have addressed urological cancer in these survivors. The aim of the present study was to investigate the clinicopathological features of prostate cancer (PCa) in A-bomb survivors. The clinicopathological features and prognosis of PCa were retrospectively reviewed in 212 survivors and 595 control patients between November 1996 and December 2010. The histopathological and clinical outcomes of surgical treatment of PCa were also evaluated in 69 survivors and 162 control patients. Despite the higher age at diagnosis compared with the control group (P=0.0031), survivors were more likely to have been diagnosed with PCa from a health check compared with the control group (P<0.0001). As a consequence, the survivors were found to exhibit metastasis significantly less frequently (199/212, 93.9%) compared with the control patients (521/595, 87.6%; P=0.0076). Prognosis in the two groups was examined, subsequent to a mean length of follow-up of 44 months. Overall survival (OS) and PCa-specific survival (CS) were similar between the two groups (OS, P=0.2196; CS, P=0.1017). A-bomb exposure was not found to be an independent predictor for prognosis by multivariate analysis (OS, P=0.7800; CS, P=0.8688). The clinicopathological features of patients who underwent a prostatectomy were similar except for the diagnosis opportunity between the two groups. Progression-free survival rates were similar between the two groups (P=0.5630). A-bomb exposure was not a significant and independent predictor for worsening of progression-free prognosis by multivariate analysis (P=0.3763). A-bomb exposure does not appear to exert deleterious effects on the biological aggressiveness of PCa and the prognosis of patients with PCa.

  20. A comparison of clinicopathological features and prognosis in prostate cancer between atomic bomb survivors and control patients

    PubMed Central

    Shoji, Koichi; Teishima, Jun; Hayashi, Tetsutaro; Shinmei, Shunsuke; Akita, Tomoyuki; Sentani, Kazuhiro; Takeshima, Yukio; Arihiro, Koji; Tanaka, Junko; Yasui, Wataru; Matsubara, Akio

    2017-01-01

    An atomic bomb (A-bomb) was dropped on Hiroshima on 6th August 1945. Although numerous studies have investigated cancer incidence and mortality among A-bomb survivors, only a small number have addressed urological cancer in these survivors. The aim of the present study was to investigate the clinicopathological features of prostate cancer (PCa) in A-bomb survivors. The clinicopathological features and prognosis of PCa were retrospectively reviewed in 212 survivors and 595 control patients between November 1996 and December 2010. The histopathological and clinical outcomes of surgical treatment of PCa were also evaluated in 69 survivors and 162 control patients. Despite the higher age at diagnosis compared with the control group (P=0.0031), survivors were more likely to have been diagnosed with PCa from a health check compared with the control group (P<0.0001). As a consequence, the survivors were found to exhibit metastasis significantly less frequently (199/212, 93.9%) compared with the control patients (521/595, 87.6%; P=0.0076). Prognosis in the two groups was examined, subsequent to a mean length of follow-up of 44 months. Overall survival (OS) and PCa-specific survival (CS) were similar between the two groups (OS, P=0.2196; CS, P=0.1017). A-bomb exposure was not found to be an independent predictor for prognosis by multivariate analysis (OS, P=0.7800; CS, P=0.8688). The clinicopathological features of patients who underwent a prostatectomy were similar except for the diagnosis opportunity between the two groups. Progression-free survival rates were similar between the two groups (P=0.5630). A-bomb exposure was not a significant and independent predictor for worsening of progression-free prognosis by multivariate analysis (P=0.3763). A-bomb exposure does not appear to exert deleterious effects on the biological aggressiveness of PCa and the prognosis of patients with PCa. PMID:28693168

  1. From Genotype to Functional Phenotype: Unraveling the Metabolomic Features of Colorectal Cancer

    PubMed Central

    Bathe, Oliver F.; Farshidfar, Farshad

    2014-01-01

    Much effort in recent years has been expended in defining the genomic and epigenetic alterations that characterize colorectal adenocarcinoma and its subtypes. However, little is known about the functional ramifications related to various subtypes. Metabolomics, the study of small molecule intermediates in disease, provides a snapshot of the functional phenotype of colorectal cancer. Data, thus far, have characterized some of the metabolic perturbations that accompany colorectal cancer. However, further studies will be required to identify biologically meaningful metabolic subsets, including those corresponding to specific genetic aberrations. Moreover, further studies are necessary to distinguish changes due to tumor and the host response to tumor. PMID:25055199

  2. The effect of HMGB1 on the clinicopathological and prognostic features of non-small cell lung cancer

    PubMed Central

    Yin, Bingjiao

    2016-01-01

    Several studies have assessed the diagnostic and prognostic values of high mobility group protein box 1 (HMGB1) expression in non-small cell lung cancer (NSCLC), but these results remain controversial. The purpose of this study was to perform a meta-analysis of the gene microarray analyses of datasets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to evaluate the association of HMGB1 expression with the clinicopathological and prognostic features of patients with NSCLC. Furthermore, we investigated the underlying molecular mechanisms by bioinformatics analysis. Twenty relevant articles involving 2651 patients were included in this meta-analysis; the HMGB1 expression in NSCLC tissues was significantly higher than that in the healthy non-cancer control tissues. We also found an indication by microarray analysis and meta-analysis that HMGB1 expression was associated with the cancer TNM Staging System. In terms of prognostic features, a survival analysis from KM-Plotter tool revealed that the high HMGB1 expression group exhibited poorer survival in lung adenocarcinoma (ADC) and overall NSCLC patients. The survival and disease-free analyses from TCGA datasets also showed that HMGB1 mainly affected the development of patients with ADC. Therefore, we focused on how HMGB1 affected the prognosis and development of ADC using bioinformatics analyses and detected that the mitogen-activated protein kinases (MAPK), apoptosis and cell cycle signaling pathways were the key pathways that varied during HMGB1 up-regulation in ADC. Moreover, various genes such as PLCG2, the phosphatidylinositol-4, 5-bisphosphate 3-kinase superfamily (PI3Ks), protein kinase C (PKC) and DGKZ were selected as hub genes in the gene regulatory network. Our results indicated that HMGB1 is a potential biomarker to predict progression and survival of NSCLC, especially of ADC types. PMID:26840258

  3. Evaluation of image features and classification methods for Barrett's cancer detection using VLE imaging

    NASA Astrophysics Data System (ADS)

    Klomp, Sander; van der Sommen, Fons; Swager, Anne-Fré; Zinger, Svitlana; Schoon, Erik J.; Curvers, Wouter L.; Bergman, Jacques J.; de With, Peter H. N.

    2017-03-01

    Volumetric Laser Endomicroscopy (VLE) is a promising technique for the detection of early neoplasia in Barrett's Esophagus (BE). VLE generates hundreds of high resolution, grayscale, cross-sectional images of the esophagus. However, at present, classifying these images is a time consuming and cumbersome effort performed by an expert using a clinical prediction model. This paper explores the feasibility of using computer vision techniques to accurately predict the presence of dysplastic tissue in VLE BE images. Our contribution is threefold. First, a benchmarking is performed for widely applied machine learning techniques and feature extraction methods. Second, three new features based on the clinical detection model are proposed, having superior classification accuracy and speed, compared to earlier work. Third, we evaluate automated parameter tuning by applying simple grid search and feature selection methods. The results are evaluated on a clinically validated dataset of 30 dysplastic and 30 non-dysplastic VLE images. Optimal classification accuracy is obtained by applying a support vector machine and using our modified Haralick features and optimal image cropping, obtaining an area under the receiver operating characteristic of 0.95 compared to the clinical prediction model at 0.81. Optimal execution time is achieved using a proposed mean and median feature, which is extracted at least factor 2.5 faster than alternative features with comparable performance.

  4. Gastric microbiota features associated with cancer risk factors and clinical outcomes: A pilot study in gastric cardia cancer patients from Shanxi, China.

    PubMed

    Yu, Guoqin; Hu, Nan; Wang, Lemin; Wang, Chaoyu; Han, Xiao-You; Humphry, Mike; Ravel, Jacques; Abnet, Christian C; Taylor, Philip R; Goldstein, Alisa M

    2017-07-01

    Little is known about the link between gastric microbiota and the epidemiology of gastric cancer. In order to determine the epidemiologic and clinical relevance of gastric microbiota, we used 16 S ribosomal RNA gene sequencing analysis to characterize the composition and structure of the gastric microbial community of 80 paired samples (non-malignant and matched tumor tissues) from gastric cardia adenocarcinoma (GCA) patients in Shanxi, China. We also used PICRUSt to predict microbial functional profiles. Compared to patients without family history of upper gastrointestinal (UGI) cancer in the non-malignant gastric tissue microbiota, patients with family history of UGI cancer had higher Helicobacter pylori (Hp) relative abundance (median: 0.83 vs. 0.38, p = 0.01) and lower alpha diversity (median observed species: 51 vs. 85, p = 0.01). Patients with higher (vs. lower) tumor grade had higher Hp relative abundance (0.73 vs. 0.18, p = 0.03), lower alpha diversity (observed species, 66 vs. 89, p = 0.01), altered beta diversity (weighted UniFrac, p = 0.002) and significant alterations in relative abundance of five KEGG functional modules in non-malignant gastric tissue microbiota. Patients without metastases had higher relative abundance of Lactobacillales than patients with metastases (0.05 vs. 0.01, p = 0.04) in non-malignant gastric tissue microbiota. These associations were observed in non-malignant tissues but not in tumor tissues. In conclusion, this study showed a link of gastric microbiota to a major gastric cancer risk factor and clinical features in GCA patients from Shanxi, China. Studies with both healthy controls and gastric cardia and noncardia cancer cases across different populations are needed to further examine the association between gastric cancer and the microbiota. © 2017 UICC.

  5. Research of Recognition Method of Discrete Wavelet Feature Extraction and PNN Classification of Rats FT-IR Pancreatic Cancer Data.

    PubMed

    Wan, Chayan; Cao, Wenqing; Cheng, Cungui

    2014-01-01

    Sprague-Dawley (SD) rats' normal and abnormal pancreatic tissues are determined directly by attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy method. In order to diagnose earlier stage of SD rats pancreatic cancer rate with FT-IR, a novel method of extraction of FT-IR feature using discrete wavelet transformation (DWT) analysis and classification with the probability neural network (PNN) was developed. The differences between normal pancreatic and abnormal samples were identified by PNN based on the indices of 4 feature variants. When error goal was 0.01, the total correct rates of pancreatic early carcinoma and advanced carcinoma were 98% and 100%, respectively. It was practical to apply PNN on the basis of ATR-FT-IR to identify abnormal tissues. The research result shows the feasibility of establishing the models with FT-IR-DWT-PNN method to identify normal pancreatic tissues, early carcinoma tissues, and advanced carcinoma tissues.

  6. Research of Recognition Method of Discrete Wavelet Feature Extraction and PNN Classification of Rats FT-IR Pancreatic Cancer Data

    PubMed Central

    Wan, Chayan; Cao, Wenqing; Cheng, Cungui

    2014-01-01

    Sprague-Dawley (SD) rats' normal and abnormal pancreatic tissues are determined directly by attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy method. In order to diagnose earlier stage of SD rats pancreatic cancer rate with FT-IR, a novel method of extraction of FT-IR feature using discrete wavelet transformation (DWT) analysis and classification with the probability neural network (PNN) was developed. The differences between normal pancreatic and abnormal samples were identified by PNN based on the indices of 4 feature variants. When error goal was 0.01, the total correct rates of pancreatic early carcinoma and advanced carcinoma were 98% and 100%, respectively. It was practical to apply PNN on the basis of ATR-FT-IR to identify abnormal tissues. The research result shows the feasibility of establishing the models with FT-IR-DWT-PNN method to identify normal pancreatic tissues, early carcinoma tissues, and advanced carcinoma tissues. PMID:25548717

  7. Feature Selection and Cancer Classification via Sparse Logistic Regression with the Hybrid L1/2 +2 Regularization

    PubMed Central

    Huang, Hai-Hui; Liu, Xiao-Ying; Liang, Yong

    2016-01-01

    Cancer classification and feature (gene) selection plays an important role in knowledge discovery in genomic data. Although logistic regression is one of the most popular classification methods, it does not induce feature selection. In this paper, we presented a new hybrid L1/2 +2 regularization (HLR) function, a linear combination of L1/2 and L2 penalties, to select the relevant gene in the logistic regression. The HLR approach inherits some fascinating characteristics from L1/2 (sparsity) and L2 (grouping effect where highly correlated variables are in or out a model together) penalties. We also proposed a novel univariate HLR thresholding approach to update the estimated coefficients and developed the coordinate descent algorithm for the HLR penalized logistic regression model. The empirical results and simulations indicate that the proposed method is highly competitive amongst several state-of-the-art methods. PMID:27136190

  8. Improving the Mann-Whitney statistical test for feature selection: an approach in breast cancer diagnosis on mammography.

    PubMed

    Pérez, Noel Pérez; Guevara López, Miguel A; Silva, Augusto; Ramos, Isabel

    2015-01-01

    This work addresses the theoretical description and experimental evaluation of a new feature selection method (named uFilter). The uFilter improves the Mann-Whitney U-test for reducing dimensionality and ranking features in binary classification problems. Also, it presented a practical uFilter application on breast cancer computer-aided diagnosis (CADx). A total of 720 datasets (ranked subsets of features) were formed by the application of the chi-square (CHI2) discretization, information-gain (IG), one-rule (1Rule), Relief, uFilter and its theoretical basis method (named U-test). Each produced dataset was used for training feed-forward backpropagation neural network, support vector machine, linear discriminant analysis and naive Bayes machine learning algorithms to produce classification scores for further statistical comparisons. A head-to-head comparison based on the mean of area under receiver operating characteristics curve scores against the U-test method showed that the uFilter method significantly outperformed the U-test method for almost all classification schemes (p<0.05); it was superior in 50%; tied in a 37.5% and lost in a 12.5% of the 24 comparative scenarios. Also, the performance of the uFilter method, when compared with CHI2 discretization, IG, 1Rule and Relief methods, was superior or at least statistically similar on the explored datasets while requiring less number of features. The experimental results indicated that uFilter method statistically outperformed the U-test method and it demonstrated similar, but not superior, performance than traditional feature selection methods (CHI2 discretization, IG, 1Rule and Relief). The uFilter method revealed competitive and appealing cost-effectiveness results on selecting relevant features, as a support tool for breast cancer CADx methods especially in unbalanced datasets contexts. Finally, the redundancy analysis as a complementary step to the uFilter method provided us an effective way for finding

  9. Diverse repetitive element RNA expression defines epigenetic and immunologic features of colon cancer

    PubMed Central

    Desai, Niyati; Sajed, Dipti; Arora, Kshitij S.; Solovyov, Alexander; Rajurkar, Mihir; Bledsoe, Jacob R.; Sil, Srinjoy; Tai, Eric; MacKenzie, Olivia C.; Mino-Kenudson, Mari; Aryee, Martin J.; Ferrone, Cristina R.; Berger, David L.; Rivera, Miguel N.; Greenbaum, Benjamin D.; Deshpande, Vikram; Ting, David T.

    2017-01-01

    There is tremendous excitement for the potential of epigenetic therapies in cancer, but the ability to predict and monitor response to these drugs remains elusive. This is in part due to the inability to differentiate the direct cytotoxic and the immunomodulatory effects of these drugs. The DNA-hypomethylating agent 5-azacitidine (AZA) has shown these distinct effects in colon cancer and appears to be linked to the derepression of repeat RNAs. LINE and HERV are two of the largest classes of repeats in the genome, and despite many commonalities, we found that there is heterogeneity in behavior among repeat subtypes. Specifically, the LINE-1 and HERV-H subtypes detected by RNA sequencing and RNA in situ hybridization in colon cancers had distinct expression patterns, which suggested that these repeats are correlated to transcriptional programs marking different biological states. We found that low LINE-1 expression correlates with global DNA hypermethylation, wild-type TP53 status, and responsiveness to AZA. HERV-H repeats were not concordant with LINE-1 expression but were found to be linked with differences in FOXP3+ Treg tumor infiltrates. Together, distinct repeat RNA expression patterns define new molecular classifications of colon cancer and provide biomarkers that better distinguish cytotoxic from immunomodulatory effects by epigenetic drugs. PMID:28194445

  10. Discovery of Cancer Driver Long Noncoding RNAs across 1112 Tumour Genomes: New Candidates and Distinguishing Features

    PubMed Central

    Lanzós, Andrés; Carlevaro-Fita, Joana; Mularoni, Loris; Reverter, Ferran; Palumbo, Emilio; Guigó, Roderic; Johnson, Rory

    2017-01-01

    Long noncoding RNAs (lncRNAs) represent a vast unexplored genetic space that may hold missing drivers of tumourigenesis, but few such “driver lncRNAs” are known. Until now, they have been discovered through changes in expression, leading to problems in distinguishing between causative roles and passenger effects. We here present a different approach for driver lncRNA discovery using mutational patterns in tumour DNA. Our pipeline, ExInAtor, identifies genes with excess load of somatic single nucleotide variants (SNVs) across panels of tumour genomes. Heterogeneity in mutational signatures between cancer types and individuals is accounted for using a simple local trinucleotide background model, which yields high precision and low computational demands. We use ExInAtor to predict drivers from the GENCODE annotation across 1112 entire genomes from 23 cancer types. Using a stratified approach, we identify 15 high-confidence candidates: 9 novel and 6 known cancer-related genes, including MALAT1, NEAT1 and SAMMSON. Both known and novel driver lncRNAs are distinguished by elevated gene length, evolutionary conservation and expression. We have presented a first catalogue of mutated lncRNA genes driving cancer, which will grow and improve with the application of ExInAtor to future tumour genome projects. PMID:28128360

  11. Computational approach to radiogenomics of breast cancer: Luminal A and luminal B molecular subtypes are associated with imaging features on routine breast MRI extracted using computer vision algorithms.

    PubMed

    Grimm, Lars J; Zhang, Jing; Mazurowski, Maciej A

    2015-10-01

    To identify associations between semiautomatically extracted MRI features and breast cancer molecular subtypes. We analyzed routine clinical pre-operative breast MRIs from 275 breast cancer patients at a single institution in this retrospective, Institutional Review Board-approved study. Six fellowship-trained breast imagers reviewed the MRIs and annotated the cancers. Computer vision algorithms were then used to extract 56 imaging features from the cancers including morphologic, texture, and dynamic features. Surrogate markers (estrogen receptor [ER], progesterone receptor [PR], human epidermal growth factor receptor-2 [HER2]) were used to categorize tumors by molecular subtype: ER/PR+, HER2- (luminal A); ER/PR+, HER2+ (luminal B); ER/PR-, HER2+ (HER2); ER/PR/HER2- (basal). A multivariate analysis was used to determine associations between the imaging features and molecular subtype. The imaging features were associated with both luminal A (P = 0.0007) and luminal B (P = 0.0063) molecular subtypes. No association was found for either HER2 (P = 0.2465) or basal (P = 0.1014) molecular subtype and the imaging features. A P-value of 0.0125 (0.05/4) was considered significant. Luminal A and luminal B molecular subtype breast cancer are associated with semiautomatically extracted features from routine contrast enhanced breast MRI. © 2015 Wiley Periodicals, Inc.

  12. Triple-Negative Breast Cancer: A Comprehensive Study of Clinical, Histomorphological, and Immunohistochemical Features in Indian Patients.

    PubMed

    Sable, Mukund; Pai, Trupti D; Shet, Tanuja; Patil, Asawari; Dhanavade, Sandeep; Desai, Sangeeta B

    2016-09-09

    Triple-negative breast cancers (TNBCs) are characterized by negative expression for estrogen (ER), progesterone (PR), and human epidermal growth factor 2 (HER2) receptors. Although the majority of basal-like breast cancers (BLBCs) diagnosed based on gene expression profiling belong to the TNBC group, both entities are not synonymous. Core BLBCs are TNBCs, which are positive for basal cytokeratin (CK) and/or epidermal growth factor receptor (EGFR). We aimed to study and correlate a TNBC cohort for various histomorphological features and immunohistochemical (IHC) profile in Indian patients. We studied 205 naïve TNBCs for histopathological features, which were further evaluated for basal CKs-namely, CK5/6, CK14, CK17-and EGFR expression to classify them as core BLBCs, using criteria of any basal CK and/or EGFR positivity and 7-negative phenotype (7NP). Among 205 TNBCs, 91% of cases were core BLBCs, and absence of ductal carcinoma in situ (DCIS) was significantly associated (P = .014) with core BLBC. Geographic necrosis was correlated with expression of CK17 (P = .002) and EGFR (P = .038). A ribbon-like trabecular pattern and absence of DCIS were associated with CK17 (P = .0002 and P = .043, respectively) and CK14 (P = .04 and P = .0008, respectively). TNBC is a heterogeneous subgroup with adverse clinicopathological features, and many of them show significant correlation with basal CKs. TNBCs cannot be classified as core BLBC or 7NP based on morphological features, except absence of DCIS. However, this study illustrates the heterogeneity in TNBCs on the basis of IHC markers.

  13. Feature Selection and Classification of MAQC-II Breast Cancer and Multiple Myeloma Microarray Gene Expression Data

    PubMed Central

    Liu, Qingzhong; Sung, Andrew H.; Chen, Zhongxue; Liu, Jianzhong; Huang, Xudong; Deng, Youping

    2009-01-01

    Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. In this paper, we propose a gene selection method called Recursive Feature Addition (RFA), which combines supervised learning and statistical similarity measures. We compare our method with the following gene selection methods: Support Vector Machine Recursive Feature Elimination (SVMRFE)Leave-One-Out Calculation Sequential Forward Selection (LOOCSFS)Gradient based Leave-one-out Gene Selection (GLGS) To evaluate the performance of these gene selection methods, we employ several popular learning classifiers on the MicroArray Quality Control phase II on predictive modeling (MAQC-II) breast cancer dataset and the MAQC-II multiple myeloma dataset. Experimental results show that gene selection is strictly paired with learning classifier. Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC) is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and AUC errors. PMID

  14. Feature selection and classification of MAQC-II breast cancer and multiple myeloma microarray gene expression data.

    PubMed

    Liu, Qingzhong; Sung, Andrew H; Chen, Zhongxue; Liu, Jianzhong; Huang, Xudong; Deng, Youping

    2009-12-11

    Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. In this paper, we propose a gene selection method called Recursive Feature Addition (RFA), which combines supervised learning and statistical similarity measures. We compare our method with the following gene selection methods: Support Vector Machine Recursive Feature Elimination (SVMRFE), Leave-One-Out Calculation Sequential Forward Selection (LOOCSFS), Gradient based Leave-one-out Gene Selection (GLGS). To evaluate the performance of these gene selection methods, we employ several popular learning classifiers on the MicroArray Quality Control phase II on predictive modeling (MAQC-II) breast cancer dataset and the MAQC-II multiple myeloma dataset. Experimental results show that gene selection is strictly paired with learning classifier. Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC) is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and AUC errors.

  15. A computerized global MR image feature analysis scheme to assist diagnosis of breast cancer: a preliminary assessment.

    PubMed

    Yang, Qian; Li, Lihua; Zhang, Juan; Shao, Guoliang; Zheng, Bin

    2014-07-01

    To develop a new computer-aided detection scheme to compute a global kinetic image feature from the dynamic contrast enhanced breast magnetic resonance imaging (DCE-MRI) and test the feasibility of using the computerized results for assisting classification between the DCE-MRI examinations associated with malignant and benign tumors. The scheme registers sequential images acquired from each DCE-MRI examination, segments breast areas on all images, searches for a fraction of voxels that have higher contrast enhancement values and computes an average contrast enhancement value of selected voxels. Combination of the maximum contrast enhancement values computed from two post-contrast series in one of two breasts is applied to predict the likelihood of the examination being positive for breast cancer. The scheme performance was evaluated when applying to a retrospectively collected database including 80 malignant and 50 benign cases. In each of 91% of malignant cases and 66% of benign cases, the average contrast enhancement value computed from the top 0.43% of voxels is higher in the breast depicted suspicious lesions as compared to another negative (lesion-free) breast. In classifying between malignant and benign cases, using the computed image feature achieved an area under a receiver operating characteristic curve of 0.839 with 95% confidence interval of [0.762, 0.898]. We demonstrated that the global contrast enhancement feature of DCE-MRI can be relatively easily and robustly computed without accurate breast tumor detection and segmentation. This global feature provides supplementary information and a higher discriminatory power in assisting diagnosis of breast cancer. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  16. From normal response to clinical problem: definition and clinical features of fear of cancer recurrence.

    PubMed

    Lebel, Sophie; Ozakinci, Gozde; Humphris, Gerald; Mutsaers, Brittany; Thewes, Belinda; Prins, Judith; Dinkel, Andreas; Butow, Phyllis

    2016-08-01

    Research to date on fear of cancer recurrence (FCR) shows that moderate to high FCR affects 22-87 % of cancer survivors and is associated with higher psychological morbidity (Simard et al J Cancer Surviv 7:300-322, 2013). Despite growing research interest in FCR, the lack of consensus on its definition and characteristics when it reaches a clinical level has impeded knowledge transfer into patient services. In order to address these gaps, expert researchers, policy makers, trainees, and patient advocates attended a 2-day colloquium at the University of Ottawa in August 2015. A Delphi method was used to identify the most relevant definition of FCR, and the attendees generated possible diagnostic characteristics of clinical FCR. After three rounds of discussion and voting, the attendees reached consensus on a new definition of FCR: "Fear, worry, or concern relating to the possibility that cancer will come back or progress." Regarding clinical FCR, five possible characteristics were proposed: (1) high levels of preoccupation, worry, rumination, or intrusive thoughts; (2) maladaptive coping; (3) functional impairments; (4) excessive distress; and (5) difficulties making plans for the future. The new proposed definition of FCR reflects the broad spectrum in which patients experience FCR. A consensual definition of FCR and the identification of the essential characteristics of clinical FCR are necessary to accurately and consistently measure FCR severity and to develop effective interventions to treat FCR. We hope this broad definition can encourage further research and the development of inclusive policies for all cancer patients and survivors who are struggling with this issue.

  17. Association of Vitamin D Level with Clinicopathological Features in Breast Cancer.

    PubMed

    Thanasitthichai, Somchai; Chaiwerawattana, Arkom; Prasitthipayong, Aree

    2015-01-01

    A population-based relationship between low vitamin D status and increased cancer risk is now generally accepted. However there were only few studies reported on prognostic impact. To determine the effect of low vitamin D on progression of breast cancer, we conducted a cross-sectional analysis of vitamin D levels and clinico- pathological characteristics in 200 cases of breast cancer diagnosed during 2011-2012 at the National Cancer Institute of Thailand. Vitamin D levels were measured by high-performance liquid chromatography (HPLC). Clinical and pathological data were accessed to examine prognostic effects of vitamin D. We found that the mean vitamin D level was 23.0±6.61 ng/ml. High vitamin D levels (≥32 ng/ml) were detected in 7% of patients, . low levels (<32 ng/ml) in 93% Mean vitamin D levels for stages 1-4 were 26.1±6.35, 22.3±6.34, 22.2±6.46 and 21.3±5.42 ng/ml respectively (P=0.016) and 24.1 and 21.3 ng/ml for lymph node negative and positive cases (P=0.006). Low vitamin D level (<32 ng/ml) was significantly found in majority of cases with advanced stage of the disease (P=0.036), positive node involvement (P=0.030) and large tumors (P=0.038). Our findings suggest that low and decreased level of vitamin D might correlate with progression and metastasis of breast cancer.

  18. Identifying Significant Features in Cancer Methylation Data Using Gene Pathway Segmentation

    PubMed Central

    Hira, Zena M.; Gillies, Duncan F.

    2016-01-01

    In order to provide the most effective therapy for cancer, it is important to be able to diagnose whether a patient’s cancer will respond to a proposed treatment. Methylation profiling could contain information from which such predictions could be made. Currently, hypothesis testing is used to determine whether possible biomarkers for cancer progression produce statistically significant results. However, this approach requires the identification of individual genes, or sets of genes, as candidate hypotheses, and with the increasing size of modern microarrays, this task is becoming progressively harder. Exhaustive testing of small sets of genes is computationally infeasible, and so hypothesis generation depends either on the use of established biological knowledge or on heuristic methods. As an alternative machine learning, methods can be used to identify groups of genes that are acting together within sets of cancer data and associate their behaviors with cancer progression. These methods have the advantage of being multivariate and unbiased but unfortunately also rapidly become computationally infeasible as the number of gene probes and datasets increases. To address this problem, we have investigated a way of utilizing prior knowledge to segment microarray datasets in such a way that machine learning can be used to identify candidate sets of genes for hypothesis testing. A methylation dataset is divided into subsets, where each subset contains only the probes that relate to a known gene pathway. Each of these pathway subsets is used independently for classification. The classification method is AdaBoost with decision trees as weak classifiers. Since each pathway subset contains a relatively small number of gene probes, it is possible to train and test its classification accuracy quickly and determine whether it has valuable diagnostic information. Finally, genes from successful pathway subsets can be combined to create a classifier of high accuracy. PMID

  19. Thermography based breast cancer detection using texture features and minimum variance quantization

    PubMed Central

    Milosevic, Marina; Jankovic, Dragan; Peulic, Aleksandar

    2014-01-01

    In this paper, we present a system based on feature extraction techniques and image segmentation techniques for detecting and diagnosing abnormal patterns in breast thermograms. The proposed system consists of three major steps: feature extraction, classification into normal and abnormal pattern and segmentation of abnormal pattern. Computed features based on gray-level co-occurrence matrices are used to evaluate the effectiveness of textural information possessed by mass regions. A total of 20 GLCM features are extracted from thermograms. The ability of feature set in differentiating abnormal from normal tissue is investigated using a Support Vector Machine classifier, Naive Bayes classifier and K-Nearest Neighbor classifier. To evaluate the classification performance, five-fold cross validation method and Receiver operating characteristic analysis was performed. The verification results show that the proposed algorithm gives the best classification results using K-Nearest Neighbor classifier and a accuracy of 92.5%. Image segmentation techniques can play an important role to segment and extract suspected hot regions of interests in the breast infrared images. Three image segmentation techniques: minimum variance quantization, dilation of image and erosion of image are discussed. The hottest regions of thermal breast images are extracted and compared to the original images. According to the results, the proposed method has potential to extract almost exact shape of tumors. PMID:26417334

  20. Thermography based breast cancer detection using texture features and minimum variance quantization.

    PubMed

    Milosevic, Marina; Jankovic, Dragan; Peulic, Aleksandar

    2014-01-01

    In this paper, we present a system based on feature extraction techniques and image segmentation techniques for detecting and diagnosing abnormal patterns in breast thermograms. The proposed system consists of three major steps: feature extraction, classification into normal and abnormal pattern and segmentation of abnormal pattern. Computed features based on gray-level co-occurrence matrices are used to evaluate the effectiveness of textural information possessed by mass regions. A total of 20 GLCM features are extracted from thermograms. The ability of feature set in differentiating abnormal from normal tissue is investigated using a Support Vector Machine classifier, Naive Bayes classifier and K-Nearest Neighbor classifier. To evaluate the classification performance, five-fold cross validation method and Receiver operating characteristic analysis was performed. The verification results show that the proposed algorithm gives the best classification results using K-Nearest Neighbor classifier and a accuracy of 92.5%. Image segmentation techniques can play an important role to segment and extract suspected hot regions of interests in the breast infrared images. Three image segmentation techniques: minimum variance quantization, dilation of image and erosion of image are discussed. The hottest regions of thermal breast images are extracted and compared to the original images. According to the results, the proposed method has potential to extract almost exact shape of tumors.

  1. An introductory analysis of digital infrared thermal imaging guided oral cancer detection using multiresolution rotation invariant texture features

    NASA Astrophysics Data System (ADS)

    Chakraborty, M.; Das Gupta, R.; Mukhopadhyay, S.; Anjum, N.; Patsa, S.; Ray, J. G.

    2017-03-01

    This manuscript presents an analytical treatment on the feasibility of multi-scale Gabor filter bank response for non-invasive oral cancer pre-screening and detection in the long infrared spectrum. Incapability of present healthcare technology to detect oral cancer in budding stage manifests in high mortality rate. The paper contributes a step towards automation in non-invasive computer-aided oral cancer detection using an amalgamation of image processing and machine intelligence paradigms. Previous works have shown the discriminative difference of facial temperature distribution between a normal subject and a patient. The proposed work, for the first time, exploits this difference further by representing the facial Region of Interest(ROI) using multiscale rotation invariant Gabor filter bank responses followed by classification using Radial Basis Function(RBF) kernelized Support Vector Machine(SVM). The proposed study reveals an initial increase in classification accuracy with incrementing image scales followed by degradation of performance; an indication that addition of more and more finer scales tend to embed noisy information instead of discriminative texture patterns. Moreover, the performance is consistently better for filter responses from profile faces compared to frontal faces.This is primarily attributed to the ineptness of Gabor kernels to analyze low spatial frequency components over a small facial surface area. On our dataset comprising of 81 malignant, 59 pre-cancerous, and 63 normal subjects, we achieve state-of-the-art accuracy of 85.16% for normal v/s precancerous and 84.72% for normal v/s malignant classification. This sets a benchmark for further investigation of multiscale feature extraction paradigms in IR spectrum for oral cancer detection.

  2. Radiologic features of breast cancer after mantle radiation therapy for Hodgkin disease: a study of 230 cases.

    PubMed

    Allen, Steven D; Wallis, Matthew G; Cooke, Rosie; Swerdlow, Anthony J

    2014-07-01

    To retrospectively review diagnostic mammography in women diagnosed with breast cancer who previously had mantle field radiation therapy for Hodgkin disease in England and Wales over a period of 30 years. From a national cohort study of 5002 women treated with supradiaphragmatic radiation therapy when they were younger than 36 years (mean, 22.1 years) during 1956-2003, 392 patients developed breast cancer. With ethics committee approval and informed consent, mammograms were obtained that showed 230 tumors in 222 (56.6%) patients from 95 hospitals, and the size and appearance of each carcinoma was recorded by two breast radiologists. Comparison was made with a historical report of more than 1000 general-population breast cancers by using Pearson χ(2) test. Thirty-eight tumors were occult on mammograms. Mean tumor maximum diameter was 12.3 mm (n = 81) on oblique view. The quadrant distribution of the tumors was significantly different (P < .001) from the historic controls, and chest radiation therapy patients had a greater proportion of tumors in the upper outer (66.9% [107 of 160] vs 48.7% [385 of 784]) and, to a lesser extent, lower inner (10.6% [17 of 160] vs 7.8% [61 of 784]) quadrants. The dominant radiologic feature was of an irregular mass (56.8% [109 of 192]) followed by microcalcifications (25.0% [48 of 192]). This study suggests that in patients who previously underwent mantle radiation therapy for Hodgkin disease, breast cancers are more commonly seen within the upper outer quadrants than are cancers in the general population. Poorly defined masses were the most common appearance. © RSNA, 2014.

  3. Conserved features of cancer cells define their sensitivity of HAMLET-induced death; c-Myc and glycolysis

    PubMed Central

    Storm, Petter; Puthia, Manoj Kumar; Aits, Sonja; Urbano, Alexander; Northen, Trent; Powers, Scott; Bowen, Ben; Chao, Yinxia; Reindl, Wolfgang; Lee, Do Yup; Sullivan, Nancy Liu; Zhang, Jianping; Trulsson, Maria; Yang, Henry; Watson, James; Svanborg, Catharina

    2014-01-01

    HAMLET is the first member of a new family of tumoricidal protein-lipid complexes that kill cancer cells broadly, while sparing healthy, differentiated cells. Many and diverse tumor cell types are sensitive to the lethal effect, suggesting that HAMLET identifies and activates conserved death pathways in cancer cells. Here we investigated the molecular basis for the difference in sensitivity between cancer cells and healthy cells. Using a combination of small hairpin RNA inhibition, proteomic and metabolomic technology we identified the c-Myc oncogene as one essential determinant of HAMLET sensitivity. Increased c-Myc expression levels promoted the sensitivity to HAMLET and shRNA knockdown of c-Myc suppressed the lethal response, suggesting that oncogenic transformation with c-Myc creates a HAMLET-sensitive phenotype. Furthermore, the HAMLET sensitivity was modified by the glycolytic state of the tumor cells. Glucose deprivation sensitized tumor cells to HAMLET-induced cell death and in the shRNA screen Hexokinase 1, PFKFB1 and HIF1α modified HAMLET sensitivity. Hexokinase 1 was shown to bind HAMLET in a protein array containing approximately 8000 targets and Hexokinase activity decreased within 15 minutes of HAMLET treatment, prior to morphological signs of tumor cell death. In parallel, HAMLET triggered rapid metabolic paralysis in carcinoma cells. The glycolytic machinery was modified and glycolysis was shifted towards the pentose phosphate pathway. Tumor cells were also shown to contain large amounts of oleic acid and its derivatives already after 15 minutes. The results identify HAMLET as a novel anti-cancer agent that kills tumor cells by exploiting unifying features of cancer cells such as oncogene-addiction or the Warburg effect. PMID:21643007

  4. Conserved features of cancer cells define their sensitivity to HAMLET-induced death; c-Myc and glycolysis.

    PubMed

    Storm, P; Aits, S; Puthia, M K; Urbano, A; Northen, T; Powers, S; Bowen, B; Chao, Y; Reindl, W; Lee, D Y; Sullivan, N L; Zhang, J; Trulsson, M; Yang, H; Watson, J D; Svanborg, C

    2011-12-01

    HAMLET is the first member of a new family of tumoricidal protein-lipid complexes that kill cancer cells broadly, while sparing healthy, differentiated cells. Many and diverse tumor cell types are sensitive to the lethal effect, suggesting that HAMLET identifies and activates conserved death pathways in cancer cells. Here, we investigated the molecular basis for the difference in sensitivity between cancer cells and healthy cells. Using a combination of small-hairpin RNA (shRNA) inhibition, proteomic and metabolomic technology, we identified the c-Myc oncogene as one essential determinant of HAMLET sensitivity. Increased c-Myc expression levels promoted sensitivity to HAMLET and shRNA knockdown of c-Myc suppressed the lethal response, suggesting that oncogenic transformation with c-Myc creates a HAMLET-sensitive phenotype. Furthermore, HAMLET sensitivity was modified by the glycolytic state of tumor cells. Glucose deprivation sensitized tumor cells to HAMLET-induced cell death and in the shRNA screen, hexokinase 1 (HK1), 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 1 and hypoxia-inducible factor 1α modified HAMLET sensitivity. HK1 was shown to bind HAMLET in a protein array containing ∼8000 targets, and HK activity decreased within 15 min of HAMLET treatment, before morphological signs of tumor cell death. In parallel, HAMLET triggered rapid metabolic paralysis in carcinoma cells. Tumor cells were also shown to contain large amounts of oleic acid and its derivatives already after 15 min. The results identify HAMLET as a novel anti-cancer agent that kills tumor cells by exploiting unifying features of cancer cells such as oncogene addiction or the Warburg effect.

  5. Do obesity and age effect the clinicopathological features and survival outcomes in premenopausal women with endometrial cancer?

    PubMed

    Topuz, S; Sozen, H; Vatansever, D; Iyibozkurt, A C; Ozgor, B Y; Bastu, E; Salihoglu, V; Berkman, S

    2016-01-01

    The purpose of this study was to review the effect of age and body mass index (BMI) on the prognosis, demographic characteristics, and pathological features of patients diagnosed with endometrial cancer, specifically before menopause. Patients that were diagnosed with endometrial cancer before menopause, were screened retrospectively. Between 1999 and 2011, 163 patients were identified while 40 were excluded. Patients were classified into three groups according to age (under 40 years, between 40-45 years, more than 45 years) and BMI (normal weight group, overweight group, and obese weight group). Demographical characteristics, histopathological features (Stage, grade and histology of the tumor, the presence of myometrial and/or lymphovascular invasion, history of diabetes mellitus, history of hypertension, hormonal contraception method, smoking, parity, infertility, family history, and recurrences) and survival rates were compared among the groups. In total, 123 patients with a mean of 65.0 months follow up were enrolled into the study. The majority of the patients had endometrioid type in all age-related subgroups. Advanced stage endometrium cancer (Stage 2 and greater) was seen more commonly in the group of patient over 45 years of age against the other age-related subgroups (27.9% vs. 8% vs. 3.3%). Ratio of myometrial invasion more than 50% and occurrence of well-differentiated tumor were seen with a similar ratio among the age-related subgroups. Ratio of nulliparity and infertility were found statistically significant in the group of patients under 45 years of age against the group of patients over 45 years of age (p = 0.001, p = 0.03). The five-year estimated disease-free survival rates of women under 40 years of, women with an age between 40-45 years, and women over the age of 45 years were calculated as 73%, 95%, and 87%, respectively (p = 0.152). Concerning the histopathological features, there were no statistical differences between weight related

  6. Cell-like features imprinted in the physical nano- and micro-topography of the environment modify the responses to anti-cancer drugs of endometrial cancer cells.

    PubMed

    Tan, Li Hui; Sykes, Peter H; Alkaisi, Maan M; Evans, John J

    2017-02-14

    Topographical features of cells at nanometre resolution were fabricated in polystyrene. The study investigated the effect of physical topography on the response of cancer cells to the common anticancer drugs, paclitaxel and doxorubicin. Human endometrial cancer cells (Ishikawa) were incubated on substrates containing cell-like features that had been fabricated using our bioimprint methodology to create moulds of cells with positive (convex) and negative (concave) topography. Control cultures were performed on flat substrates. Effects of the drugs on caspase-3 expression, proliferating nuclear antigen (PCNA) expression, cell number and vascular endothelial growth factor (VEGF) secretion were determined. Results revealed that the topography influenced the cell responses in a drug-dependent manner i.e. paclitaxel effects were sensitive to topography differently to those of doxorubicin. In addition, function signalling pathways were sensitive to the detailed topography i.e. positive imprint and negative imprint induced distinct response patterns. The results in this study show for the first time that a culture surface with cell-like topography, that has both nano- and micro-resolution, influences endometrial cancer cell responses to chemotherapy drugs. The effects are dependent on the topography and also on the chemotherapy drug. In particular, the platforms described have potential to provide substrates with high physical relevancy on which to undertake preclinical testing of new drugs. The method also allows for use of different cell types to provide cell-specific topography. The results imply that physical architecture of the cancer cell environment may be a suitable prospective target to enhance clinical activity of traditional drugs. Additionally or alternatively we provide compelling support for the notion that understanding the physical component of the nano- and micro-environment may encourage a redirection of drug development. Further, our observation that the

  7. Morphological feature extraction for the classification of digital images of cancerous tissues.

    PubMed

    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.

  8. Prognostic features of breast cancer differ between women in the Democratic Republic of Congo and Belgium.

    PubMed

    Luyeye Mvila, Gertrude; Batalansi, Donatien; Praet, Marleen; Marchal, Guy; Laenen, Annouschka; Christiaens, Marie-Rose; Brouckaert, Olivier; Ali-Risasi, Catherine; Neven, Patrick; Van Ongeval, Chantal

    2015-10-01

    Compared to European women, breast cancers in African women present at a younger age, with a higher tumor grade and are more often estrogen receptor (ER)/progesterone receptor (PR) negative. We here investigate the histopathological and immunohistochemical characteristics (ER, PR and human epidermal growth receptor 2 (HER2)) and the proportion of triple negative (Tneg) invasive breast cancers from an unselected series of patients diagnosed in Kinshasa, and compare them to a population of Caucasian women with a palpable breast cancer. From 2010 till 2013, during the first breast cancer awareness campaign, organized in Kinshasa, 87 patients were diagnosed with invasive breast cancer. Diagnose was based on core biopsy. The control group consisted of Caucasian women (University Hospitals of Leuven, Belgium) with a palpable mass, diagnosed between 2000 till 2009, treated with surgery of which the histopathological and immunohistochemical characteristics were collected on excision specimens. Each patient in the Kinshasa group was matched based on age and tumor size to one or more patients of the Leuven database. Differences between both groups with respect to hormone receptors (ER, PR, HER2, Tneg) or grade are presented as relative risks (RR). The analysis is based on a log-binomial model accounting for clustering through matching by a random intercept for cluster. Differences between both groups with respect to hormone receptors correcting for grade is performed by the inclusion of grade as a covariate in the model. After adjusting for age, tumor volume and tumor grade, ER was more frequently negative (RR = 0.71, p < 0.001), with a trend in the same direction for PR (RR = 0.87, p = 0.057), and HER2 more often positive (RR = 1.60, p = 0.015) compared to the group from the University Hospitals of Leuven. There was no difference in the proportion of breast cancers being triple negative. Sub-analysis showed that the higher HER2 positive rate was only observed in older

  9. Molecular features of doxorubicin-resistance development in colorectal cancer CX-1 cell line.

    PubMed

    Kubiliūtė, Raimonda; Šulskytė, Indrė; Daniūnaitė, Kristina; Daugelavičius, Rimantas; Jarmalaitė, Sonata

    2016-01-01

    Resistance to chemotherapy is the key obstacle to the effective treatment of various cancers. Accumulating evidence suggests significant involvement of the epithelial-to-mesenchymal transition (EMT) in the chemoresistance of most cancer types. This study aimed at analyzing the gene expression profile of doxorubicin (DOX)-resistant colorectal cancer cells CX-1. DOX-resistant CX-1 cell sublines were acquired by stepwise increment of DOX concentrations in cell growth media. Global gene expression profiling was performed using human gene expression microarrays. The expression levels of individual genes were assessed by means of quantitative PCR (qPCR), while the DNA methylation pattern of several selected genes was determined by methylation-specific PCR. Four DOX-resistant CX-1 sublines were established as a valuable tool for cell chemoresistance studies. Altered expression of the EMT, cell adhesion and motility, and chemoresistance-related genes was observed in DOX-resistant cells by genome-wide gene expression analysis. Besides, early and significant upregulation of the key EMT genes ZEB1 (5.8×; P<0.001) and CDH2 (6.2×; P=0.044) was identified by qPCR, with subsequent activation of drug transporter gene ABCC1 (3.3×; P=0.007) and cell stemness gene NANOG (2.4×; P=0.008). Downregulation of TET1 (2.1×; P=0.041) and changes in the methylation status of the p16 gene were also involved in the acquisition of cell resistance to DOX. The results of our study suggest possible involvement of the key EMT and drug transporter genes in the early phase of cancer cell chemoresistance development. Copyright © 2016 The Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

  10. Use of genetic algorithms for computer-aided diagnosis of breast cancers from image features

    NASA Astrophysics Data System (ADS)

    Floyd, Carey E., Jr.; Tourassi, Georgia D.; Baker, Jay A.

    1996-04-01

    In this investigation we explore genetic algorithms as a technique to train the weights in a feed forward neural network designed to predict breast cancer based on mammographic findings and patient history. Mammograms were obtained from 206 patients who obtained breast biopsies. Mammographic findings were recorded by radiologists for each patient. In addition, the outcome of the biopsy was recorded. Of the 206 cases, 73 were malignant while 133 were benign at the time of biopsy. A genetic algorithm (GA) was developed to adjust the weights of an artificial neural network (ANN) so that the ANN would output the outcome of the biopsy when the mammographic findings were given as inputs. The GA is a technique for function optimization that reflects biological genetic evolution. The ANN was a fully connected feed- forward network using a sigmoid activation with 11 inputs, one hidden layer with 10 nodes, and one output node (benign/malignant). The GA approach allows much flexibility in selecting the function to be optimized. In this work both mean-squared error (MSE) and receiver operating characteristic (ROC) curve area (Az) were explored as optimization criteria. The system was trained using a bootstrap sampling. Optimizing for the two criteria result in different solutions. The 'best' solution was obtained by minimizing a linear combination of MSE and (1-Az). ROC areas were 0.82 plus or minus 0.07, somewhat less than those obtained using backpropagation for ANN training: 0.90 plus or minus 0.05. This is the first description of a genetic algorithm for breast cancer diagnosis. The novel advantage of this technique is the ability to optimize the system for maximizing ROC area rather than minimizing mean squared error. A new technique for computer-aided diagnosis of breast cancer has been explored. The flexibility of the GA approach allows optimization of cost functions that have relevance to breast cancer prediction.

  11. Telomere Length in Leukocyte DNA in Gastric Cancer Patients and its Association with Clinicopathological Features and Prognosis.

    PubMed

    Tahara, Tomomitsu; Tahara, Sayumi; Horiguchi, Noriyuki; Kawamura, Tomohiko; Okubo, Masaaki; Ishizuka, Takamitsu; Yamada, Hyuga; Yoshida, Dai; Ohmori, Takafumi; Maeda, Kohei; Komura, Naruomi; Ikuno, Hirokazu; Jodai, Yasutaka; Kamano, Toshiaki; Nagasaka, Mitsuo; Nakagawa, Yoshihito; Tuskamoto, Tetsuya; Urano, Makoto; Shibata, Tomoyuki; Kuroda, Makoto; Ohmiya, Naoki

    2017-04-01

    Telomere shortening in leukocytes has been thought to be associated with reduced immune response capacity and increased chromosome instability. Several studies indicate that telomere length in the peripheral blood leukocyte DNA can predict clinical outcome of several cancers. We evaluated the potential association between telomere shortening in the leukocyte DNA and clinicopathological features and prognosis of gastric cancer (GC) in Japanese patients. Telomere length in leukocyte DNA was measured using quantitative real-time polymerase chain reaction (PCR) in 207 GC patients. The association between telomere length and clinicopathological features and prognosis was evaluated. These short-telomere group was significantly associated with advanced stage (p=0.015), worse overall survival (OS) and progression-free survival (PFS) (p=0.046 and 0.026, respectively). The same group was also weakly associated with overall and peritoneal recurrences (p=0.052 and 0.059, respectively). Telomere shortening in leukocyte DNA is associated with advanced stage and poor prognosis of GC, which may reflect their reduced immune response capacity or increased chromosome instability. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  12. Bacterial pneumonia following cytotoxic chemotherapy for lung cancer: clinical features, treatment outcome and prognostic factors.

    PubMed

    Yoo, Seung Soo; Cha, Seung-Ick; Shin, Kyung-Min; Lee, Shin-Yup; Kim, Chang-Ho; Park, Jae-Yong; Jung, Tae-Hoon

    2010-10-01

    Data regarding treatment outcomes and prognosis in pneumonia that occurs after lung cancer chemotherapy are lacking. We performed a retrospective study of 84 patients with clinically suspected bacterial pneumonia after cytotoxic chemotherapy for lung cancer. Small cell carcinoma was the most common histological type (36.9%, n = 31), followed by squamous cell carcinoma (35.7%, n = 30) and adenocarcinoma (21.4%, n = 18). The most frequent pathogen was Streptococcus pneumoniae (n = 14), followed by Klebsiella pneumoniae (n = 10), Staphylococcus aureus (n = 8), and Pseudomonas aeruginosa (n = 7). Of 84 patients, treatment outcome was determined for 80; the outcome was success in 52 (61.9%) and failure in 28 (33.3%); outcome remained undetermined for 4 patients (4.8%). Based on multivariate analysis, tachypnoea (respiratory rate ≥20/min) was the only significant predictor of treatment failure (odds ratio 4.79, 95% confidence interval 1.17-19.70; p = 0.030). In conclusion, bacterial pneumonia after cytotoxic chemotherapy for lung cancer was found to be caused more often by S. pneumoniae and K. pneumoniae than P. aeruginosa, and treatment failure leading to death was found to be high. Tachypnoea was independently associated with treatment failure in this population.

  13. Behavioral, Medical Imaging and Histopathological Features of a New Rat Model of Bone Cancer Pain

    PubMed Central

    Doré-Savard, Louis; Otis, Valérie; Belleville, Karine; Lemire, Myriam; Archambault, Mélanie; Tremblay, Luc; Beaudoin, Jean-François; Beaudet, Nicolas; Lecomte, Roger; Lepage, Martin; Gendron, Louis; Sarret, Philippe

    2010-01-01

    Pre-clinical bone cancer pain models mimicking the human condition are required to respond to clinical realities. Breast or prostate cancer patients coping with bone metastases experience intractable pain, which affects their quality of life. Advanced monitoring is thus required to clarify bone cancer pain mechanisms and refine treatments. In our model of rat femoral mammary carcinoma MRMT-1 cell implantation, pain onset and tumor growth were monitored for 21 days. The surgical procedure performed without arthrotomy allowed recording of incidental pain in free-moving rats. Along with the gradual development of mechanical allodynia and hyperalgesia, behavioral signs of ambulatory pain were detected at day 14 by using a dynamic weight-bearing apparatus. Osteopenia was revealed from day 14 concomitantly with disorganization of the trabecular architecture (µCT). Bone metastases were visualized as early as day 8 by MRI (T1-Gd-DTPA) before pain detection. PET (Na18F) co-registration revealed intra-osseous activity, as determined by anatomical superimposition over MRI in accordance with osteoclastic hyperactivity (TRAP staining). Pain and bone destruction were aggravated with time. Bone remodeling was accompanied by c-Fos (spinal) and ATF3 (DRG) neuronal activation, sustained by astrocyte (GFAP) and microglia (Iba1) reactivity in lumbar spinal cord. Our animal model demonstrates the importance of simultaneously recording pain and tumor progression and will allow us to better characterize therapeutic strategies in the future. PMID:21048940

  14. MRI Features of Mucinous Cancer of the Breast: Correlation With Pathologic Findings and Other Imaging Methods.

    PubMed

    Bitencourt, Almir G V; Graziano, Luciana; Osório, Cynthia A B T; Guatelli, Camila S; Souza, Juliana A; Mendonça, Maria Helena S; Marques, Elvira F

    2016-02-01

    Mucinous breast carcinoma is an uncommon histologic type of invasive breast carcinoma that can be differentiated in pure and mixed forms, which have different prognosis and treatment. MRI features of both types of mucinous breast carcinomas are discussed, illustrated, and compared with pathologic findings and with other imaging methods, including mammography, ultrasound, and PET/CT.

  15. Assessment of histopathological features of needle biopsy in recurrent prostate cancer following salvage high-intensity focused ultrasound

    PubMed Central

    Billia, Michele; Siddiqui, Khurram M.; Chan, Susanne; Li, Fan; Al-Zahrani, Ali; Gomez, Jose A.; Chin, Joseph L.

    2016-01-01

    Introduction Local recurrence of prostate cancer (PCa) following radiotherapy may be treated with curative intent using salvage high-intensity focused ultrasound (s-HIFU). The interpretation of needle core biopsy specimens following s-HIFU is a daunting task, even for experienced pathologists. We describe various histopathological features encountered in biopsy specimens following whole-gland s-HIFU in one of the largest descriptive studies to date. Methods Fifty-five patients with biopsy-proven localized radio-recurrent PCa underwent s-HIFU and transrectal ultrasound (TRUS)-guided prostatic needle biopsies at 180 days post-treatment. All biopsies were reviewed by two genitourinary pathologists. Results PCa was detected in 11 (24%) biopsies. Radiation therapy-associated changes were identified in all cases. Additional findings included extensive coagulative stromal necrosis (100%), smudgy chromatin of cancer nuclei (82%), and markedly enlarged bizarre nuclei in the residual cancer (55%). Gleason grade assignment was possible in 10 (91%) of these biopsies and concordance of Gleason grading between pre- and post-therapy specimens was observed in six (60%) cases. Conclusions The histological interpretation of needle biopsies following salvage HIFU is challenging and requires an understanding of the histopathological changes associated with this procedure in both tumoural and non-tumoural prostatic tissue. Accurate interpretation of the morphological changes following s-HIFU is instrumental for optimization of clinical decision-making and treatment planning in recurrent PCa. PMID:28096917

  16. Clinicopathological Features and Prognostic Factors Affecting Survival Outcomes in Isolated Locoregional Recurrence of Breast Cancer: Single-Institutional Series

    PubMed Central

    Kim, Hae Su; Lee, Ji Yun; Lim, Sung Hee; Lee, Jeong Eon; Kim, Seok Won; Nam, Seok Jin; Ahn, Jin Seok; Im, Young-Hyuck; Park, Yeon Hee

    2016-01-01

    Purpose The purpose of this study was to investigate the clinicopathologic features and prognostic factors affecting outcome in patients with isolated locoregional recurrence of breast cancer (ILRR). Methods We retrospectively analyzed the medical records of 104 patients who were diagnosed with ILRR and underwent curative surgery from January 2000 to December 2010 at Samsung Medical Center. Results Among 104 patients, 43 (41%) underwent total mastectomy and 61 (59%) underwent breast-conserving surgery for primary breast cancer. The median time from initial operation to ILRR was 35.7 months (4.5–132.3 months). After diagnosis of ILRR, 45 (43%) patients were treated with mastectomy, 41 (39%) with excision of recurred lesion, and 18 (17%) with node dissection. During a median follow-up of 8.9 years, the 5-year overall survival was 77% and 5-year distant metastasis-free survival (DMFS) was 54%. On multivariate analysis, younger age (< 35 years), higher stage, early onset of elapse (≤ 24 months), lymph node recurrences, and subtype of triple negative breast cancer (TNBC) were found to be independently associated with DMFS. Patients in the no chemotherapy group showed a longer DMFS after surgery for ILRR than those treated with chemotherapy (median 101.5 vs. 48.0 months, p = 0.072) but without statistical significance. Conclusion Our analysis showed that younger age (< 35 years), higher stage, early onset of relapse (≤ 24 months), lymph node recurrence, and subtype of TNBC are the worst prognostic factors for ILRR. PMID:27648567

  17. Long non-coding RNA lnc-MX1-1 is associated with poor clinical features and promotes cellular proliferation and invasiveness in prostate cancer

    SciTech Connect

    Jiang, Chen-Yi; Gao, Yuan; Wang, Xing-Jie; Ruan, Yuan; Bei, Xiao-Yu; Wang, Xiao-Hai; Jing, Yi-Feng; Zhao, Wei; Jiang, Qi; Li, Jia; Han, Bang-Min; Xia, Shu-Jie; Zhao, Fu-Jun

    2016-02-12

    Long non-coding RNAs (lncRNAs) are emerging as key molecules in human cancer genesis and progression, including prostate cancer. Large amount of lncRNAs have been found that differentially expressed between prostate cancer tissues and normal prostate tissues. Whether these lncRNAs could serve as a novel biomarker for prostate cancer diagnosis or prognosis, and their biological functions in prostate cancer need further investigation. In the present study, we identified that lncRNA lnc-MX1-1 is over-expressed in prostate cancer tissues compared with their adjacent normal prostate tissues by gene expression array profiling. The expression of lnc-MX1-1 in 60 prostate cancer cases was determined by real-time quantitative PCR and the correlations between lnc-MX1-1 expression and patients' clinical features were further analyzed. Next, we impaired lnc-MX1-1 expression using RNAi in LNCaP and 22Rv1 prostate cancer cells to explore the effects of lnc-MX1-1 on proliferation and invasiveness of the cells. Our results showed that there was a significant association between over-expression of lnc-MX1-1 and patients' clinical features such as PSA, Gleason score, metastasis, and recurrence free survival. Moreover, knockdown of lnc-MX1-1 reduced both proliferation and invasiveness of LNCaP and 22Rv1 cells. In conclusion, the results suggest that lnc-MX1-1 may serve as a potential biomarker and therapeutic target for prostate cancer. - Highlights: • LncRNA lnc-MX1-1 is up-regulated in prostate cancer. • Overexpression of lnc-MX1-1 is correlated with poor prostate cancer clinical features. • Knockdown of lnc-MX1-1 reduces proliferation and invasiveness of prostate cancer cells.

  18. Relationship between MLH-1, MSH-2, PMS-2,MSH-6 expression and clinicopathological features in colorectal cancer.

    PubMed

    Karahan, Birgül; Argon, Asuman; Yıldırım, Mehmet; Vardar, Enver

    2015-01-01

    Colorectal cancers are the third most common in both sexes and they are the second most common cause of cancer-related death. 12-15% of colorectal cancers develop through microsatellite instability (the hereditary mutation in at least one of DNA mismatch repair genes) pathway and they are 2-5% hereditary. In this study, we investigated the correlation between the clinicopathological features themselves and also the correlation between them and the immunohistochemical MLH-1, MSH-2, PMS-2, MSH-6 expressions in a total of 186 resection materials with colorectal adenocarcinoma between 2008 and 2012. All the cases were retrospectively evaluated in terms of age, sex, localization, size, accompanying polyp, multiple tumor, arising from polyp, differentiation, mucinous differentiation, pathological tumor stage, lymphovascular and perineural invasion, lymphocyte amount in the tumor microenvironment, surgical border and lymph node metastasis. We prepared multiple tissue blocks which had 4-millimeter tumor. Immunohistochemically, MLH-1, MSH-2, PMS-2, MSH-6 primary antibodies were studied. Statistically, "Kruskal-Wallis" ve "Pearson's chi-squared" tests were used. We found a positive correlation between loss of MLH-1 and PMS-2 expressions and the right-colon location, poor and mucinous differentiation and dense lymphocytic infiltration. In addition, loss of MSH-2 and MSH-6 expressions was correlated with the right-colon location, poor and mucinous differentiation. We found a meaningful relationship between immunohistochemical markers and clinicopathological features usually observed in tumors with microsatellite instability. This finding may arouse suspicion for MSI. However, the findings in our study must be supported with studies conducted in large series including molecular methods.

  19. TU-C-17A-10: Patient Features Based Dosimetric Pareto Front Prediction In Esophagus Cancer Radiotherapy

    SciTech Connect

    Wang, J; Zhao, K; Peng, J; Hu, W; Jin, X

    2014-06-15

    Purpose: The purpose of this study is to study the feasibility of the dosimetric pareto front (PF) prediction based on patient anatomic and dosimetric parameters for esophagus cancer patients. Methods: Sixty esophagus patients in our institution were enrolled in this study. A total 2920 IMRT plans were created to generated PF for each patient. On average, each patient had 48 plans. The anatomic and dosimetric features were extracted from those plans. The mean lung dose (MLD), mean heart dose (MHD), spinal cord max dose and PTV homogeneous index (PTVHI) were recorded for each plan. The principal component analysis (PCA) was used to extract overlap volume histogram (OVH) features between PTV and other critical organs. The full dataset was separated into two parts include the training dataset and the validation dataset. The prediction outcomes were the MHD and MLD for the current study. The spearman rank correlation coefficient was used to evaluate the correlation between the anatomical features and dosimetric features. The PF was fit by the the stepwise multiple regression method. The cross-validation method was used to evaluation the model. Results: The mean prediction error of the MHD was 465 cGy with 100 repetitions. The most correlated factors were the first principal components of the OVH between heart and PTV, and the overlap between heart and PTV in Z-axis. The mean prediction error of the MLD was 195 cGy. The most correlated factors were the first principal components of the OVH between lung and PTV, and the overlap between lung and PTV in Z-axis. Conclusion: It is feasible to use patients anatomic and dosimetric features to generate a predicted PF. Additional samples and further studies were required to get a better prediction model.

  20. Supervised multi-view canonical correlation analysis (sMVCCA): integrating histologic and proteomic features for predicting recurrent prostate cancer.

    PubMed

    Lee, George; Singanamalli, Asha; Wang, Haibo; Feldman, Michael D; Master, Stephen R; Shih, Natalie N C; Spangler, Elaine; Rebbeck, Timothy; Tomaszewski, John E; Madabhushi, Anant

    2015-01-01

    In this work, we present a new methodology to facilitate prediction of recurrent prostate cancer (CaP) following radical prostatectomy (RP) via the integration of quantitative image features and protein expression in the excised prostate. Creating a fused predictor from high-dimensional data streams is challenging because the classifier must 1) account for the "curse of dimensionality" problem, which hinders classifier performance when the number of features exceeds the number of patient studies and 2) balance potential mismatches in the number of features across different channels to avoid classifier bias towards channels with more features. Our new data integration methodology, supervised Multi-view Canonical Correlation Analysis (sMVCCA), aims to integrate infinite views of highdimensional data to provide more amenable data representations for disease classification. Additionally, we demonstrate sMVCCA using Spearman's rank correlation which, unlike Pearson's correlation, can account for nonlinear correlations and outliers. Forty CaP patients with pathological Gleason scores 6-8 were considered for this study. 21 of these men revealed biochemical recurrence (BCR) following RP, while 19 did not. For each patient, 189 quantitative histomorphometric attributes and 650 protein expression levels were extracted from the primary tumor nodule. The fused histomorphometric/proteomic representation via sMVCCA combined with a random forest classifier predicted BCR with a mean AUC of 0.74 and a maximum AUC of 0.9286. We found sMVCCA to perform statistically significantly (p < 0.05) better than comparative state-of-the-art data fusion strategies for predicting BCR. Furthermore, Kaplan-Meier analysis demonstrated improved BCR-free survival prediction for the sMVCCA-fused classifier as compared to histology or proteomic features alone.

  1. Association between bilateral asymmetry of kinetic features computed from the DCE-MRI images and breast cancer

    NASA Astrophysics Data System (ADS)

    Yang, Qian; Li, Lihua; Zhang, Juan; Zhang, Chengjie; Zheng, Bin

    2013-03-01

    Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of breast yields high sensitivity but relatively lower specificity. To improve diagnostic accuracy of DCE-MRI, we investigated the association between bilateral asymmetry of kinetic features computed from the left and right breasts and breast cancer detection with the hypothesis that due to the growth of angiogenesis associated with malignant lesions, the average dynamic contrast enhancement computed from the breasts depicting malignant lesions should be higher than negative or benign breasts. To test this hypothesis, we assembled a database involving 130 DCE-MRI examinations including 81 malignant and 49 benign cases. We developed a computerized scheme that automatically segments breast areas depicted on MR images and computes kinetic features related to the bilateral asymmetry of contrast enhancement ratio between two breasts. An artificial neural network (ANN) was then used to classify between malignant and benign cases. To identify the optimal approach to compute the bilateral kinetic feature asymmetry, we tested 4 different thresholds to select the enhanced pixels (voxels) from DCE-MRI images and compute the kinetic features. Using the optimal threshold, the ANN had a classification performance measured by the area under the ROC curve of AUC=0.79+/-0.04. The positive and negative predictive values were 0.75 and 0.67, respectively. The study suggested that the bilateral asymmetry of kinetic features or contrast enhancement of breast background tissue could provide valuable supplementary information to distinguish between the malignant and benign cases, which can be fused into existing computer-aided detection schemes to improve classification performance.

  2. [Impacts of hypoxia on the features and chemoresistance of cancer stem cells in Hep-2 cells and underlying mechanism].

    PubMed

    Qu, Yong-tao; Li, Xiao-ming; Xu, Ou; Wang, Mao-xin; Lu, Xiu-ying

    2012-03-01

    To investigate the effects of hypoxia on the features and chemoresistance of cancer stem cells in Hep-2 cells and underlying mechanism. The shRNA interference recombinant plasmid targeting HIF-1α was synthesized and transfected into Hep-2 cells. The HIF-1α knockdown Hep-2 cells were established after clonal selection and the expression of HIF-1α was measured. The cellular features including proliferation, clonal formation, cell cycle, apoptosis and CD133 phenotype were measured in Hep-2 cells cultured under hypoxic condition in vitro. CD133+ cells were sorted from Hep-2 cells with flow cytometry. Clonal formation test and cisplatin treatment were carried out, and the expressions of related genes (Oct-4, suvivin and p53) in CD133+ cells were measured. HIF-1α knockdown Hep-2 cells was successfully established, as evidenced by the reduced mRNA and protein expressions of HIF-1α. The Hep-2 cells cultured under hypoxic microenvironment showed higher proliferation and clonal formation activity, cell cycle arrest in G0/G1, lower apoptosis, up-regulated CD133, however the effects of hypoxia reduced in HIF-1α knockdown Hep-2 cells. CD133+ cells were successfully sorted from Hep-2 cells, and the CD133+ cells showed increased clonal formation activity and cisplatin treatment resistance in hypoxia. Also the effects of hypoxia on CD133+ cells decreased with HIF-1α knockdown, showing down-regulated Oct-4 and survivin and up-regulated p53. Hypoixa can induce the