Screening and validation of serum protein biomarkers for early postmenopausal osteoporosis diagnosis.

PubMed

Wang, Long; Hu, Ya-Qian; Zhao, Zhuo-Jie; Zhang, Hong-Yang; Gao, Bo; Lu, Wei-Guang; Xu, Xiao-Long; Lin, Xi-Sheng; Wang, Jin-Peng; Jie, Qiang; Luo, Zhuo-Jing; Yang, Liu

2017-12-01

Postmenopausal osteoporosis is one of the most prominent worldwide public health problems and the morbidity is increasing with the aging population. It has been demonstrated that early diagnosis and intervention delay the disease progression and improve the outcome. Therefore, searching for biomarkers that are able to identify postmenopausal women at high risk for developing osteoporosis is an effective way to improve the quality of life of patients, and alleviate social and economic burdens. In the present study, a protein array was used to identify potential biomarkers. The bone mineral densities of 10 rats were dynamically measured in an ovariectomized model by micro‑computed tomography assessment, and the early stage of osteoporosis was defined. Through the protein array‑based screening, the expression levels of six serum protein biomarkers in ovariectomized rats were observed to alter at the initiation stage of the postmenopausal osteoporosis. Fractalkine, tissue inhibitor of metalloproteinases‑1 and monocyte chemotactic protein‑1 were finally demonstrated to be increased in the serum of eight enrolled postmenopausal osteoporosis patients using ELISA assay and were correlated with the severity of progressive bone loss. These biomarkers may be explored as potential early biomarkers to readily evaluate and diagnose postmenopausal osteoporosis in the clinic.

Bladder Cancer-associated Protein, a Potential Prognostic Biomarker in Human Bladder Cancer*

PubMed Central

Moreira, José M. A.; Ohlsson, Gita; Gromov, Pavel; Simon, Ronald; Sauter, Guido; Celis, Julio E.; Gromova, Irina

2010-01-01

It is becoming increasingly clear that no single marker will have the sensitivity and specificity necessary to be used on its own for diagnosis/prognosis of tumors. Interpatient and intratumor heterogeneity provides overwhelming odds against the existence of such an ideal marker. With this in mind, our laboratory has been applying a long term systematic approach to identify multiple biomarkers that can be used for clinical purposes. As a result of these studies, we have identified and reported several candidate biomarker proteins that are deregulated in bladder cancer. Following the conceptual biomarker development phases proposed by the Early Detection Research Network, we have taken some of the most promising candidate proteins into postdiscovery validation studies, and here we report on the characterization of one such biomarker, the bladder cancer-associated protein (BLCAP), formerly termed Bc10. To characterize BLCAP protein expression and cellular localization patterns in benign bladder urothelium and urothelial carcinomas (UCs), we used two independent sets of samples from different patient cohorts: a reference set consisting of 120 bladder specimens (formalin-fixed as well as frozen biopsies) and a validation set consisting of 2,108 retrospectively collected UCs with long term clinical follow-up. We could categorize the UCs examined into four groups based on levels of expression and subcellular localization of BLCAP protein and showed that loss of BLCAP expression is associated with tumor progression. The results indicated that increased expression of this protein confers an adverse patient outcome, suggesting that categorization of staining patterns for this protein may have prognostic value. Finally, we applied a combinatorial two-marker discriminator using BLCAP and adipocyte-type fatty acid-binding protein, another UC biomarker previously reported by us, and found that the combination of the two markers correlated more closely with grade and/or stage of

Interactomic approach for evaluating nucleophosmin-binding proteins as biomarkers for Ewing's sarcoma.

PubMed

Haga, Ayako; Ogawara, Yoko; Kubota, Daisuke; Kitabayashi, Issay; Murakami, Yasufumi; Kondo, Tadashi

2013-06-01

Nucleophosmin (NPM) is a novel prognostic biomarker for Ewing's sarcoma. To evaluate the prognostic utility of NPM, we conducted an interactomic approach to characterize the NPM protein complex in Ewing's sarcoma cells. A gene suppression assay revealed that NPM promoted cell proliferation and the invasive properties of Ewing's sarcoma cells. FLAG-tag-based affinity purification coupled with liquid chromatography-tandem mass spectrometry identified 106 proteins in the NPM protein complex. The functional classification suggested that the NPM complex participates in critical biological events, including ribosome biogenesis, regulation of transcription and translation, and protein folding, that are mediated by these proteins. In addition to JAK1, a candidate prognostic biomarker for Ewing's sarcoma, the NPM complex, includes 11 proteins known as prognostic biomarkers for other malignancies. Meta-analysis of gene expression profiles of 32 patients with Ewing's sarcoma revealed that 6 of 106 were significantly and independently associated with survival period. These observations suggest a functional role as well as prognostic value of these NPM complex proteins in Ewing's sarcoma. Further, our study suggests the potential applications of interactomics in conjunction with meta-analysis for biomarker discovery. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identifying Thoracic Malignancies Through Pleural Fluid Biomarkers: A Predictive Multivariate Model.

PubMed

Porcel, José M; Esquerda, Aureli; Martínez-Alonso, Montserrat; Bielsa, Silvia; Salud, Antonieta

2016-03-01

The diagnosis of malignant pleural effusions may be challenging when cytological examination of aspirated pleural fluid is equivocal or noncontributory. The purpose of this study was to identify protein candidate biomarkers differentially expressed in the pleural fluid of patients with mesothelioma, lung adenocarcinoma, lymphoma, and tuberculosis (TB).A multiplex protein biochip comprising 120 biomarkers was used to determine the pleural fluid protein profile of 29 mesotheliomas, 29 lung adenocarcinomas, 12 lymphomas, and 35 tuberculosis. The relative abundance of these predetermined biomarkers among groups served to establish the differential diagnosis of: malignant versus benign (TB) effusions, lung adenocarcinoma versus mesothelioma, and lymphoma versus TB. The selected putative markers were validated using widely available commercial techniques in an independent sample of 102 patients.Significant differences were found in the protein expressions of metalloproteinase-9 (MMP-9), cathepsin-B, C-reactive protein, and chondroitin sulfate between malignant and TB effusions. When integrated into a scoring model, these proteins yielded 85% sensitivity, 100% specificity, and an area under the curve (AUC) of 0.98 for labeling malignancy in the verification sample. For lung adenocarcinoma-mesothelioma discrimination, combining CA19-9, CA15-3, and kallikrein-12 had maximal discriminatory capacity (65% sensitivity, 100% specificity, AUC 0.94); figures which also refer to the validation set. Last, cathepsin-B in isolation was only moderately useful (sensitivity 89%, specificity 62%, AUC 0.75) in separating lymphomatous and TB effusions. However, this last differentiation improved significantly when cathepsin-B was used with respect to the patient's age (sensitivity 72%, specificity 100%, AUC 0.94).In conclusion, panels of 4 (i.e., MMP-9, cathepsin-B, C-reactive protein, chondroitin sulfate), or 3 (i.e., CA19-9, CA15-3, kallikrein-12) different protein biomarkers on pleural

Exosomal Fetuin-A identified by proteomics: a novel urinary biomarker for detecting acute kidney injury

PubMed Central

Zhou, Hua; Pisitkun, Trairak; Aponte, Angel; Yuen, Peter S.T.; Hoffert, Jason D.; Yasuda, Hideo; Hu, Xuzhen; Chawla, Lakhmir; Shen, Rong-Fong; Knepper, Mark A.; Star., Robert A.

2008-01-01

Urinary exosomes containing apical membrane and intracellular fluid are normally secreted into the urine from all nephron segments, and may carry protein markers of renal dysfunction and structural injury. We aimed to discover biomarkers in urinary exosomes to detect acute kidney injury (AKI) which has a high mortality and morbidity. Animals were injected intravenously with cisplatin. Urinary exosomes were isolated by differential centrifugation. Protein changes were evaluated by two-dimensional difference in gel electrophoresis and changed proteins were identified by MALDI-TOF-TOF or LC-MS/MS. The identified candidate biomarkers were validated by western blotting in individual urine samples from rats subjected to cisplatin injection; bilateral ischemia and reperfusion (I/R); volume depletion (VD); and ICU patients with and without AKI. We identified 18 proteins that were increased and 9 proteins that were decreased 8 hr after cisplatin. Most of the candidates could not be validated by western blotting. However, exosomal Fetuin-A increased 52.5-fold at day 2 (1 day before serum creatinine increase and tubule damage) and remained elevated 51.5-fold at day 5 (peak renal injury) after cisplatin injection. By immuno-electron microscopy and elution studies, Fetuin-A was located inside urinary exosomes. Urinary Fetuin-A was increased 31.6-fold in the early phase (2~8hr) of ischemia/reperfusion, but not in prerenal azotemia. Urinary exosomal Fetuin-A also increased in three ICU patients with AKI compared to the patients without AKI. We conclude that 1) Proteomic analysis of urinary exosomes can provide biomarker candidates for the diagnosis of AKI; 2) Urinary Fetuin-A might be a predictive biomarker of structural renal injury. PMID:17021608

RNA Sequencing Identifies Novel Translational Biomarkers of Kidney Fibrosis

PubMed Central

Craciun, Florin L.; Bijol, Vanesa; Ajay, Amrendra K.; Rao, Poornima; Kumar, Ramya K.; Hutchinson, John; Hofmann, Oliver; Joshi, Nikita; Luyendyk, James P.; Kusebauch, Ulrike; Moss, Christopher L.; Srivastava, Anand; Himmelfarb, Jonathan; Waikar, Sushrut S.; Moritz, Robert L.

2016-01-01

CKD is the gradual, asymptomatic loss of kidney function, but current tests only identify CKD when significant loss has already happened. Several potential biomarkers of CKD have been reported, but none have been approved for preclinical or clinical use. Using RNA sequencing in a mouse model of folic acid-induced nephropathy, we identified ten genes that track kidney fibrosis development, the common pathologic finding in patients with CKD. The gene expression of all ten candidates was confirmed to be significantly higher (approximately ten- to 150-fold) in three well established, mechanistically distinct mouse models of kidney fibrosis than in models of nonfibrotic AKI. Protein expression of these genes was also high in the folic acid model and in patients with biopsy-proven kidney fibrosis. mRNA expression of the ten genes increased with increasing severity of kidney fibrosis, decreased in response to therapeutic intervention, and increased only modestly (approximately two- to five-fold) with liver fibrosis in mice and humans, demonstrating specificity for kidney fibrosis. Using targeted selected reaction monitoring mass spectrometry, we detected three of the ten candidates in human urine: cadherin 11 (CDH11), macrophage mannose receptor C1 (MRC1), and phospholipid transfer protein (PLTP). Furthermore, urinary levels of each of these three proteins distinguished patients with CKD (n=53) from healthy individuals (n=53; P<0.05). In summary, we report the identification of urinary CDH11, MRC1, and PLTP as novel noninvasive biomarkers of CKD. PMID:26449608

Proteomic Analysis of Saliva Identifies Potential Biomarkers for Orthodontic Tooth Movement

PubMed Central

Ellias, Mohd Faiz; Zainal Ariffin, Shahrul Hisham; Karsani, Saiful Anuar; Abdul Rahman, Mariati; Senafi, Shahidan; Megat Abdul Wahab, Rohaya

2012-01-01

Orthodontic treatment has been shown to induce inflammation, followed by bone remodelling in the periodontium. These processes trigger the secretion of various proteins and enzymes into the saliva. This study aims to identify salivary proteins that change in expression during orthodontic tooth movement. These differentially expressed proteins can potentially serve as protein biomarkers for the monitoring of orthodontic treatment and tooth movement. Whole saliva from three healthy female subjects were collected before force application using fixed appliance and at 14 days after 0.014′′ Niti wire was applied. Salivary proteins were resolved using two-dimensional gel electrophoresis (2DE) over a pH range of 3–10, and the resulting proteome profiles were compared. Differentially expressed protein spots were then identified by MALDI-TOF/TOF tandem mass spectrometry. Nine proteins were found to be differentially expressed; however, only eight were identified by MALDI-TOF/TOF. Four of these proteins—Protein S100-A9, immunoglobulin J chain, Ig alpha-1 chain C region, and CRISP-3—have known roles in inflammation and bone resorption. PMID:22919344

Glycosylation Changes in Serum Proteins Identify Patients with Pancreatic Cancer.

PubMed

Drabik, Anna; Bodzon-Kulakowska, Anna; Suder, Piotr; Silberring, Jerzy; Kulig, Jan; Sierzega, Marek

2017-04-07

After more than a decade of biomarker discovery using advanced proteomic and genomic approaches, very few biomarkers have been involved in clinical diagnostics. Most candidate biomarkers are focused on the protein component. Targeting post-translational modifications (PTMs) in combination with protein sequences will provide superior diagnostic information with regards to sensitivity and specificity. Glycosylation is one of the most common and functionally important PTMs. It plays a central role in many biological processes, including protein folding, host-pathogen interactions, immune response, and inflammation. Cancer-associated aberrant glycosylation has been identified in various types of cancer. Expression of cancer-specific glycan epitopes represents an excellent opportunity for diagnostics and potentially specific detection of tumors. Here, we report four proteins (LIFR, CE350, VP13A, HPT) found in sera from pancreatic cancer patients carrying aberrant glycan structures as compared to those of controls.

Protein biomarker validation via proximity ligation assays.

PubMed

Blokzijl, A; Nong, R; Darmanis, S; Hertz, E; Landegren, U; Kamali-Moghaddam, M

2014-05-01

The ability to detect minute amounts of specific proteins or protein modifications in blood as biomarkers for a plethora of human pathological conditions holds great promise for future medicine. Despite a large number of plausible candidate protein biomarkers published annually, the translation to clinical use is impeded by factors such as the required size of the initial studies, and limitations of the technologies used. The proximity ligation assay (PLA) is a versatile molecular tool that has the potential to address some obstacles, both in validation of biomarkers previously discovered using other techniques, and for future routine clinical diagnostic needs. The enhanced specificity of PLA extends the opportunities for large-scale, high-performance analyses of proteins. Besides advantages in the form of minimal sample consumption and an extended dynamic range, the PLA technique allows flexible assay reconfiguration. The technology can be adapted for detecting protein complexes, proximity between proteins in extracellular vesicles or in circulating tumor cells, and to address multiple post-translational modifications in the same protein molecule. We discuss herein requirements for biomarker validation, and how PLA may play an increasing role in this regard. We describe some recent developments of the technology, including proximity extension assays, the use of recombinant affinity reagents suitable for use in proximity assays, and the potential for single cell proteomics. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. © 2013.

Identification of Surface Protein Biomarkers of Listeria monocytogenes via Bioinformatics and Antibody-Based Protein Detection Tools

PubMed Central

Zhang, Cathy X. Y.; Brooks, Brian W.; Huang, Hongsheng; Pagotto, Franco

2016-01-01

ABSTRACT The Gram-positive bacterium Listeria monocytogenes causes a significant percentage of the fatalities among foodborne illnesses in humans. Surface proteins specifically expressed in a wide range of L. monocytogenes serotypes under selective enrichment culture conditions could serve as potential biomarkers for detection and isolation of this pathogen via antibody-based methods. Our study aimed to identify such biomarkers. Interrogation of the L. monocytogenes serotype 4b strain F2365 genome identified 130 putative or known surface proteins. The homologues of four surface proteins, LMOf2365_0578, LMOf2365_0581, LMOf2365_0639, and LMOf2365_2117, were assessed as biomarkers due to the presence of conserved regions among strains of L. monocytogenes which are variable among other Listeria species. Rabbit polyclonal antibodies against the four recombinant proteins revealed the expression of only LMOf2365_0639 on the surface of serotype 4b strain LI0521 cells despite PCR detection of mRNA transcripts for all four proteins in the organism. Three of 35 monoclonal antibodies (MAbs) to LMOf2365_0639, MAbs M3643, M3644, and M3651, specifically recognized 42 (91.3%) of 46 L. monocytogenes lineage I and II isolates grown in nonselective brain heart infusion medium. While M3644 and M3651 reacted with 14 to 15 (82.4 to 88.2%) of 17 L. monocytogenes lineage I and II isolates, M3643 reacted with 22 (91.7%) of 24 lineage I, II, and III isolates grown in selective enrichment media (UVM1, modified Fraser, Palcam, and UVM2 media). The three MAbs exhibited only weak reactivities (the optical densities at 414 nm were close to the cutoff value) to some other Listeria species grown in selective enrichment media. Collectively, the data indicate the potential of LMOf2365_0639 as a surface biomarker of L. monocytogenes, with the aid of specific MAbs, for pathogen detection, identification, and isolation in clinical, environmental, and food samples. IMPORTANCE L. monocytogenes is

SWATH-based proteomics identified carbonic anhydrase 2 as a potential diagnosis biomarker for nasopharyngeal carcinoma

PubMed Central

Luo, Yanzhang; Mok, Tin Seak; Lin, Xiuxian; Zhang, Wanling; Cui, Yizhi; Guo, Jiahui; Chen, Xing; Zhang, Tao; Wang, Tong

2017-01-01

Nasopharyngeal carcinoma (NPC) is a serious threat to public health, and the biomarker discovery is of urgent needs. The data-independent mode (DIA) based sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry (MS) has been proved to be precise in protein quantitation and efficient for cancer biomarker researches. In this study, we performed the first SWATH-MS analysis comparing the NPC and normal tissues. Spike-in stable isotope labeling by amino acids in cell culture (super-SILAC) MS was used as a shotgun reference. We identified and quantified 1414 proteins across all SWATH-MS analyses. We found that SWATH-MS had a unique feature to preferentially detect proteins with smaller molecular weights than either super-SILAC MS or human proteome background. With SWATH-MS, 29 significant differentially express proteins (DEPs) were identified. Among them, carbonic anhydrase 2 (CA2) was selected for further validation per novelty, MS quality and other supporting rationale. With the tissue microarray analysis, we found that CA2 had an AUC of 0.94 in differentiating NPC from normal tissue samples. In conclusion, SWATH-MS has unique features in proteome analysis, and it leads to the identification of CA2 as a potentially new diagnostic biomarker for NPC. PMID:28117408

Major depressive disorder: insight into candidate cerebrospinal fluid protein biomarkers from proteomics studies.

PubMed

Al Shweiki, Mhd Rami; Oeckl, Patrick; Steinacker, Petra; Hengerer, Bastian; Schönfeldt-Lecuona, Carlos; Otto, Markus

2017-06-01

Major Depressive Disorder (MDD) is the leading cause of global disability, and an increasing body of literature suggests different cerebrospinal fluid (CSF) proteins as biomarkers of MDD. The aim of this review is to summarize the suggested CSF biomarkers and to analyze the MDD proteomics studies of CSF and brain tissues for promising biomarker candidates. Areas covered: The review includes the human studies found by a PubMed search using the following terms: 'depression cerebrospinal fluid biomarker', 'major depression biomarker CSF', 'depression CSF biomarker', 'proteomics depression', 'proteomics biomarkers in depression', 'proteomics CSF biomarker in depression', and 'major depressive disorder CSF'. The literature analysis highlights promising biomarker candidates and demonstrates conflicting results on others. It reveals 42 differentially regulated proteins in MDD that were identified in more than one proteomics study. It discusses the diagnostic potential of the biomarker candidates and their association with the suggested pathologies. Expert commentary: One ultimate goal of finding biomarkers for MDD is to improve the diagnostic accuracy to achieve better treatment outcomes; due to the heterogeneous nature of MDD, using bio-signatures could be a good strategy to differentiate MDD from other neuropsychiatric disorders. Notably, further validation studies of the suggested biomarkers are still needed.

A cross sectional study of two independent cohorts identifies serum biomarkers for facioscapulohumeral muscular dystrophy (FSHD)

PubMed Central

Petek, Lisa M.; Rickard, Amanda M.; Budech, Christopher; Poliachik, Sandra L.; Shaw, Dennis; Ferguson, Mark R.; Tawil, Rabi; Friedman, Seth D.; Miller, Daniel G.

2016-01-01

Measuring the severity and progression of facioscapulohumeral muscular dystrophy (FSHD) is particularly challenging because muscle weakness progresses over long periods of time and can be sporadic. Biomarkers are essential for measuring disease burden and testing treatment strategies. We utilized the sensitive, specific, high-throughput SomaLogic proteomics platform of 1129 proteins to identify proteins with levels that correlate with FSHD severity in a cross-sectional study of two independent cohorts. We discovered biomarkers that correlate with clinical severity and disease burden measured by magnetic resonance imaging. Sixty-eight proteins in the Rochester cohort (n = 48) and 51 proteins in the Seattle cohort (n = 30) had significantly different levels in FSHD-affected individuals when compared with controls (p-value ≤ .005). A subset of these varied by at least 1.5 fold and four biomarkers were significantly elevated in both cohorts. Levels of creatine kinase MM and MB isoforms, carbonic anhydrase III, and troponin I type 2 reliably predicted the disease state and correlated with disease severity. Other novel biomarkers were also discovered that may reveal mechanisms of disease pathology. Assessing the levels of these biomarkers during clinical trials may add significance to other measures of quantifying disease progression or regression. PMID:27185459

Selenium-binding protein 1: a sensitive urinary biomarker to detect heavy metal-induced nephrotoxicity.

PubMed

Lee, Eui Kyung; Shin, Young-Jun; Park, Eun Young; Kim, Nam Deuk; Moon, Aree; Kwack, Seung Jun; Son, Ji Yeon; Kacew, Sam; Lee, Byung Mu; Bae, Ok-Nam; Kim, Hyung Sik

2017-04-01

Identifying novel biomarkers to detect nephrotoxicity is clinically important. Here, we attempted to identify new biomarkers for mercury-induced nephrotoxicity and compared their sensitivity to that of traditional biomarkers in animal models. Comparative proteomics analysis was performed in kidney tissues of Sprague-Dawley rats after oral treatment with HgCl 2 (0.1, 1, or 5 mg/kg/day) for 21 days. Kidney cortex tissues were analyzed by two-dimensional gel electrophoresis/matrix-assisted laser desorption/ionization, and differentially expressed proteins were identified. The corresponding spots were quantitated by RT-PCR. Selenium-binding protein 1 (SBP1) was found to be the most markedly upregulated protein in the kidney cortex of rats after HgCl 2 administration. However, blood urea nitrogen, serum creatinine, and glucose levels increased significantly only in the 1 or 5 mg/kg HgCl 2 -treated groups. A number of urinary excretion proteins, including kidney injury molecule-1, clusterin, monocyte chemoattractant protein-1, and β-microglobulin, increased dose-dependently. Histopathological examination revealed severe proximal tubular damage in high-dose (5 mg/kg) HgCl 2 -exposed groups. In addition, urinary excretion of SBP1 significantly increased in a dose-dependent manner. To confirm the critical role of SBP1 as a biomarker for nephrotoxicity, normal kidney proximal tubular cells were treated with HgCl 2 , CdCl 2 , or cisplatin for 24 h. SBP1 levels significantly increased in conditioned media exposed to nephrotoxicants, but decreased in cell lysates. Our investigations suggest that SBP1 may play a critical role in the pathological processes underlying chemical-induced nephrotoxicity. Thus, urinary excretion of SBP1 might be a sensitive and specific biomarker to detect early stages of kidney injury.

Protein isoform-specific validation defines multiple chloride intracellular channel and tropomyosin isoforms as serological biomarkers of ovarian cancer.

PubMed

Tang, Hsin-Yao; Beer, Lynn A; Tanyi, Janos L; Zhang, Rugang; Liu, Qin; Speicher, David W

2013-08-26

New serological biomarkers for early detection and clinical management of ovarian cancer are urgently needed, and many candidates have been reported. A major challenge frequently encountered when validating candidates in patients is establishing quantitative assays that distinguish between highly homologous proteins. The current study tested whether multiple members of two recently discovered ovarian cancer biomarker protein families, chloride intracellular channel (CLIC) proteins and tropomyosins (TPM), were detectable in ovarian cancer patient sera. A multiplexed, label-free multiple reaction monitoring (MRM) assay was established to target peptides specific to all detected CLIC and TPM family members, and their serum levels were quantitated for ovarian cancer patients and non-cancer controls. In addition to CLIC1 and TPM1, which were the proteins initially discovered in a xenograft mouse model, CLIC4, TPM2, TPM3, and TPM4 were present in ovarian cancer patient sera at significantly elevated levels compared with controls. Some of the additional biomarkers identified in this homolog-centric verification and validation approach may be superior to the previously identified biomarkers at discriminating between ovarian cancer and non-cancer patients. This demonstrates the importance of considering all potential protein homologs and using quantitative assays for cancer biomarker validation with well-defined isoform specificity. This manuscript addresses the importance of distinguishing between protein homologs and isoforms when identifying and validating cancer biomarkers in plasma or serum. Specifically, it describes the use of targeted in-depth LC-MS/MS analysis to determine the members of two protein families, chloride intracellular channel (CLIC) and tropomyosin (TPM) proteins that are detectable in sera of ovarian cancer patients. It then establishes a multiplexed isoform- and homology-specific MRM assay to quantify all observed gene products in these two protein

Proteomics-based approach identified differentially expressed proteins with potential roles in endometrial carcinoma.

PubMed

Li, Zhengyu; Min, Wenjiao; Huang, Canhua; Bai, Shujun; Tang, Minghai; Zhao, Xia

2010-01-01

We used proteomic approaches to identify altered expressed proteins in endometrial carcinoma, with the aim of discovering potential biomarkers or therapeutic targets for endometrial carcinoma. The global proteins extracted from endometrial carcinoma and normal endometrial tissues were separated by 2-dimensional electrophoresis and analyzed with PDQuest (Bio-Rad, Hercules, Calif) software. The differentially expressed spots were identified by mass spectrometry and searched against NCBInr protein database. Those proteins with potential roles were confirmed by Western blotting and immunohistochemical assays. Ninety-nine proteins were identified by mass spectrometry, and a cluster diagram analysis indicated that these proteins were involved in metabolism, cell transformation, protein folding, translation and modification, proliferation and apoptosis, signal transduction, cytoskeleton, and so on. In confirmatory immunoblotting and immunohistochemical analyses, overexpressions of epidermal fatty acid-binding protein, calcyphosine, and cyclophilin A were also observed in endometrial carcinoma tissues, which were consistent with the proteomic results. Our results suggested that these identified proteins, including epidermal fatty acid-binding protein, calcyphosine, and cyclophilin A, might be of potential values in the studies of endometrial carcinogenesis or investigations of diagnostic biomarkers or treatment targets for endometrial carcinoma.

A structured proteomic approach identifies 14-3-3Sigma as a novel and reliable protein biomarker in panel based differential diagnostics of liver tumors.

PubMed

Reis, Henning; Pütter, Carolin; Megger, Dominik A; Bracht, Thilo; Weber, Frank; Hoffmann, Andreas-C; Bertram, Stefanie; Wohlschläger, Jeremias; Hagemann, Sascha; Eisenacher, Martin; Scherag, André; Schlaak, Jörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

2015-06-01

Hepatocellular carcinoma (HCC) is a major lethal cancer worldwide. Despite sophisticated diagnostic algorithms, the differential diagnosis of small liver nodules still is difficult. While imaging techniques have advanced, adjuvant protein-biomarkers as glypican3 (GPC3), glutamine-synthetase (GS) and heat-shock protein 70 (HSP70) have enhanced diagnostic accuracy. The aim was to further detect useful protein-biomarkers of HCC with a structured systematic approach using differential proteome techniques, bring the results to practical application and compare the diagnostic accuracy of the candidates with the established biomarkers. After label-free and gel-based proteomics (n=18 HCC/corresponding non-tumorous liver tissue (NTLT)) biomarker candidates were tested for diagnostic accuracy in immunohistochemical analyses (n=14 HCC/NTLT). Suitable candidates were further tested for consistency in comparison to known protein-biomarkers in HCC (n=78), hepatocellular adenoma (n=25; HCA), focal nodular hyperplasia (n=28; FNH) and cirrhosis (n=28). Of all protein-biomarkers, 14-3-3Sigma (14-3-3S) exhibited the most pronounced up-regulation (58.8×) in proteomics and superior diagnostic accuracy (73.0%) in the differentiation of HCC from non-tumorous hepatocytes also compared to established biomarkers as GPC3 (64.7%) and GS (45.4%). 14-3-3S was part of the best diagnostic three-biomarker panel (GPC3, HSP70, 14-3-3S) for the differentiation of HCC and HCA which is of most important significance. Exclusion of GS and inclusion of 14-3-3S in the panel (>1 marker positive) resulted in a profound increase in specificity (+44.0%) and accuracy (+11.0%) while sensitivity remained stable (96.0%). 14-3-3S is an interesting protein biomarker with the potential to further improve the accuracy of differential diagnostic process of hepatocellular tumors. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Biomarker Candidates of Chlamydophila pneumoniae Proteins and Protein Fragments Identified by Affinity-Proteomics Using FTICR-MS and LC-MS/MS

NASA Astrophysics Data System (ADS)

Susnea, Iuliana; Bunk, Sebastian; Wendel, Albrecht; Hermann, Corinna; Przybylski, Michael

2011-04-01

We report here an affinity-proteomics approach that combines 2D-gel electrophoresis and immunoblotting with high performance mass spectrometry to the identification of both full length protein antigens and antigenic fragments of Chlamydophila pneumoniae (C. pneumoniae). The present affinity-mass spectrometry approach effectively utilized high resolution FTICR mass spectrometry and LC-tandem-MS for protein identification, and enabled the identification of several new highly antigenic C. pneumoniae proteins that were not hitherto reported or previously detected only in other Chlamydia species, such as Chlamydia trachomatis. Moreover, high resolution affinity-MS provided the identification of several neo-antigenic protein fragments containing N- and C-terminal, and central domains such as fragments of the membrane protein Pmp21 and the secreted chlamydial proteasome-like factor (Cpaf), representing specific biomarker candidates.

Normalization of Patient-Identified Plasma Biomarkers in SMNΔ7 Mice following Postnatal SMN Restoration

PubMed Central

Arnold, W. David; Duque, Sandra; Iyer, Chitra C.; Zaworski, Phillip; McGovern, Vicki L.; Taylor, Shannon J.; von Herrmann, Katharine M.; Kobayashi, Dione T.; Chen, Karen S.; Kolb, Stephen J.; Paushkin, Sergey V.; Burghes, Arthur H. M.

2016-01-01

Introduction and Objective Spinal muscular atrophy (SMA) is an autosomal recessive motor neuron disorder. SMA is caused by homozygous loss of the SMN1 gene and retention of the SMN2 gene resulting in reduced levels of full length SMN protein that are insufficient for motor neuron function. Various treatments that restore levels of SMN are currently in clinical trials and biomarkers are needed to determine the response to treatment. Here, we sought to investigate in SMA mice a set of plasma analytes, previously identified in patients with SMA to correlate with motor function. The goal was to determine whether levels of plasma markers were altered in the SMNΔ7 mouse model of SMA and whether postnatal SMN restoration resulted in normalization of the biomarkers. Methods SMNΔ7 and control mice were treated with antisense oligonucleotides (ASO) targeting ISS-N1 to increase SMN protein from SMN2 or scramble ASO (sham treatment) via intracerebroventricular injection on postnatal day 1 (P1). Brain, spinal cord, quadriceps muscle, and liver were analyzed for SMN protein levels at P12 and P90. Ten plasma biomarkers (a subset of biomarkers in the SMA-MAP panel available for analysis in mice) were analyzed in plasma obtained at P12, P30, and P90. Results Of the eight plasma biomarkers assessed, 5 were significantly changed in sham treated SMNΔ7 mice compared to control mice and were normalized in SMNΔ7 mice treated with ASO. Conclusion This study defines a subset of the SMA-MAP plasma biomarker panel that is abnormal in the most commonly used mouse model of SMA. Furthermore, some of these markers are responsive to postnatal SMN restoration. These findings support continued clinical development of these potential prognostic and pharmacodynamic biomarkers. PMID:27907033

Identifying novel biomarkers in sarcoidosis using genome-based approaches

PubMed Central

Knox, Kenneth S.; Garcia, Joe G.N.

2015-01-01

Synopsis We briefly review conventional biomarkers used clinically to 1) support a diagnosis and 2) monitor disease progression in patients with sarcoidosis. We describe potential new biomarkers identified by genome-wide screening and the approaches to discover these biomarkers. PMID:26593137

SurvNet: a web server for identifying network-based biomarkers that most correlate with patient survival data.

PubMed

Li, Jun; Roebuck, Paul; Grünewald, Stefan; Liang, Han

2012-07-01

An important task in biomedical research is identifying biomarkers that correlate with patient clinical data, and these biomarkers then provide a critical foundation for the diagnosis and treatment of disease. Conventionally, such an analysis is based on individual genes, but the results are often noisy and difficult to interpret. Using a biological network as the searching platform, network-based biomarkers are expected to be more robust and provide deep insights into the molecular mechanisms of disease. We have developed a novel bioinformatics web server for identifying network-based biomarkers that most correlate with patient survival data, SurvNet. The web server takes three input files: one biological network file, representing a gene regulatory or protein interaction network; one molecular profiling file, containing any type of gene- or protein-centred high-throughput biological data (e.g. microarray expression data or DNA methylation data); and one patient survival data file (e.g. patients' progression-free survival data). Given user-defined parameters, SurvNet will automatically search for subnetworks that most correlate with the observed patient survival data. As the output, SurvNet will generate a list of network biomarkers and display them through a user-friendly interface. SurvNet can be accessed at http://bioinformatics.mdanderson.org/main/SurvNet.

Candidate Proteins, Metabolites and Transcripts in the Biomarkers for Spinal Muscular Atrophy (BforSMA) Clinical Study

PubMed Central

Finkel, Richard S.; Crawford, Thomas O.; Swoboda, Kathryn J.; Kaufmann, Petra; Juhasz, Peter; Li, Xiaohong; Guo, Yu; Li, Rebecca H.; Trachtenberg, Felicia; Forrest, Suzanne J.; Kobayashi, Dione T.; Chen, Karen S.; Joyce, Cynthia L.; Plasterer, Thomas

2012-01-01

Background Spinal Muscular Atrophy (SMA) is a neurodegenerative motor neuron disorder resulting from a homozygous mutation of the survival of motor neuron 1 (SMN1) gene. The gene product, SMN protein, functions in RNA biosynthesis in all tissues. In humans, a nearly identical gene, SMN2, rescues an otherwise lethal phenotype by producing a small amount of full-length SMN protein. SMN2 copy number inversely correlates with disease severity. Identifying other novel biomarkers could inform clinical trial design and identify novel therapeutic targets. Objective: To identify novel candidate biomarkers associated with disease severity in SMA using unbiased proteomic, metabolomic and transcriptomic approaches. Materials and Methods: A cross-sectional single evaluation was performed in 108 children with genetically confirmed SMA, aged 2–12 years, manifesting a broad range of disease severity and selected to distinguish factors associated with SMA type and present functional ability independent of age. Blood and urine specimens from these and 22 age-matched healthy controls were interrogated using proteomic, metabolomic and transcriptomic discovery platforms. Analyte associations were evaluated against a primary measure of disease severity, the Modified Hammersmith Functional Motor Scale (MHFMS) and to a number of secondary clinical measures. Results A total of 200 candidate biomarkers correlate with MHFMS scores: 97 plasma proteins, 59 plasma metabolites (9 amino acids, 10 free fatty acids, 12 lipids and 28 GC/MS metabolites) and 44 urine metabolites. No transcripts correlated with MHFMS. Discussion In this cross-sectional study, “BforSMA” (Biomarkers for SMA), candidate protein and metabolite markers were identified. No transcript biomarker candidates were identified. Additional mining of this rich dataset may yield important insights into relevant SMA-related pathophysiology and biological network associations. Additional prospective studies are needed to confirm

Wound outcome in combat injuries is associated with a unique set of protein biomarkers

PubMed Central

2013-01-01

Background The ability to forecast whether a wound will heal after closure without further debridement(s), would provide substantial benefits to patients with severe extremity trauma. Methods Wound effluent is a readily available material which can be collected without disturbing healthy tissue. For analysis of potential host response biomarkers, forty four serial combat wound effluent samples from 19 patients with either healing or failing traumatic- and other combat-related wounds were examined by 2-D DIGE. Spot map patterns were correlated to eventual wound outcome (healed or wound failure) and analyzed using DeCyder 7.0 and differential proteins identified via LC-MS/MS. Results This approach identified 52 protein spots that were differentially expressed and thus represent candidate biomarkers for this clinical application. Many of these proteins are intimately involved in inflammatory and immune responses. Furthermore, discriminate analysis further refined the 52 differential protein spots to a smaller subset of which successfully differentiate between wounds that will heal and those that will fail and require further surgical intervention with greater than 83% accuracy. Conclusion These results suggest candidates for a panel of protein biomarkers that may aid traumatic wound care prognosis and treatment. We recommend that this strategy be refined, and then externally validated, in future studies of traumatic wounds. PMID:24192341

Protein biomarkers of alcohol abuse

PubMed Central

Torrente, Mariana P; Freeman, Willard M; Vrana, Kent E

2012-01-01

Alcohol abuse can lead to a number of health and social issues. Our current inability to accurately assess long-term drinking behaviors is an important obstacle to its diagnosis and treatment. Biomarkers for chronic alcohol consumption have made a number of important advances but have yet to become highly accurate and as accepted as objective tests for other diseases. Thus, there is a crucial need for the development of more sensitive and specific markers of alcohol abuse. Recent advancements in proteomic technologies have greatly increased the potential for alcohol abuse biomarker discovery. Here, the authors review established and novel protein biomarkers for long-term alcohol consumption and the proteomic technologies that have been used in their study. PMID:22967079

A proteomic analysis identifies candidate early biomarkers to predict ovarian hyperstimulation syndrome in polycystic ovarian syndrome patients.

PubMed

Wu, Lan; Sun, Yazhou; Wan, Jun; Luan, Ting; Cheng, Qing; Tan, Yong

2017-07-01

Ovarian hyperstimulation syndrome (OHSS) is a potentially life‑threatening, iatrogenic complication that occurs during assisted reproduction. Polycystic ovarian syndrome (PCOS) significantly increases the risk of OHSS during controlled ovarian stimulation. Therefore, a more effective early prediction technique is required in PCOS patients. Quantitative proteomic analysis of serum proteins indicates the potential diagnostic value for disease. In the present study, the authors revealed the differentially expressed proteins in OHSS patients with PCOS as new diagnostic biomarkers. The promising proteins obtained from liquid chromatography‑mass spectrometry were subjected to ELISA and western blotting assay for further confirmation. A total of 57 proteins were identified with significant difference, of which 29 proteins were upregulated and 28 proteins were downregulated in OHSS patients. Haptoglobin, fibrinogen and lipoprotein lipase were selected as candidate biomarkers. Receiver operating characteristic curve analysis demonstrated all three proteins may have potential as biomarkers to discriminate OHSS in PCOS patients. Haptoglobin, fibrinogen and lipoprotein lipase have never been reported as a predictive marker of OHSS in PCOS patients, and their potential roles in OHSS occurrence deserve further studies. The proteomic results reported in the present study may gain deeper insights into the pathophysiology of OHSS.

Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers

PubMed Central

Chen, Hao; Zhu, Zhitu; Zhu, Yichun; Wang, Jian; Mei, Yunqing; Cheng, Yunfeng

2015-01-01

It is known that a disease is rarely a consequence of an abnormality of a single gene, but reflects the interactions of various processes in a complex network. Annotated molecular networks offer new opportunities to understand diseases within a systems biology framework and provide an excellent substrate for network-based identification of biomarkers. The network biomarkers and dynamic network biomarkers (DNBs) represent new types of biomarkers with protein–protein or gene–gene interactions that can be monitored and evaluated at different stages and time-points during development of disease. Clinical bioinformatics as a new way to combine clinical measurements and signs with human tissue-generated bioinformatics is crucial to translate biomarkers into clinical application, validate the disease specificity, and understand the role of biomarkers in clinical settings. In this article, the recent advances and developments on network biomarkers and DNBs are comprehensively reviewed. How network biomarkers help a better understanding of molecular mechanism of diseases, the advantages and constraints of network biomarkers for clinical application, clinical bioinformatics as a bridge to the development of diseases-specific, stage-specific, severity-specific and therapy predictive biomarkers, and the potentials of network biomarkers are also discussed. PMID:25560835

Protein isoform-specific validation defines multiple chloride intracellular channel and tropomyosin isoforms as serological biomarkers of ovarian cancer

PubMed Central

Tang, Hsin-Yao; Beer, Lynn A.; Tanyi, Janos L.; Zhang, Rugang; Liu, Qin; Speicher, David W.

2013-01-01

New serological biomarkers for early detection and clinical management of ovarian cancer are urgently needed, and many candidates have been reported. A major challenge frequently encountered when validating candidates in patients is establishing quantitative assays that distinguish between highly homologous proteins. The current study tested whether multiple members of two recently discovered ovarian cancer biomarker protein families, chloride intracellular channel (CLIC) proteins and tropomyosins (TPM), were detectable in ovarian cancer patient sera. A multiplexed, label-free multiple reaction monitoring (MRM) assay was established to target peptides specific to all detected CLIC and TPM family members, and their serum levels were quantitated for ovarian cancer patients and non-cancer controls. In addition to CLIC1 and TPM1, which were the proteins initially discovered in a xenograft mouse model, CLIC4, TPM2, TPM3, and TPM4 were present in ovarian cancer patient sera at significantly elevated levels compared with controls. Some of the additional biomarkers identified in this homolog-centric verification and validation approach may be superior to the previously identified biomarkers at discriminating between ovarian cancer and non-cancer patients. This demonstrates the importance of considering all potential protein homologs and using quantitative assays for cancer biomarker validation with well-defined isoform specificity. PMID:23792823

Analytical validation considerations of multiplex mass-spectrometry-based proteomic platforms for measuring protein biomarkers.

PubMed

Boja, Emily S; Fehniger, Thomas E; Baker, Mark S; Marko-Varga, György; Rodriguez, Henry

2014-12-05

Protein biomarker discovery and validation in current omics era are vital for healthcare professionals to improve diagnosis, detect cancers at an early stage, identify the likelihood of cancer recurrence, stratify stages with differential survival outcomes, and monitor therapeutic responses. The success of such biomarkers would have a huge impact on how we improve the diagnosis and treatment of patients and alleviate the financial burden of healthcare systems. In the past, the genomics community (mostly through large-scale, deep genomic sequencing technologies) has been steadily improving our understanding of the molecular basis of disease, with a number of biomarker panels already authorized by the U.S. Food and Drug Administration (FDA) for clinical use (e.g., MammaPrint, two recently cleared devices using next-generation sequencing platforms to detect DNA changes in the cystic fibrosis transmembrane conductance regulator (CFTR) gene). Clinical proteomics, on the other hand, albeit its ability to delineate the functional units of a cell, more likely driving the phenotypic differences of a disease (i.e., proteins and protein-protein interaction networks and signaling pathways underlying the disease), "staggers" to make a significant impact with only an average ∼ 1.5 protein biomarkers per year approved by the FDA over the past 15-20 years. This statistic itself raises the concern that major roadblocks have been impeding an efficient transition of protein marker candidates in biomarker development despite major technological advances in proteomics in recent years.

Differential proteomic and tissue expression analyses identify valuable diagnostic biomarkers of hepatocellular differentiation and hepatoid adenocarcinomas.

PubMed

Reis, Henning; Padden, Juliet; Ahrens, Maike; Pütter, Carolin; Bertram, Stefanie; Pott, Leona L; Reis, Anna-Carinna; Weber, Frank; Juntermanns, Benjamin; Hoffmann, Andreas-C; Eisenacher, Martin; Schlaak, Joörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

2015-10-01

The exact discrimination of lesions with true hepatocellular differentiation from secondary tumours and neoplasms with hepatocellular histomorphology like hepatoid adenocarcinomas (HAC) is crucial. Therefore, we aimed to identify ancillary protein biomarkers by using complementary proteomic techniques (2D-DIGE, label-free MS). The identified candidates were immunohistochemically validated in 14 paired samples of hepatocellular carcinoma (HCC) and non-tumourous liver tissue (NT). The candidates and HepPar1/Arginase1 were afterwards tested for consistency in a large cohort of hepatocellular lesions and NT (n = 290), non-hepatocellular malignancies (n = 383) and HAC (n = 13). Eight non-redundant, differentially expressed proteins were suitable for further immunohistochemical validation and four (ABAT, BHMT, FABP1, HAOX1) for further evaluation. Sensitivity and specificity rates for HCC/HAC were as follows: HepPar1 80.2%, 94.3% / 80.2%, 46.2%; Arginase1 82%, 99.4% / 82%, 69.2%; BHMT 61.4%, 93.8% / 61.4%, 100%; ABAT 84.4%, 33.7% / 84.4%, 30.8%; FABP1 87.2%, 95% / 87.2%, 69.2%; HAOX1 95.5%, 36.3% / 95.5%, 46.2%. The best 2×/3× biomarker panels for the diagnosis of HCC consisted of Arginase1/HAOX1 and BHMT/Arginase1/HAOX1 and for HAC consisted of Arginase1/FABP1 and BHMT/Arginase1/FABP1. In summary, we successfully identified, validated and benchmarked protein biomarker candidates of hepatocellular differentiation. BHMT in particular exhibited superior diagnostic characteristics in hepatocellular lesions and specifically in HAC. BHMT is therefore a promising (panel based) biomarker candidate in the differential diagnostic process of lesions with hepatocellular aspect.

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow.

PubMed

Kulkarni, Shilpa; Koller, Antonius; Mani, Kartik M; Wen, Ruofeng; Alfieri, Alan; Saha, Subhrajit; Wang, Jian; Patel, Purvi; Bandeira, Nuno; Guha, Chandan; Chen, Emily I

2016-11-01

Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kulkarni, Shilpa; Koller, Antonius; Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York

Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24more » and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially

SELDI-TOF-MS ProteinChip array profiling of T-cell clones propagated in long-term culture identifies human profilin-1 as a potential bio-marker of immunosenescence.

PubMed

Mazzatti, Dawn J; Pawelec, Graham; Longdin, Robin; Powell, Jonathan R; Forsey, Rosalyn J

2007-06-05

The adaptive immune response requires waves of T-cell clonal expansion on contact with pathogen and elimination after clearance of the source of antigen. However, lifelong persistent infections with common viruses cause chronic antigenic stimulation which takes its toll on adaptive immunity in late life. Chronic antigenic stress results in deregulation of the T-cell response and accumulation of anergic cells. Longitudinal studies of the elderly show that this impacts on survival. Identifying the nature of the defects in chronically-stimulated T-cells and protein bio-markers of these dysfunctional cells would help to understand age-associated compromised T-cell function (immunosenescence) and facilitate the development of targeted intervention strategies.The purpose of this work was to use surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to analyse proteins associated with T-cell senescence in order to identify potential bio-markers. Clonal populations of T-cells isolated from elderly octogenarian and centenarian donors were grown in vitro until senescence, and early passage and late passage (pre-senescent) cells were analysed using SELDI-TOF-MS ProteinChip arrays. Discriminant analysis identified several protein or peptide peaks in the region of 14.5-16.5 kDa that were associated with T-cell clone senescence. Human profilin-1, a ubiquitous protein associated with actin remodelling and cellular motility was unambiguously identified. Altered expression of profilin-1 in senescent T-cell clones was confirmed by Western blot analysis. Due to the proposed roles of profilin-1 in cellular survival, cytoskeleton remodelling, motility, and proliferation, it is hypothesised that differential expression of profilin-1 in ageing may contribute directly to immunosenescence.

Identification of urine protein biomarkers with the potential for early detection of lung cancer.

PubMed

Zhang, Hongjuan; Cao, Jing; Li, Lin; Liu, Yanbin; Zhao, Hong; Li, Nan; Li, Bo; Zhang, Aiqun; Huang, Huanwei; Chen, She; Dong, Mengqiu; Yu, Lei; Zhang, Jian; Chen, Liang

2015-07-02

Lung cancer is the leading cause of cancer-related deaths and has an overall 5-year survival rate lower than 15%. Large-scale clinical trials have demonstrated a significant relative reduction in mortality in high-risk individuals with low-dose computed tomography screening. However, biomarkers capable of identifying the most at-risk population and detecting lung cancer before it becomes clinically apparent are urgently needed in the clinic. Here, we report the identification of urine biomarkers capable of detecting lung cancer. Using the well-characterized inducible Kras (G12D) mouse model of lung cancer, we identified alterations in the urine proteome in tumor-bearing mice compared with sibling controls. Marked differences at the proteomic level were also detected between the urine of patients and that of healthy population controls. Importantly, we identified 7 proteins commonly found to be significantly up-regulated in both tumor-bearing mice and patients. In an independent cohort, we showed that 2 of the 7 proteins were up-regulated in urine samples from lung cancer patients but not in those from controls. The kinetics of these proteins correlated with the disease state in the mouse model. These tumor biomarkers could potentially aid in the early detection of lung cancer.

Proteomic-based detection of a protein cluster dysregulated during cardiovascular development identifies biomarkers of congenital heart defects.

PubMed

Nath, Anjali K; Krauthammer, Michael; Li, Puyao; Davidov, Eugene; Butler, Lucas C; Copel, Joshua; Katajamaa, Mikko; Oresic, Matej; Buhimschi, Irina; Buhimschi, Catalin; Snyder, Michael; Madri, Joseph A

2009-01-01

Cardiovascular development is vital for embryonic survival and growth. Early gestation embryo loss or malformation has been linked to yolk sac vasculopathy and congenital heart defects (CHDs). However, the molecular pathways that underlie these structural defects in humans remain largely unknown hindering the development of molecular-based diagnostic tools and novel therapies. Murine embryos were exposed to high glucose, a condition known to induce cardiovascular defects in both animal models and humans. We further employed a mass spectrometry-based proteomics approach to identify proteins differentially expressed in embryos with defects from those with normal cardiovascular development. The proteins detected by mass spectrometry (WNT16, ST14, Pcsk1, Jumonji, Morca2a, TRPC5, and others) were validated by Western blotting and immunoflorescent staining of the yolk sac and heart. The proteins within the proteomic dataset clustered to adhesion/migration, differentiation, transport, and insulin signaling pathways. A functional role for several proteins (WNT16, ADAM15 and NOGO-A/B) was demonstrated in an ex vivo model of heart development. Additionally, a successful application of a cluster of protein biomarkers (WNT16, ST14 and Pcsk1) as a prenatal screen for CHDs was confirmed in a study of human amniotic fluid (AF) samples from women carrying normal fetuses and those with CHDs. The novel finding that WNT16, ST14 and Pcsk1 protein levels increase in fetuses with CHDs suggests that these proteins may play a role in the etiology of human CHDs. The information gained through this bed-side to bench translational approach contributes to a more complete understanding of the protein pathways dysregulated during cardiovascular development and provides novel avenues for diagnostic and therapeutic interventions, beneficial to fetuses at risk for CHDs.

Proteomic-Based Detection of a Protein Cluster Dysregulated during Cardiovascular Development Identifies Biomarkers of Congenital Heart Defects

PubMed Central

Nath, Anjali K.; Krauthammer, Michael; Li, Puyao; Davidov, Eugene; Butler, Lucas C.; Copel, Joshua; Katajamaa, Mikko; Oresic, Matej; Buhimschi, Irina; Buhimschi, Catalin; Snyder, Michael; Madri, Joseph A.

2009-01-01

Background Cardiovascular development is vital for embryonic survival and growth. Early gestation embryo loss or malformation has been linked to yolk sac vasculopathy and congenital heart defects (CHDs). However, the molecular pathways that underlie these structural defects in humans remain largely unknown hindering the development of molecular-based diagnostic tools and novel therapies. Methodology/Principal Findings Murine embryos were exposed to high glucose, a condition known to induce cardiovascular defects in both animal models and humans. We further employed a mass spectrometry-based proteomics approach to identify proteins differentially expressed in embryos with defects from those with normal cardiovascular development. The proteins detected by mass spectrometry (WNT16, ST14, Pcsk1, Jumonji, Morca2a, TRPC5, and others) were validated by Western blotting and immunoflorescent staining of the yolk sac and heart. The proteins within the proteomic dataset clustered to adhesion/migration, differentiation, transport, and insulin signaling pathways. A functional role for several proteins (WNT16, ADAM15 and NOGO-A/B) was demonstrated in an ex vivo model of heart development. Additionally, a successful application of a cluster of protein biomarkers (WNT16, ST14 and Pcsk1) as a prenatal screen for CHDs was confirmed in a study of human amniotic fluid (AF) samples from women carrying normal fetuses and those with CHDs. Conclusions/Significance The novel finding that WNT16, ST14 and Pcsk1 protein levels increase in fetuses with CHDs suggests that these proteins may play a role in the etiology of human CHDs. The information gained through this bed-side to bench translational approach contributes to a more complete understanding of the protein pathways dysregulated during cardiovascular development and provides novel avenues for diagnostic and therapeutic interventions, beneficial to fetuses at risk for CHDs. PMID:19156209

The relative contribution of DNA methylation and genetic variants on protein biomarkers for human diseases

PubMed Central

Ahsan, Muhammad; Ek, Weronica E.; Karlsson, Torgny; Gyllensten, Ulf

2017-01-01

Associations between epigenetic alterations and disease status have been identified for many diseases. However, there is no strong evidence that epigenetic alterations are directly causal for disease pathogenesis. In this study, we combined SNP and DNA methylation data with measurements of protein biomarkers for cancer, inflammation or cardiovascular disease, to investigate the relative contribution of genetic and epigenetic variation on biomarker levels. A total of 121 protein biomarkers were measured and analyzed in relation to DNA methylation at 470,000 genomic positions and to over 10 million SNPs. We performed epigenome-wide association study (EWAS) and genome-wide association study (GWAS) analyses, and integrated biomarker, DNA methylation and SNP data using between 698 and 1033 samples depending on data availability for the different analyses. We identified 124 and 45 loci (Bonferroni adjusted P < 0.05) with effect sizes up to 0.22 standard units’ change per 1% change in DNA methylation levels and up to four standard units’ change per copy of the effective allele in the EWAS and GWAS respectively. Most GWAS loci were cis-regulatory whereas most EWAS loci were located in trans. Eleven EWAS loci were associated with multiple biomarkers, including one in NLRC5 associated with CXCL11, CXCL9, IL-12, and IL-18 levels. All EWAS signals that overlapped with a GWAS locus were driven by underlying genetic variants and three EWAS signals were confounded by smoking. While some cis-regulatory SNPs for biomarkers appeared to have an effect also on DNA methylation levels, cis-regulatory SNPs for DNA methylation were not observed to affect biomarker levels. We present associations between protein biomarker and DNA methylation levels at numerous loci in the genome. The associations are likely to reflect the underlying pattern of genetic variants, specific environmental exposures, or represent secondary effects to the pathogenesis of disease. PMID:28915241

Combining micro-RNA and protein sequencing to detect robust biomarkers for Graves' disease and orbitopathy.

PubMed

Zhang, Lei; Masetti, Giulia; Colucci, Giuseppe; Salvi, Mario; Covelli, Danila; Eckstein, Anja; Kaiser, Ulrike; Draman, Mohd Shazli; Muller, Ilaria; Ludgate, Marian; Lucini, Luigi; Biscarini, Filippo

2018-05-30

Graves' Disease (GD) is an autoimmune condition in which thyroid-stimulating antibodies (TRAB) mimic thyroid-stimulating hormone function causing hyperthyroidism. 5% of GD patients develop inflammatory Graves' orbitopathy (GO) characterized by proptosis and attendant sight problems. A major challenge is to identify which GD patients are most likely to develop GO and has relied on TRAB measurement. We screened sera/plasma from 14 GD, 19 GO and 13 healthy controls using high-throughput proteomics and miRNA sequencing (Illumina's HiSeq2000 and Agilent-6550 Funnel quadrupole-time-of-flight mass spectrometry) to identify potential biomarkers for diagnosis or prognosis evaluation. Euclidean distances and differential expression (DE) based on miRNA and protein quantification were analysed by multidimensional scaling (MDS) and multinomial regression respectively. We detected 3025 miRNAs and 1886 proteins and MDS revealed good separation of the 3 groups. Biomarkers were identified by combined DE and Lasso-penalized predictive models; accuracy of predictions was 0.86 (±0:18), and 5 miRNA and 20 proteins were found including Zonulin, Alpha-2 macroglobulin, Beta-2 glycoprotein 1 and Fibronectin. Functional analysis identified relevant metabolic pathways, including hippo signaling, bacterial invasion of epithelial cells and mRNA surveillance. Proteomic and miRNA analyses, combined with robust bioinformatics, identified circulating biomarkers applicable to diagnose GD, predict GO disease status and optimize patient management.

A novel quantification-driven proteomic strategy identifies an endogenous peptide of pleiotrophin as a new biomarker of Alzheimer's disease.

PubMed

Skillbäck, Tobias; Mattsson, Niklas; Hansson, Karl; Mirgorodskaya, Ekaterina; Dahlén, Rahil; van der Flier, Wiesje; Scheltens, Philip; Duits, Floor; Hansson, Oskar; Teunissen, Charlotte; Blennow, Kaj; Zetterberg, Henrik; Gobom, Johan

2017-10-17

We present a new, quantification-driven proteomic approach to identifying biomarkers. In contrast to the identification-driven approach, limited in scope to peptides that are identified by database searching in the first step, all MS data are considered to select biomarker candidates. The endopeptidome of cerebrospinal fluid from 40 Alzheimer's disease (AD) patients, 40 subjects with mild cognitive impairment, and 40 controls with subjective cognitive decline was analyzed using multiplex isobaric labeling. Spectral clustering was used to match MS/MS spectra. The top biomarker candidate cluster (215% higher in AD compared to controls, area under ROC curve = 0.96) was identified as a fragment of pleiotrophin located near the protein's C-terminus. Analysis of another cohort (n = 60 over four clinical groups) verified that the biomarker was increased in AD patients while no change in controls, Parkinson's disease or progressive supranuclear palsy was observed. The identification of the novel biomarker pleiotrophin 151-166 demonstrates that our quantification-driven proteomic approach is a promising method for biomarker discovery, which may be universally applicable in clinical proteomics.

The first decade of MALDI protein profiling: a lesson in translational biomarker research.

PubMed

Albrethsen, Jakob

2011-05-16

MALDI protein profiling has identified several important challenges in omics-based biomarker research. First, research into the analytical performance of a novel omics-platform of potential diagnostic impact must be carried out in a critical manner and according to common guidelines. Evaluation studies should be performed at an early time and preferably before massive advancement into explorative biomarker research. In particular, MALDI profiling underscores the need for an adequate understanding of the causal relationship between molecular abundance and the quantitative measure in multivariate biomarker research. Secondly, MALDI profiling has raised awareness of the significant risk of false-discovery in biomarker research due to several confounding factors, including sample processing and unspecific host-response to disease. Here, the experience from MALDI profiling supports that a central challenge in unbiased molecular profiling is to pinpoint the aberrations of clinical interest among potentially massive unspecific changes that can accompany disease. The lessons from the first decade of MALDI protein profiling are relevant for future efforts in advancing omics-based biomarker research beyond the laboratory setting and into clinical verification. Copyright © 2011 Elsevier B.V. All rights reserved.

A novel workflow combining plaque imaging, plaque and plasma proteomics identifies biomarkers of human coronary atherosclerotic plaque disruption.

PubMed

Lee, Regent; Fischer, Roman; Charles, Philip D; Adlam, David; Valli, Alessandro; Di Gleria, Katalin; Kharbanda, Rajesh K; Choudhury, Robin P; Antoniades, Charalambos; Kessler, Benedikt M; Channon, Keith M

2017-01-01

Atherosclerotic plaque rupture is the culprit event which underpins most acute vascular syndromes such as acute myocardial infarction. Novel biomarkers of plaque rupture could improve biological understanding and clinical management of patients presenting with possible acute vascular syndromes but such biomarker(s) remain elusive. Investigation of biomarkers in the context of de novo plaque rupture in humans is confounded by the inability to attribute the plaque rupture as the source of biomarker release, as plaque ruptures are typically associated with prompt down-stream events of myocardial necrosis and systemic inflammation. We developed a novel approach to identify potential biomarkers of plaque rupture by integrating plaque imaging, using optical coherence tomography, with both plaque and plasma proteomic analysis in a human model of angioplasty-induced plaque disruption. We compared two pairs of coronary plaque debris, captured by a FilterWire Device, and their corresponding control samples and found matrix metalloproteinase 9 (MMP9) to be significantly enriched in plaque. Plaque contents, as defined by optical coherence tomography, affect the systemic changes of MMP9. Disruption of lipid-rich plaque led to prompt elevation of plasma MMP9, whereas disruption of non-lipid-rich plaque resulted in delayed elevation of plasma MMP9. Systemic MMP9 elevation is independent of the associated myocardial necrosis and systemic inflammation (measured by Troponin I and C-reactive protein, respectively). This information guided the selection of a subset of subjects of for further label free proteomics analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). We discovered five novel, plaque-enriched proteins (lipopolysaccharide binding protein, Annexin A5, eukaryotic translocation initiation factor, syntaxin 11, cytochrome B5 reductase 3) to be significantly elevated in systemic circulation at 5 min after plaque disruption. This novel approach for biomarker

Rapid label-free profiling of oral cancer biomarker proteins using nano-UPLC-Q-TOF ion mobility mass spectrometry.

PubMed

Nassar, Ala F; Williams, Brad J; Yaworksy, Dustin C; Patel, Vyomesh; Rusling, James F

2016-03-01

It has become quite clear that single cancer biomarkers cannot in general provide high sensitivity and specificity for reliable clinical cancer diagnostics. This paper explores the feasibility of rapid detection of multiple biomarker proteins in model oral cancer samples using label-free protein relative quantitation. MS-based label-free quantitative proteomics offer a rapid alternative that bypasses the need for stable isotope containing compounds to chemically bind and label proteins. Total protein content in oral cancer cell culture conditioned media was precipitated, subjected to proteolytic digestion, and then analyzed using a nano-UPLC (where UPLC is ultra-performance liquid chromatography) coupled to a hybrid Q-Tof ion-mobility mass spectrometry (MS). Rapid, simultaneous identification and quantification of multiple possible cancer biomarker proteins was achieved. In a comparative study between cancer and noncancer samples, approximately 952 proteins were identified using a high-throughput 1D ion mobility assisted data independent acquisition (IM-DIA) approach. As we previously demonstrated that interleukin-8 (IL-8) and vascular endothelial growth factor A (VEGF-A) were readily detected in oral cancer cell conditioned media(1), we targeted these biomarker proteins to validate our approach. Target biomarker protein IL-8 was found between 3.5 and 8.8 fmol, while VEGF-A was found at 1.45 fmol in the cancer cell media. Overall, our data suggest that the nano-UPLC-IM-DIA bioassay is a feasible approach to identify and quantify proteins in complex samples without the need for stable isotope labeling. These results have significant implications for rapid tumor diagnostics and prognostics by monitoring proteins such as IL-8 and VEGF-A implicated in cancer development and progression. The analysis in tissue or plasma is not possible at this time, but the subsequent work would be needed for validation. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset.

PubMed

Metz, Thomas O; Qian, Wei-Jun; Jacobs, Jon M; Gritsenko, Marina A; Moore, Ronald J; Polpitiya, Ashoka D; Monroe, Matthew E; Camp, David G; Mueller, Patricia W; Smith, Richard D

2008-02-01

Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted "-omics" approaches are underutilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program, with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. alpha-2-Glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples.

Transcript and protein environmental biomarkers in fish--a review.

PubMed

Tom, Moshe; Auslander, Meirav

2005-04-01

The levels of contaminant-affected gene products (transcripts and proteins) are increasingly utilized as environmental biomarkers, and their appropriate implementation as diagnostic tools is discussed. The required characteristics of a gene product biomarker are accurate evaluation using properly normalized absolute units, aiming at long-term comparability of biomarker levels over a wide geographical range and among many laboratories. Quantitative RT-PCR and competitive ELISA are suggested as preferred evaluation methods for transcript and protein, respectively. Constitutively expressed RNAs or proteins which are part of the examined homogenate are suggested as normalizing agents, compensating for variable processing efficiency. Essential characterization of expression patterns is suggested, providing reference values to be compared to the monitored levels. This comparison would enable estimation of the intensity of biological effects of contaminants. Contaminant-independent reference expression patterns should include natural fluctuations of the biomarker level. Contaminant-dependent patterns should include dose response to model contaminants chronically administered in two environmentally-realistic routes, reaching extreme sub-lethal affected levels. Recent studies using fish as environmental sentinel species, applying gene products as environmental biomarkers, and implementing at least part of the depicted methodologies are reviewed.

Novel Stool-Based Protein Biomarkers for Improved Colorectal Cancer Screening: A Case-Control Study.

PubMed

Bosch, Linda J W; de Wit, Meike; Pham, Thang V; Coupé, Veerle M H; Hiemstra, Annemieke C; Piersma, Sander R; Oudgenoeg, Gideon; Scheffer, George L; Mongera, Sandra; Sive Droste, Jochim Terhaar; Oort, Frank A; van Turenhout, Sietze T; Larbi, Ilhame Ben; Louwagie, Joost; van Criekinge, Wim; van der Hulst, Rene W M; Mulder, Chris J J; Carvalho, Beatriz; Fijneman, Remond J A; Jimenez, Connie R; Meijer, Gerrit A

2017-12-19

The fecal immunochemical test (FIT) for detecting hemoglobin is used widely for noninvasive colorectal cancer (CRC) screening, but its sensitivity leaves room for improvement. To identify novel protein biomarkers in stool that outperform or complement hemoglobin in detecting CRC and advanced adenomas. Case-control study. Colonoscopy-controlled referral population from several centers. 315 stool samples from one series of 12 patients with CRC and 10 persons without colorectal neoplasia (control samples) and a second series of 81 patients with CRC, 40 with advanced adenomas, and 43 with nonadvanced adenomas, as well as 129 persons without colorectal neoplasia (control samples); 72 FIT samples from a third independent series of 14 patients with CRC, 16 with advanced adenomas, and 18 with nonadvanced adenomas, as well as 24 persons without colorectal neoplasia (control samples). Stool samples were analyzed by mass spectrometry. Classification and regression tree (CART) analysis and logistic regression analyses were performed to identify protein combinations that differentiated CRC or advanced adenoma from control samples. Antibody-based assays for 4 selected proteins were done on FIT samples. In total, 834 human proteins were identified, 29 of which were statistically significantly enriched in CRC versus control stool samples in both series. Combinations of 4 proteins reached sensitivities of 80% and 45% for detecting CRC and advanced adenomas, respectively, at 95% specificity, which was higher than that of hemoglobin alone (P < 0.001 and P = 0.003, respectively). Selected proteins could be measured in small sample volumes used in FIT-based screening programs and discriminated between CRC and control samples (P < 0.001). Lack of availability of antibodies prohibited validation of the top protein combinations in FIT samples. Mass spectrometry of stool samples identified novel candidate protein biomarkers for CRC screening. Several protein combinations outperformed

Identifying technical aliases in SELDI mass spectra of complex mixtures of proteins

PubMed Central

2013-01-01

Background Biomarker discovery datasets created using mass spectrum protein profiling of complex mixtures of proteins contain many peaks that represent the same protein with different charge states. Correlated variables such as these can confound the statistical analyses of proteomic data. Previously we developed an algorithm that clustered mass spectrum peaks that were biologically or technically correlated. Here we demonstrate an algorithm that clusters correlated technical aliases only. Results In this paper, we propose a preprocessing algorithm that can be used for grouping technical aliases in mass spectrometry protein profiling data. The stringency of the variance allowed for clustering is customizable, thereby affecting the number of peaks that are clustered. Subsequent analysis of the clusters, instead of individual peaks, helps reduce difficulties associated with technically-correlated data, and can aid more efficient biomarker identification. Conclusions This software can be used to pre-process and thereby decrease the complexity of protein profiling proteomics data, thus simplifying the subsequent analysis of biomarkers by decreasing the number of tests. The software is also a practical tool for identifying which features to investigate further by purification, identification and confirmation. PMID:24010718

Biomarkers identified by urinary metabonomics for noninvasive diagnosis of nutritional rickets.

PubMed

Wang, Maoqing; Yang, Xue; Ren, Lihong; Li, Songtao; He, Xuan; Wu, Xiaoyan; Liu, Tingting; Lin, Liqun; Li, Ying; Sun, Changhao

2014-09-05

Nutritional rickets is a worldwide public health problem; however, the current diagnostic methods retain shortcomings for accurate diagnosis of nutritional rickets. To identify urinary biomarkers associated with nutritional rickets and establish a noninvasive diagnosis method, urinary metabonomics analysis by ultra-performance liquid chromatography/quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis were employed to investigate the metabolic alterations associated with nutritional rickets in 200 children with or without nutritional rickets. The pathophysiological changes and pathogenesis of nutritional rickets were illustrated by the identified biomarkers. By urinary metabolic profiling, 31 biomarkers of nutritional rickets were identified and five candidate biomarkers for clinical diagnosis were screened and identified by quantitative analysis and receiver operating curve analysis. Urinary levels of five candidate biomarkers were measured using mass spectrometry or commercial kits. In the validation step, the combination of phosphate and sebacic acid was able to give a noninvasive and accurate diagnostic with high sensitivity (94.0%) and specificity (71.2%). Furthermore, on the basis of the pathway analysis of biomarkers, our urinary metabonomics analysis gives new insight into the pathogenesis and pathophysiology of nutritional rickets.

Breast cancer and protein biomarkers

PubMed Central

Gam, Lay-Harn

2012-01-01

Breast cancer is a healthcare concern of women worldwide. Despite procedures being available for diagnosis, prognosis and treatment of breast cancer, researchers are working intensively on the disease in order to improve the life quality of breast cancer patients. At present, there is no single treatment known to bring a definite cure for breast cancer. One of the possible solutions for combating breast cancer is through identification of reliable protein biomarkers that can be effectively used for early detection, prognosis and treatments of the cancer. Therefore, the task of identification of biomarkers for breast cancer has become the focus of many researchers worldwide. PMID:24520539

Protein biomarkers identify patients unlikely to benefit from primary prevention implantable cardioverter defibrillators: findings from the Prospective Observational Study of Implantable Cardioverter Defibrillators (PROSE-ICD).

PubMed

Cheng, Alan; Zhang, Yiyi; Blasco-Colmenares, Elena; Dalal, Darshan; Butcher, Barbara; Norgard, Sanaz; Eldadah, Zayd; Ellenbogen, Kenneth A; Dickfeld, Timm; Spragg, David D; Marine, Joseph E; Guallar, Eliseo; Tomaselli, Gordon F

2014-12-01

Primary prevention implantable cardioverter defibrillators (ICDs) reduce all-cause mortality, but the benefits are heterogeneous. Current risk stratification based on left ventricular ejection fraction has limited discrimination power. We hypothesize that biomarkers for inflammation, neurohumoral activation, and cardiac injury can predict appropriate shocks and all-cause mortality in patients with primary prevention ICDs. The Prospective Observational Study of Implantable Cardioverter Defibrillators (PROSe-ICD) enrolled 1189 patients with systolic heart failure who underwent ICD implantation for primary prevention of sudden cardiac death. The primary end point was an ICD shock for adjudicated ventricular tachyarrhythmia. The secondary end point was all-cause mortality. After a median follow-up of 4.0 years, 137 subjects experienced an appropriate ICD shock and 343 participants died (incidence rates of 3.2 and 5.8 per 100 person-years, respectively). In multivariable-adjusted models, higher interleukin-6 levels increased the risk of appropriate ICD shocks. In contrast, C-reactive protein, interleukin-6, tumor necrosis factor-α receptor II, pro-brain natriuretic peptide (pro-BNP), and cardiac troponin T showed significant linear trends for increased risk of all-cause mortality across quartiles. A score combining these 5 biomarkers identified patients who were much more likely to die than to receive an appropriate shock from the ICD. An increase in serum biomarkers of inflammation, neurohumoral activation, and myocardial injury increased the risk for death but poorly predicted the likelihood of an ICD shock. These findings highlight the potential importance of serum-based biomarkers in identifying patients who are unlikely to benefit from primary prevention ICDs. clinicaltrials.gov; Unique Identifier: NCT00733590. © 2014 American Heart Association, Inc.

Current and Prospective Protein Biomarkers of Lung Cancer

PubMed Central

Zamay, Tatiana N.; Zamay, Galina S.; Kolovskaya, Olga S.; Zukov, Ruslan A.; Petrova, Marina M.; Gargaun, Ana; Berezovski, Maxim V.

2017-01-01

Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate. PMID:29137182

Novel Serum Biomarkers Detected by Protein Array in Polycystic Ovary Syndrome with Low Progesterone Level.

PubMed

Zheng, Qin; Zhou, Feifei; Cui, Xinyuan; Liu, Mulin; Li, Yulin; Liu, Shuai; Tan, Jichun; Yan, Qiu

2018-01-01

Polycystic ovary syndrome (PCOS), characterized by female infertility and metabolic abnormalities, is one of the most common endocrine disorders. The etiology of PCOS remains unknown. The comprehensive analysis of protein alterations in PCOS patients is meaningful for identifying diagnostic biomarkers of PCOS. Here, we explored the clinical value of serum proteins as novel biomarkers to detect PCOS with low progesterone level. A total of 43 patients with PCOS and 30 healthy women were enrolled. Protein array was used to detect the variations of serum proteins between PCOS patients and healthy women. The level of five serum proteins was further confirmed by ELISA and western blot. The human ovarian granulosa cells (KGN) was cultured to examine the underlying mechanism of PCOS. CCK8 assay and western blot were carried out to evaluate the alterations in proliferative ability, TUNEL assay and DAPI staining to detect the apoptosis of KGN cells. Among the 507 proteins, we identified 76 differentially expressed serum proteins (≧1.5 fold), with 40 elevated and 36 decreased proteins. Moreover, 47 proteins were newly reported in PCOS. The alterations in the five significantly decreased proteins (EREG, inhibin βA, IDE, PDGF-D and KNG1) were further confirmed by ELISA and western blot. The level of these proteins were directly associated with the low progesterone, and the expression could be upregulated by progesterone. EREG and inhibin βA also promoted the proliferation and inhibited the apoptosis of ovarian granulosa cells. The study highlights that serum proteins are differentially expressed in PCOS patients and healthy women, and EREG and inhibin βA levels are upregulated by progesterone, which are correlated with ovarian functions. The study suggests that EREG and inhibin βA may be applied as novel potential biomarkers for PCOS with low progesterone level. © 2018 The Author(s). Published by S. Karger AG, Basel.

Proteomic analysis of first trimester maternal serum to identify candidate biomarkers potentially predictive of spontaneous preterm birth.

PubMed

D'Silva, Arlene M; Hyett, Jon A; Coorssen, Jens R

2018-04-30

Spontaneous preterm birth (sPTB) remains a major clinical dilemma; current diagnostics and interventions have not reduced the rate of this serious healthcare burden. This study characterizes differential protein profiles and post-translational modifications (PTMs) in first trimester maternal serum using a refined top-down approach coupling two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS) to directly compare subsequent term and preterm labour events and identify marked protein differences. 30 proteoforms were found to be significantly increased or decreased in the sPTB group including 9 phosphoproteins and 11 glycoproteins. Changes occurred in proteins associated with immune and defence responses. We identified protein species that are associated with several clinically relevant biological processes, including interrelated biological networks linked to regulation of the complement cascade and coagulation pathways, immune modulation, metabolic processes and cell signalling. The finding of altered proteoforms in maternal serum from pregnancies that delivered preterm suggests these as potential early biomarkers of sPTB and also possible mediators of the disorder. Identifying changes in protein profiles is critical in the study of cell biology, and disease treatment and prevention. Identifying consistent changes in the maternal serum proteome during early pregnancy, including specific protein PTMs (e.g. phosphorylation, glycosylation), is likely to provide better opportunities for prediction, intervention and prevention of preterm birth. This is the first study to examine first trimester maternal serum using a highly refined top-down proteomic analytical approach based on high resolution 2DE coupled with mass spectrometry to directly compare preterm (<37 weeks) and preterm (≥37 weeks) events and identify select protein differences between these conditions. As such, the data present a promising avenue for translation of biomarker discovery to a

Application of proteomics in the discovery of candidate protein biomarkers in a Diabetes Autoantibody Standardization Program (DASP) sample subset

PubMed Central

Metz, Thomas O.; Qian, Wei-Jun; Jacobs, Jon M.; Gritsenko, Marina A.; Moore, Ronald J.; Polpitiya, Ashoka D.; Monroe, Matthew E.; Camp, David G.; Mueller, Patricia W.; Smith, Richard D.

2009-01-01

Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted “-omics” approaches are under-utilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. Alpha-2-glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples. PMID:18092746

Standardization of protein biomarker measurements: is it feasible?

PubMed

Schimmel, Heinz; Zegers, Ingrid; Emons, Hendrik

2010-01-01

The standardisation of measurements of protein biomarkers, which are potentially heterogeneous in terms of fragmentation, modification, substitution, primary, secondary, tertiary and quaternary structure, is a demanding task. However, they are a prime target for standardisation efforts due to the importance of protein biomarkers in diagnostics and health care and the typically observed significant discrepancies in measurement results obtained with non-standardized platforms. Based on the experience gathered during successfully completed projects for the production of reference materials, pragmatic approaches are described how standardisation could become feasible despite the fuzziness of the target analytes.

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity

PubMed Central

Barkla, Bronwyn J.

2016-01-01

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised. PMID:28248236

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity.

PubMed

Barkla, Bronwyn J

2016-09-08

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

Urinary vitamin D-binding protein, a novel biomarker for lupus nephritis, predicts the development of proteinuric flare.

PubMed

Go, D J; Lee, J Y; Kang, M J; Lee, E Y; Lee, E B; Yi, E C; Song, Y W

2018-01-01

Lupus nephritis (LN) is a major complication of systemic lupus erythematosus (SLE). Conventional biomarkers for assessing renal disease activity are imperfect in predicting clinical outcomes associated with LN. The aim of this study is to identify urinary protein biomarkers that reliably reflect the disease activity or predict clinical outcomes. A quantitative proteomic analysis was performed to identify protein biomarker candidates that can differentiate between SLE patients with and without LN. Selected biomarker candidates were further verified by enzyme-linked immunosorbent assay using urine samples from a larger cohort of SLE patients ( n = 121) to investigate their predictive values for LN activity measure. Furthermore, the association between urinary levels of a selected panel of potential biomarkers and prognosis of LN was assessed with a four-year follow-up study of renal outcomes. Urinary vitamin D-binding protein (VDBP), transthyretin (TTR), retinol binding protein 4 (RBP4), and prostaglandin D synthase (PTGDS) were significantly elevated in SLE patients with LN, especially in patients with active LN ( n = 21). Among them, VDBP well correlated with severity of proteinuria (rho = 0.661, p < 0.001) and renal SLE Disease Activity Index (renal SLEDAI) (rho = 0.520, p < 0.001). In the four-year follow-up, VDBP was a significant risk factor (hazard ratio 9.627, 95% confidence interval 1.698 to 54.571, p = 0.011) for the development of proteinuric flare in SLE patients without proteinuria ( n = 100) after adjustments for multiple confounders. Urinary VDBP correlated with proteinuria and renal SLEDAI, and predicted the development of proteinuria.

A protocol for identifying suitable biomarkers to assess fish health: A systematic review

PubMed Central

2017-01-01

Background Biomarkers have been used extensively to provide the connection between external levels of contaminant exposure, internal levels of tissue contamination, and early adverse effects in organisms. Objectives To present a three-step protocol for identifying suitable biomarkers to assess fish health in coastal and marine ecosystems, using Gladstone Harbour (Australia) as a case study. Methods Prior to applying our protocol, clear working definitions for biomarkers were developed to ensure consistency with the global literature on fish health assessment. First, contaminants of concern were identified based on the presence of point and diffuse sources of pollution and available monitoring data for the ecosystem of interest. Second, suitable fish species were identified using fisheries dependent and independent data, and prioritised based on potential pathways of exposure to the contaminants of concern. Finally, a systematic and critical literature review was conducted on the use of biomarkers to assess the health of fish exposed to the contaminants of concern. Results/Discussion We present clear working definitions for bioaccumulation markers, biomarkers of exposure, biomarkers of effect and biomarkers of susceptibility. Based on emission and concentration information, seven metals were identified as contaminants of concern for Gladstone Harbour. Twenty out of 232 fish species were abundant enough to be potentially suitable for biomarker studies; five of these were prioritised based on potential pathways of exposure and susceptibility to metals. The literature search on biomarkers yielded 5,035 articles, of which 151met the inclusion criteria. Based on our review, the most suitable biomarkers include bioaccumulation markers, biomarkers of exposure (CYP1A, EROD, SOD, LPOX, HSP, MT, DNA strand breaks, micronuclei, apoptosis), and biomarkers of effect (histopathology, TAG:ST). Conclusion Our protocol outlines a clear pathway to identify suitable biomarkers to

Strategies to design clinical studies to identify predictive biomarkers in cancer research.

PubMed

Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

2017-02-01

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Computational prediction of human salivary proteins from blood circulation and application to diagnostic biomarker identification.

PubMed

Wang, Jiaxin; Liang, Yanchun; Wang, Yan; Cui, Juan; Liu, Ming; Du, Wei; Xu, Ying

2013-01-01

Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer.

Computational Prediction of Human Salivary Proteins from Blood Circulation and Application to Diagnostic Biomarker Identification

PubMed Central

Wang, Jiaxin; Liang, Yanchun; Wang, Yan; Cui, Juan; Liu, Ming; Du, Wei; Xu, Ying

2013-01-01

Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer. PMID:24324552

Calling Biomarkers in Milk Using a Protein Microarray on Your Smartphone

PubMed Central

Ludwig, Susann K. J.; Tokarski, Christian; Lang, Stefan N.; van Ginkel, Leendert A.; Zhu, Hongying; Ozcan, Aydogan; Nielen, Michel W. F.

2015-01-01

Here we present the concept of a protein microarray-based fluorescence immunoassay for multiple biomarker detection in milk extracts by an ordinary smartphone. A multiplex immunoassay was designed on a microarray chip, having built-in positive and negative quality controls. After the immunoassay procedure, the 48 microspots were labelled with Quantum Dots (QD) depending on the protein biomarker levels in the sample. QD-fluorescence was subsequently detected by the smartphone camera under UV light excitation from LEDs embedded in a simple 3D-printed opto-mechanical smartphone attachment. The somewhat aberrant images obtained under such conditions, were corrected by newly developed Android-based software on the same smartphone, and protein biomarker profiles were calculated. The indirect detection of recombinant bovine somatotropin (rbST) in milk extracts based on altered biomarker profile of anti-rbST antibodies was selected as a real-life challenge. RbST-treated and untreated cows clearly showed reproducible treatment-dependent biomarker profiles in milk, in excellent agreement with results from a flow cytometer reference method. In a pilot experiment, anti-rbST antibody detection was multiplexed with the detection of another rbST-dependent biomarker, insulin-like growth factor 1 (IGF-1). Milk extract IGF-1 levels were found to be increased after rbST treatment and correlated with the results obtained from the reference method. These data clearly demonstrate the potential of the portable protein microarray concept towards simultaneous detection of multiple biomarkers. We envisage broad application of this ‘protein microarray on a smartphone’-concept for on-site testing, e.g., in food safety, environment and health monitoring. PMID:26308444

Biomarkers for ragwort poisoning in horses: identification of protein targets

PubMed Central

Moore, Rowan E; Knottenbelt, Derek; Matthews, Jacqueline B; Beynon, Robert J; Whitfield, Phillip D

2008-01-01

Background Ingestion of the poisonous weed ragwort (Senecio jacobea) by horses leads to irreversible liver damage. The principal toxins of ragwort are the pyrrolizidine alkaloids that are rapidly metabolised to highly reactive and cytotoxic pyrroles, which can escape into the circulation and bind to proteins. In this study a non-invasive in vitro model system has been developed to investigate whether pyrrole toxins induce specific modifications of equine blood proteins that are detectable by proteomic methods. Results One dimensional gel electrophoresis revealed a significant alteration in the equine plasma protein profile following pyrrole exposure and the formation of a high molecular weight protein aggregate. Using mass spectrometry and confirmation by western blotting the major components of this aggregate were identified as fibrinogen, serum albumin and transferrin. Conclusion These findings demonstrate that pyrrolic metabolites can modify equine plasma proteins. The high molecular weight aggregate may result from extensive inter- and intra-molecular cross-linking of fibrinogen with the pyrrole. This model has the potential to form the basis of a novel proteomic strategy aimed at identifying surrogate protein biomarkers of ragwort exposure in horses and other livestock. PMID:18691403

Gene expression profiling combined with bioinformatics analysis identify biomarkers for Parkinson disease.

PubMed

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result.

Gene Expression Profiling Combined with Bioinformatics Analysis Identify Biomarkers for Parkinson Disease

PubMed Central

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result. PMID:23284986

Myocardial Injury Is Distinguished from Stable Angina by a Set of Candidate Plasma Biomarkers Identified Using iTRAQ/MRM-Based Approach.

PubMed

Cheow, Esther Sok Hwee; Cheng, Woo Chin; Yap, Terence; Dutta, Bamaprasad; Lee, Chuen Neng; Kleijn, Dominique P V de; Sorokin, Vitaly; Sze, Siu Kwan

2018-01-05

The lack of precise biomarkers that identify patients at risk for myocardial injury and stable angina delays administration of optimal therapy. Hence, the search for noninvasive biomarkers that could accurately stratify patients with impending heart attack, from patients with stable coronary artery disease (CAD), is urgently needed in the clinic. Herein, we performed comparative quantitative proteomics on whole plasma sampled from patients with stable angina (NMI), acute myocardial infarction (MI), and healthy control subjects (Ctrl). We detected a total of 371 proteins with high confidence (FDR < 1%, p < 0.05) including 53 preliminary biomarkers that displayed ≥2-fold modulated expression in patients with CAD (27 associated with atherosclerotic stable angina, 26 with myocardial injury). In the verification phase, we used label-free LC-MRM-MS-based targeted method to verify the preliminary biomarkers in pooled plasma, excluded peptides that were poorly distinguished from background, and performed further validation of the remaining candidates in 49 individual plasma samples. Using this approach, we identified a final panel of eight novel candidate biomarkers that were significantly modulated in CAD (p < 0.05) including proteins associated with atherosclerotic stable angina that were implicated in endothelial dysfunction (F10 and MST1), proteins associated with myocardial injury reportedly involved in plaque destabilization (SERPINA3, CPN2, LUM), and in tissue protection/repair mechanisms (ORM2, ACTG1, NAGLU). Taken together, our data showed that candidate biomarkers with potential diagnostic values can be successfully detected in nondepleted human plasma using an iTRAQ/MRM-based discovery-validation approach and demonstrated the plausible clinical utility of the proposed panel in discriminating atherosclerotic stable angina from myocardial injury in the studied cohort.

Identifying module biomarkers from gastric cancer by differential correlation network

PubMed Central

Liu, Xiaoping; Chang, Xiao

2016-01-01

Gastric cancer (stomach cancer) is a severe disease caused by dysregulation of many functionally correlated genes or pathways instead of the mutation of individual genes. Systematic identification of gastric cancer biomarkers can provide insights into the mechanisms underlying this deadly disease and help in the development of new drugs. In this paper, we present a novel network-based approach to predict module biomarkers of gastric cancer that can effectively distinguish the disease from normal samples. Specifically, by assuming that gastric cancer has mainly resulted from dysfunction of biomolecular networks rather than individual genes in an organism, the genes in the module biomarkers are potentially related to gastric cancer. Finally, we identified a module biomarker with 27 genes, and by comparing the module biomarker with known gastric cancer biomarkers, we found that our module biomarker exhibited a greater ability to diagnose the samples with gastric cancer. PMID:27703371

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

Mor, Gil G.; Ward, David C.; Bray-Ward, Patricia

2016-10-18

The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

Mor, Gil G; Ward, David C; Bray-Ward, Patricia

2015-03-10

The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

Mor, Gil G.; Ward, David C.; Bray-Ward, Patricia

2010-02-23

The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

Protein Biomarkers for Insulin Resistance and Type 2 Diabetes Risk in Two Large Community Cohorts

PubMed Central

Nowak, Christoph; Sundström, Johan; Gustafsson, Stefan; Giedraitis, Vilmantas; Lind, Lars; Ingelsson, Erik; Fall, Tove

2016-01-01

Insulin resistance (IR) is a precursor of type 2 diabetes (T2D), and improved risk prediction and understanding of the pathogenesis are needed. We used a novel high-throughput 92-protein assay to identify circulating biomarkers for HOMA of IR in two cohorts of community residents without diabetes (n = 1,367) (mean age 73 ± 3.6 years). Adjusted linear regression identified cathepsin D and confirmed six proteins (leptin, renin, interleukin-1 receptor antagonist [IL-1ra], hepatocyte growth factor, fatty acid–binding protein 4, and tissue plasminogen activator [t-PA]) as IR biomarkers. Mendelian randomization analysis indicated a positive causal effect of IR on t-PA concentrations. Two biomarkers, IL-1ra (hazard ratio [HR] 1.28, 95% CI 1.03–1.59) and t-PA (HR 1.30, 1.02–1.65) were associated with incident T2D, and t-PA predicted 5-year transition to hyperglycemia (odds ratio 1.30, 95% CI 1.02–1.65). Additional adjustment for fasting glucose rendered both coefficients insignificant and revealed an association between renin and T2D (HR 0.79, 0.62–0.99). LASSO regression suggested a risk model including IL-1ra, t-PA, and the Framingham Offspring Study T2D score, but prediction improvement was nonsignificant (difference in C-index 0.02, 95% CI −0.08 to 0.12) over the T2D score only. In conclusion, proteomic blood profiling indicated cathepsin D as a new IR biomarker and suggested a causal effect of IR on t-PA. PMID:26420861

The molecular signature of impaired diabetic wound healing identifies serpinB3 as a healing biomarker.

PubMed

Fadini, Gian Paolo; Albiero, Mattia; Millioni, Renato; Poncina, Nicol; Rigato, Mauro; Scotton, Rachele; Boscari, Federico; Brocco, Enrico; Arrigoni, Giorgio; Villano, Gianmarco; Turato, Cristian; Biasiolo, Alessandra; Pontisso, Patrizia; Avogaro, Angelo

2014-09-01

Chronic foot ulceration is a severe complication of diabetes, driving morbidity and mortality. The mechanisms underlying delaying wound healing in diabetes are incompletely understood and tools to identify such pathways are eagerly awaited. Wound biopsies were obtained from 75 patients with diabetic foot ulcers. Matched subgroups of rapidly healing (RH, n = 17) and non-healing (NH, n = 11) patients were selected. Proteomic analysis was performed by labelling with isobaric tag for relative and absolute quantification and mass spectrometry. Differentially expressed proteins were analysed in NH vs RH for identification of pathogenic pathways. Individual sample gene/protein validation and in vivo validation of candidate pathways in mouse models were carried out. Pathway analyses were conducted on 92/286 proteins that were differentially expressed in NH vs RH. The following pathways were enriched in NH vs RH patients: apoptosis, protease inhibitors, epithelial differentiation, serine endopeptidase activity, coagulation and regulation of defence response. SerpinB3 was strongly upregulated in RH vs NH wounds, validated as protein and mRNA in individual samples. To test the relevance of serpinB3 in vivo, we used a transgenic mouse model with α1-antitrypsin promoter-driven overexpression of human SERPINB3. In this model, wound healing was unaffected by SERPINB3 overexpression in non-diabetic or diabetic mice with or without hindlimb ischaemia. In an independent validation cohort of 47 patients, high serpinB3 protein content was confirmed as a biomarker of healing improvement. We provide a benchmark for the unbiased discovery of novel molecular targets and biomarkers of impaired diabetic wound healing. High serpinB3 protein content was found to be a biomarker of successful healing in diabetic patients.

Large-scale serum protein biomarker discovery in Duchenne muscular dystrophy.

PubMed

Hathout, Yetrib; Brody, Edward; Clemens, Paula R; Cripe, Linda; DeLisle, Robert Kirk; Furlong, Pat; Gordish-Dressman, Heather; Hache, Lauren; Henricson, Erik; Hoffman, Eric P; Kobayashi, Yvonne Monique; Lorts, Angela; Mah, Jean K; McDonald, Craig; Mehler, Bob; Nelson, Sally; Nikrad, Malti; Singer, Britta; Steele, Fintan; Sterling, David; Sweeney, H Lee; Williams, Steve; Gold, Larry

2015-06-09

Serum biomarkers in Duchenne muscular dystrophy (DMD) may provide deeper insights into disease pathogenesis, suggest new therapeutic approaches, serve as acute read-outs of drug effects, and be useful as surrogate outcome measures to predict later clinical benefit. In this study a large-scale biomarker discovery was performed on serum samples from patients with DMD and age-matched healthy volunteers using a modified aptamer-based proteomics technology. Levels of 1,125 proteins were quantified in serum samples from two independent DMD cohorts: cohort 1 (The Parent Project Muscular Dystrophy-Cincinnati Children's Hospital Medical Center), 42 patients with DMD and 28 age-matched normal volunteers; and cohort 2 (The Cooperative International Neuromuscular Research Group, Duchenne Natural History Study), 51 patients with DMD and 17 age-matched normal volunteers. Forty-four proteins showed significant differences that were consistent in both cohorts when comparing DMD patients and healthy volunteers at a 1% false-discovery rate, a large number of significant protein changes for such a small study. These biomarkers can be classified by known cellular processes and by age-dependent changes in protein concentration. Our findings demonstrate both the utility of this unbiased biomarker discovery approach and suggest potential new diagnostic and therapeutic avenues for ameliorating the burden of DMD and, we hope, other rare and devastating diseases.

CNS Injury: Posttranslational Modification of the Tau Protein as a Biomarker.

PubMed

Caprelli, Mitchell T; Mothe, Andrea J; Tator, Charles H

2017-11-01

The ideal biomarker for central nervous system (CNS) trauma in patients would be a molecular marker specific for injured nervous tissue that would provide a consistent and reliable assessment of the presence and severity of injury and the prognosis for recovery. One candidate biomarker is the protein tau, a microtubule-associated protein abundant in the axonal compartment of CNS neurons. Following axonal injury, tau becomes modified primarily by hyperphosphorylation of its various amino acid residues and cleavage into smaller fragments. These posttrauma products can leak into the cerebrospinal fluid or bloodstream and become candidate biomarkers of CNS injury. This review examines the primary molecular changes that tau undergoes following traumatic brain injury and spinal cord injury, and reviews the current literature in traumatic CNS biomarker research with a focus on the potential for hyperphosphorylated and cleaved tau as sensitive biomarkers of injury.

Enrichment of low-molecular-weight proteins from biofluids for biomarker discovery.

PubMed

Chertov, Oleg; Simpson, John T; Biragyn, Arya; Conrads, Thomas P; Veenstra, Timothy D; Fisher, Robert J

2005-01-01

The dramatic progress in mass spectrometry-based methods of protein identification has triggered a new quest for disease-associated biomarkers. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and its variant surface-enhanced laser desorption/ionization mass spectrometry, provide effective means to explore the less studied information slice of the human serum proteome -- low-molecular-weight proteins and peptides. These low-molecular-weight proteins and peptides are promising for the detection of important biomarkers. Due to the significant experimental problems imposed by high-abundance and high-molecular-weight proteins, it is important to effectively remove these species prior to mass spectrometry analysis of the low-molecular-weight serum and plasma proteomes. In this review, the advantages afforded by recently introduced methods for prefractionation of serum, as they pertain to the detection and identification of biomarkers, will be discussed.

Identification of multiple novel protein biomarkers shed by human serous ovarian tumors into the blood of immunocompromised mice and verified in patient sera.

PubMed

Beer, Lynn A; Wang, Huan; Tang, Hsin-Yao; Cao, Zhijun; Chang-Wong, Tony; Tanyi, Janos L; Zhang, Rugang; Liu, Qin; Speicher, David W

2013-01-01

The most cancer-specific biomarkers in blood are likely to be proteins shed directly by the tumor rather than less specific inflammatory or other host responses. The use of xenograft mouse models together with in-depth proteome analysis for identification of human proteins in the mouse blood is an under-utilized strategy that can clearly identify proteins shed by the tumor. In the current study, 268 human proteins shed into mouse blood from human OVCAR-3 serous tumors were identified based upon human vs. mouse species differences using a four-dimensional plasma proteome fractionation strategy. A multi-step prioritization and verification strategy was subsequently developed to efficiently select some of the most promising biomarkers from this large number of candidates. A key step was parallel analysis of human proteins detected in the tumor supernatant, because substantially greater sequence coverage for many of the human proteins initially detected in the xenograft mouse plasma confirmed assignments as tumor-derived human proteins. Verification of candidate biomarkers in patient sera was facilitated by in-depth, label-free quantitative comparisons of serum pools from patients with ovarian cancer and benign ovarian tumors. The only proteins that advanced to multiple reaction monitoring (MRM) assay development were those that exhibited increases in ovarian cancer patients compared with benign tumor controls. MRM assays were facilely developed for all 11 novel biomarker candidates selected by this process and analysis of larger pools of patient sera suggested that all 11 proteins are promising candidate biomarkers that should be further evaluated on individual patient blood samples.

Identification of Multiple Novel Protein Biomarkers Shed by Human Serous Ovarian Tumors into the Blood of Immunocompromised Mice and Verified in Patient Sera

PubMed Central

Beer, Lynn A.; Wang, Huan; Tang, Hsin-Yao; Cao, Zhijun; Chang-Wong, Tony; Tanyi, Janos L.; Zhang, Rugang; Liu, Qin; Speicher, David W.

2013-01-01

The most cancer-specific biomarkers in blood are likely to be proteins shed directly by the tumor rather than less specific inflammatory or other host responses. The use of xenograft mouse models together with in-depth proteome analysis for identification of human proteins in the mouse blood is an under-utilized strategy that can clearly identify proteins shed by the tumor. In the current study, 268 human proteins shed into mouse blood from human OVCAR-3 serous tumors were identified based upon human vs. mouse species differences using a four-dimensional plasma proteome fractionation strategy. A multi-step prioritization and verification strategy was subsequently developed to efficiently select some of the most promising biomarkers from this large number of candidates. A key step was parallel analysis of human proteins detected in the tumor supernatant, because substantially greater sequence coverage for many of the human proteins initially detected in the xenograft mouse plasma confirmed assignments as tumor-derived human proteins. Verification of candidate biomarkers in patient sera was facilitated by in-depth, label-free quantitative comparisons of serum pools from patients with ovarian cancer and benign ovarian tumors. The only proteins that advanced to multiple reaction monitoring (MRM) assay development were those that exhibited increases in ovarian cancer patients compared with benign tumor controls. MRM assays were facilely developed for all 11 novel biomarker candidates selected by this process and analysis of larger pools of patient sera suggested that all 11 proteins are promising candidate biomarkers that should be further evaluated on individual patient blood samples. PMID:23544127

Mammalian plasma membrane proteins as potential biomarkers and drug targets.

PubMed

Rucevic, Marijana; Hixson, Douglas; Josic, Djuro

2011-06-01

Defining the plasma membrane proteome is crucial to understand the role of plasma membrane in fundamental biological processes. Change in membrane proteins is one of the first events that take place under pathological conditions, making plasma membrane proteins a likely source of potential disease biomarkers with prognostic or diagnostic potential. Membrane proteins are also potential targets for monoclonal antibodies and other drugs that block receptors or inhibit enzymes essential to the disease progress. Despite several advanced methods recently developed for the analysis of hydrophobic proteins and proteins with posttranslational modifications, integral membrane proteins are still under-represented in plasma membrane proteome. Recent advances in proteomic investigation of plasma membrane proteins, defining their roles as diagnostic and prognostic disease biomarkers and as target molecules in disease treatment, are presented. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

PubMed

Borrebaeck, Carl A K

2017-03-01

Interest in precision diagnostics has been fuelled by the concept that early detection of cancer would benefit patients; that is, if detected early, more tumours should be resectable and treatment more efficacious. Serum contains massive amounts of potentially diagnostic information, and affinity proteomics has risen as an accurate approach to decipher this, to generate actionable information that should result in more precise and evidence-based options to manage cancer. To achieve this, we need to move from single to multiplex biomarkers, a so-called signature, that can provide significantly increased diagnostic accuracy. This Opinion article focuses on the progress being made in identifying protein biomarker signatures of clinical utility, using blood-based proteomics.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays.

PubMed

Parker, Carol E; Borchers, Christoph H

2014-06-01

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Serum Immunoproteomics Combined With Pathological Reassessment of Surgical Specimens Identifies TCP-1ζ Autoantibody as a Potential Biomarker in Thyroid Neoplasia.

PubMed

Belousov, Pavel V; Bogolyubova, Apollinariya V; Kim, Yan S; Abrosimov, Alexander Y; Kopylov, Arthur T; Tvardovskiy, Andrey A; Lanshchakov, Kirill V; Sazykin, Alexei Y; Dvinskikh, Nina Y; Bobrovskaya, Yana I; Selivanova, Lilia S; Shilov, Evgeniy S; Schwartz, Anton M; Shebzukhov, Yuriy V; Severskaia, Natalya V; Vanushko, Vladimir E; Moshkovskii, Sergei A; Nedospasov, Sergei A; Kuprash, Dmitry V

2015-09-01

Current methods of preoperative diagnostics frequently fail to discriminate between benign and malignant thyroid neoplasms. In encapsulated follicular-patterned tumors (EnFPT), this discrimination is challenging even using histopathological analysis. Autoantibody response against tumor-associated antigens is a well-documented phenomenon with prominent diagnostic potential; however, autoantigenicity of thyroid tumors remains poorly explored. Objectives were exploration of tumor-associated antigen repertoire of thyroid tumors and identification of candidate autoantibody biomarkers capable of discrimination between benign and malignant thyroid neoplasms. Proteins isolated from FTC-133 cells were subjected to two-dimensional Western blotting using pooled serum samples of patients originally diagnosed with either papillary thyroid carcinoma (PTC) or EnFPT represented by apparently benign follicular thyroid adenomas, as well as healthy individuals. Immunoreactive proteins were identified using liquid chromatography-tandem mass-spectrometry. Pathological reassessment of EnFPT was performed applying nonconservative criteria for capsular invasion and significance of focal PTC nuclear changes (PTC-NCs). Recombinant T-complex protein 1 subunitζ (TCP-1ζ) was used to examine an expanded serum sample set of patients with various thyroid neoplasms (n = 89) for TCP-1ζ autoantibodies. All patients were included in tertiary referral centers. A protein demonstrating a distinct pattern of EnFPT-specific seroreactivity was identified as TCP-1ζ protein. A subsequent search for clinicopathological correlates of TCP-1ζ seroreactivity revealed nonclassical capsular invasion or focal PTC-NC in all TCP-1ζ antibody-positive cases. Further studies in an expanded sample set confirmed the specificity of TCP-1ζ autoantibodies to malignant EnFPT. We identified TCP-1ζ autoantibodies as a potential biomarker for presurgical discrimination between benign and malignant encapsulated follicular

Fluorescence alteration of MPA capped CdSe quantum dots by spontaneous biomarker protein adsorption.

PubMed

Rowley, Amber; Parks, Tegan; Parks, Kaden; Medley, Kyle; Cordner, Alex; Yu, Ming

2018-05-23

Quantum dots (QDs) have significant potentials in biomedical applications of bioimaging and biosensing. Spontaneous adsorption of proteins on QDs surface is a common phenomenon, which occurred to serum proteins in biological samples, and has been observed to enhance QDs fluorescence. In this study, fluorescence alteration of 3-mercaptopropionic acid (MPA) capped CdSe quantum dots by four individual biomarker proteins was investigated. By monitoring the fluorescence emission of QDs, the biomarker protein adsorbed spontaneously on QDs surface was recognized and quantified. When alpha fetoprotein (AFP) or heat shock protein 90 alpha (HSP90α) were present, the QDs became brighter. The presence of cytochrome C (CytoC) or lysozyme (Lyz) made the QDs dimmer first, and then brighter. Within 5 min response time all four biomarker proteins were detected individually with the estimated detection limit in the range of 1-10 ng/mL and good linear dynamic ranges. The results suggested that the fluorescence of QDs was responsive to not only serum proteins but also biomarker proteins. The fluorescence response was able to correlate quantitatively with the amount of biomarker proteins in relatively low concentrations. These results provide more information to understand QDs and support their applications in biomedical fields. Copyright © 2018. Published by Elsevier Inc.

Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids

PubMed Central

2014-01-01

Background Computational methods for mining of biomedical literature can be useful in augmenting manual searches of the literature using keywords for disease-specific biomarker discovery from biofluids. In this work, we develop and apply a semi-automated literature mining method to mine abstracts obtained from PubMed to discover putative biomarkers of breast and lung cancers in specific biofluids. Methodology A positive set of abstracts was defined by the terms ‘breast cancer’ and ‘lung cancer’ in conjunction with 14 separate ‘biofluids’ (bile, blood, breastmilk, cerebrospinal fluid, mucus, plasma, saliva, semen, serum, synovial fluid, stool, sweat, tears, and urine), while a negative set of abstracts was defined by the terms ‘(biofluid) NOT breast cancer’ or ‘(biofluid) NOT lung cancer.’ More than 5.3 million total abstracts were obtained from PubMed and examined for biomarker-disease-biofluid associations (34,296 positive and 2,653,396 negative for breast cancer; 28,355 positive and 2,595,034 negative for lung cancer). Biological entities such as genes and proteins were tagged using ABNER, and processed using Python scripts to produce a list of putative biomarkers. Z-scores were calculated, ranked, and used to determine significance of putative biomarkers found. Manual verification of relevant abstracts was performed to assess our method’s performance. Results Biofluid-specific markers were identified from the literature, assigned relevance scores based on frequency of occurrence, and validated using known biomarker lists and/or databases for lung and breast cancer [NCBI’s On-line Mendelian Inheritance in Man (OMIM), Cancer Gene annotation server for cancer genomics (CAGE), NCBI’s Genes & Disease, NCI’s Early Detection Research Network (EDRN), and others]. The specificity of each marker for a given biofluid was calculated, and the performance of our semi-automated literature mining method assessed for breast and lung cancer

Dynamic application of microprojection arrays to skin induces circulating protein extravasation for enhanced biomarker capture and detection.

PubMed

Coffey, Jacob W; Meliga, Stefano C; Corrie, Simon R; Kendall, Mark A F

2016-04-01

Surface modified microprojection arrays are a needle-free alternative to capture circulating biomarkers from the skin in vivo for diagnosis. The concentration and turnover of biomarkers in the interstitial fluid, however, may limit the amount of biomarker that can be accessed by microprojection arrays and ultimately their capture efficiency. Here we report that microprojection array insertion induces protein extravasation from blood vessels and increases the concentration of biomarkers in skin, which can synergistically improve biomarker capture. Regions of blood vessels in skin were identified in the upper dermis and subcutaneous tissue by multi-photon microscopy. Insertion of microprojection array designs with varying projection length (40-190 μm), density (5000-20,408 proj.cm(-2)) and array size (4-36 mm(2)) did not affect the degree of extravasation. Furthermore, the location of extravasated protein did not correlate with projection penetration to these highly vascularised regions, suggesting extravasation was not caused by direct puncture of blood vessels. Biomarker extravasation was also induced by dynamic application of flat control surfaces, and varied with the impact velocity, further supporting this conclusion. The extravasated protein distribution correlated well with regions of high mechanical stress generated during insertion, quantified by finite element models. Using this approach to induce extravasation prior to microprojection array-based biomarker capture, anti-influenza IgG was captured within a 2 min application time, demonstrating that extravasation can lead to rapid biomarker sampling and significantly improved microprojection array capture efficiency. These results have broad implications for the development of transdermal devices that deliver to and sample from the skin. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Phage display for identification of serum biomarkers of traumatic brain injury.

PubMed

Ghoshal, Sarbani; Bondada, Vimala; Saatman, Kathryn E; Guttmann, Rodney P; Geddes, James W

2016-10-15

The extent and severity of traumatic brain injuries (TBIs) can be difficult to determine with current diagnostic methods. To address this, there has been increased interest in developing biomarkers to assist in the diagnosis, determination of injury severity, evaluation of recovery and therapeutic efficacy, and prediction of outcomes. Several promising serum TBI biomarkers have been identified using hypothesis-driven approaches, largely examining proteins that are abundant in neurons and non-neural cells in the CNS. An unbiased approach, phage display, was used to identify serum TBI biomarkers. In this proof-of-concept study, mice received a TBI using the controlled cortical impact model of TBI (1mm injury depth, 3.5m/s velocity) and phage display was utilized to identify putative serum biomarkers at 6h postinjury. An engineered phage which preferentially bound to injured serum was sequenced to identify the 12-mer 'recognizer' peptide expressed on the coat protein. Following synthesis of the recognizer peptide, pull down, and mass spectrometry analysis, the target protein was identified as glial fibrillary acidic protein (GFAP). GFAP has previously been identified as a promising TBI biomarker. The results provide proof of concept regarding the ability of phage display to identify TBI serum biomarkers. This methodology is currently being applied to serum biomarkers of mild TBI. Copyright © 2016 Elsevier B.V. All rights reserved.

Identifying Disease Associated miRNAs Based on Protein Domains.

PubMed

Qin, Gui-Min; Li, Rui-Yi; Zhao, Xing-Ming

2016-01-01

MicroRNAs (miRNAs) are a class of small endogenous non-coding genes, acting as regulators in the post-transcriptional processes. Recently, the miRNAs are found to be widely involved in different types of diseases. Therefore, the identification of disease associated miRNAs can help understand the mechanisms that underlie the disease and identify new biomarkers. However, it is not easy to identify the miRNAs related to diseases due to its extensive involvements in various biological processes. In this work, we present a new approach to identify disease associated miRNAs based on domains, the functional and structural blocks of proteins. The results on real datasets demonstrate that our method can effectively identify disease related miRNAs with high precision.

Epithelial membrane protein-1 is a biomarker of gefitinib resistance.

PubMed

Jain, Anjali; Tindell, Charles A; Laux, Isett; Hunter, Jacob B; Curran, John; Galkin, Anna; Afar, Daniel E; Aronson, Nina; Shak, Steven; Natale, Ronald B; Agus, David B

2005-08-16

We describe a molecular resistance biomarker to gefitinib, epithelial membrane protein-1 (EMP-1). Gefitinib is a small-molecule inhibitor that competes for the ATP-binding site on EGF receptor (EGFR) and has been approved for patients with advanced lung cancers. Treatment with gefitinib has resulted in clinical benefit in patients, and, recently, heterozygous somatic mutations within the EGFR catalytic domain have been identified as a clinical correlate to objective response to gefitinib. However, clinical resistance to gefitinib limits the utility of this therapeutic to a fraction of patients, and objective clinical responses are rare. We aimed to assess the molecular phenotype and mechanism of in vivo gefitinib resistance in xenograft models and in patient samples. We generated in vivo gefitinib-resistance models in an adenocarcinoma xenograft model by serially passaging tumors in nude mice in presence of gefitinib until resistance was acquired. EMP-1 was identified as a surface biomarker whose expression correlated with acquisition of gefitinib resistance. EMP-1 expression was further correlated with lack of complete or partial response to gefitinib in lung cancer patient samples as well as clinical progression to secondary gefitinib resistance. EMP-1 expression and acquisition of gefitinib clinical resistance was independent of gefitinib-sensitizing EGFR somatic mutations. This report suggests the role of the adhesion molecule, EMP-1, as a biomarker of gefitinib clinical resistance, and further suggests a probable cross-talk between this molecule and the EGFR signaling pathway.

Epithelial membrane protein-1 is a biomarker of gefitinib resistance

PubMed Central

Jain, Anjali; Tindell, Charles A.; Laux, Isett; Hunter, Jacob B.; Curran, John; Galkin, Anna; Afar, Daniel E.; Aronson, Nina; Shak, Steven; Natale, Ronald B.; Agus, David B.

2005-01-01

We describe a molecular resistance biomarker to gefitinib, epithelial membrane protein-1 (EMP-1). Gefitinib is a small-molecule inhibitor that competes for the ATP-binding site on EGF receptor (EGFR) and has been approved for patients with advanced lung cancers. Treatment with gefitinib has resulted in clinical benefit in patients, and, recently, heterozygous somatic mutations within the EGFR catalytic domain have been identified as a clinical correlate to objective response to gefitinib. However, clinical resistance to gefitinib limits the utility of this therapeutic to a fraction of patients, and objective clinical responses are rare. We aimed to assess the molecular phenotype and mechanism of in vivo gefitinib resistance in xenograft models and in patient samples. We generated in vivo gefitinib-resistance models in an adenocarcinoma xenograft model by serially passaging tumors in nude mice in presence of gefitinib until resistance was acquired. EMP-1 was identified as a surface biomarker whose expression correlated with acquisition of gefitinib resistance. EMP-1 expression was further correlated with lack of complete or partial response to gefitinib in lung cancer patient samples as well as clinical progression to secondary gefitinib resistance. EMP-1 expression and acquisition of gefitinib clinical resistance was independent of gefitinib-sensitizing EGFR somatic mutations. This report suggests the role of the adhesion molecule, EMP-1, as a biomarker of gefitinib clinical resistance, and further suggests a probable cross-talk between this molecule and the EGFR signaling pathway. PMID:16087880

High-throughput serum proteomics for the identification of protein biomarkers of mortality in older men

DOE Office of Scientific and Technical Information (OSTI.GOV)

Orwoll, Eric S.; Wiedrick, Jack; Jacobs, Jon

The biological perturbations associated with incident mortality are not well elucidated, and there are limited biomarkers for the prediction of mortality. We used a novel high throughput proteomics approach to identify serum peptides and proteins associated with 5 year mortality in community dwelling men age >65 years who participated in a longitudinal observational study of musculoskeletal aging (Osteoporotic Fractures in Men: MrOS). In a discovery phase, serum specimens collected at baseline in 2473 men were analyzed using liquid chromatography-ion mobility-mass spectrometry, and incident mortality in the subsequent 5 years was ascertained by tri-annual questionnaire. Rigorous statistical methods were utilized tomore » identify 56 peptides (31 proteins) that were associated with 5-year mortality. In an independent replication phase, selected reaction monitoring was used to examine 21 of those peptides in baseline serum from 750 additional men; 81% of those peptides remained significantly associated with mortality. Mortality-associated proteins included a variety involved in inflammation or complement activation; several have been previously linked to mortality (e.g. C reactive protein, alpha 1-antichymotrypsin) and others are not previously known to be associated with mortality. Other novel proteins of interest included pregnancy-associated plasma protein, VE cadherin, leucine-rich α-2 glycoprotein 1, vinculin, vitronectin, mast/stem cell growth factor receptor and Saa4. A panel of peptides improved the predictive value of a commonly used clinical predictor of mortality. Overall, these results suggest that complex inflammatory pathways, and proteins in other pathways, are linked to 5-year mortality risk. This work may serve to identify novel biomarkers for near term mortality.« less

Discovery of potential protein biomarkers of lung adenocarcinoma in bronchoalveolar lavage fluid by SWATH MS data-independent acquisition and targeted data extraction.

PubMed

Ortea, I; Rodríguez-Ariza, A; Chicano-Gálvez, E; Arenas Vacas, M S; Jurado Gámez, B

2016-04-14

Lung cancer currently ranks as the neoplasia with the highest global mortality rate. Although some improvements have been introduced in recent years, new advances in diagnosis are required in order to increase survival rates. New mildly invasive endoscopy-based diagnostic techniques include the collection of bronchoalveolar lavage fluid (BALF), which is discarded after using a portion of the fluid for standard pathological procedures. BALF proteomic analysis can contribute to clinical practice with more sensitive biomarkers, and can complement cytohistological studies by aiding in the diagnosis, prognosis, and subtyping of lung cancer, as well as the monitoring of treatment response. The range of quantitative proteomics methodologies used for biomarker discovery is currently being broadened with the introduction of data-independent acquisition (DIA) analysis-related approaches that address the massive quantitation of the components of a proteome. Here we report for the first time a DIA-based quantitative proteomics study using BALF as the source for the discovery of potential lung cancer biomarkers. The results have been encouraging in terms of the number of identified and quantified proteins. A panel of candidate protein biomarkers for adenocarcinoma in BALF is reported; this points to the activation of the complement network as being strongly over-represented and suggests this pathway as a potential target for lung cancer research. In addition, the results reported for haptoglobin, complement C4-A, and glutathione S-transferase pi are consistent with previous studies, which indicates that these proteins deserve further consideration as potential lung cancer biomarkers in BALF. Our study demonstrates that the analysis of BALF proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS), combining a simple sample pre-treatment and SWATH DIA MS, is a useful method for the discovery of potential lung cancer biomarkers. Bronchoalveolar lavage fluid (BALF

Quantitative HDL Proteomics Identifies Peroxiredoxin-6 as a Biomarker of Human Abdominal Aortic Aneurysm

PubMed Central

Burillo, Elena; Jorge, Inmaculada; Martínez-López, Diego; Camafeita, Emilio; Blanco-Colio, Luis Miguel; Trevisan-Herraz, Marco; Ezkurdia, Iakes; Egido, Jesús; Michel, Jean-Baptiste; Meilhac, Olivier; Vázquez, Jesús; Martin-Ventura, Jose Luis

2016-01-01

High-density lipoproteins (HDLs) are complex protein and lipid assemblies whose composition is known to change in diverse pathological situations. Analysis of the HDL proteome can thus provide insight into the main mechanisms underlying abdominal aortic aneurysm (AAA) and potentially detect novel systemic biomarkers. We performed a multiplexed quantitative proteomics analysis of HDLs isolated from plasma of AAA patients (N = 14) and control study participants (N = 7). Validation was performed by western-blot (HDL), immunohistochemistry (tissue), and ELISA (plasma). HDL from AAA patients showed elevated expression of peroxiredoxin-6 (PRDX6), HLA class I histocompatibility antigen (HLA-I), retinol-binding protein 4, and paraoxonase/arylesterase 1 (PON1), whereas α-2 macroglobulin and C4b-binding protein were decreased. The main pathways associated with HDL alterations in AAA were oxidative stress and immune-inflammatory responses. In AAA tissue, PRDX6 colocalized with neutrophils, vascular smooth muscle cells, and lipid oxidation. Moreover, plasma PRDX6 was higher in AAA (N = 47) than in controls (N = 27), reflecting increased systemic oxidative stress. Finally, a positive correlation was recorded between PRDX6 and AAA diameter. The analysis of the HDL proteome demonstrates that redox imbalance is a major mechanism in AAA, identifying the antioxidant PRDX6 as a novel systemic biomarker of AAA. PMID:27934969

Protein Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: Progress and Challenges.

PubMed

Root, Alex; Allen, Peter; Tempst, Paul; Yu, Kenneth

2018-03-07

Approximately 75% of patients with pancreatic ductal adenocarcinoma are diagnosed with advanced cancer, which cannot be safely resected. The most commonly used biomarker CA19-9 has inadequate sensitivity and specificity for early detection, which we define as Stage I/II cancers. Therefore, progress in next-generation biomarkers is greatly needed. Recent reports have validated a number of biomarkers, including combination assays of proteins and DNA mutations; however, the history of translating promising biomarkers to clinical utility suggests that several major hurdles require careful consideration by the medical community. The first set of challenges involves nominating and verifying biomarkers. Candidate biomarkers need to discriminate disease from benign controls with high sensitivity and specificity for an intended use, which we describe as a two-tiered strategy of identifying and screening high-risk patients. Community-wide efforts to share samples, data, and analysis methods have been beneficial and progress meeting this challenge has been achieved. The second set of challenges is assay optimization and validating biomarkers. After initial candidate validation, assays need to be refined into accurate, cost-effective, highly reproducible, and multiplexed targeted panels and then validated in large cohorts. To move the most promising candidates forward, ideally, biomarker panels, head-to-head comparisons, meta-analysis, and assessment in independent data sets might mitigate risk of failure. Much more investment is needed to overcome these challenges. The third challenge is achieving clinical translation. To moonshot an early detection test to the clinic requires a large clinical trial and organizational, regulatory, and entrepreneurial know-how. Additional factors, such as imaging technologies, will likely need to improve concomitant with molecular biomarker development. The magnitude of the clinical translational challenge is uncertain, but interdisciplinary

Tubulin Beta-3 Chain as a New Candidate Protein Biomarker of Human Skin Aging: A Preliminary Study

PubMed Central

2017-01-01

Skin aging is a complex process, and a lot of efforts have been made to identify new and specific targets that could help to diagnose, prevent, and treat skin aging. Several studies concerning skin aging have analyzed the changes in gene expression, and very few investigations have been performed at the protein level. Moreover, none of these proteomic studies has used a global quantitative labeled proteomic offgel approach that allows a more accurate description of aging phenotype. We applied such an approach on human primary keratinocytes obtained from sun-nonexposed skin biopsies of young and elderly women. A total of 517 unique proteins were identified, and 58 proteins were significantly differentially expressed with 40 that were downregulated and 18 upregulated with aging. Gene ontology and pathway analysis performed on these 58 putative biomarkers of skin aging evidenced that these dysregulated proteins were mostly involved in metabolism and cellular processes such as cell cycle and signaling pathways. Change of expression of tubulin beta-3 chain was confirmed by western blot on samples originated from several donors. Thus, this study suggested the tubulin beta-3 chain has a promising biomarker in skin aging. PMID:28626498

Tubulin Beta-3 Chain as a New Candidate Protein Biomarker of Human Skin Aging: A Preliminary Study.

PubMed

Lehmann, Sylvia G; Bourgoin-Voillard, Sandrine; Seve, Michel; Rachidi, Walid

2017-01-01

Skin aging is a complex process, and a lot of efforts have been made to identify new and specific targets that could help to diagnose, prevent, and treat skin aging. Several studies concerning skin aging have analyzed the changes in gene expression, and very few investigations have been performed at the protein level. Moreover, none of these proteomic studies has used a global quantitative labeled proteomic offgel approach that allows a more accurate description of aging phenotype. We applied such an approach on human primary keratinocytes obtained from sun-nonexposed skin biopsies of young and elderly women. A total of 517 unique proteins were identified, and 58 proteins were significantly differentially expressed with 40 that were downregulated and 18 upregulated with aging. Gene ontology and pathway analysis performed on these 58 putative biomarkers of skin aging evidenced that these dysregulated proteins were mostly involved in metabolism and cellular processes such as cell cycle and signaling pathways. Change of expression of tubulin beta-3 chain was confirmed by western blot on samples originated from several donors. Thus, this study suggested the tubulin beta-3 chain has a promising biomarker in skin aging.

Harnessing pain heterogeneity and RNA transcriptome to identify blood–based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model

PubMed Central

Grace, Peter M.; Hurley, Daniel; Barratt, Daniel T.; Tsykin, Anna; Watkins, Linda R.; Rolan, Paul E.; Hutchinson, Mark R.

2017-01-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. PMID:22697386

Coronin-1C is a novel biomarker for hepatocellular carcinoma invasive progression identified by proteomics analysis and clinical validation

PubMed Central

2010-01-01

Background To better search for potential markers for hepatocellular carcinoma (HCC) invasion and metastasis, proteomic approach was applied to identify potential metastasis biomarkers associated with HCC. Methods Membrane proteins were extracted from MHCC97L and HCCLM9 cells, with a similar genetic background and remarkably different metastasis potential, and compared by SDS-PAGE and identified by ESI-MS/MS. The results were further validated by western blot analysis, immunohistochemistry (IHC) of tumor tissues from HCCLM9- and MHCC97L-nude mice, and clinical specimens. Results Membrane proteins were extracted from MHCC97L and HCCLM9 cell and compared by SDS-PAGE analyses. A total of 14 differentially expressed proteins were identified by ESI-MS/MS. Coronin-1C, a promising candidate, was found to be overexpressed in HCCLM9 cells as compared with MHCC97L cells, and validated by western blot and IHC from both nude mice tumor tissues and clinical specimens. Coronin-1C level showed an abrupt upsurge when pulmonary metastasis occurred. Increasing coronin-1C expression was found in liver cancer tissues of HCCLM9-nude mice with spontaneous pulmonary metastasis. IHC study on human HCC specimens revealed that more patients in the higher coronin-1C group had overt larger tumor and more advanced stage. Conclusions Coronin-1C could be a candidate biomarker to predict HCC invasive behavior. PMID:20181269

Coronin-1C is a novel biomarker for hepatocellular carcinoma invasive progression identified by proteomics analysis and clinical validation.

PubMed

Wu, Long; Peng, Chun-Wei; Hou, Jin-Xuan; Zhang, Yan-Hua; Chen, Chuang; Chen, Liang-Dong; Li, Yan

2010-02-24

To better search for potential markers for hepatocellular carcinoma (HCC) invasion and metastasis, proteomic approach was applied to identify potential metastasis biomarkers associated with HCC. Membrane proteins were extracted from MHCC97L and HCCLM9 cells, with a similar genetic background and remarkably different metastasis potential, and compared by SDS-PAGE and identified by ESI-MS/MS. The results were further validated by western blot analysis, immunohistochemistry (IHC) of tumor tissues from HCCLM9- and MHCC97L-nude mice, and clinical specimens. Membrane proteins were extracted from MHCC97L and HCCLM9 cell and compared by SDS-PAGE analyses. A total of 14 differentially expressed proteins were identified by ESI-MS/MS. Coronin-1C, a promising candidate, was found to be overexpressed in HCCLM9 cells as compared with MHCC97L cells, and validated by western blot and IHC from both nude mice tumor tissues and clinical specimens. Coronin-1C level showed an abrupt upsurge when pulmonary metastasis occurred. Increasing coronin-1C expression was found in liver cancer tissues of HCCLM9-nude mice with spontaneous pulmonary metastasis. IHC study on human HCC specimens revealed that more patients in the higher coronin-1C group had overt larger tumor and more advanced stage. Coronin-1C could be a candidate biomarker to predict HCC invasive behavior.

Protein biomarkers in vernix with potential to predict the development of atopic eczema in early childhood

PubMed Central

Holm, T; Rutishauser, D; Kai-Larsen, Y; Lyutvinskiy, Y; Stenius, F; Zubarev, R A; Agerberth, B; Alm, J; Scheynius, A

2014-01-01

Background Atopic eczema (AE) is a chronic inflammatory skin disease, which has increased in prevalence. Evidence points toward lifestyle as a major risk factor. AE is often the first symptom early in life later followed by food allergy, asthma, and allergic rhinitis. Thus, there is a great need to find early, preferentially noninvasive, biomarkers to identify individuals that are predisposed to AE with the goal to prevent disease development. Objective To investigate whether the protein abundances in vernix can predict later development of AE. Methods Vernix collected at birth from 34 newborns within the Assessment of Lifestyle and Allergic Disease During INfancy (ALADDIN) birth cohort was included in the study. At 2 years of age, 18 children had developed AE. Vernix proteins were identified and quantified with liquid chromatography coupled to tandem mass spectrometry. Results We identified and quantified 203 proteins in all vernix samples. An orthogonal projections to latent structures-discriminant analysis (OPLS-DA) model was found with R2 = 0.85, Q2 = 0.39, and discrimination power between the AE and healthy group of 73.5%. Polyubiquitin-C and calmodulin-like protein 5 showed strong negative correlation to the AE group, with a correlation coefficient of 0.73 and 0.68, respectively, and a P-value of 8.2 E-7 and 1.8 E-5, respectively. For these two proteins, the OPLS-DA model showed a prediction accuracy of 91.2%. Conclusion The protein abundances in vernix, and particularly that of polyubiquitin-C and calmodulin-like protein 5, are promising candidates as biomarkers for the identification of newborns predisposed to develop AE. PMID:24205894

Muscle-Derived Proteins as Serum Biomarkers for Monitoring Disease Progression in Three Forms of Muscular Dystrophy

PubMed Central

Burch, Peter M.; Pogoryelova, Oksana; Goldstein, Richard; Bennett, Donald; Guglieri, Michela; Straub, Volker; Bushby, Kate; Lochmüller, Hanns; Morris, Carl

2015-01-01

Abstract Background: Identifying translatable, non-invasive biomarkers of muscular dystrophy that better reflect the disease pathology than those currently available would aid the development of new therapies, the monitoring of disease progression and the response to therapy. Objective: The goal of this study was to evaluate a panel of serum protein biomarkers with the potential to specifically detect skeletal muscle injury. Method: Serum concentrations of skeletal troponin I (sTnI), myosin light chain 3 (Myl3), fatty acid binding protein 3 (FABP3) and muscle-type creatine kinase (CKM) proteins were measured in 74 Duchenne muscular dystrophy (DMD), 38 Becker muscular dystrophy (BMD) and 49 Limb-girdle muscular dystrophy type 2B (LGMD2B) patients and 32 healthy controls. Results: All four proteins were significantly elevated in the serum of these three muscular dystrophy patient populations when compared to healthy controls, but, interestingly, displayed different profiles depending on the type of muscular dystrophy. Additionally, the effects of patient age, ambulatory status, cardiac function and treatment status on the serum concentrations of the proteins were investigated. Statistical analysis revealed correlations between the serum concentrations and certain clinical endpoints including forced vital capacity in DMD patients and the time to walk ten meters in LGMD2B patients. Serum concentrations of these proteins were also elevated in two preclinical models of muscular dystrophy, the mdx mouse and the golden-retriever muscular dystrophy dog. Conclusions: These proteins, therefore, are potential muscular dystrophy biomarkers for monitoring disease progression and therapeutic response in both preclinical and clinical studies. PMID:26870665

Carbonylated plasma proteins as potential biomarkers of obesity induced type 2 diabetes mellitus.

PubMed

Bollineni, Ravi Chand; Fedorova, Maria; Blüher, Matthias; Hoffmann, Ralf

2014-11-07

Protein carbonylation is a common nonenzymatic oxidative post-translational modification, which is often considered as biomarker of oxidative stress. Recent evidence links protein carbonylation also to obesity and type 2 diabetes mellitus (T2DM), though the protein targets of carbonylation in human plasma have not been identified. In this study, we profiled carbonylated proteins in plasma samples obtained from lean individuals and obese patients with or without T2DM. The plasma samples were digested with trypsin, carbonyl groups were derivatized with O-(biotinylcarbazoylmethyl)hydroxylamine, enriched by avidin affinity chromatography, and analyzed by RPC-MS/MS. Signals of potentially modified peptides were targeted in a second LC-MS/MS analysis to retrieve the peptide sequence and the modified residues. A total of 158 unique carbonylated proteins were identified, of which 52 were detected in plasma samples of all three groups. Interestingly, 36 carbonylated proteins were detected only in obese patients with T2DM, whereas 18 were detected in both nondiabetic groups. The carbonylated proteins originated mostly from liver, plasma, platelet, and endothelium. Functionally, they were mainly involved in cell adhesion, signaling, angiogenesis, and cytoskeletal remodeling. Among the identified carbonylated proteins were several candidates, such as VEGFR-2, MMP-1, argin, MKK4, and compliment C5, already connected before to diabetes, obesity and metabolic diseases.

Biomarkers of sepsis

PubMed Central

2013-01-01

Sepsis is an unusual systemic reaction to what is sometimes an otherwise ordinary infection, and it probably represents a pattern of response by the immune system to injury. A hyper-inflammatory response is followed by an immunosuppressive phase during which multiple organ dysfunction is present and the patient is susceptible to nosocomial infection. Biomarkers to diagnose sepsis may allow early intervention which, although primarily supportive, can reduce the risk of death. Although lactate is currently the most commonly used biomarker to identify sepsis, other biomarkers may help to enhance lactate’s effectiveness; these include markers of the hyper-inflammatory phase of sepsis, such as pro-inflammatory cytokines and chemokines; proteins such as C-reactive protein and procalcitonin which are synthesized in response to infection and inflammation; and markers of neutrophil and monocyte activation. Recently, markers of the immunosuppressive phase of sepsis, such as anti-inflammatory cytokines, and alterations of the cell surface markers of monocytes and lymphocytes have been examined. Combinations of pro- and anti-inflammatory biomarkers in a multi-marker panel may help identify patients who are developing severe sepsis before organ dysfunction has advanced too far. Combined with innovative approaches to treatment that target the immunosuppressive phase, these biomarkers may help to reduce the mortality rate associated with severe sepsis which, despite advances in supportive measures, remains high. PMID:23480440

Prespecified candidate biomarkers identify follicular lymphoma patients who achieved longer progression-free survival with bortezomib-rituximab versus rituximab.

PubMed

Coiffier, Bertrand; Li, Weimin; Henitz, Erin D; Karkera, Jayaprakash D; Favis, Reyna; Gaffney, Dana; Shapiro, Alice; Theocharous, Panteli; Elsayed, Yusri A; van de Velde, Helgi; Schaffer, Michael E; Osmanov, Evgenii A; Hong, Xiaonan; Scheliga, Adriana; Mayer, Jiri; Offner, Fritz; Rule, Simon; Teixeira, Adriana; Romejko-Jarosinska, Joanna; de Vos, Sven; Crump, Michael; Shpilberg, Ofer; Zinzani, Pier Luigi; Cakana, Andrew; Esseltine, Dixie-Lee; Mulligan, George; Ricci, Deborah

2013-05-01

Identify subgroups of patients with relapsed/refractory follicular lymphoma deriving substantial progression-free survival (PFS) benefit with bortezomib-rituximab versus rituximab in the phase III LYM-3001 study. A total of 676 patients were randomized to five 5-week cycles of bortezomib-rituximab or rituximab. The primary end point was PFS; this prespecified analysis of candidate protein biomarkers and genes was an exploratory objective. Archived tumor tissue and whole blood samples were collected at baseline. Immunohistochemistry and genetic analyses were completed for 4 proteins and 8 genes. In initial pairwise analyses, using individual single-nucleotide polymorphism genotypes, one biomarker pair (PSMB1 P11A C/G heterozygote, low CD68 expression) was associated with a significant PFS benefit with bortezomib-rituximab versus rituximab, controlling for multiple comparison corrections. The pair was analyzed under dominant, recessive, and additive genetic models, with significant association with PFS seen under the dominant model (G/G+C/G). In patients carrying this biomarker pair [PSMB1 P11A G allele, low CD68 expression (≤50 CD68-positive cells), population frequency: 43.6%], median PFS was 14.2 months with bortezomib-rituximab versus 9.1 months with rituximab (HR 0.47, P < 0.0001), and there was a significant overall survival benefit (HR 0.49, P = 0.0461). Response rates were higher and time to next antilymphoma therapy was longer in the bortezomib-rituximab group. In biomarker-negative patients, no significant efficacy differences were seen between treatment groups. Similar proportions of patients had high-risk features in the biomarker-positive and biomarker-negative subsets. Patients with PSMB1 P11A (G allele) and low CD68 expression seemed to have significantly longer PFS and greater clinical benefit with bortezomib-rituximab versus rituximab. ©2013 AACR.

Creation of a federated database of blood proteins: a powerful new tool for finding and characterizing biomarkers in serum

PubMed Central

2014-01-01

Protein biomarkers offer major benefits for diagnosis and monitoring of disease processes. Recent advances in protein mass spectrometry make it feasible to use this very sensitive technology to detect and quantify proteins in blood. To explore the potential of blood biomarkers, we conducted a thorough review to evaluate the reliability of data in the literature and to determine the spectrum of proteins reported to exist in blood with a goal of creating a Federated Database of Blood Proteins (FDBP). A unique feature of our approach is the use of a SQL database for all of the peptide data; the power of the SQL database combined with standard informatic algorithms such as BLAST and the statistical analysis system (SAS) allowed the rapid annotation and analysis of the database without the need to create special programs to manage the data. Our mathematical analysis and review shows that in addition to the usual secreted proteins found in blood, there are many reports of intracellular proteins and good agreement on transcription factors, DNA remodelling factors in addition to cellular receptors and their signal transduction enzymes. Overall, we have catalogued about 12,130 proteins identified by at least one unique peptide, and of these 3858 have 3 or more peptide correlations. The FDBP with annotations should facilitate testing blood for specific disease biomarkers. PMID:24476026

Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation

PubMed Central

Cohen Freue, Gabriela V.; Meredith, Anna; Smith, Derek; Bergman, Axel; Sasaki, Mayu; Lam, Karen K. Y.; Hollander, Zsuzsanna; Opushneva, Nina; Takhar, Mandeep; Lin, David; Wilson-McManus, Janet; Balshaw, Robert; Keown, Paul A.; Borchers, Christoph H.; McManus, Bruce; Ng, Raymond T.; McMaster, W. Robert

2013-01-01

Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac

Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer's Disease Diagnosis and Prognosis

PubMed Central

Craig-Schapiro, Rebecca; Kuhn, Max; Xiong, Chengjie; Pickering, Eve H.; Liu, Jingxia; Misko, Thomas P.; Perrin, Richard J.; Bales, Kelly R.; Soares, Holly; Fagan, Anne M.; Holtzman, David M.

2011-01-01

Background Clinicopathological studies suggest that Alzheimer's disease (AD) pathology begins ∼10–15 years before the resulting cognitive impairment draws medical attention. Biomarkers that can detect AD pathology in its early stages and predict dementia onset would, therefore, be invaluable for patient care and efficient clinical trial design. We utilized a targeted proteomics approach to discover novel cerebrospinal fluid (CSF) biomarkers that can augment the diagnostic and prognostic accuracy of current leading CSF biomarkers (Aβ42, tau, p-tau181). Methods and Findings Using a multiplexed Luminex platform, 190 analytes were measured in 333 CSF samples from cognitively normal (Clinical Dementia Rating [CDR] 0), very mildly demented (CDR 0.5), and mildly demented (CDR 1) individuals. Mean levels of 37 analytes (12 after Bonferroni correction) were found to differ between CDR 0 and CDR>0 groups. Receiver-operating characteristic curve analyses revealed that small combinations of a subset of these markers (cystatin C, VEGF, TRAIL-R3, PAI-1, PP, NT-proBNP, MMP-10, MIF, GRO-α, fibrinogen, FAS, eotaxin-3) enhanced the ability of the best-performing established CSF biomarker, the tau/Aβ42 ratio, to discriminate CDR>0 from CDR 0 individuals. Multiple machine learning algorithms likewise showed that the novel biomarker panels improved the diagnostic performance of the current leading biomarkers. Importantly, most of the markers that best discriminated CDR 0 from CDR>0 individuals in the more targeted ROC analyses were also identified as top predictors in the machine learning models, reconfirming their potential as biomarkers for early-stage AD. Cox proportional hazards models demonstrated that an optimal panel of markers for predicting risk of developing cognitive impairment (CDR 0 to CDR>0 conversion) consisted of calbindin, Aβ42, and age. Conclusions/Significance Using a targeted proteomic screen, we identified novel candidate biomarkers that complement the best

Neuroproteomics and Systems Biology Approach to Identify Temporal Biomarker Changes Post Experimental Traumatic Brain Injury in Rats.

PubMed

Kobeissy, Firas H; Guingab-Cagmat, Joy D; Zhang, Zhiqun; Moghieb, Ahmed; Glushakova, Olena Y; Mondello, Stefania; Boutté, Angela M; Anagli, John; Rubenstein, Richard; Bahmad, Hisham; Wagner, Amy K; Hayes, Ronald L; Wang, Kevin K W

2016-01-01

Traumatic brain injury (TBI) represents a critical health problem of which diagnosis, management, and treatment remain challenging. TBI is a contributing factor in approximately one-third of all injury-related deaths in the United States. The Centers for Disease Control and Prevention estimate that 1.7 million people suffer a TBI in the United States annually. Efforts continue to focus on elucidating the complex molecular mechanisms underlying TBI pathophysiology and defining sensitive and specific biomarkers that can aid in improving patient management and care. Recently, the area of neuroproteomics-systems biology is proving to be a prominent tool in biomarker discovery for central nervous system injury and other neurological diseases. In this work, we employed the controlled cortical impact (CCI) model of experimental TBI in rat model to assess the temporal-global proteome changes after acute (1 day) and for the first time, subacute (7 days), post-injury time frame using the established cation-anion exchange chromatography-1D SDS gel electrophoresis LC-MS/MS platform for protein separation combined with discrete systems biology analyses to identify temporal biomarker changes related to this rat TBI model. Rather than focusing on any one individual molecular entity, we used in silico systems biology approach to understand the global dynamics that govern proteins that are differentially altered post-injury. In addition, gene ontology analysis of the proteomic data was conducted in order to categorize the proteins by molecular function, biological process, and cellular localization. Results show alterations in several proteins related to inflammatory responses and oxidative stress in both acute (1 day) and subacute (7 days) periods post-TBI. Moreover, results suggest a differential upregulation of neuroprotective proteins at 7 days post-CCI involved in cellular functions such as neurite growth, regeneration, and axonal guidance. Our study is among the

Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study

PubMed Central

Wu, Hongyu; Yu, Zhijie; Qi, Qibin; Li, Huaixing; Sun, Qi

2011-01-01

Objective Identifying individuals with high risk of type 2 diabetes is important. To evaluate discriminatory ability of multiple biomarkers for type 2 diabetes in a Chinese population. Methods Plasma adiponectin, plasminogen activator inhibitor-1, retinol-binding protein 4, resistin, C-reactive protein, interleukin 6 (IL-6), tumour necrosis factor α receptor 2 and ferritin were measured in a population-based sample of 3189 Chinese (1419 men and 1770 women) aged 50–70 years. A weighted biomarkers risk score (BRS) was developed based on the strength of associations of these biomarkers with type 2 diabetes. The discriminatory ability was tested by the area under receiver operating characteristics curve (AUC). Results Adiponectin, plasminogen activator inhibitor-1, IL-6 and ferritin were independently associated with the prevalence of type 2 diabetes, and they were used to calculate the biomarkers risk score (BRS). After adjustment for the confounding factors, the ORs for type 2 diabetes and impaired fasting glucose with each point increment of BRS were 1.28 (95% CI 1.22 to 1.34) and 1.16 (1.12 to 1.20), respectively. Compared with those in the lowest quintile of the BRS, the participants in the highest quintile have an OR (95% CI) of 6.67 (4.21 to 10.55) for type 2 diabetes. The area under the curve for the BRS and conventional risk factors alone was 0.73 and 0.76, respectively, and substantially increased to 0.81 after combining both BRS and conventional risk factors (p<0.001). Conclusions These data suggest that combining multiple biomarkers and conventional risk factors might substantially enhance the ability to identify individuals with type 2 diabetes. More prospective data are warranted to confirm this observation. PMID:22021786

A CONCISE PANEL OF BIOMARKERS IDENTIFIES NEUROCOGNITIVE FUNCTIONING CHANGES IN HIV-INFECTED INDIVIDUALS

PubMed Central

Marcotte, Thomas D.; Deutsch, Reena; Michael, Benedict Daniel; Franklin, Donald; Cookson, Debra Rosario; Bharti, Ajay R.; Grant, Igor; Letendre, Scott L.

2013-01-01

Background Neurocognitive (NC) impairment (NCI) occurs commonly in people living with HIV. Despite substantial effort, no biomarkers have been sufficiently validated for diagnosis and prognosis of NCI in the clinic. The goal of this project was to identify diagnostic or prognostic biomarkers for NCI in a comprehensively characterized HIV cohort. Methods Multidisciplinary case review selected 98 HIV-infected individuals and categorized them into four NC groups using normative data: stably normal (SN), stably impaired (SI), worsening (Wo), or improving (Im). All subjects underwent comprehensive NC testing, phlebotomy, and lumbar puncture at two timepoints separated by a median of 6.2 months. Eight biomarkers were measured in CSF and blood by immunoassay. Results were analyzed using mixed model linear regression and staged recursive partitioning. Results At the first visit, subjects were mostly middle-aged (median 45) white (58%) men (84%) who had AIDS (70%). Of the 73% who took antiretroviral therapy (ART), 54% had HIV RNA levels below 50 c/mL in plasma. Mixed model linear regression identified that only MCP-1 in CSF was associated with neurocognitive change group. Recursive partitioning models aimed at diagnosis (i.e., correctly classifying neurocognitive status at the first visit) were complex and required most biomarkers to achieve misclassification limits. In contrast, prognostic models were more efficient. A combination of three biomarkers (sCD14, MCP-1, SDF-1α) correctly classified 82% of Wo and SN subjects, including 88% of SN subjects. A combination of two biomarkers (MCP-1, TNF-α) correctly classified 81% of Im and SI subjects, including 100% of SI subjects. Conclusions This analysis of well-characterized individuals identified concise panels of biomarkers associated with NC change. Across all analyses, the two most frequently identified biomarkers were sCD14 and MCP-1, indicators of monocyte/macrophage activation. While the panels differed depending on

Harnessing pain heterogeneity and RNA transcriptome to identify blood-based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model.

PubMed

Grace, Peter M; Hurley, Daniel; Barratt, Daniel T; Tsykin, Anna; Watkins, Linda R; Rolan, Paul E; Hutchinson, Mark R

2012-09-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. © 2012 The Authors. Journal of Neurochemistry © 2012 International Society for Neurochemistry.

Salivary proteins and microbiota as biomarkers for early childhood caries risk assessment

PubMed Central

Hemadi, Abdullah S; Huang, Ruijie; Zhou, Yuan; Zou, Jing

2017-01-01

Early childhood caries (ECC) is a term used to describe dental caries in children aged 6 years or younger. Oral streptococci, such as Streptococcus mutans and Streptococcus sorbrinus, are considered to be the main etiological agents of tooth decay in children. Other bacteria, such as Prevotella spp. and Lactobacillus spp., and fungus, that is, Candida albicans, are related to the development and progression of ECC. Biomolecules in saliva, mainly proteins, affect the survival of oral microorganisms by multiple innate defensive mechanisms, thus modulating the oral microflora. Therefore, the protein composition of saliva can be a sensitive indicator for dental health. Resistance or susceptibility to caries may be significantly correlated with alterations in salivary protein components. Some oral microorganisms and saliva proteins may serve as useful biomarkers in predicting the risk and prognosis of caries. Current research has generated abundant information that contributes to a better understanding of the roles of microorganisms and salivary proteins in ECC occurrence and prevention. This review summarizes the microorganisms that cause caries and tooth-protective salivary proteins with their potential as functional biomarkers for ECC risk assessment. The identification of biomarkers for children at high risk of ECC is not only critical for early diagnosis but also important for preventing and treating the disease. PMID:29125139

Top-Down Quantitative Proteomics Identified Phosphorylation of Cardiac Troponin I as a Candidate Biomarker for Chronic Heart Failure

PubMed Central

Zhang, Jiang; Guy, Moltu J.; Norman, Holly S.; Chen, Yi-Chen; Xu, Qingge; Dong, Xintong; Guner, Huseyin; Wang, Sijian; Kohmoto, Takushi; Young, Ken H.; Moss, Richard L.; Ge, Ying

2011-01-01

The rapid increase in the prevalence of chronic heart failure (CHF) worldwide underscores an urgent need to identify biomarkers for the early detection of CHF. Post-translational modifications (PTMs) are associated with many critical signaling events during disease progression and thus offer a plethora of candidate biomarkers. We have employed top-down quantitative proteomics methodology for comprehensive assessment of PTMs in whole proteins extracted from normal and diseased tissues. We have systematically analyzed thirty-six clinical human heart tissue samples and identified phosphorylation of cardiac troponin I (cTnI) as a candidate biomarker for CHF. The relative percentages of the total phosphorylated cTnI forms over the entire cTnI populations (%Ptotal) were 56.4±3.5%, 36.9±1.6%, 6.1±2.4%, and 1.0±0.6% for postmortem hearts with normal cardiac function (n=7), early-stage of mild hypertrophy (n=5), severe hypertrophy/dilation (n=4), and end-stage CHF (n=6), respectively. In fresh transplant samples, the %Ptotal of cTnI from non-failing donor (n=4), and end-stage failing hearts (n=10) were 49.5±5.9% and 18.8±2.9%, respectively. Top-down MS with electron capture dissociation unequivocally localized the altered phosphorylation sites to Ser22/23 and determined the order of phosphorylation/dephosphorylation. This study represents the first clinical application of top-down MS-based quantitative proteomics for biomarker discovery from tissues, highlighting the potential of PTM as disease biomarkers. PMID:21751783

Nano and Microparticle-Enhanced Immunosensor Approaches for the Detection of Cancer Biomarker Proteins

NASA Astrophysics Data System (ADS)

Mani, Vigneshwaran

Accurate, sensitive, point-of-care multiplexed protein measurements are critical for early disease detection and monitoring, impacting biomarker and drug discovery, and personalized medicine. Significant application involves monitoring panels of proteins in the blood that are biomarkers for diagnosing cancer. However, measurements of biomarker panels in blood or other bodily fluids have been slow to integrate into current practice of cancer diagnostics partly due to the lack of technically simple, low-cost, sensitive, point-of-care multiplexed measurement devices, as well as the lack of rigorously validated protein panels. The present thesis in part addresses these limitations by the development of electrochemical and surface plasmon resonance (SPR) immunosensors utilizing 1mum superparamagnetic labels for accurate detection of prostate cancer biomarker proteins in patient serum samples. Electrochemical discrete immunosensors featuring nanostructured surface with densely packed 5 nm glutathione-coated gold nanoparticles coupled with multi-enzyme magnetic particle (MP) labels enabled measurement of prostate specific antigen (PSA) with a detection limit (DL) of 0.5 pg mL-1 in undiluted serum. Such low DLs are attributed to high surface area, conductivity of nanostructured surface, and multi-enzyme signal amplification. DLs are further improved by utilizing MP bioconjugated with more than 100,000 antibody labels to offline capture proteins from the serum sample matrix, minimizing nonspecific binding of interfering proteins on sensor surface before detection. This approach provided an unprecedented 10 fg DL mL-1 for PSA in undiluted serum using a flow SPR biosensor. Finally electrochemical microfluidic immunoarrays featuring nanostructured surface and offline protein capture by multi-label MPs enabled multiplexed detection of prostate cancer biomarkers PSA and interleukin-6 (IL-6). These approaches provided up to 1000-fold lower DLs compared to commercial bead based

MRM for the verification of cancer biomarker proteins: recent applications to human plasma and serum.

PubMed

Chambers, Andrew G; Percy, Andrew J; Simon, Romain; Borchers, Christoph H

2014-04-01

Accurate cancer biomarkers are needed for early detection, disease classification, prediction of therapeutic response and monitoring treatment. While there appears to be no shortage of candidate biomarker proteins, a major bottleneck in the biomarker pipeline continues to be their verification by enzyme linked immunosorbent assays. Multiple reaction monitoring (MRM), also known as selected reaction monitoring, is a targeted mass spectrometry approach to protein quantitation and is emerging to bridge the gap between biomarker discovery and clinical validation. Highly multiplexed MRM assays are readily configured and enable simultaneous verification of large numbers of candidates facilitating the development of biomarker panels which can increase specificity. This review focuses on recent applications of MRM to the analysis of plasma and serum from cancer patients for biomarker verification. The current status of this approach is discussed along with future directions for targeted mass spectrometry in clinical biomarker validation.

Fusion peptides from oncogenic chimeric proteins as putative specific biomarkers of cancer.

PubMed

Conlon, Kevin P; Basrur, Venkatesha; Rolland, Delphine; Wolfe, Thomas; Nesvizhskii, Alexey I; MacCoss, Michael J; Lim, Megan S; Elenitoba-Johnson, Kojo S J

2013-10-01

Chromosomal translocations encoding chimeric fusion proteins constitute one of the most common mechanisms underlying oncogenic transformation in human cancer. Fusion peptides resulting from such oncogenic chimeric fusions, though unique to specific cancer subtypes, are unexplored as cancer biomarkers. Here we show, using an approach termed fusion peptide multiple reaction monitoring mass spectrometry, the direct identification of different cancer-specific fusion peptides arising from protein chimeras that are generated from the juxtaposition of heterologous genes fused by recurrent chromosomal translocations. Using fusion peptide multiple reaction monitoring mass spectrometry in a clinically relevant scenario, we demonstrate the specific, sensitive, and unambiguous detection of a specific diagnostic fusion peptide in clinical samples of anaplastic large cell lymphoma, but not in a diverse array of benign lymph nodes or other forms of primary malignant lymphomas and cancer-derived cell lines. Our studies highlight the utility of fusion peptides as cancer biomarkers and carry broad implications for the use of protein biomarkers in cancer detection and monitoring.

Plasma protein absolute quantification by nano-LC Q-TOF UDMSE for clinical biomarker verification

PubMed Central

ILIES, MARIA; IUGA, CRISTINA ADELA; LOGHIN, FELICIA; DHOPLE, VISHNU MUKUND; HAMMER, ELKE

2017-01-01

Background and aims Proteome-based biomarker studies are targeting proteins that could serve as diagnostic, prognosis, and prediction molecules. In the clinical routine, immunoassays are currently used for the absolute quantification of such biomarkers, with the major limitation that only one molecule can be targeted per assay. The aim of our study was to test a mass spectrometry based absolute quantification method for the verification of plasma protein sets which might serve as reliable biomarker panels for the clinical practice. Methods Six EDTA plasma samples were analyzed after tryptic digestion using a high throughput data independent acquisition nano-LC Q-TOF UDMSE proteomics approach. Synthetic Escherichia coli standard peptides were spiked in each sample for the absolute quantification. Data analysis was performed using ProgenesisQI v2.0 software (Waters Corporation). Results Our method ensured absolute quantification of 242 non redundant plasma proteins in a single run analysis. The dynamic range covered was 105. 86% were represented by classical plasma proteins. The overall median coefficient of variation was 0.36, while a set of 63 proteins was found to be highly stable. Absolute protein concentrations strongly correlated with values reviewed in the literature. Conclusions Nano-LC Q-TOF UDMSE proteomic analysis can be used for a simple and rapid determination of absolute amounts of plasma proteins. A large number of plasma proteins could be analyzed, while a wide dynamic range was covered with low coefficient of variation at protein level. The method proved to be a reliable tool for the quantification of protein panel for biomarker verification in the clinical practice. PMID:29151793

Mining the Immune Cell Proteome to Identify Ovarian Cancer-Specific Biomarkers

DTIC Science & Technology

2012-03-01

data and are in the process of identifying gene signatures that can be used as biomarkers for the identification of ovarian cancer-specific biomarkers...groups. The groups showed significant difference in age as well as gestational age, which is expected when considering the disease process . Isolation of...MUC4 in intracellular signaling.32 Oligosaccharides attached to the extracellular domains of mucins have also been shown to interact with different

Application of “omics” to Prion Biomarker Discovery

PubMed Central

Huzarewich, Rhiannon L. C. H.; Siemens, Christine G.; Booth, Stephanie A.

2010-01-01

The advent of genomics and proteomics has been a catalyst for the discovery of biomarkers able to discriminate biological processes such as the pathogenesis of complex diseases. Prompt detection of prion diseases is particularly desirable given their transmissibility, which is responsible for a number of human health risks stemming from exogenous sources of prion protein. Diagnosis relies on the ability to detect the biomarker PrPSc, a pathological isoform of the host protein PrPC, which is an essential component of the infectious prion. Immunochemical detection of PrPSc is specific and sensitive enough for antemortem testing of brain tissue, however, this is not the case in accessible biological fluids or for the detection of recently identified novel prions with unique biochemical properties. A complementary approach to the detection of PrPSc itself is to identify alternative, “surrogate” gene or protein biomarkers indicative of disease. Biomarkers are also useful to track the progress of disease, especially important in the assessment of therapies, or to identify individuals “at risk”. In this review we provide perspective on current progress and pitfalls in the use of “omics” technologies to screen body fluids and tissues for biomarker discovery in prion diseases. PMID:20224650

Multiplexed MRM-based quantitation of candidate cancer biomarker proteins in undepleted and non-enriched human plasma.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Borchers, Christoph H

2013-07-01

An emerging approach for multiplexed targeted proteomics involves bottom-up LC-MRM-MS, with stable isotope-labeled internal standard peptides, to accurately quantitate panels of putative disease biomarkers in biofluids. In this paper, we used this approach to quantitate 27 candidate cancer-biomarker proteins in human plasma that had not been treated by immunoaffinity depletion or enrichment techniques. These proteins have been reported as biomarkers for a variety of human cancers, from laryngeal to ovarian, with breast cancer having the highest correlation. We implemented measures to minimize the analytical variability, improve the quantitative accuracy, and increase the feasibility and applicability of this MRM-based method. We have demonstrated excellent retention time reproducibility (median interday CV: 0.08%) and signal stability (median interday CV: 4.5% for the analytical platform and 6.1% for the bottom-up workflow) for the 27 biomarker proteins (represented by 57 interference-free peptides). The linear dynamic range for the MRM assays spanned four orders-of-magnitude, with 25 assays covering a 10(3) -10(4) range in protein concentration. The lowest abundance quantifiable protein in our biomarker panel was insulin-like growth factor 1 (calculated concentration: 127 ng/mL). Overall, the analytical performance of this assay demonstrates high robustness and sensitivity, and provides the necessary throughput and multiplexing capabilities required to verify and validate cancer-associated protein biomarker panels in human plasma, prior to clinical use. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection.

PubMed

Sun, Huishan; Pan, Liping; Jia, Hongyan; Zhang, Zhiguo; Gao, Mengqiu; Huang, Mailing; Wang, Jinghui; Sun, Qi; Wei, Rongrong; Du, Boping; Xing, Aiying; Zhang, Zongde

2018-01-01

The lack of effective differential diagnostic methods for active tuberculosis (TB) and latent infection (LTBI) is still an obstacle for TB control. Furthermore, the molecular mechanism behind the progression from LTBI to active TB has been not elucidated. Therefore, we performed label-free quantitative proteomics to identify plasma biomarkers for discriminating pulmonary TB (PTB) from LTBI. A total of 31 overlapping proteins with significant difference in expression level were identified in PTB patients ( n = 15), compared with LTBI individuals ( n = 15) and healthy controls (HCs, n = 15). Eight differentially expressed proteins were verified using western blot analysis, which was 100% consistent with the proteomics results. Statistically significant differences of six proteins were further validated in the PTB group compared with the LTBI and HC groups in the training set ( n = 240), using ELISA. Classification and regression tree (CART) analysis was employed to determine the ideal protein combination for discriminating PTB from LTBI and HC. A diagnostic model consisting of alpha-1-antichymotrypsin (ACT), alpha-1-acid glycoprotein 1 (AGP1), and E-cadherin (CDH1) was established and presented a sensitivity of 81.2% (69/85) and a specificity of 95.2% (80/84) in discriminating PTB from LTBI, and a sensitivity of 81.2% (69/85) and a specificity of 90.1% (64/81) in discriminating PTB from HCs. Additional validation was performed by evaluating the diagnostic model in blind testing set ( n = 113), which yielded a sensitivity of 75.0% (21/28) and specificity of 96.1% (25/26) in PTB vs. LTBI, 75.0% (21/28) and 92.3% (24/26) in PTB vs. HCs, and 75.0% (21/28) and 81.8% (27/33) in PTB vs. lung cancer (LC), respectively. This study obtained the plasma proteomic profiles of different M.TB infection statuses, which contribute to a better understanding of the pathogenesis involved in the transition from latent infection to TB activation and provide new potential diagnostic

De Novo Identification of Biomarker Proteins Using Tandem Mass Spectrometry

EPA Science Inventory

Many studies have shown that biological fluids contain an important number of biomarkers associated with various pathologies. For instance, there has been extensive research to identify effective biomarkers as prognostic indicators of breast cancer. An effective approach for biom...

Cerebrospinal Fluid Biomarkers for Huntington's Disease.

PubMed

Byrne, Lauren M; Wild, Edward J

2016-01-01

Cerebrospinal fluid (CSF) is enriched in brain-derived components and represents an accessible and appealing means of interrogating the CNS milieu to study neurodegenerative diseases and identify biomarkers to facilitate the development of novel therapeutics. Many such CSF biomarkers have been proposed for Huntington's disease (HD) but none has been validated for clinical trial use. Across many studies proposing dozens of biomarker candidates, there is a notable lack of statistical power, consistency, rigor and validation. Here we review proposed CSF biomarkers including neurotransmitters, transglutaminase activity, kynurenine pathway metabolites, oxidative stress markers, inflammatory markers, neuroendocrine markers, protein markers of neuronal death, proteomic approaches and mutant huntingtin protein itself. We reflect on the need for large-scale, standardized CSF collections with detailed phenotypic data to validate and qualify much-needed CSF biomarkers for clinical trial use in HD.

Protein Biomarkers of New-Onset Cardiovascular Disease: A Prospective Study from the Systems Approach to Biomarker Research in Cardiovascular Disease (SABRe CVD) Initiative

PubMed Central

Yin, Xiaoyan; Subramanian, Subha; Hwang, Shih-Jen; O’Donnell, Christopher J.; Fox, Caroline S.; Courchesne, Paul; Muntendam, Pieter; Adourian, Aram; Juhasz, Peter; Larson, Martin G.; Levy, Daniel

2014-01-01

Objective Incorporation of novel plasma protein biomarkers may improve current models for prediction of atherosclerotic cardiovascular disease (ASCVD) risk. Approach and Results We utilized discovery mass spectrometry (MS) to determine plasma concentrations of 861 proteins in 135 myocardial infarction (MI) cases and 135 matched controls. We then measured 59markers by targeted MS in 336 ASCVD case-control pairs. Associations with MI or ASCVD were tested in single marker and multimarker analyses adjusted for established ASCVD risk factors. Twelve single markers from discovery MS were associated with MI incidence (at p<0.01) adjusting for clinical risk factors. Seven proteins in aggregate (cyclophilin A, CD5 antigen-like, cell surface glycoprotein MUC18, collagen-alpha 1 [XVIII] chain, salivary alpha-amylase 1, C-reactive protein, and multimerin-2) were highly associated with MI (p<0.0001) and significantly improved its prediction compared to a model with clinical risk factors alone (C-statistic of 0.71 vs. 0.84). Through targeted MS, twelve single proteins were predictors of ASCVD (at p<0.05) after adjusting for established risk factors. In multimarker analyses, four proteins in combination (alpha-1-acid glycoprotein 1, paraoxonase 1, tetranectin, and CD5 antigen-like, predicted incident ASCVD (p<0.0001) and moderately improved the C-statistic from the model with clinical covariates alone (C-statistic of 0.69 vs. 0.73). Conclusions Proteomics profiling identified single and multimarker protein panels that are associated with new onset ASCVD and may lead to a better understanding of underlying disease mechanisms. Our findings include many novel protein biomarkers that, if externally validated, may improve risk assessment for MI and ASCVD. PMID:24526693

Success, Failure, and Transparency in Biomarker-Based Drug Development: A Case Study of Cholesteryl Ester Transfer Protein Inhibitors.

PubMed

Hey, Spencer Phillips; Franklin, Jessica M; Avorn, Jerry; Kesselheim, Aaron S

2017-06-01

Although biomarkers are used as surrogate measures for drug targeting and approval and are generally based on plausible biological hypotheses, some are found to not correlate well with clinical outcomes. Over-reliance on inadequately validated biomarkers in drug development can lead to harm to trial subjects and patients and to research waste. To shed greater light on the process and ethics of biomarker-based drug development, we conducted a systematic portfolio analysis of cholesterol ester transfer protein inhibitors, a drug class designed to improve lipid profiles and prevent cardiovascular events. Despite years of development, no cholesterol ester transfer protein inhibitor has yet been approved for clinical use. We searched PubMed and Clinicaltrials.gov for clinical studies of 5 known cholesterol ester transfer protein inhibitors: anacetrapib, dalcetrapib, evacetrapib, TA-8995, and torcetrapib. Published reports and registration records were extracted for patient demographic characteristics and study authors' recommendations of clinical usage or further testing. We used Accumulating Evidence and Research Organization graphing to depict the portfolio of research activities and a Poisson model to examine trends. We identified 100 studies for analysis that involved 96 944 human subjects. The data from only 41 201 (42%) of the human subjects had been presented in a published report. For the 3 discontinued cholesterol ester transfer protein inhibitors, we found a pattern of consistently positive results on lipid-modification end points followed by negative results using clinical end points. Inefficiencies and harms can arise if a biomarker hypothesis continues to drive trials despite successive failures. Regulators, research funding bodies, and public policy makers may need to play a greater role in evaluating and coordinating biomarker-driven research programs. © 2017 American Heart Association, Inc.

Programmed cell death 6 interacting protein (PDCD6IP) and Rabenosyn-5 (ZFYVE20) are potential urinary biomarkers for upper gastrointestinal cancer.

PubMed

Husi, Holger; Skipworth, Richard J E; Cronshaw, Andrew; Stephens, Nathan A; Wackerhage, Henning; Greig, Carolyn; Fearon, Kenneth C H; Ross, James A

2015-06-01

Cancer of the upper digestive tract (uGI) is a major contributor to cancer-related death worldwide. Due to a rise in occurrence, together with poor survival rates and a lack of diagnostic or prognostic clinical assays, there is a clear need to establish molecular biomarkers. Initial assessment was performed on urine samples from 60 control and 60 uGI cancer patients using MS to establish a peak pattern or fingerprint model, which was validated by a further set of 59 samples. We detected 86 cluster peaks by MS above frequency and detection thresholds. Statistical testing and model building resulted in a peak profiling model of five relevant peaks with 88% overall sensitivity and 91% specificity, and overall correctness of 90%. High-resolution MS of 40 samples in the 2-10 kDa range resulted in 646 identified proteins, and pattern matching identified four of the five model peaks within significant parameters, namely programmed cell death 6 interacting protein (PDCD6IP/Alix/AIP1), Rabenosyn-5 (ZFYVE20), protein S100A8, and protein S100A9, of which the first two were validated by Western blotting. We demonstrate that MS analysis of human urine can identify lead biomarker candidates in uGI cancers, which makes this technique potentially useful in defining and consolidating biomarker patterns for uGI cancer screening. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic analysis identifies insulin-like growth factor-binding protein-related protein-1 as a podocyte product.

PubMed

Matsumoto, Takayuki; Hess, Sonja; Kajiyama, Hiroshi; Sakairi, Toru; Saleem, Moin A; Mathieson, Peter W; Nojima, Yoshihisa; Kopp, Jeffrey B

2010-10-01

The podocyte secretory proteome may influence the phenotype of adjacent podocytes, endothelial cells, parietal epithelial cells, and tubular epithelial cells but has not been systematically characterized. We have initiated studies to characterize this proteome, with the goal of further understanding the podocyte cell biology. We cultured differentiated conditionally immortalized human podocytes and subjected the proteins in conditioned medium to mass spectrometry. At a false discovery rate of <3%, we identified 111 candidates from conditioned medium, including 44 proteins that have signal peptides or are described as secreted proteins in the UniProt database. As validation, we confirmed that one of these proteins, insulin-like growth factor-binding protein-related protein-1 (IGFBP-rP1), was expressed in mRNA and protein of cultured podocytes. In addition, transforming growth factor-β1 stimulation increased IGFBP-rP1 in conditioned medium. We analyzed IGFBP-rP1 glomerular expression in a mouse model of human immunodeficiency virus-associated nephropathy. IGFBP-rP1 was absent from podocytes of normal mice and was expressed in podocytes and pseudocrescents of transgenic mice, where it was coexpressed with desmin, a podocyte injury marker. We conclude that IGFBP-rP1 may be a product of injured podocytes. Further analysis of the podocyte secretory proteome may identify biomarkers of podocyte injury.

Blood Pyrrole-Protein Adducts--A Biomarker of Pyrrolizidine Alkaloid-Induced Liver Injury in Humans.

PubMed

Ruan, Jianqing; Gao, Hong; Li, Na; Xue, Junyi; Chen, Jie; Ke, Changqiang; Ye, Yang; Fu, Peter Pi-Cheng; Zheng, Jiang; Wang, Jiyao; Lin, Ge

2015-01-01

Pyrrolizidine alkaloids (PAs) induce liver injury (PA-ILI) and is very likely to contribute significantly to drug-induced liver injury (DILI). In this study we used a newly developed ultra-high performance liquid chromatography-triple quadrupole-mass spectrometry (UHPLC-MS)-based method to detect and quantitate blood pyrrole-protein adducts in DILI patients. Among the 46 suspected DILI patients, 15 were identified as PA-ILI by the identification of PA-containing herbs exposed. Blood pyrrole-protein adducts were detected in all PA-ILI patients (100%). These results confirm that PA-ILI is one of the major causes of DILI and that blood pyrrole-protein adducts quantitated by the newly developed UHPLC-MS method can serve as a specific biomarker of PA-ILI.

The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

PubMed Central

Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

2010-01-01

The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

Imaging Biomarkers for Adult Medulloblastomas: Genetic Entities May Be Identified by Their MR Imaging Radiophenotype.

PubMed

Keil, V C; Warmuth-Metz, M; Reh, C; Enkirch, S J; Reinert, C; Beier, D; Jones, D T W; Pietsch, T; Schild, H H; Hattingen, E; Hau, P

2017-10-01

The occurrence of medulloblastomas in adults is rare; nevertheless, these tumors can be subdivided into genetic and histologic entities each having distinct prognoses. This study aimed to identify MR imaging biomarkers to classify these entities and to uncover differences in MR imaging biomarkers identified in pediatric medulloblastomas. Eligible preoperative MRIs from 28 patients (11 women; 22-53 years of age) of the Multicenter Pilot-study for the Therapy of Medulloblastoma of Adults (NOA-7) cohort were assessed by 3 experienced neuroradiologists. Lesions and perifocal edema were volumetrized and multiparametrically evaluated for classic morphologic characteristics, location, hydrocephalus, and Chang criteria. To identify MR imaging biomarkers, we correlated genetic entities sonic hedgehog ( SHH ) TP53 wild type, wingless ( WNT ), and non -WNT/ non -SHH medulloblastomas (in adults, Group 4), and histologic entities were correlated with the imaging criteria. These MR imaging biomarkers were compared with corresponding data from a pediatric study. There were 19 SHH TP53 wild type (69%), 4 WNT -activated (14%), and 5 Group 4 (17%) medulloblastomas. Six potential MR imaging biomarkers were identified, 3 of which, hydrocephalus ( P = .03), intraventricular macrometastases ( P = .02), and hemorrhage ( P = .04), when combined, could identify WNT medulloblastoma with 100% sensitivity and 88.3% specificity (95% CI, 39.8%-100.0% and 62.6%-95.3%). WNT -activated nuclear β-catenin accumulating medulloblastomas were smaller than the other entities (95% CI, 5.2-22.3 cm 3 versus 35.1-47.6 cm 3 ; P = .03). Hemorrhage was exclusively present in non -WNT/ non -SHH medulloblastomas ( P = .04; n = 2/5). MR imaging biomarkers were all discordant from those identified in the pediatric cohort. Desmoplastic/nodular medulloblastomas were more rarely in contact with the fourth ventricle (4/15 versus 7/13; P = .04). MR imaging biomarkers can help distinguish histologic and genetic

A critical insight into the development pipeline of microfluidic immunoassay devices for the sensitive quantitation of protein biomarkers at the point of care.

PubMed

Barbosa, Ana I; Reis, Nuno M

2017-03-13

biological matrix interference, (v) fluid control, (vi) the signal detection modes and (vii) the affordability of the manufacturing process and detection system, were identified as the key to the effective development of a sensitive and affordable microfluidic protein biomarker POC test.

Accurate Quantification of Cardiovascular Biomarkers in Serum Using Protein Standard Absolute Quantification (PSAQ™) and Selected Reaction Monitoring*

PubMed Central

Huillet, Céline; Adrait, Annie; Lebert, Dorothée; Picard, Guillaume; Trauchessec, Mathieu; Louwagie, Mathilde; Dupuis, Alain; Hittinger, Luc; Ghaleh, Bijan; Le Corvoisier, Philippe; Jaquinod, Michel; Garin, Jérôme; Bruley, Christophe; Brun, Virginie

2012-01-01

Development of new biomarkers needs to be significantly accelerated to improve diagnostic, prognostic, and toxicity monitoring as well as therapeutic follow-up. Biomarker evaluation is the main bottleneck in this development process. Selected Reaction Monitoring (SRM) combined with stable isotope dilution has emerged as a promising option to speed this step, particularly because of its multiplexing capacities. However, analytical variabilities because of upstream sample handling or incomplete trypsin digestion still need to be resolved. In 2007, we developed the PSAQ™ method (Protein Standard Absolute Quantification), which uses full-length isotope-labeled protein standards to quantify target proteins. In the present study we used clinically validated cardiovascular biomarkers (LDH-B, CKMB, myoglobin, and troponin I) to demonstrate that the combination of PSAQ and SRM (PSAQ-SRM) allows highly accurate biomarker quantification in serum samples. A multiplex PSAQ-SRM assay was used to quantify these biomarkers in clinical samples from myocardial infarction patients. Good correlation between PSAQ-SRM and ELISA assay results was found and demonstrated the consistency between these analytical approaches. Thus, PSAQ-SRM has the capacity to improve both accuracy and reproducibility in protein analysis. This will be a major contribution to efficient biomarker development strategies. PMID:22080464

Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease

PubMed Central

Zetterberg, Henrik; Mattsson, Niklas; Johansson, Per; Minthon, Lennart; Blennow, Kaj; Olsson, Mattias

2015-01-01

Objective: To compare the diagnostic accuracy of CSF biomarkers and amyloid PET for diagnosing early-stage Alzheimer disease (AD). Methods: From the prospective, longitudinal BioFINDER study, we included 122 healthy elderly and 34 patients with mild cognitive impairment who developed AD dementia within 3 years (MCI-AD). β-Amyloid (Aβ) deposition in 9 brain regions was examined with [18F]-flutemetamol PET. CSF was analyzed with INNOTEST and EUROIMMUN ELISAs. The results were replicated in 146 controls and 64 patients with MCI-AD from the Alzheimer's Disease Neuroimaging Initiative study. Results: The best CSF measures for identifying MCI-AD were Aβ42/total tau (t-tau) and Aβ42/hyperphosphorylated tau (p-tau) (area under the curve [AUC] 0.93–0.94). The best PET measures performed similarly (AUC 0.92–0.93; anterior cingulate, posterior cingulate/precuneus, and global neocortical uptake). CSF Aβ42/t-tau and Aβ42/p-tau performed better than CSF Aβ42 and Aβ42/40 (AUC difference 0.03–0.12, p < 0.05). Using nonoptimized cutoffs, CSF Aβ42/t-tau had the highest accuracy of all CSF/PET biomarkers (sensitivity 97%, specificity 83%). The combination of CSF and PET was not better than using either biomarker separately. Conclusions: Amyloid PET and CSF biomarkers can identify early AD with high accuracy. There were no differences between the best CSF and PET measures and no improvement when combining them. Regional PET measures were not better than assessing the global Aβ deposition. The results were replicated in an independent cohort using another CSF assay and PET tracer. The choice between CSF and amyloid PET biomarkers for identifying early AD can be based on availability, costs, and doctor/patient preferences since both have equally high diagnostic accuracy. Classification of evidence: This study provides Class III evidence that amyloid PET and CSF biomarkers identify early-stage AD equally accurately. PMID:26354982

Search for breast cancer biomarkers in fractionated serum samples by protein profiling with SELDI-TOF MS.

PubMed

Opstal-van Winden, Annemieke W J; Beijnen, Jos H; Loof, Arnoud; van Heerde, Waander L; Vermeulen, Roel; Peeters, Petra H M; van Gils, Carla H

2012-01-01

Many high-abundant acute phase reactants have been previously detected as potential breast cancer biomar-kers. However, they are unlikely to be specific for breast cancer. Cancer-specific biomarkers are thought to be among the lower abundant proteins. We aimed to detect lower abundant discriminating proteins by performing serum fractionation by strong anion exchange chromatography preceding protein profiling with SELDI-TOF MS. In a pilot study, we tested the different fractions resulting from fractionation, on several array types. Fraction 3 on IMAC30 and Fraction 6 on Q10 yielded the most discriminative proteins and were used for serum protein profiling of 73 incident breast cancer cases and 73 matched controls. Eight peaks showed statistically significantly different intensities between cases and controls (P⧁0.05), and had less than 10% chance to be a false-positive finding. Seven of these were tentatively identified as apolipoprotein C-II (m/z 8,909), oxidized apolipoprotein C-II (m/z 8,925), apolipoprotein C-III (m/z 8,746), fragment of coagulation factor XIIIa (m/z 3,959), heterodimer of apolipoprotein A-I and apolipoprotein A-II (m/z 45,435), hemoglobin B-chain (m/z 15,915), and post-translational modified hemoglobin (m/z 15,346). By extensive serum fractionation, we detected many more proteins than in previous studies without fractionation. However, discriminating proteins were still high abundant. Results indicate that either lower abundant proteins are less distinctive, or more rigorous fractionation and selective protein depletion, or a more sensitive assay, are needed to detect lower abundant discriminative proteins. © 2012 Wiley Periodicals, Inc.

Protein and microRNA biomarkers from lavage, urine, and serum in military personnel evaluated for dyspnea

PubMed Central

2014-01-01

Background We have identified candidate protein and microRNA (miRNA) biomarkers for dyspnea by studying serum, lavage fluid, and urine from military personnel who reported serious respiratory symptoms after they were deployed to Iraq or Afghanistan. Methods Forty-seven soldiers with the complaint of dyspnea who enrolled in the STudy of Active Duty Military Personnel for Environmental Dust Exposure (STAMPEDE) underwent comprehensive pulmonary evaluations at the San Antonio Military Medical Center. The evaluation included fiber-optic bronchoscopy with bronchoalveolar lavage. The clinical findings from the STAMPEDE subjects pointed to seven general underlying diagnoses or findings including airway hyperreactivity, asthma, low diffusivity of carbon monoxide, and abnormal cell counts. The largest category was undiagnosed. As an exploratory study, not a classification study, we profiled proteins or miRNAs in lavage fluid, serum, or urine in this group to look for any underlying molecular patterns that might lead to biomarkers. Proteins in lavage fluid and urine were identified by accurate mass tag (database-driven) proteomics methods while miRNAs were profiled by a hybridization assay applied to serum, urine, and lavage fluid. Results Over seventy differentially expressed proteins were reliably identified both from lavage and from urine in forty-eight dyspnea subjects compared to fifteen controls with no known lung disorder. Six of these proteins were detected both in urine and lavage. One group of subjects was distinguished from controls by expressing a characteristic group of proteins. A related group of dyspnea subjects expressed a unique group of miRNAs that included one miRNA that was differentially overexpressed in all three fluids studied. The levels of several miRNAs also showed modest but direct associations with several standard clinical measures of lung health such as forced vital capacity or gas exchange efficiency. Conclusions Candidate proteins and mi

Protein and microRNA biomarkers from lavage, urine, and serum in military personnel evaluated for dyspnea.

PubMed

Brown, Joseph N; Brewer, Heather M; Nicora, Carrie D; Weitz, Karl K; Morris, Michael J; Skabelund, Andrew J; Adkins, Joshua N; Smith, Richard D; Cho, Ji-Hoon; Gelinas, Richard

2014-10-05

We have identified candidate protein and microRNA (miRNA) biomarkers for dyspnea by studying serum, lavage fluid, and urine from military personnel who reported serious respiratory symptoms after they were deployed to Iraq or Afghanistan. Forty-seven soldiers with the complaint of dyspnea who enrolled in the STudy of Active Duty Military Personnel for Environmental Dust Exposure (STAMPEDE) underwent comprehensive pulmonary evaluations at the San Antonio Military Medical Center. The evaluation included fiber-optic bronchoscopy with bronchoalveolar lavage. The clinical findings from the STAMPEDE subjects pointed to seven general underlying diagnoses or findings including airway hyperreactivity, asthma, low diffusivity of carbon monoxide, and abnormal cell counts. The largest category was undiagnosed. As an exploratory study, not a classification study, we profiled proteins or miRNAs in lavage fluid, serum, or urine in this group to look for any underlying molecular patterns that might lead to biomarkers. Proteins in lavage fluid and urine were identified by accurate mass tag (database-driven) proteomics methods while miRNAs were profiled by a hybridization assay applied to serum, urine, and lavage fluid. Over seventy differentially expressed proteins were reliably identified both from lavage and from urine in forty-eight dyspnea subjects compared to fifteen controls with no known lung disorder. Six of these proteins were detected both in urine and lavage. One group of subjects was distinguished from controls by expressing a characteristic group of proteins. A related group of dyspnea subjects expressed a unique group of miRNAs that included one miRNA that was differentially overexpressed in all three fluids studied. The levels of several miRNAs also showed modest but direct associations with several standard clinical measures of lung health such as forced vital capacity or gas exchange efficiency. Candidate proteins and miRNAs associated with the general diagnosis of

Protein and microRNA biomarkers from lavage, urine, and serum in military personnel evaluated for dyspnea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Joseph N.; Brewer, Heather M.; Nicora, Carrie D.

Background: We have identified candidate protein and microRNA (miRNA) biomarkers for dyspnea by studying serum, lavage fluid, and urine from military personnel who reported serious respiratory symptoms after they were deployed to Iraq or Afghanistan. Methods: Forty-seven soldiers with the complaint of dyspnea who enrolled in the STudy of Active Duty Military Personnel for Environmental Dust Exposure (STAMPEDE) underwent comprehensive pulmonary evaluations at the San Antonio Military Medical Center. The evaluation included fiber-optic bronchoscopy with bronchoalveolar lavage. The clinical findings from the STAMPEDE subjects pointed to seven general underlying diagnoses or findings including airway hyperreactivity, asthma, low diffusivity of carbonmore » monoxide, and abnormal cell counts. The largest category was undiagnosed. As an exploratory study, not a classification study, we profiled proteins or miRNAs in lavage fluid, serum, or urine in this group to look for any underlying molecular patterns that might lead to biomarkers. Proteins in lavage fluid and urine were identified by accurate mass tag (database-driven) proteomics methods while miRNAs were profiled by a hybridization assay applied to serum, urine, and lavage fluid. Results: Over seventy differentially expressed proteins were reliably identified both from lavage and from urine in forty-eight dyspnea subjects compared to fifteen controls with no known lung disorder. Six of these proteins were detected both in urine and lavage. One group of subjects was distinguished from controls by expressing a characteristic group of proteins. A related group of dyspnea subjects expressed a unique group of miRNAs that included one miRNA that was differentially overexpressed in all three fluids studied. The levels of several miRNAs also showed modest but direct associations with several standard clinical measures of lung health such as forced vital capacity or gas exchange efficiency. Conclusions: Candidate proteins

Protein and microRNA biomarkers from lavage, urine, and serum in military personnel evaluated for dyspnea

DOE PAGES

Brown, Joseph N.; Brewer, Heather M.; Nicora, Carrie D.; ...

2014-10-05

Background: We have identified candidate protein and microRNA (miRNA) biomarkers for dyspnea by studying serum, lavage fluid, and urine from military personnel who reported serious respiratory symptoms after they were deployed to Iraq or Afghanistan. Methods: Forty-seven soldiers with the complaint of dyspnea who enrolled in the STudy of Active Duty Military Personnel for Environmental Dust Exposure (STAMPEDE) underwent comprehensive pulmonary evaluations at the San Antonio Military Medical Center. The evaluation included fiber-optic bronchoscopy with bronchoalveolar lavage. The clinical findings from the STAMPEDE subjects pointed to seven general underlying diagnoses or findings including airway hyperreactivity, asthma, low diffusivity of carbonmore » monoxide, and abnormal cell counts. The largest category was undiagnosed. As an exploratory study, not a classification study, we profiled proteins or miRNAs in lavage fluid, serum, or urine in this group to look for any underlying molecular patterns that might lead to biomarkers. Proteins in lavage fluid and urine were identified by accurate mass tag (database-driven) proteomics methods while miRNAs were profiled by a hybridization assay applied to serum, urine, and lavage fluid. Results: Over seventy differentially expressed proteins were reliably identified both from lavage and from urine in forty-eight dyspnea subjects compared to fifteen controls with no known lung disorder. Six of these proteins were detected both in urine and lavage. One group of subjects was distinguished from controls by expressing a characteristic group of proteins. A related group of dyspnea subjects expressed a unique group of miRNAs that included one miRNA that was differentially overexpressed in all three fluids studied. The levels of several miRNAs also showed modest but direct associations with several standard clinical measures of lung health such as forced vital capacity or gas exchange efficiency. Conclusions: Candidate proteins

Metabolomic profiling to identify potential serum biomarkers for schizophrenia and risperidone action.

PubMed

Xuan, Jiekun; Pan, Guihua; Qiu, Yunping; Yang, Lun; Su, Mingming; Liu, Yumin; Chen, Jian; Feng, Guoyin; Fang, Yiru; Jia, Wei; Xing, Qinghe; He, Lin

2011-12-02

Despite recent advances in understanding the pathophysiology of schizophrenia and the mechanisms of antipsychotic drug action, the development of biomarkers for diagnosis and therapeutic monitoring in schizophrenia remains challenging. Metabolomics provides a powerful approach to discover diagnostic and therapeutic biomarkers by analyzing global changes in an individual's metabolic profile in response to pathophysiological stimuli or drug intervention. In this study, we performed gas chromatography-mass spectrometry based metabolomic profiling in serum of unmedicated schizophrenic patients before and after an 8-week risperidone monotherapy, to detect potential biomarkers associated with schizophrenia and risperidone treatment. Twenty-two marker metabolites contributing to the complete separation of schizophrenic patients from matched healthy controls were identified, with citrate, palmitic acid, myo-inositol, and allantoin exhibiting the best combined classification performance. Twenty marker metabolites contributing to the complete separation between posttreatment and pretreatment patients were identified, with myo-inositol, uric acid, and tryptophan showing the maximum combined classification performance. Metabolic pathways including energy metabolism, antioxidant defense systems, neurotransmitter metabolism, fatty acid biosynthesis, and phospholipid metabolism were found to be disturbed in schizophrenic patients and partially normalized following risperidone therapy. Further study of these metabolites may facilitate the development of noninvasive biomarkers and more efficient therapeutic strategies for schizophrenia.

Identifying cut points for biomarker defined subset effects in clinical trials with survival endpoints.

PubMed

He, Pei

2014-07-01

The advancements in biotechnology and genetics lead to an increasing research interest in personalized medicine, where a patient's genetic profile or biological traits contribute to choosing the most effective treatment for the patient. The process starts with finding a specific biomarker among all possible candidates that can best predict the treatment effect. After a biomarker is chosen, identifying a cut point of the biomarker value that splits the patients into treatment effective and non-effective subgroups becomes an important scientific problem. Numerous methods have been proposed to validate the predictive marker and select the appropriate cut points either prospectively or retrospectively using clinical trial data. In trials with survival outcomes, the current practice applies an interaction testing procedure and chooses the cut point that minimizes the p-values for the tests. Such method assumes independence between the baseline hazard and biomarker value. In reality, however, this assumption is often violated, as the chosen biomarker might also be prognostic in addition to its predictive nature for treatment effect. In this paper we propose a block-wise estimation and a sequential testing approach to identify the cut point in biomarkers that can group the patients into subsets based on their distinct treatment outcomes without assuming independence between the biomarker and baseline hazard. Numerical results based on simulated survival data show that the proposed method could pinpoint accurately the cut points in biomarker values that separate the patient subpopulations into subgroups with distinctive treatment outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2016-10-01

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis PRINCIPAL...4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis 5b...Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad

Integrative epigenomic analysis identifies biomarkers and therapeutic targets in adult B-acute lymphoblastic leukemia

PubMed Central

Geng, Huimin; Brennan, Sarah; Milne, Thomas A.; Chen, Wei-Yi; Li, Yushan; Hurtz, Christian; Kweon, Soo-Mi; Zickl, Lynette; Shojaee, Seyedmehdi; Neuberg, Donna; Huang, Chuanxin; Biswas, Debabrata; Xin, Yuan; Racevskis, Janis; Ketterling, Rhett P.; Luger, Selina M.; Lazarus, Hillard; Tallman, Martin S.; Rowe, Jacob M.; Litzow, Mark R.; Guzman, Monica L.; Allis, C. David; Roeder, Robert G.; Müschen, Markus; Paietta, Elisabeth; Elemento, Olivier; Melnick, Ari M.

2012-01-01

Genetic lesions such as BCR-ABL1, E2A-PBX1 and MLL rearrangements (MLLr) are associated with unfavorable outcomes in adult B-acute lymphoblastic leukemia (B-ALL). Leukemia oncoproteins may directly or indirectly disrupt cytosine methylation patterning to mediate the malignant phenotype. We postulated that DNA methylation signatures in these aggressive B-ALLs would point towards disease mechanisms and useful biomarkers and therapeutic targets. We therefore performed DNA methylation and gene expression profiling on a cohort of 215 adult B-ALL patients enrolled in a single phase III clinical trial (ECOG E2993) and normal control B-cells. In BCR-ABL1-positive B-ALL, aberrant cytosine methylation patterning centered around a cytokine network defined by hypomethylation and overexpression of IL2RA(CD25). The E2993 trial clinical data showed that CD25 expression was strongly associated with a poor outcome in ALL patients regardless of BCR-ABL1 status, suggesting CD25 as a novel prognostic biomarker for risk stratification in B-ALL. In E2A-PBX1-positive B-ALL, aberrant DNA methylation patterning was strongly associated with direct fusion protein binding as shown by the E2A-PBX1 ChIP sequencing (ChIP-seq), suggesting that E2A-PBX1 fusion protein directly remodels the epigenome to impose an aggressive B-ALL phenotype. MLLr B-ALL featured prominent cytosine hypomethylation, which was linked with MLL fusion protein binding, H3K79 dimethylation and transcriptional upregulation, affecting a set of known and newly identified MLL fusion direct targets with oncogenic activity such as FLT3 and BCL6. Notably, BCL6 blockade or loss of function suppressed proliferation and survival of MLLr leukemia cells, suggesting BCL6 targeted therapy as a new therapeutic strategy for MLLr B-ALL. PMID:23107779

Application of a proteomic approach to identify proteins associated with primary graft non-function after liver transplantation.

PubMed

Kornasiewicz, Oskar; Bojarczuk, Kamil; Bugajski, Marek; Golab, Jakub; Krawczyk, Marek

2012-10-01

Primary graft non-function (PNF) is a rare, life-threatening complication of liver transplantation. Increasing use of extended criteria donor pools and high-risk recipients seem to influence the incidence of PNF. Primary failure is associated with high patient morbidity and inferior graft survival. The only available treatment for PNF is emergency hepatic retransplantation, which is also correlated with significant morbidity and mortality. Therefore, researchers are working to identify risk factors of diagnostic value to prevent PNF. The current study attempted to explore liver proteomic patterns in patients with PNF. Using two-dimensional gel electrophoresis and liquid chromatography-mass spectrometry (LC-MS), we compared liver protein homogenates from 3 patients with PNF to those obtained from 6 healthy liver samples to identify potential new biomarkers of PNF. Our comparisons revealed 21 proteins with differential expression (13 upregulated and 8 downregulated). Most of these proteins are involved in energy metabolism, lipid metabolism, peptide cleavage, cell differentiation, and apoptosis. Although none of these proteins appeared more than once in separate analyses, this preliminary study shows that two-dimensional gel electrophoresis and LC-MS may allow identification of characteristic proteins to be used as biomarkers of a life-threatening complication of liver transplantation. Larger-scale analyses could improve patient care by finding suitable prognostic and therapeutic options. These data represent the first global proteomic approach to study PNF.

[Biomarkers of Metabolism and Iron Nutrition].

PubMed

Sermini, Carmen Gloria; Acevedo, María José; Arredondo, Miguel

2017-01-01

Iron deficiency anemia is the most common nutritional deficiency worldwide, and the most susceptible groups are infants, preschoolers, women of childbearing age, and pregnant women. It is therefore essential to understand the mechanisms of regulation of iron uptake, transport, and absorption at the cellular level, particularly in enterocytes, and to identify blood biomarkers that allow the evaluation of iron status. This review describes how iron absorption is regulated by intestinal epithelial cells, the main proteins involved (iron transporters, oxidoreductases, storage proteins), and the main blood biomarkers of iron metabolism.

Blood/Brain Biomarkers of Inflammation After Stroke and Their Association With Outcome: From C-Reactive Protein to Damage-Associated Molecular Patterns.

PubMed

Bustamante, Alejandro; Simats, Alba; Vilar-Bergua, Andrea; García-Berrocoso, Teresa; Montaner, Joan

2016-10-01

Stroke represents one of the most important causes of disability and death in developed countries. However, there is a lack of prognostic tools in clinical practice to monitor the neurological condition and predict the final outcome. Blood biomarkers have been proposed and studied in this indication; however, no biomarker is currently used in clinical practice. The stroke-related neuroinflammatory processes have been associated with a poor outcome in stroke, as well as with poststroke complications. In this review, we focus on the most studied blood biomarkers of this inflammatory processes, cytokines, and C-reactive protein, evaluating its association with outcome and complications in stroke through the literature, and performing a systematic review on the association of C-reactive protein and functional outcome after stroke. Globally, we identified uncertainty with regard to the association of the evaluated biomarkers with stroke outcome, with little added value on top of clinical predictors such as age or stroke severity, which makes its implementation unlikely in clinical practice for global outcome prediction. Regarding poststroke complications, despite being more practical scenarios in which to make medical decisions following a biomarker prediction, not many studies have been performed, although there are now some candidates for prediction of poststroke infections. Finally, as potential new candidates, we reviewed the pathophysiological actions of damage-associated molecular patterns as triggers of the neuroinflammatory cascade of stroke, and their possible use as biomarkers.

Novel Bioinformatics-Based Approach for Proteomic Biomarkers Prediction of Calpain-2 & Caspase-3 Protease Fragmentation: Application to βII-Spectrin Protein

NASA Astrophysics Data System (ADS)

El-Assaad, Atlal; Dawy, Zaher; Nemer, Georges; Kobeissy, Firas

2017-01-01

The crucial biological role of proteases has been visible with the development of degradomics discipline involved in the determination of the proteases/substrates resulting in breakdown-products (BDPs) that can be utilized as putative biomarkers associated with different biological-clinical significance. In the field of cancer biology, matrix metalloproteinases (MMPs) have shown to result in MMPs-generated protein BDPs that are indicative of malignant growth in cancer, while in the field of neural injury, calpain-2 and caspase-3 proteases generate BDPs fragments that are indicative of different neural cell death mechanisms in different injury scenarios. Advanced proteomic techniques have shown a remarkable progress in identifying these BDPs experimentally. In this work, we present a bioinformatics-based prediction method that identifies protease-associated BDPs with high precision and efficiency. The method utilizes state-of-the-art sequence matching and alignment algorithms. It starts by locating consensus sequence occurrences and their variants in any set of protein substrates, generating all fragments resulting from cleavage. The complexity exists in space O(mn) as well as in O(Nmn) time, where N, m, and n are the number of protein sequences, length of the consensus sequence, and length per protein sequence, respectively. Finally, the proposed methodology is validated against βII-spectrin protein, a brain injury validated biomarker.

Verification of Ribosomal Proteins of Aspergillus fumigatus for Use as Biomarkers in MALDI-TOF MS Identification.

PubMed

Nakamura, Sayaka; Sato, Hiroaki; Tanaka, Reiko; Yaguchi, Takashi

2016-01-01

We have previously proposed a rapid identification method for bacterial strains based on the profiles of their ribosomal subunit proteins (RSPs), observed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). This method can perform phylogenetic characterization based on the mass of housekeeping RSP biomarkers, ideally calculated from amino acid sequence information registered in public protein databases. With the aim of extending its field of application to medical mycology, this study investigates the actual state of information of RSPs of eukaryotic fungi registered in public protein databases through the characterization of ribosomal protein fractions extracted from genome-sequenced Aspergillus fumigatus strains Af293 and A1163 as a model. In this process, we have found that the public protein databases harbor problems. The RSP names are in confusion, so we have provisionally unified them using the yeast naming system. The most serious problem is that many incorrect sequences are registered in the public protein databases. Surprisingly, more than half of the sequences are incorrect, due chiefly to mis-annotation of exon/intron structures. These errors could be corrected by a combination of in silico inspection by sequence homology analysis and MALDI-TOF MS measurements. We were also able to confirm conserved post-translational modifications in eleven RSPs. After these verifications, the masses of 31 expressed RSPs under 20,000 Da could be accurately confirmed. These RSPs have a potential to be useful biomarkers for identifying clinical isolates of A. fumigatus .

Chromatography/Mass Spectrometry-Based Biomarkers in the Field of Obstructive Sleep Apnea

PubMed Central

Xu, Huajun; Zheng, Xiaojiao; Jia, Wei; Yin, Shankai

2015-01-01

Abstract Biomarker assessment is based on quantifying several proteins and metabolites. Recent developments in proteomics and metabolomics have enabled detection of these small molecules in biological samples and exploration of the underlying disease mechanisms in obstructive sleep apnea (OSA). This systemic review was performed to identify biomarkers, which were only detected by chromatography and/or mass spectrometry (MS) and to discuss the role of these biomarkers in the field of OSA. We systemically reviewed relevant articles from PubMed and EMBASE referring to proteins and metabolite profiles of biological samples in patients with OSA. The analytical platforms in this review were focused on chromatography and/or MS. In total, 30 studies evaluating biomarkers in patients with OSA using chromatography and/or MS methods were included. Numerous proteins and metabolites, including lipid profiles, adrenergic/dopaminergic biomarkers and derivatives, amino acids, oxidative stress biomarkers, and other micromolecules were identified in patients with OSA. Applying chromatography and/or MS methods to detect biomarkers helps develop an understanding of OSA mechanisms. More proteomic and metabolomic studies are warranted to develop potential diagnostic and clinical monitoring methods for OSA. PMID:26448002

Tissue is alive: New technologies are needed to address the problems of protein biomarker pre-analytical variability.

PubMed

Espina, Virginia; Mueller, Claudius; Edmiston, Kirsten; Sciro, Manuela; Petricoin, Emanuel F; Liotta, Lance A

2009-08-01

Instability of tissue protein biomarkers is a critical issue for molecular profiling. Pre-analytical variables during tissue procurement, such as time delays during which the tissue remains stored at room temperature, can cause significant variability and bias in downstream molecular analysis. Living tissue, ex vivo, goes through a defined stage of reactive changes that begin with oxidative, hypoxic and metabolic stress, and culminate in apoptosis. Depending on the delay time ex vivo, and reactive stage, protein biomarkers, such as signal pathway phosphoproteins will be elevated or suppressed in a manner which does not represent the biomarker levels at the time of excision. Proteomic data documenting reactive tissue protein changes post collection indicate the need to recognize and address tissue stability, preservation of post-translational modifications, and preservation of morphologic features for molecular analysis. Based on the analysis of phosphoproteins, one of the most labile tissue protein biomarkers, we set forth tissue procurement guidelines for clinical research. We propose technical solutions for (i) assessing the state of protein analyte preservation and specimen quality via identification of a panel of natural proteins (surrogate stability markers), and (ii) using multi-purpose fixative solution designed to stabilize, preserve and maintain proteins, nucleic acids, and tissue architecture.

Tissue is alive: New technologies are needed to address the problems of protein biomarker pre-analytical variability

PubMed Central

Espina, Virginia; Mueller, Claudius; Edmiston, Kirsten; Sciro, Manuela; Petricoin, Emanuel F.; Liotta, Lance A.

2010-01-01

Instability of tissue protein biomarkers is a critical issue for molecular profiling. Pre-analytical variables during tissue procurement, such as time delays during which the tissue remains stored at room temperature, can cause significant variability and bias in downstream molecular analysis. Living tissue, ex vivo, goes through a defined stage of reactive changes that begin with oxidative, hypoxic and metabolic stress, and culminate in apoptosis. Depending on the delay time ex vivo, and reactive stage, protein biomarkers, such as signal pathway phosphoproteins will be elevated or suppressed in a manner which does not represent the biomarker levels at the time of excision. Proteomic data documenting reactive tissue protein changes post collection indicate the need to recognize and address tissue stability, preservation of post-translational modifications, and preservation of morphologic features for molecular analysis. Based on the analysis of phosphoproteins, one of the most labile tissue protein biomarkers, we set forth tissue procurement guidelines for clinical research. We propose technical solutions for (i) assessing the state of protein analyte preservation and specimen quality via identification of a panel of natural proteins (surrogate stability markers), and (ii) using multi-purpose fixative solution designed to stabilize, preserve and maintain proteins, nucleic acids, and tissue architecture. PMID:20871745

Quantification of Protein Biomarker Using SERS Nano-Stress Sensing with Peak Intensity Ratiometry

NASA Astrophysics Data System (ADS)

Goh, Douglas; Kong, Kien Voon; Jayakumar, Perumal; Gong, Tianxun; Dinish, U. S.; Olivo, Malini

We report a surface enhanced Raman spectroscopy (SERS) ratiometry method based on peak intensity coupled in a nano-stress sensing platform to detect and quantify biological molecules. Herein, we employed an antibody-conjugated p-aminothiophenol (ATP) functionalized on a bimetallic-film-over-nanosphere (BMFON) substrate as a sensitive SERS platform to detect human haptoglobin (Hp) protein, which is an acute phase protein and a biomarker for various cancers. Correlation between change in the ATP spectral characteristics and concentration of Hp protein was established by examining the peak intensity ratio at 1572cm-1 and 1592cm-1 that reflects the degree of stress experienced by the aromatic ring of ATP during Hp protein-antibody interaction. Development of this platform shows the potential in developing a low-cost and sensitive SERS sensor for the pre-screening of various biomarkers.

Identification of a sensitive urinary biomarker, selenium-binding protein 1, for early detection of acute kidney injury.

PubMed

Kim, Kyeong Seok; Yang, Hun Yong; Song, Hosup; Kang, Ye Rim; Kwon, JiHoon; An, JiHye; Son, Ji Yeon; Kwack, Seung Jun; Kim, Young-Mi; Bae, Ok-Nam; Ahn, Mee-Young; Lee, Jaewon; Yoon, Sungpil; Lee, Byung Mu; Kim, Hyung Sik

2017-01-01

Acute kidney injury (AKI) is associated with increased mortality rate in patients but clinically available biomarkers for disease detection are currently not available. Recently, a new biomarker, selenium-binding protein 1 (SBP1), was identified for detection of nephrotoxicity using proteomic analysis. The aim of this study was to assess the sensitivity of urinary SBP1 levels as an early detection of AKI using animal models such as cisplatin or ischemia/reperfusion (I/R). Sprague-Dawley rats were injected with cisplatin (6 mg/kg, once i.p.) and sacrificed at 1, 3, or 5 days after treatment. Ischemia was achieved by bilaterally occluding both kidneys with a microvascular clamp for 45 min and verified visually by a change in tissue color. After post-reperfusion, urine samples were collected at 9, 24, and 48 hr intervals. Urinary excretion of protein-based biomarkers was measured by Western blot analysis. In cisplatin-treated rats, mild histopathologic alterations were noted at day 1 which became severe at day 3. Blood urea nitrogen (BUN) and serum creatinine (SCr) levels were significantly increased at day 3. Levels of urinary excretion of SBP1, neutrophil gelatinase-associated lipocalin (NGAL), and a tissue inhibitor of metalloproteinase-1 (TIMP-1) were markedly elevated at day 3 and 5 following drug treatment. In the vehicle-treated I/R group, serum levels of BUN and SCr and AST activity were significantly increased compared to sham. Urinary excretion of SBP1 and NGAL rose markedly following I/R. The urinary levels of SBP1, NGAL, TIMP-1, and KIM-1 proteins excreted by AKI patients and normal subjects were compared. Among these proteins, a marked rise in SBP1 was observed in urine of patients with AKI compared to normal subjects. Based upon receiver-operator curves (ROC), SBP1 displayed a higher area under the curve (AUC) scores than levels of SCr, BUN, total protein, and glucose. In particular, SBP1 protein was readily detected in small amounts of urine without

Meconium proteins as a source of biomarkers for the assessment of the intrauterine environment of the fetus.

PubMed

Lisowska-Myjak, B; Skarżyńska, E; Bakun, M

2018-06-01

Intrauterine environmental factors can be associated with perinatal complications and long-term health outcomes although the underlying mechanisms remain poorly defined. Meconium formed exclusively in utero and passed naturally by a neonate may contain proteins which characterise the intrauterine environment. The aim of the study was proteomic analysis of the composition of meconium proteins and their classification by biological function. Proteomic techniques combining isoelectrofocussing fractionation and LC-MS/MS analysis were used to study the protein composition of a meconium sample obtained by pooling 50 serial meconium portions from 10 healthy full-term neonates. The proteins were classified by function based on the literature search for each protein in the PubMed database. A total of 946 proteins were identified in the meconium, including 430 proteins represented by two or more peptides. When the proteins were classified by their biological function the following were identified: immunoglobulin fragments and enzymatic, neutrophil-derived, structural and fetal intestine-specific proteins. Meconium is a rich source of proteins deposited in the fetal intestine during its development in utero. A better understanding of their specific biological functions in the intrauterine environment may help to identify these proteins which may serve as biomarkers associated with specific clinical conditions/diseases with the possible impact on the fetal development and further health consequences in infants, older children and adults.

Fluorescence-based Western blotting for quantitation of protein biomarkers in clinical samples.

PubMed

Zellner, Maria; Babeluk, Rita; Diestinger, Michael; Pirchegger, Petra; Skeledzic, Senada; Oehler, Rudolf

2008-09-01

Since most high throughput techniques used in biomarker discovery are very time and cost intensive, highly specific and quantitative analytical alternative application methods are needed for the routine analysis. Conventional Western blotting allows detection of specific proteins to the level of single isotypes while its quantitative accuracy is rather limited. We report a novel and improved quantitative Western blotting method. The use of fluorescently labelled secondary antibodies strongly extends the dynamic range of the quantitation and improves the correlation with the protein amount (r=0.997). By an additional fluorescent staining of all proteins immediately after their transfer to the blot membrane, it is possible to visualise simultaneously the antibody binding and the total protein profile. This allows for an accurate correction for protein load. Applying this normalisation it could be demonstrated that fluorescence-based Western blotting is able to reproduce a quantitative analysis of two specific proteins in blood platelet samples from 44 subjects with different diseases as initially conducted by 2D-DIGE. These results show that the proposed fluorescence-based Western blotting is an adequate application technique for biomarker quantitation and suggest possibilities of employment that go far beyond.

Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach.

PubMed

de Seny, Dominique; Fillet, Marianne; Meuwis, Marie-Alice; Geurts, Pierre; Lutteri, Laurence; Ribbens, Clio; Bours, Vincent; Wehenkel, Louis; Piette, Jacques; Malaise, Michel; Merville, Marie-Paule

2005-12-01

To identify serum protein biomarkers specific for rheumatoid arthritis (RA), using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. A total of 103 serum samples from patients and healthy controls were analyzed. Thirty-four of the patients had a diagnosis of RA, based on the American College of Rheumatology criteria. The inflammation control group comprised 20 patients with psoriatic arthritis (PsA), 9 with asthma, and 10 with Crohn's disease. The noninflammation control group comprised 14 patients with knee osteoarthritis and 16 healthy control subjects. Serum protein profiles were obtained by SELDI-TOF-MS and compared in order to identify new biomarkers specific for RA. Data were analyzed by a machine learning algorithm called decision tree boosting, according to different preprocessing steps. The most discriminative mass/charge (m/z) values serving as potential biomarkers for RA were identified on arrays for both patients with RA versus controls and patients with RA versus patients with PsA. From among several candidates, the following peaks were highlighted: m/z values of 2,924 (RA versus controls on H4 arrays), 10,832 and 11,632 (RA versus controls on CM10 arrays), 4,824 (RA versus PsA on H4 arrays), and 4,666 (RA versus PsA on CM10 arrays). Positive results of proteomic analysis were associated with positive results of the anti-cyclic citrullinated peptide test. Our observations suggested that the 10,832 peak could represent myeloid-related protein 8. SELDI-TOF-MS technology allows rapid analysis of many serum samples, and use of decision tree boosting analysis as the main statistical method allowed us to propose a pattern of protein peaks specific for RA.

Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics.

PubMed

Magdalinou, N K; Noyce, A J; Pinto, R; Lindstrom, E; Holmén-Larsson, J; Holtta, M; Blennow, K; Morris, H R; Skillbäck, T; Warner, T T; Lees, A J; Pike, I; Ward, M; Zetterberg, H; Gobom, J

2017-04-01

Neurodegenerative parkinsonian syndromes have significant clinical and pathological overlap, making early diagnosis difficult. Cerebrospinal fluid (CSF) biomarkers may aid the differentiation of these disorders, but other than α-synuclein and neurofilament light chain protein, which have limited diagnostic power, specific protein biomarkers remain elusive. To study disease mechanisms and identify possible CSF diagnostic biomarkers through discovery proteomics, which discriminate parkinsonian syndromes from healthy controls. CSF was collected consecutively from 134 participants; Parkinson's disease (n = 26), atypical parkinsonian syndromes (n = 78, including progressive supranuclear palsy (n = 36), multiple system atrophy (n = 28), corticobasal syndrome (n = 14)), and elderly healthy controls (n = 30). Participants were divided into a discovery and a validation set for analysis. The samples were subjected to tryptic digestion, followed by liquid chromatography-mass spectrometry analysis for identification and relative quantification by isobaric labelling. Candidate protein biomarkers were identified based on the relative abundances of the identified tryptic peptides. Their predictive performance was evaluated by analysis of the validation set. 79 tryptic peptides, derived from 26 proteins were found to differ significantly between atypical parkinsonism patients and controls. They included acute phase/inflammatory markers and neuronal/synaptic markers, which were respectively increased or decreased in atypical parkinsonism, while their levels in PD subjects were intermediate between controls and atypical parkinsonism. Using an unbiased proteomic approach, proteins were identified that were able to differentiate atypical parkinsonian syndrome patients from healthy controls. Our study indicates that markers that may reflect neuronal function and/or plasticity, such as the amyloid precursor protein, and inflammatory markers may hold future promise as

Protein mass spectra data analysis for clinical biomarker discovery: a global review.

PubMed

Roy, Pascal; Truntzer, Caroline; Maucort-Boulch, Delphine; Jouve, Thomas; Molinari, Nicolas

2011-03-01

The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years there has been a growing interest in using high throughput technologies for the detection of such biomarkers. In particular, mass spectrometry appears as an exciting tool with great potential. However, to extract any benefit from the massive potential of clinical proteomic studies, appropriate methods, improvement and validation are required. To better understand the key statistical points involved with such studies, this review presents the main data analysis steps of protein mass spectra data analysis, from the pre-processing of the data to the identification and validation of biomarkers.

Targeted Metabolomics Identifies Pharmacodynamic Biomarkers for BIO 300 Mitigation of Radiation-Induced Lung Injury.

PubMed

Jones, Jace W; Jackson, Isabel L; Vujaskovic, Zeljko; Kaytor, Michael D; Kane, Maureen A

2017-12-01

Biomarkers serve a number of purposes during drug development including defining the natural history of injury/disease, serving as a secondary endpoint or trigger for intervention, and/or aiding in the selection of an effective dose in humans. BIO 300 is a patent-protected pharmaceutical formulation of nanoparticles of synthetic genistein being developed by Humanetics Corporation. The primary goal of this metabolomic discovery experiment was to identify biomarkers that correlate with radiation-induced lung injury and BIO 300 efficacy for mitigating tissue damage based upon the primary endpoint of survival. High-throughput targeted metabolomics of lung tissue from male C57L/J mice exposed to 12.5 Gy whole thorax lung irradiation, treated daily with 400 mg/kg BIO 300 for either 2 weeks or 6 weeks starting 24 h post radiation exposure, were assayed at 180 d post-radiation to identify potential biomarkers. A panel of lung metabolites that are responsive to radiation and able to distinguish an efficacious treatment schedule of BIO 300 from a non-efficacious treatment schedule in terms of 180 d survival were identified. These metabolites represent potential biomarkers that could be further validated for use in drug development of BIO 300 and in the translation of dose from animal to human.

Detection of colorectal neoplasia: Combination of eight blood-based, cancer-associated protein biomarkers.

PubMed

Wilhelmsen, Michael; Christensen, Ib J; Rasmussen, Louise; Jørgensen, Lars N; Madsen, Mogens R; Vilandt, Jesper; Hillig, Thore; Klaerke, Michael; Nielsen, Knud T; Laurberg, Søren; Brünner, Nils; Gawel, Susan; Yang, Xiaoqing; Davis, Gerard; Heijboer, Annemieke; Martens, Frans; Nielsen, Hans J

2017-03-15

Serological biomarkers may be an option for early detection of colorectal cancer (CRC). The present study assessed eight cancer-associated protein biomarkers in plasma from subjects undergoing first time ever colonoscopy due to symptoms attributable to colorectal neoplasia. Plasma AFP, CA19-9, CEA, hs-CRP, CyFra21-1, Ferritin, Galectin-3 and TIMP-1 were determined in EDTA-plasma using the Abbott ARCHITECT® automated immunoassay platform. Primary endpoints were detection of (i) CRC and high-risk adenoma and (ii) CRC. Logistic regression was performed. Final reduced models were constructed selecting the four biomarkers with the highest likelihood scores. Subjects (N = 4,698) were consecutively included during 2010-2012. Colonoscopy detected 512 CRC patients, 319 colonic cancer and 193 rectal cancer. Extra colonic malignancies were detected in 177 patients, 689 had adenomas of which 399 were high-risk, 1,342 had nonneoplastic bowell disease and 1,978 subjects had 'clean' colorectum. Univariable analysis demonstrated that all biomarkers were statistically significant. Multivariate logistic regression demonstrated that the blood-based biomarkers in combination significantly predicted the endpoints. The reduced model resulted in the selection of CEA, hs-CRP, CyFra21-1 and Ferritin for the two endpoints; AUCs were 0.76 and 0.84, respectively. The postive predictive value at 90% sensitivity was 25% for endpoint 1 and the negative predictive value was 93%. For endpoint 2, the postive predictive value was 18% and the negative predictive value was 97%. Combinations of serological protein biomarkers provided a significant identification of subjects with high risk of the presence of colorectal neoplasia. The present set of biomarkers could become important adjunct in early detection of CRC. © 2016 UICC.

Proteomics of gliomas: Initial biomarker discovery and evolution of technology

PubMed Central

Kalinina, Juliya; Peng, Junmin; Ritchie, James C.; Van Meir, Erwin G.

2011-01-01

Gliomas are a group of aggressive brain tumors that diffusely infiltrate adjacent brain tissues, rendering them largely incurable, even with multiple treatment modalities and agents. Mostly asymptomatic at early stages, they present in several subtypes with astrocytic or oligodendrocytic features and invariably progress to malignant forms. Gliomas are difficult to classify precisely because of interobserver variability during histopathologic grading. Identifying biological signatures of each glioma subtype through protein biomarker profiling of tumor or tumor-proximal fluids is therefore of high priority. Such profiling not only may provide clues regarding tumor classification but may identify clinical biomarkers and pathologic targets for the development of personalized treatments. In the past decade, differential proteomic profiling techniques have utilized tumor, cerebrospinal fluid, and plasma from glioma patients to identify the first candidate diagnostic, prognostic, predictive, and therapeutic response markers, highlighting the potential for glioma biomarker discovery. The number of markers identified, however, has been limited, their reproducibility between studies is unclear, and none have been validated for clinical use. Recent technological advancements in methodologies for high-throughput profiling, which provide easy access, rapid screening, low sample consumption, and accurate protein identification, are anticipated to accelerate brain tumor biomarker discovery. Reliable tools for biomarker verification forecast translation of the biomarkers into clinical diagnostics in the foreseeable future. Herein we update the reader on the recent trends and directions in glioma proteomics, including key findings and established and emerging technologies for analysis, together with challenges we are still facing in identifying and verifying potential glioma biomarkers. PMID:21852429

Protein C: a potential biomarker in severe sepsis and a possible tool for monitoring treatment with drotrecogin alfa (activated)

PubMed Central

Shorr, Andrew F; Nelson, David R; Wyncoll, Duncan LA; Reinhart, Konrad; Brunkhorst, Frank; Vail, George Matthew; Janes, Jonathan

2008-01-01

Introduction Drotrecogin alfa (activated; DrotAA) treatment, a 96-hour infusion, reduces 28-day mortality in severe sepsis to approximately 25%. The question remains whether a longer infusion or higher dose could increase rate of survival. The goal of this study was to identify a dependable, sensitive measure with which to monitor disease progression and response in patients during DrotAA treatment. Methods Data on severe sepsis patients included in PROWESS (placebo-controlled, double-blind, randomized study of 850 DrotAA and 840 placebo individuals) and ENHANCE (single-arm, open-label study of 2,375 DrotAA patients) studies were analyzed. In these studies, DrotAA (24 μg/kg per hour) or placebo was infused for 96 hours and patients were followed for 28 days. Data on six laboratory measures and five organ dysfunctions were systematically analyzed to identify a potential surrogate end-point for monitoring DrotAA therapy and predicting 28-day mortality at the end of therapy. To allow comparison across variables, sensitivity and specificity analyses identified cut-off values for preferred outcome, and relative risks for being above or below cut-offs were calculated, as was the 'proportion of treatment effect explained' (PTEE) to identify biomarkers that contribute to benefit from DrotAA. Results Protein C was the only variable that correlated with outcome across all analyses. Using placebo data, a baseline protein C under 40% was established as a useful predictor of outcome (odds ratio 2.12). Similar odds ratios were associated with cut-off values of other biomarkers, but the treatment benefit associated with DrotAA was significantly greater below the cut-off than above the cut-off only for protein C (relative risk for 28-day mortality 0.66 versus 0.88; P = 0.04). Protein C was the only end-of-infusion biomarker that potentially explained at least 50% of the benefit from DrotAA (PTEE 57.2%). The PTEE was 41% for cardiovascular Sequential Organ Failure Assessment score

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer.

PubMed

Whiteaker, Jeffrey R; Zhang, Heidi; Zhao, Lei; Wang, Pei; Kelly-Spratt, Karen S; Ivey, Richard G; Piening, Brian D; Feng, Li-Chia; Kasarda, Erik; Gurley, Kay E; Eng, Jimmy K; Chodosh, Lewis A; Kemp, Christopher J; McIntosh, Martin W; Paulovich, Amanda G

2007-10-01

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.

Systematic approach identifies RHOA as a potential biomarker therapeutic target for Asian gastric cancer.

PubMed

Chang, Hae Ryung; Nam, Seungyoon; Lee, Jinhyuk; Kim, Jin-Hee; Jung, Hae Rim; Park, Hee Seo; Park, Sungjin; Ahn, Young Zoo; Huh, Iksoo; Balch, Curt; Ku, Ja-Lok; Powis, Garth; Park, Taesung; Jeong, Jin-Hyun; Kim, Yon Hui

2016-12-06

Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer "Big Data" has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors. To develop evidence-based precision medicine for heterogeneous cancers, we established a systematic approach to integrate transcriptomic and genomic data. Predicted signaling subpathways were then laboratory-validated both in vitro and in vivo, resulting in the identification of new candidate therapeutic targets. Here, we show: i) differences in RHOA expression patterns, and its pathway activity, between Asian and Caucasian GC tumors; ii) in vitro and in vivo perturbed RHOA expression inhibits GC cell growth in high RHOA-expressing cell lines; iii) inverse correlation between RHOA and RHOB expression; and iv) an innovative small molecule design strategy for RHOA inhibitors. In summary, RHOA, and its oncogenic signaling pathway, represent a strong biomarker-driven therapeutic target for Asian GC. This comprehensive strategy represents a promising approach for the development of "hit" compounds.

Methodology and Applications of Disease Biomarker Identification in Human Serum

PubMed Central

Sahab, Ziad J.; Semaan, Suzan M.; Sang, Qing-Xiang Amy

2007-01-01

Biomarkers are biomolecules that serve as indicators of biological and pathological processes, or physiological and pharmacological responses to a drug treatment. Because of the high abundance of albumin and heterogeneity of plasma lipoproteins and glycoproteins, biomarkers are difficult to identify in human serum. Due to the clinical significance the identification of disease biomarkers in serum holds great promise for personalized medicine, especially for disease diagnosis and prognosis. This review summarizes some common and emerging proteomics techniques utilized in the separation of serum samples and identification of disease signatures. The practical application of each protein separation or identification technique is analyzed using specific examples. Biomarkers of cancers of prostate, breast, ovary, and lung in human serum have been reviewed, as well as those of heart disease, arthritis, asthma, and cystic fibrosis. Despite the advancement of technology few biomarkers have been approved by the Food and Drug Administration for disease diagnosis and prognosis due to the complexity of structure and function of protein biomarkers and lack of high sensitivity, specificity, and reproducibility for those putative biomarkers. The combination of different types of technologies and statistical analysis may provide more effective methods to identify and validate new disease biomarkers in blood. PMID:19662190

Verification of Ribosomal Proteins of Aspergillus fumigatus for Use as Biomarkers in MALDI-TOF MS Identification

PubMed Central

Nakamura, Sayaka; Sato, Hiroaki; Tanaka, Reiko; Yaguchi, Takashi

2016-01-01

We have previously proposed a rapid identification method for bacterial strains based on the profiles of their ribosomal subunit proteins (RSPs), observed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). This method can perform phylogenetic characterization based on the mass of housekeeping RSP biomarkers, ideally calculated from amino acid sequence information registered in public protein databases. With the aim of extending its field of application to medical mycology, this study investigates the actual state of information of RSPs of eukaryotic fungi registered in public protein databases through the characterization of ribosomal protein fractions extracted from genome-sequenced Aspergillus fumigatus strains Af293 and A1163 as a model. In this process, we have found that the public protein databases harbor problems. The RSP names are in confusion, so we have provisionally unified them using the yeast naming system. The most serious problem is that many incorrect sequences are registered in the public protein databases. Surprisingly, more than half of the sequences are incorrect, due chiefly to mis-annotation of exon/intron structures. These errors could be corrected by a combination of in silico inspection by sequence homology analysis and MALDI-TOF MS measurements. We were also able to confirm conserved post-translational modifications in eleven RSPs. After these verifications, the masses of 31 expressed RSPs under 20,000 Da could be accurately confirmed. These RSPs have a potential to be useful biomarkers for identifying clinical isolates of A. fumigatus. PMID:27843740

The Protein Identifier Cross-Referencing (PICR) service: reconciling protein identifiers across multiple source databases.

PubMed

Côté, Richard G; Jones, Philip; Martens, Lennart; Kerrien, Samuel; Reisinger, Florian; Lin, Quan; Leinonen, Rasko; Apweiler, Rolf; Hermjakob, Henning

2007-10-18

Each major protein database uses its own conventions when assigning protein identifiers. Resolving the various, potentially unstable, identifiers that refer to identical proteins is a major challenge. This is a common problem when attempting to unify datasets that have been annotated with proteins from multiple data sources or querying data providers with one flavour of protein identifiers when the source database uses another. Partial solutions for protein identifier mapping exist but they are limited to specific species or techniques and to a very small number of databases. As a result, we have not found a solution that is generic enough and broad enough in mapping scope to suit our needs. We have created the Protein Identifier Cross-Reference (PICR) service, a web application that provides interactive and programmatic (SOAP and REST) access to a mapping algorithm that uses the UniProt Archive (UniParc) as a data warehouse to offer protein cross-references based on 100% sequence identity to proteins from over 70 distinct source databases loaded into UniParc. Mappings can be limited by source database, taxonomic ID and activity status in the source database. Users can copy/paste or upload files containing protein identifiers or sequences in FASTA format to obtain mappings using the interactive interface. Search results can be viewed in simple or detailed HTML tables or downloaded as comma-separated values (CSV) or Microsoft Excel (XLS) files suitable for use in a local database or a spreadsheet. Alternatively, a SOAP interface is available to integrate PICR functionality in other applications, as is a lightweight REST interface. We offer a publicly available service that can interactively map protein identifiers and protein sequences to the majority of commonly used protein databases. Programmatic access is available through a standards-compliant SOAP interface or a lightweight REST interface. The PICR interface, documentation and code examples are available at

The Protein Identifier Cross-Referencing (PICR) service: reconciling protein identifiers across multiple source databases

PubMed Central

Côté, Richard G; Jones, Philip; Martens, Lennart; Kerrien, Samuel; Reisinger, Florian; Lin, Quan; Leinonen, Rasko; Apweiler, Rolf; Hermjakob, Henning

2007-01-01

Background Each major protein database uses its own conventions when assigning protein identifiers. Resolving the various, potentially unstable, identifiers that refer to identical proteins is a major challenge. This is a common problem when attempting to unify datasets that have been annotated with proteins from multiple data sources or querying data providers with one flavour of protein identifiers when the source database uses another. Partial solutions for protein identifier mapping exist but they are limited to specific species or techniques and to a very small number of databases. As a result, we have not found a solution that is generic enough and broad enough in mapping scope to suit our needs. Results We have created the Protein Identifier Cross-Reference (PICR) service, a web application that provides interactive and programmatic (SOAP and REST) access to a mapping algorithm that uses the UniProt Archive (UniParc) as a data warehouse to offer protein cross-references based on 100% sequence identity to proteins from over 70 distinct source databases loaded into UniParc. Mappings can be limited by source database, taxonomic ID and activity status in the source database. Users can copy/paste or upload files containing protein identifiers or sequences in FASTA format to obtain mappings using the interactive interface. Search results can be viewed in simple or detailed HTML tables or downloaded as comma-separated values (CSV) or Microsoft Excel (XLS) files suitable for use in a local database or a spreadsheet. Alternatively, a SOAP interface is available to integrate PICR functionality in other applications, as is a lightweight REST interface. Conclusion We offer a publicly available service that can interactively map protein identifiers and protein sequences to the majority of commonly used protein databases. Programmatic access is available through a standards-compliant SOAP interface or a lightweight REST interface. The PICR interface, documentation and

Proteomic profiling for plasma biomarkers of tuberculosis progression.

PubMed

Liu, Qiuyue; Pan, Liping; Han, Fen; Luo, Baojian; Jia, Hongyan; Xing, Aiying; Li, Qi; Zhang, Zongde

2018-06-05

Severe pulmonary tuberculosis (STB) is a life‑threatening condition with high economic and social burden. The present study aimed to screen for distinct proteins in different stages of TB and identify biomarkers for a better understanding of TB progression and pathogenesis. Blood samples were obtained from 81 patients with STB, 80 with mild TB (MTB) and 50 healthy controls. Differentially expressed proteins were identified using liquid chromatography‑tandem mass spectrometry‑based label‑free quantitative proteomic analysis. Functional and pathway enrichment analyses were performed for the identified proteins. The expression of potential biomarkers was further validated by western blot analysis and enzyme‑linked immunosorbent assays. The accuracy, sensitivity and specificity for selected protein biomarkers in diagnosing STB were also evaluated. A total of 1,011 proteins were identified in all three groups, and 153 differentially expressed proteins were identified in patients with STB. These proteins were involved in 'cellular process', 'response to stimulus', 'apoptotic process', 'immune system process' and 'select metabolic process'. Significant differences in protein expression were detected in α‑1‑acid glycoprotein 2 (ORM2), interleukin‑36α (IL‑36α), S100 calcium binding protein A9 (S100‑A9), superoxide dismutase (SOD)1 in the STB group, compared with the MTB and control groups. The combination of plasma ORM2, IL‑36α, S100A9 and SOD1 levels achieved 90.00% sensitivity and 92.16% specificity to discriminate between patients with STB and MTB, and 89.66% sensitivity and 98.9% specificity to discriminate between patients with STB and healthy controls. ORM2, S100A9, IL‑36α and SOD1 were associated with the development of TB, and have the potential to distinguish between different stages of TB. Differential protein expression during disease progression may improve the current understanding of STB pathogenesis.

Is myelin basic protein a potential biomarker of brain cancer?

PubMed

Zavialova, M G; Shevchenko, V E; Nikolaev, E N; Zgoda, V G

2017-08-01

Myelin basic protein is a potential biomarker for the central nervous system diseases in which the myelin sheath is destroyed. Using pseudo-selected reaction monitoring and the method of standard additions, we have measured the myelin basic protein level in the cerebrospinal fluid of patients with neurotrauma (n = 6), chronic neurodegenerative diseases (n = 2) and brain cancer (n = 5). Myelin basic protein was detected only in four out of five cerebrospinal fluid samples of patients with brain cancer. The cerebrospinal fluid myelin basic protein level ranged from 3.7 to 8.8 ng ml -1 . We suggest that monitoring of myelin basic protein in cerebrospinal fluid can serve as a diagnostic test for the brain cancer.

Oncofetal protein IMP3, a new cancer biomarker.

PubMed

Gong, Yuna; Woda, Bruce A; Jiang, Zhong

2014-05-01

IMP3 is a member of a family of RNA-binding proteins that consists of IMP1, IMP2 and IMP3. These proteins contain 2 RNA recognition motifs and 4 K-homology domains that allow them to bind RNAs strongly and specifically. IMP3 is an oncofetal protein involved in embryogenesis and its expression is associated with a number of malignant neoplasms. IMP3 is associated with aggressive and advanced cancers and is specifically expressed in malignant tumors but is not found in adjacent benign tissues. Moreover, in vitro studies have shown that IMP3 promotes tumor cell proliferation, adhesion, and invasion. This review focuses on the studies of IMP3 expression in different cancers and emphasizes the potential utility of IMP3 in routine surgical pathology practice. We also discuss IMP3 as a prognostic biomarker for cancer patients' outcomes.

Fn3 proteins engineered to recognize tumor biomarker mesothelin internalize upon binding

PubMed Central

Sirois, Allison R.; Deny, Daniela A.; Baierl, Samantha R.; George, Katia S.

2018-01-01

Mesothelin is a cell surface protein that is overexpressed in numerous cancers, including breast, ovarian, lung, liver, and pancreatic tumors. Aberrant expression of mesothelin has been shown to promote tumor progression and metastasis through interaction with established tumor biomarker CA125. Therefore, molecules that specifically bind to mesothelin have potential therapeutic and diagnostic applications. However, no mesothelin-targeting molecules are currently approved for routine clinical use. While antibodies that target mesothelin are in development, some clinical applications may require a targeting molecule with an alternative protein fold. For example, non-antibody proteins are more suitable for molecular imaging and may facilitate diverse chemical conjugation strategies to create drug delivery complexes. In this work, we engineered variants of the fibronectin type III domain (Fn3) non-antibody protein scaffold to bind to mesothelin with high affinity, using directed evolution and yeast surface display. Lead engineered Fn3 variants were solubly produced and purified from bacterial culture at high yield. Upon specific binding to mesothelin on human cancer cell lines, the engineered Fn3 proteins internalized and co-localized to early endosomes. To our knowledge, this is the first report of non-antibody proteins engineered to bind mesothelin. The results validate that non-antibody proteins can be engineered to bind to tumor biomarker mesothelin, and encourage the continued development of engineered variants for applications such as targeted diagnostics and therapeutics. PMID:29738555

Advances in multiplexed MRM-based protein biomarker quantitation toward clinical utility.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Hardie, Darryl B; Borchers, Christoph H

2014-05-01

Accurate and rapid protein quantitation is essential for screening biomarkers for disease stratification and monitoring, and to validate the hundreds of putative markers in human biofluids, including blood plasma. An analytical method that utilizes stable isotope-labeled standard (SIS) peptides and selected/multiple reaction monitoring-mass spectrometry (SRM/MRM-MS) has emerged as a promising technique for determining protein concentrations. This targeted approach has analytical merit, but its true potential (in terms of sensitivity and multiplexing) has yet to be realized. Described herein is a method that extends the multiplexing ability of the MRM method to enable the quantitation 142 high-to-moderate abundance proteins (from 31mg/mL to 44ng/mL) in undepleted and non-enriched human plasma in a single run. The proteins have been reported to be associated to a wide variety of non-communicable diseases (NCDs), from cardiovascular disease (CVD) to diabetes. The concentrations of these proteins in human plasma are inferred from interference-free peptides functioning as molecular surrogates (2 peptides per protein, on average). A revised data analysis strategy, involving the linear regression equation of normal control plasma, has been instituted to enable the facile application to patient samples, as demonstrated in separate nutrigenomics and CVD studies. The exceptional robustness of the LC/MS platform and the quantitative method, as well as its high throughput, makes the assay suitable for application to patient samples for the verification of a condensed or complete protein panel. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. © 2013.

Identifying Exosome-Derived MicroRNAs as Candidate Biomarkers of Frailty.

PubMed

Ipson, B R; Fletcher, M B; Espinoza, S E; Fisher, A L

2018-01-01

Frailty is a geriatric syndrome associated with progressive physical decline and significantly increases risk for falls, disability, hospitalizations, and death. However, much remains unknown regarding the biological mechanisms that contribute to aging and frailty, and to date, there are no clinically used prognostic or diagnostic molecular biomarkers. The present study profiled exosome-derived microRNAs isolated from the plasma of young, robust older, and frail older individuals and identified eight miRNAs that are uniquely enriched in frailty: miR-10a-3p, miR-92a-3p, miR-185-3p, miR-194-5p, miR-326, miR-532-5p, miR-576-5p, and miR-760. Furthermore, since exosomes can deliver miRNAs to alter cellular activity and behavior, these miRNAs may also provide insights into the biological mechanisms underlying frailty; KEGG analysis of their target genes revealed multiple pathways implicated in aging and age-related processes. Although further validation and research studies are warranted, our study identified eight novel candidate biomarkers of frailty that may help to elucidate the multifactorial pathogenesis of frailty.

A Proteomics View of the Molecular Mechanisms and Biomarkers of Glaucomatous Neurodegeneration

PubMed Central

Tezel, Gülgün

2013-01-01

Despite improving understanding of glaucoma, key molecular players of neurodegeneration that can be targeted for treatment of glaucoma, or molecular biomarkers that can be useful for clinical testing, remain unclear. Proteomics technology offers a powerful toolbox to accomplish these important goals of the glaucoma research and is increasingly being applied to identify molecular mechanisms and biomarkers of glaucoma. Recent studies of glaucoma using proteomics analysis techniques have resulted in the lists of differentially expressed proteins in human glaucoma and animal models. The global analysis of protein expression in glaucoma has been followed by cell-specific proteome analysis of retinal ganglion cells and astrocytes. The proteomics data have also guided targeted studies to identify post-translational modifications and protein-protein interactions during glaucomatous neurodegeneration. In addition, recent applications of proteomics have provided a number of potential biomarker candidates. Proteomics technology holds great promise to move glaucoma research forward toward new treatment strategies and biomarker discovery. By reviewing the major proteomics approaches and their applications in the field of glaucoma, this article highlights the power of proteomics in translational and clinical research related to glaucoma and also provides a framework for future research to functionally test the importance of specific molecular pathways and validate candidate biomarkers. PMID:23396249

Overlap of proteomics biomarkers between women with pre-eclampsia and PCOS: a systematic review and biomarker database integration

PubMed Central

Khan, Gulafshana Hafeez; Galazis, Nicolas; Docheva, Nikolina; Layfield, Robert; Atiomo, William

2015-01-01

STUDY QUESTION Do any proteomic biomarkers previously identified for pre-eclampsia (PE) overlap with those identified in women with polycystic ovary syndrome (PCOS). SUMMARY ANSWER Five previously identified proteomic biomarkers were found to be common in women with PE and PCOS when compared with controls. WHAT IS KNOWN ALREADY Various studies have indicated an association between PCOS and PE; however, the pathophysiological mechanisms supporting this association are not known. STUDY DESIGN, SIZE, DURATION A systematic review and update of our PCOS proteomic biomarker database was performed, along with a parallel review of PE biomarkers. The study included papers from 1980 to December 2013. PARTICIPANTS/MATERIALS, SETTING, METHODS In all the studies analysed, there were a total of 1423 patients and controls. The number of proteomic biomarkers that were catalogued for PE was 192. MAIN RESULTS AND THE ROLE OF CHANCE Five proteomic biomarkers were shown to be differentially expressed in women with PE and PCOS when compared with controls: transferrin, fibrinogen α, β and γ chain variants, kininogen-1, annexin 2 and peroxiredoxin 2. In PE, the biomarkers were identified in serum, plasma and placenta and in PCOS, the biomarkers were identified in serum, follicular fluid, and ovarian and omental biopsies. LIMITATIONS, REASONS FOR CAUTION The techniques employed to detect proteomics have limited ability in identifying proteins that are of low abundance, some of which may have a diagnostic potential. The sample sizes and number of biomarkers identified from these studies do not exclude the risk of false positives, a limitation of all biomarker studies. The biomarkers common to PE and PCOS were identified from proteomic analyses of different tissues. WIDER IMPLICATIONS OF THE FINDINGS This data amalgamation of the proteomic studies in PE and in PCOS, for the first time, discovered a panel of five biomarkers for PE which are common to women with PCOS, including transferrin

Adding biological meaning to human protein-protein interactions identified by yeast two-hybrid screenings: A guide through bioinformatics tools.

PubMed

Felgueiras, Juliana; Silva, Joana Vieira; Fardilha, Margarida

2018-01-16

"A man is known by the company he keeps" is a popular expression that perfectly fits proteins. A common approach to characterize the function of a target protein is to identify its interacting partners and thus infer its roles based on the known functions of the interactors. Protein-protein interaction networks (PPINs) have been created for several organisms, including humans, primarily as results of high-throughput screenings, such as yeast two-hybrid (Y2H). Their unequivocal use to understand events underlying human pathophysiology is promising in identifying genes and proteins associated with diseases. Therefore, numerous opportunities have emerged for PPINs as tools for clinical management of diseases: network-based disease classification systems, discovery of biomarkers and identification of therapeutic targets. Despite the great advantages of PPINs, their use is still unrecognised by several researchers who generate high-throughput data to generally characterize interactions in a certain model or to select an interaction to study in detail. We strongly believe that both approaches are not exclusive and that we can use PPINs as a complementary methodology and rich-source of information to the initial study proposal. Here, we suggest a pipeline to deal with Y2H results using bioinformatics tools freely available for academics. Yeast two-hybrid is widely-used to identify protein-protein interactions. Conventionally, the positive clones that result from a yeast two-hybrid screening are sequenced to identify the interactors of the protein of interest (also known as bait protein), and few interactions, thought as potentially relevant for the model in study, are selected for further validation using biochemical methods (e.g. co-immunoprecipitation and co-localization). The huge amount of data that is potentially lost during this conservative approach motivated us to write this tutorial-like review, so that researchers feel encouraged to take advantage of

Urinary metabolomics analysis identifies key biomarkers of different stages of nonalcoholic fatty liver disease

PubMed Central

Dong, Shu; Zhan, Zong-Ying; Cao, Hong-Yan; Wu, Chao; Bian, Yan-Qin; Li, Jian-Yuan; Cheng, Gen-Hong; Liu, Ping; Sun, Ming-Yu

2017-01-01

AIM To identify a panel of biomarkers that can distinguish between non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), and explore molecular mechanism involved in the process of developing NASH from NAFLD. METHODS Biomarkers may differ during stages of NAFLD. Urine and blood were obtained from non-diabetic subjects with NAFLD and steatosis, with normal liver function (n = 33), from patients with NASH, with abnormal liver function (n = 45), and from healthy age and sex-matched controls (n = 30). Samples were subjected to metabolomic analysis to identify potential non-invasive biomarkers. Differences in urinary metabolic profiles were analyzed using liquid chromatography tandem mass spectrometry with principal component analysis and partial least squares-discriminate analysis. RESULTS Compared with NAFLD patients, patients with NASH had abnormal liver function and high serum lipid concentrations. Urinary metabonomics found differences in 31 metabolites between these two groups, including differences in nucleic acids and amino acids. Pathway analysis based on overlapping metabolites showed that pathways of energy and amino acid metabolism, as well as the pentose phosphate pathway, were closely associated with pathological processes in NAFLD and NASH. CONCLUSION These findings suggested that a panel of biomarkers could distinguish between NAFLD and NASH, and could help to determine the molecular mechanism involved in the process of developing NASH from NAFLD. Urinary biomarkers may be diagnostic in these patients and could be used to assess responses to therapeutic interventions. PMID:28487615

Head-to-Head Comparison and Evaluation of 92 Plasma Protein Biomarkers for Early Detection of Colorectal Cancer in a True Screening Setting.

PubMed

Chen, Hongda; Zucknick, Manuela; Werner, Simone; Knebel, Phillip; Brenner, Hermann

2015-07-15

Novel noninvasive blood-based screening tests are strongly desirable for early detection of colorectal cancer. We aimed to conduct a head-to-head comparison of the diagnostic performance of 92 plasma-based tumor-associated protein biomarkers for early detection of colorectal cancer in a true screening setting. Among all available 35 carriers of colorectal cancer and a representative sample of 54 men and women free of colorectal neoplasms recruited in a cohort of screening colonoscopy participants in 2005-2012 (N = 5,516), the plasma levels of 92 protein biomarkers were measured. ROC analyses were conducted to evaluate the diagnostic performance. A multimarker algorithm was developed through the Lasso logistic regression model and validated in an independent validation set. The .632+ bootstrap method was used to adjust for the potential overestimation of diagnostic performance. Seventeen protein markers were identified to show statistically significant differences in plasma levels between colorectal cancer cases and controls. The adjusted area under the ROC curves (AUC) of these 17 individual markers ranged from 0.55 to 0.70. An eight-marker classifier was constructed that increased the adjusted AUC to 0.77 [95% confidence interval (CI), 0.59-0.91]. When validating this algorithm in an independent validation set, the AUC was 0.76 (95% CI, 0.65-0.85), and sensitivities at cutoff levels yielding 80% and 90% specificities were 65% (95% CI, 41-80%) and 44% (95% CI, 24-72%), respectively. The identified profile of protein biomarkers could contribute to the development of a powerful multimarker blood-based test for early detection of colorectal cancer. ©2015 American Association for Cancer Research.

Systematic approach identifies RHOA as a potential biomarker therapeutic target for Asian gastric cancer

PubMed Central

Jung, Hae Rim; Park, Hee Seo; Park, Sungjin; Ahn, Young Zoo; Huh, Iksoo; Balch, Curt; Ku, Ja-Lok; Powis, Garth; Park, Taesung; Jeong, Jin-Hyun; Kim, Yon Hui

2016-01-01

Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer “Big Data” has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors. To develop evidence-based precision medicine for heterogeneous cancers, we established a systematic approach to integrate transcriptomic and genomic data. Predicted signaling subpathways were then laboratory-validated both in vitro and in vivo, resulting in the identification of new candidate therapeutic targets. Here, we show: i) differences in RHOA expression patterns, and its pathway activity, between Asian and Caucasian GC tumors; ii) in vitro and in vivo perturbed RHOA expression inhibits GC cell growth in high RHOA-expressing cell lines; iii) inverse correlation between RHOA and RHOB expression; and iv) an innovative small molecule design strategy for RHOA inhibitors. In summary, RHOA, and its oncogenic signaling pathway, represent a strong biomarker-driven therapeutic target for Asian GC. This comprehensive strategy represents a promising approach for the development of “hit” compounds. PMID:27806312

Global transcriptome analysis of formalin-fixed prostate cancer specimens identifies biomarkers of disease recurrence.

PubMed

Long, Qi; Xu, Jianpeng; Osunkoya, Adeboye O; Sannigrahi, Soma; Johnson, Brent A; Zhou, Wei; Gillespie, Theresa; Park, Jong Y; Nam, Robert K; Sugar, Linda; Stanimirovic, Aleksandra; Seth, Arun K; Petros, John A; Moreno, Carlos S

2014-06-15

Prostate cancer remains the second leading cause of cancer death in American men and there is an unmet need for biomarkers to identify patients with aggressive disease. In an effort to identify biomarkers of recurrence, we performed global RNA sequencing on 106 formalin-fixed, paraffin-embedded prostatectomy samples from 100 patients at three independent sites, defining a 24-gene signature panel. The 24 genes in this panel function in cell-cycle progression, angiogenesis, hypoxia, apoptosis, PI3K signaling, steroid metabolism, translation, chromatin modification, and transcription. Sixteen genes have been associated with cancer, with five specifically associated with prostate cancer (BTG2, IGFBP3, SIRT1, MXI1, and FDPS). Validation was performed on an independent publicly available dataset of 140 patients, where the new signature panel outperformed markers published previously in terms of predicting biochemical recurrence. Our work also identified differences in gene expression between Gleason pattern 4 + 3 and 3 + 4 tumors, including several genes involved in the epithelial-to-mesenchymal transition and developmental pathways. Overall, this study defines a novel biomarker panel that has the potential to improve the clinical management of prostate cancer. ©2014 American Association for Cancer Research.

The Urine Proteome as a Biomarker of Radiation Injury

PubMed Central

Sharma, Mukut; Halligan, Brian D.; Wakim, Bassam T.; Savin, Virginia J.; Cohen, Eric P.; Moulder, John E.

2009-01-01

Terrorist attacks or nuclear accidents could expose large numbers of people to ionizing radiation, and early biomarkers of radiation injury would be critical for triage, treatment and follow-up of such individuals. However, no such biomarkers have yet been proven to exist. We tested the potential of high throughput proteomics to identify protein biomarkers of radiation injury after total body X-ray irradiation in a rat model. Subtle functional changes in the kidney are suggested by an increased glomerular permeability for macromolecules measured within 24 hours after TBI. Ultrastructural changes in glomerular podocytes include partial loss of the interdigitating organization of foot processes. Analysis of urine by LC-MS/MS and 2D-GE showed significant changes in the urine proteome within 24 hours after TBI. Tissue kallikrein 1-related peptidase, cysteine proteinase inhibitor cystatin C and oxidized histidine were found to be increased while a number of proteinase inhibitors including kallikrein-binding protein and albumin were found to be decreased post-irradiation. Thus, TBI causes immediately detectable changes in renal structure and function and in the urinary protein profile. This suggests that both systemic and renal changes are induced by radiation and it may be possible to identify a set of biomarkers unique to radiation injury. PMID:19746194

A reverse-phase protein microarray-based screen identifies host signaling dynamics upon Burkholderia spp. infection

PubMed Central

Chiang, Chih-Yuan; Uzoma, Ijeoma; Lane, Douglas J.; Memišević, Vesna; Alem, Farhang; Yao, Kuan; Kota, Krishna P.; Bavari, Sina; Wallqvist, Anders; Hakami, Ramin M.; Panchal, Rekha G.

2015-01-01

Burkholderia is a diverse genus of gram-negative bacteria that causes high mortality rate in humans, equines and cattle. The lack of effective therapeutic treatments poses serious public health threats. Developing insights toward host-Burkholderia spp. interaction is critical for understanding the pathogenesis of infection as well as identifying therapeutic targets for drug development. Reverse-phase protein microarray technology was previously proven to identify and characterize novel biomarkers and molecular signatures associated with infectious disease and cancer. In the present study, this technology was utilized to interrogate changes in host protein expression and phosphorylation events in macrophages infected with a collection of geographically diverse strains of Burkholderia spp. The expression or phosphorylation state of 25 proteins was altered during Burkholderia spp. infections of which eight proteins were selected for further characterization by immunoblotting. Increased phosphorylation of AMPK-α1, Src, and GSK3β suggested the importance of their roles in regulating Burkholderia spp. mediated innate immune response. Modulating the inflammatory response by perturbing their activities may provide therapeutic routes for future treatments. PMID:26284031

Inter-individual variation in expression: a missing link in biomarker biology?

PubMed

Little, Peter F R; Williams, Rohan B H; Wilkins, Marc R

2009-01-01

The past decade has seen an explosion of variation data demonstrating that diversity of both protein-coding sequences and of regulatory elements of protein-coding genes is common and of functional importance. In this article, we argue that genetic diversity can no longer be ignored in studies of human biology, even research projects without explicit genetic experimental design, and that this knowledge can, and must, inform research. By way of illustration, we focus on the potential role of genetic data in case-control studies to identify and validate cancer protein biomarkers. We argue that a consideration of genetics, in conjunction with proteomic biomarker discovery projects, should improve the proportion of biomarkers that can accurately classify patients.

Total Protein of Whole Saliva as a Biomarker of Anaerobic Threshold

ERIC Educational Resources Information Center

Bortolini, Miguel Junior Sordi; De Agostini, Guilherme Gularte; Reis, Ismair Teodoro; Lamounier, Romeu Paulo Martins Silva; Blumberg, Jeffrey B.; Espindola, Foued Salmen

2009-01-01

Saliva provides a convenient and noninvasive matrix for assessing specific physiological parameters, including some biomarkers of exercise. We investigated whether the total protein concentration of whole saliva (TPWS) would reflect the anaerobic threshold during an incremental exercise test. After a warm-up period, 13 nonsmoking men performed a…

BluePen Biomarkers LLC: integrated biomarker solutions

PubMed Central

Blair, Ian A; Mesaros, Clementina; Lilley, Patrick; Nunez, Matthew

2016-01-01

BluePen Biomarkers provides a unique comprehensive multi-omics biomarker discovery and validation platform. We can quantify, integrate and analyze genomics, proteomics, metabolomics and lipidomics biomarkers, alongside clinical data, demographics and other phenotypic data. A unique bio-inspired signal processing analytic approach is used that has the proven ability to identify biomarkers in a wide variety of diseases. The resulting biomarkers can be used for diagnosis, prognosis, mechanistic studies and predicting treatment response, in contexts from core research through clinical trials. BluePen Biomarkers provides an additional groundbreaking research goal: identifying surrogate biomarkers from different modalities. This not only provides new biological insights, but enables least invasive, least-cost tests that meet or exceed the predictive quality of current tests. PMID:28031971

A Systematic Review of the Diagnostic and Prognostic Value of Urinary Protein Biomarkers in Urothelial Bladder Cancer

PubMed Central

D’Costa, Jamie J.; Goldsmith, James C.; Wilson, Jayne S.; Bryan, Richard T.; Ward, Douglas G.

2016-01-01

For over 80 years, cystoscopy has remained the gold-standard for detecting tumours of the urinary bladder. Since bladder tumours have a tendency to recur and progress, many patients are subjected to repeated cystoscopies during long-term surveillance, with the procedure being both unpleasant for the patient and expensive for healthcare providers. The identification and validation of bladder tumour specific molecular markers in urine could enable tumour detection and reduce reliance on cystoscopy, and numerous classes of biomarkers have been studied. Proteins represent the most intensively studied class of biomolecule in this setting. As an aid to researchers searching for better urinary biomarkers, we report a comprehensive systematic review of the literature and a searchable database of proteins that have been investigated to date. Our objective was to classify these proteins as: 1) those with robustly characterised sensitivity and specificity for bladder cancer detection; 2) those that show potential but further investigation is required; 3) those unlikely to warrant further investigation; and 4) those investigated as prognostic markers. This work should help to prioritise certain biomarkers for rigorous validation, whilst preventing wasted effort on proteins that have shown no association whatsoever with the disease, or only modest biomarker performance despite large-scale efforts at validation. PMID:27500198

Using bacterial biomarkers to identify early indicators of cystic fibrosis pulmonary exacerbation onset

PubMed Central

Rogers, Geraint B; Hoffman, Lucas R; Johnson, Matt W; Mayer-Hamblett, Nicole; Schwarze, Jürgen; Carroll, Mary P; Bruce, Kenneth D

2011-01-01

Acute periods of pulmonary exacerbation are the single most important cause of morbidity in cystic fibrosis patients, and may be associated with a loss of lung function. Intervening prior to the onset of a substantially increased inflammatory response may limit the associated damage to the airways. While a number of biomarker assays based on inflammatory markers have been developed, providing useful and important measures of disease during these periods, such factors are typically only elevated once the process of exacerbation has been initiated. Identifying biomarkers that can predict the onset of pulmonary exacerbation at an early stage would provide an opportunity to intervene before the establishment of a substantial immune response, with major implications for the advancement of cystic fibrosis care. The precise triggers of pulmonary exacerbation remain to be determined; however, the majority of models relate to the activity of microbes present in the patient's lower airways of cystic fibrosis. Advances in diagnostic microbiology now allow for the examination of these complex systems at a level likely to identify factors on which biomarker assays can be based. In this article, we discuss key considerations in the design and testing of assays that could predict pulmonary exacerbations. PMID:21405970

Proximal tubule proteins are significantly elevated in bladder urine of patients with ureteropelvic junction obstruction and may represent novel biomarkers: A pilot study.

PubMed

Gerber, Claire; Harel, Miriam; Lynch, Miranda L; Herbst, Katherine W; Ferrer, Fernando A; Shapiro, Linda H

2016-04-01

Ureteropelvic junction obstruction (UPJO) is the major cause of hydronephrosis in children and may lead to renal injury and early renal dysfunction. However, diagnosis of the degree of obstruction and severity of renal injury relies on invasive and often inconclusive renal scans. Biomarkers from voided urine that detect early renal injury are highly desirable because of their noninvasive collection and their potential to assist in earlier and more reliable diagnosis of the severity of obstruction. Early in response to UPJO, increased intrarenal pressure directly impacts the proximal tubule brush border. We hypothesize that single-pass, apically expressed proximal tubule brush border proteins will be shed into the urine early and rapidly and will be reliable noninvasive urinary biomarkers, providing the tools for a more reliable stratification of UPJO patients. We performed a prospective cohort study at Connecticut Children's Medical Center. Bladder urine samples from 12 UPJO patients were obtained prior to surgical intervention. Control urine samples were collected from healthy pediatric patients presenting with primary nocturnal enuresis. We determined levels of NGAL, KIM-1 (previously identified biomarkers), CD10, CD13, and CD26 (potentially novel biomarkers) by ELISA in control and experimental urine samples. Urinary creatinine levels were used to normalize the urinary protein levels measured by ELISA. Each of the proximal tubule proteins outperformed the previously published biomarkers. No differences in urinary NGAL and KIM-1 levels were observed between control and obstructed patients (p = 0.932 and p = 0.799, respectively). However, levels of CD10, CD13, and CD26 were significantly higher in the voided urine of obstructed individuals when compared with controls (p = 0.002, p = 0.024, and p = 0.007, respectively) (Figure). Targeted identification of reliable, noninvasive biomarkers of renal injury is critical to aid in diagnosing patients at risk, guiding

Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer.

PubMed

Shukla, Hem D

2017-10-25

During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA), and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein-protein interaction, and pharmacogenomics

Alpha-fetoprotein, a fascinating protein and biomarker in neurology.

PubMed

Schieving, J H; de Vries, M; van Vugt, J M G; Weemaes, C; van Deuren, M; Nicolai, J; Wevers, R A; Willemsen, M A

2014-05-01

Alpha-fetoprotein (AFP) is present in fetal serum in concentrations up to 5,000,000 μg/l. After birth, AFP gene expression is turned down with a subsequent fall of the serum concentrations of this albumin-like protein to 'adult values' of circa 0.5-15 μg/l from the age of 2 years onwards. Irrespective of its assumed important functions, individuals with AFP deficiency appear fully healthy. The other way around, the presence of AFP in the circulation after the first years of life doesn't seem to harm, since individuals with 'hereditary persistence of AFP' are also without clinical abnormalities. During pregnancy, AFP (in maternal serum) has long been recognized as a marker for congenital anomalies of the fetus. Equally well known is AFP as biomarker for hepatocellular carcinoma and some other malignancies. There are at least four neurodegenerative disorders, all inherited as autosomal recessive traits and characterized by the presence of cerebellar ataxia, abnormal ocular movements, and neuropathy, for which an elevated concentration of serum AFP is an important diagnostic biomarker. The availability of a reliable biomarker is not only important during screening or diagnostic processes, but is also relevant for objective follow-up during (future) therapeutic interventions. Copyright © 2013. Published by Elsevier Ltd.

Acute diagnostic biomarkers for spinal cord injury: review of the literature and preliminary research report.

PubMed

Yokobori, Shoji; Zhang, Zhiqun; Moghieb, Ahmed; Mondello, Stefania; Gajavelli, Shyam; Dietrich, W Dalton; Bramlett, Helen; Hayes, Ronald L; Wang, Michael; Wang, Kevin K W; Bullock, M Ross

2015-05-01

Many efforts have been made to create new diagnostic technologies for use in the diagnosis of central nervous system injury. However, there is still no consensus for the use of biomarkers in clinical acute spinal cord injury (SCI). The aims of this review are (1) to evaluate the current status of neurochemical biomarkers and (2) to discuss their potential acute diagnostic role in SCI by reviewing the literature. PubMed (http://www.ncbi.nlm.nih.gov/pubmed) was searched up to 2012 to identify publications concerning diagnostic biomarkers in SCI. To support more knowledge, we also checked secondary references in the primarily retrieved literature. Neurofilaments, cleaved-Tau, microtubule-associated protein 2, myelin basic protein, neuron-specific enolase, S100β, and glial fibrillary acidic protein were identified as structural protein biomarkers in SCI by this review process. We could not find reports relating ubiquitin C-terminal hydrolase-L1 and α-II spectrin breakdown products, which are widely researched in other central nervous system injuries. Therefore, we present our preliminary data relating to these two biomarkers. Some of biomarkers showed promising results for SCI diagnosis and outcome prediction; however, there were unresolved issues relating to accuracy and their accessibility. Currently, there still are not many reports focused on diagnostic biomarkers in SCI. This fact warranted the need for greater efforts to innovate sensitive and reliable biomarkers for SCI. Copyright © 2015 Elsevier Inc. All rights reserved.

Novel heart failure biomarkers: why do we fail to exploit their potential?

PubMed

Piek, Arnold; Du, Weijie; de Boer, Rudolf A; Silljé, Herman H W

2018-06-01

Plasma biomarkers are useful tools in the diagnosis and prognosis of heart failure (HF). In the last decade, numerous studies have aimed to identify novel HF biomarkers that would provide superior and/or additional diagnostic, prognostic, or stratification utility. Although numerous biomarkers have been identified, their implementation in clinical practice has so far remained largely unsuccessful. Whereas cardiac-specific biomarkers, including natriuretic peptides (ANP and BNP) and high sensitivity troponins (hsTn), are widely used in clinical practice, other biomarkers have not yet proven their utility. Galectin-3 (Gal-3) and soluble suppression of tumorigenicity 2 (sST2) are the only novel HF biomarkers that are included in the ACC/AHA HF guidelines, but their clinical utility still needs to be demonstrated. In this review, we will describe natriuretic peptides, hsTn, and novel HF biomarkers, including Gal-3, sST2, human epididymis protein 4 (HE4), insulin-like growth factor-binding protein 7 (IGFBP-7), heart fatty acid-binding protein (H-FABP), soluble CD146 (sCD146), interleukin-6 (IL-6), growth differentiation factor 15 (GDF-15), procalcitonin (PCT), adrenomedullin (ADM), microRNAs (miRNAs), and metabolites like 5-oxoproline. We will discuss the biology of these HF biomarkers and conclude that most of them are markers of general pathological processes like fibrosis, cell death, and inflammation, and are not cardiac- or HF-specific. These characteristics explain to a large degree why it has been difficult to relate these biomarkers to a single disease. We propose that, in addition to clinical investigations, it will be pivotal to perform comprehensive preclinical biomarker investigations in animal models of HF in order to fully reveal the potential of these novel HF biomarkers.

Protein biomarkers distinguish between high- and low-risk pediatric acute lymphoblastic leukemia in a tissue specific manner

PubMed Central

2013-01-01

The current study evaluated the differential expression detected in the proteomic profiles of low risk- and high risk- ALL pediatric patients to characterize candidate biomarkers related to diagnosis, prognosis and patient targeted therapy. Bone marrow and peripheral blood plasma and cell lysates samples were obtained from pediatric patients with low- (LR) and high-risk (HR) ALL at diagnosis. As controls, non-leukemic pediatric patients were studied. Cytogenetic analysis was carried out by G- banding and interphase fluorescent in situ hybridization. Differential proteomic analysis was performed using two-dimensional gel electrophoresis and protein identification by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The differential expression of certain proteins was confirmed by Western blot analysis. The obtained data revealed that CLUS, CERU, APOE, APOA4, APOA1, GELS, S10A9, AMBP, ACTB, CATA and AFAM proteins play a significant role in leukemia prognosis, potentially serving as distinctive biomarkers for leukemia aggressiveness, or as suppressor proteins in HR-ALL cases. In addition, vitronectin and plasminogen probably contributed to leukemogenesis, whilst bicaudal D-related protein 1 could afford a significant biomarker for pediatric ALL therapeutics. PMID:23849470

Epitope presentation is an important determinant of the utility of antigens identified from protein arrays in the development of autoantibody diagnostic assays.

PubMed

Murphy, Mairead A; O'Connell, David J; O'Kane, Sara L; O'Brien, John K; O'Toole, Sharon; Martin, Cara; Sheils, Orla; O'Leary, John J; Cahill, Dolores J

2012-08-03

Autoantibodies represent an attractive biomarker for diagnostic assays principally due to the stability of immunoglobulin in patient serum facilitating measurement with conventional assays. Immune responses to tumorigenesis may facilitate detection of ovarian cancer in the early stages of the disease with identification of a panel of tumour specific autoantibodies. Despite the reporting of many tumour associated autoantibodies using arrays of tumour antigens, this has not led to the advance in diagnostic capability as rapidly as was initially expected. Here we examine the potential diagnostic utility of candidate autoantibody biomarkers identified via screening of serum samples on a high content human protein array from a unique cohort of early stage and late stage ovarian cancer patients. We analyse the performance of autoantibodies to the tumour suppressor protein p53 and the novel autoantigens alpha adducin and endosulfine alpha identified in our array screen. Each antigen has different performance characteristics using conventional ELISA format and Western blot immunoassay. The high attrition rate of promising autoantigens identified by array screening can in part be explained by the presentation of the epitope of the antigen in the subsequent method of validation and this study provides directions on maximising the potential of candidate biomarkers. This article is part of a Special Issue entitled: Translational Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.

Proteomic Profiling of Paraffin-Embedded Samples Identifies Metaplasia-Specific and Early-Stage Gastric Cancer Biomarkers

PubMed Central

Sousa, Josane F.; Ham, Amy-Joan L.; Whitwell, Corbin; Nam, Ki Taek; Lee, Hyuk-Joon; Yang, Han-Kwang; Kim, Woo Ho; Zhang, Bing; Li, Ming; LaFleur, Bonnie; Liebler, Daniel C.; Goldenring, James R.

2013-01-01

Early diagnosis and curative resection are the predominant factors associated with increased survival in patients with gastric cancer. However, most gastric cancer cases are still diagnosed at later stages. Since most pathologic specimens are archived as FFPE samples, the ability to use them to generate expression profiles can greatly improve cancer biomarker discovery. We sought to uncover new biomarkers for stomach preneoplastic metaplasias and neoplastic lesions by generating proteome profiles using FFPE samples. We combined peptide isoelectric focusing and liquid chromatography–tandem mass spectrometry analysis to generate proteomic profiles from FFPE samples of intestinal-type gastric cancer, metaplasia, and normal mucosa. The expression patterns of selected proteins were analyzed by immunostaining first in single tissue sections from normal stomach, metaplasia, and gastric cancer and later in larger tissue array cohorts. We detected 60 proteins up-regulated and 87 proteins down-regulated during the progression from normal mucosa to metaplasia to gastric cancer. Two of the up-regulated proteins, LTF and DMBT1, were validated as specific markers for spasmolytic polypeptide–expressing metaplasia and intestinal metaplasia, respectively. In cancers, significantly lower levels of DMBT1 or LTF correlated with more advanced disease and worse prognosis. Thus, proteomic profiling using FFPE samples has led to the identification of two novel markers for stomach metaplasias and gastric cancer prognosis. PMID:22944598

A data-analytic strategy for protein biomarker discovery: profiling of high-dimensional proteomic data for cancer detection.

PubMed

Yasui, Yutaka; Pepe, Margaret; Thompson, Mary Lou; Adam, Bao-Ling; Wright, George L; Qu, Yinsheng; Potter, John D; Winget, Marcy; Thornquist, Mark; Feng, Ziding

2003-07-01

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of 'signature' protein profiles specific to each pathologic state (e.g. normal vs. cancer) or differential profiles between experimental conditions (e.g. treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data-analytic strategy for discovering protein biomarkers based on such high-dimensional mass spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data-analytic strategy takes properties of the SELDI mass spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After this pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary

Biomarkers of Oxidative Stress Study V: Ozone exposure of rats and its effect on lipids, proteins and DNA in plasma and urine

PubMed Central

Kadiiska, Maria B.; Basu, Samar; Brot, Nathan; Cooper, Christopher; Csallany, A. Saari; Davies, Michael J.; George, Magdalene M.; Murray, Dennis M.; Roberts, L. Jackson; Shigenaga, Mark K.; Sohal, Rajindar S.; Stocker, Roland; Van Thiel, David H.; Wiswedel, Ingrid; Hatch, Gary E.; Mason, Ronald P.

2014-01-01

Ozone exposure effect on free radical-catalyzed oxidation products of lipids, proteins and DNA in the plasma and urine of rats was studied as a continuation of the international Biomarker of Oxidative Stress Study (BOSS) sponsored by NIEHS/NIH. The goal was to identify a biomarker for ozone-induced oxidative stress and to assess whether inconsistent results often reported in the literature might be due to the limitations of the available methods for measuring the various types of oxidative products. The time and dose-dependent effects of ozone exposure on rat plasma lipid hydroperoxides, malondialdehyde, F2-isoprostanes, protein carbonyls, methionine oxidation, tyrosine- and phenylalanine oxidation products, as well as urinary malondialdehyde and F2-isoprostanes were investigated with various techniques. The criterion used to recognize a marker in the model of ozone exposure was that a significant effect could be identified and measured in a biological fluid seen at both doses at more than one time point. No statistically significant differences between the experimental and control groups at either ozone dose and time point studied could be identified in this study. Tissue samples were not included. Despite all the work accomplished in the BOSS study of ozone, no available product of oxidation in biological fluid has yet met the required criteria of being a biomarker. The current negative findings as a consequence of ozone exposure are of great importance, because they document that in complex systems, as the present in vivo experiment, the assays used may not provide meaningful data of ozone oxidation, especially in human studies. PMID:23608465

Development of a sequential workflow based on LC-PRM for the verification of endometrial cancer protein biomarkers in uterine aspirate samples.

PubMed

Martinez-Garcia, Elena; Lesur, Antoine; Devis, Laura; Campos, Alexandre; Cabrera, Silvia; van Oostrum, Jan; Matias-Guiu, Xavier; Gil-Moreno, Antonio; Reventos, Jaume; Colas, Eva; Domon, Bruno

2016-08-16

About 30% of endometrial cancer (EC) patients are diagnosed at an advanced stage of the disease, which is associated with a drastic decrease in the 5-year survival rate. The identification of biomarkers in uterine aspirate samples, which are collected by a minimally invasive procedure, would improve early diagnosis of EC. We present a sequential workflow to select from a list of potential EC biomarkers, those which are the most promising to enter a validation study. After the elimination of confounding contributions by residual blood proteins, 52 potential biomarkers were analyzed in uterine aspirates from 20 EC patients and 18 non-EC controls by a high-resolution accurate mass spectrometer operated in parallel reaction monitoring mode. The differential abundance of 26 biomarkers was observed, and among them ten proteins showed a high sensitivity and specificity (AUC > 0.9). The study demonstrates that uterine aspirates are valuable samples for EC protein biomarkers screening. It also illustrates the importance of a biomarker verification phase to fill the gap between discovery and validation studies and highlights the benefits of high resolution mass spectrometry for this purpose. The proteins verified in this study have an increased likelihood to become a clinical assay after a subsequent validation phase.

Proteomics as a Tool for Biomarker Discovery

PubMed Central

Kohn, Elise C.; Azad, Nilofer; Annunziata, Christina; Dhamoon, Amit S.; Whiteley, Gordon

2007-01-01

Novel technologies are now being advanced for the purpose of identification and validation of new disease biomarkers. A reliable and useful clinical biomarker must a) come from a readily attainable source, such as blood or urine, b) have sufficient sensitivity to correctly identify affected individuals, c) have sufficient specificity to avoid incorrect labeling of unaffected persons, and d) result in a notable benefit for the patient through intervention, such as survival or life quality improvement. Despite these critical descriptors, the few available FDA-approved biomarkers for cancer do not completely fit this definition and their benefits are limited to a small number of cancers. Ovarian cancer exemplifies the need for a diagnostic biomarker of early stage disease. Symptoms are present but not specific to the disease, delaying diagnosis until an advanced and generally incurable stage in over 70% of affected women. As such, diagnostic intervention in the form of oopherectomy can be performed in the appropriate at-risk population if identified such as with a new accurate, sensitive, and specific biomarker. If early stage disease is identified, the requirement for survival and life quality improvement will be met. One of the new technologies applied to biomarker discovery is tour-de-force analysis of serum peptides and proteins. Optimization of mass spectrometry techniques coupled with advanced bioinformatics approaches has yielded informative biomarker signatures discriminating presence of cancer from unaffected in multiple studies from different groups. Validation and randomized outcome studies are needed to determine the true value of these new biomarkers in early diagnosis, and improved survival and quality of life. PMID:18057524

Peroxiredoxin I protein, a potential biomarker of hydronephrosis in fetal mice exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin.

PubMed

Liu, Mingxue; Liu, Jing; Liu, Xing; Wei, Guanghui

2014-06-01

In previous studies, we established an animal model of human congenital hydronephrosis with exposure of developing mice to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), but the etiopathogenesis is not entirely clear. The present study was to identify the changes that may be involved in the etiology at the protein level. C57BL/6J mice fetuses were treated with TCDD. Comparative proteomic analysis was adopted to identify the proteins associated with hydronephrosis induced by TCDD. Two-dimensional electrophoresis display revealed that 19 protein spots were differentially expressed in the upper urinary tract tissues in fetal mice after exposure to TCDD. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) identified 12 up-regulated proteins: peroxiredoxin I (Prx I), cadherin 6, gamma-actin, radixin, desmin, type II transforming growth factor-beta receptor, chromogranin B, serum albumin precursor, transferrin, hypothetical protein LOC70984, lipk protein, and zinc finger protein 336. Histochemical staining indicated that Prx I protein was positively expressed in the ureteric epithelium in the treated group, and not in the control group, which is consistent with MALDI-TOF-MS. Prx I protein may be a potential biomarker or responsive protein of hydronephrosis in fetal mice induced by TCDD. Copyright © 2013 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

Identifying disease-related subnetwork connectome biomarkers by sparse hypergraph learning.

PubMed

Zu, Chen; Gao, Yue; Munsell, Brent; Kim, Minjeong; Peng, Ziwen; Cohen, Jessica R; Zhang, Daoqiang; Wu, Guorong

2018-06-14

The functional brain network has gained increased attention in the neuroscience community because of its ability to reveal the underlying architecture of human brain. In general, majority work of functional network connectivity is built based on the correlations between discrete-time-series signals that link only two different brain regions. However, these simple region-to-region connectivity models do not capture complex connectivity patterns between three or more brain regions that form a connectivity subnetwork, or subnetwork for short. To overcome this current limitation, a hypergraph learning-based method is proposed to identify subnetwork differences between two different cohorts. To achieve our goal, a hypergraph is constructed, where each vertex represents a subject and also a hyperedge encodes a subnetwork with similar functional connectivity patterns between different subjects. Unlike previous learning-based methods, our approach is designed to jointly optimize the weights for all hyperedges such that the learned representation is in consensus with the distribution of phenotype data, i.e. clinical labels. In order to suppress the spurious subnetwork biomarkers, we further enforce a sparsity constraint on the hyperedge weights, where a larger hyperedge weight indicates the subnetwork with the capability of identifying the disorder condition. We apply our hypergraph learning-based method to identify subnetwork biomarkers in Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). A comprehensive quantitative and qualitative analysis is performed, and the results show that our approach can correctly classify ASD and ADHD subjects from normal controls with 87.65 and 65.08% accuracies, respectively.

A Proteomic Analysis of Eccrine Sweat: Implications for the Discovery of Schizophrenia Biomarker Proteins

PubMed Central

Raiszadeh, Michelle M.; Ross, Mark M.; Russo, Paul S.; Schaepper, Mary Ann H.; Zhou, Weidong; Deng, Jianghong; Ng, Daniel; Dickson, April; Dickson, Cindy; Strom, Monica; Osorio, Carolina; Soeprono, Thomas; Wulfkuhle, Julia D.; Kabbani, Nadine; Petricoin, Emanuel F.; Liotta, Lance A.; Kirsch, Wolff M.

2012-01-01

Liquid chromatography tandem mass spectrometry (LC-MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC-MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate, and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC-MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately two-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC-MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers. PMID:22256890

Utility of salivary biomarkers for demonstrating acute myocardial infarction.

PubMed

Miller, C S; Foley, J D; Floriano, P N; Christodoulides, N; Ebersole, J L; Campbell, C L; Bailey, A L; Rose, B G; Kinane, D F; Novak, M J; McDevitt, J T; Ding, X; Kryscio, R J

2014-07-01

The comparative utility of serum and saliva as diagnostic fluids for identifying biomarkers of acute myocardial infarction (AMI) was investigated. The goal was to determine if salivary biomarkers could facilitate a screening diagnosis of AMI, especially in cases of non-ST elevation MI (NSTEMI), since these cases are not readily identified by electrocardiogram (ECG). Serum and unstimulated whole saliva (UWS) collected from 92 AMI patients within 48 hours of chest pain onset and 105 asymptomatic healthy control individuals were assayed for 13 proteins relevant to cardiovascular disease, by Beadlyte technology (Luminex(®)) and enzyme immunoassays. Data were analyzed with concentration cut-points, ECG findings, logistic regression (LR) (adjusted for matching for age, gender, race, smoking, number of teeth, and oral health status), and classification and regression tree (CART) analysis. A sensitivity analysis was conducted by repetition of the CART analysis in 58 cases and 58 controls, each matched by age and gender. Serum biomarkers demonstrated AMI sensitivity and specificity superior to that of saliva, as determined by LR and CART. The predominant discriminators in serum by LR were troponin I (TnI), B-type natriuretic peptide (BNP), and creatine kinase-MB (CK-MB), and TnI and BNP by CART. In saliva, LR identified C-reactive protein (CRP) as the biomarker most predictive of AMI. A combination of smoking tobacco, UWS CRP, CK-MB, sCD40 ligand, gender, and number of teeth identified AMI in the CART decision trees. When ECG findings, salivary biomarkers, and confounders were included, AMI was predicted with 80.0% sensitivity and 100% specificity. These analyses support the potential utility of salivary biomarker measurements used with ECG for the identification of AMI. Thus, saliva-based tests may provide additional diagnostic screening information in the clinical course for patients suspected of having an AMI. © International & American Associations for Dental Research.

[Cellular microparticles, potential useful biomarkers in the identification of cerebrovascular accidents].

PubMed

Anglés-Cano, Eduardo; Vivien, Denis

2009-10-01

The clinical utility of biomarkers depends on their ability to identify high-risk individuals in order to establish preventive, diagnostic or therapeutic measures. Currently, no practical, rapid and sensitive test is available for the diagnosis of acute ischemic stroke. A number of soluble molecules have been identified that are merely associated to these cerebrovascular accidents. Despite this association not a single molecule has the characteristics of a true biomarker directly involved in the pathophysiology of ischemic stroke-none of them is organ-specific and may therefore be elevated in the context of medical comorbidities. When explored as a combination of biomarkers, e.g. matrix metalloproteinase 9, brain natriuretic protein, D-dimer, protein S100B, the question still remains whether serial biomarker analysis provides additional prognostic information. Even S100B, a glial activation protein, has a low specificity for acute ischemic stroke because it may originate from extracranial sources. Current knowledge from the field of cell-derived microparticles suggests that these membrane fragments may represent reliable biomarkers as they are cell-specific and are released early in the pathophysiological cascade of a disease. These microparticles can be found not only in the cerebrospinal fluid but also in tears and circulating blood in case of blood-brain barrier dysfunction. They represent a new challenge in stroke diagnosis and management.

Discovery and identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

PubMed Central

Shi, Linan; Zhang, Jun; Wu, Peng; Feng, Kai; Li, Jing; Xie, Zhensheng; Xue, Peng; Cai, Tanxi; Cui, Ziyou; Chen, Xiulan; Hou, Junjie; Zhang, Jianzhong; Yang, Fuquan

2009-01-01

Background Acute lymphoblastic leukemia (ALL) is a common form of cancer in children. Currently, bone marrow biopsy is used for diagnosis. Noninvasive biomarkers for the early diagnosis of pediatric ALL are urgently needed. The aim of this study was to discover potential protein biomarkers for pediatric ALL. Methods Ninety-four pediatric ALL patients and 84 controls were randomly divided into a "training" set (45 ALL patients, 34 healthy controls) and a test set (49 ALL patients, 30 healthy controls and 30 pediatric acute myeloid leukemia (AML) patients). Serum proteomic profiles were measured using surface-enhanced laser desorption/ionization-time-of-flight mass spectroscopy (SELDI-TOF-MS). A classification model was established by Biomarker Pattern Software (BPS). Candidate protein biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays. Results A total of 7 protein peaks (9290 m/z, 7769 m/z, 15110 m/z, 7564 m/z, 4469 m/z, 8937 m/z, 8137 m/z) were found with differential expression levels in the sera of pediatric ALL patients and controls using SELDI-TOF-MS and then analyzed by BPS to construct a classification model in the "training" set. The sensitivity and specificity of the model were found to be 91.8%, and 90.0%, respectively, in the test set. Two candidate protein peaks (7769 and 9290 m/z) were found to be down-regulated in ALL patients, where these were identified as platelet factor 4 (PF4) and pro-platelet basic protein precursor (PBP). Two other candidate protein peaks (8137 and 8937 m/z) were found up-regulated in the sera of ALL patients, and these were identified as fragments of the complement component 3a (C3a). Conclusion Platelet factor (PF4), connective tissue activating peptide III (CTAP-III) and two fragments of C3a may be potential protein biomarkers of pediatric ALL and used to distinguish pediatric ALL patients from healthy controls and pediatric AML patients. Further studies with additional

Genomic reprograming analysis of the Mesothelial to Mesenchymal Transition identifies biomarkers in peritoneal dialysis patients

PubMed Central

Ruiz-Carpio, Vicente; Sandoval, Pilar; Aguilera, Abelardo; Albar-Vizcaíno, Patricia; Perez-Lozano, María Luisa; González-Mateo, Guadalupe T.; Acuña-Ruiz, Adrián; García-Cantalejo, Jesús; Botías, Pedro; Bajo, María Auxiliadora; Selgas, Rafael; Sánchez-Tomero, José Antonio; Passlick-Deetjen, Jutta; Piecha, Dorothea; Büchel, Janine; Steppan, Sonja; López-Cabrera, Manuel

2017-01-01

Peritoneal dialysis (PD) is an effective renal replacement therapy, but a significant proportion of patients suffer PD-related complications, which limit the treatment duration. Mesothelial-to-mesenchymal transition (MMT) contributes to the PD-related peritoneal dysfunction. We analyzed the genetic reprograming of MMT to identify new biomarkers that may be tested in PD-patients. Microarray analysis revealed a partial overlapping between MMT induced in vitro and ex vivo in effluent-derived mesothelial cells, and that MMT is mainly a repression process being higher the number of genes that are down-regulated than those that are induced. Cellular morphology and number of altered genes showed that MMT ex vivo could be subdivided into two stages: early/epithelioid and advanced/non-epithelioid. RT-PCR array analysis demonstrated that a number of genes differentially expressed in effluent-derived non-epithelioid cells also showed significant differential expression when comparing standard versus low-GDP PD fluids. Thrombospondin-1 (TSP1), collagen-13 (COL13), vascular endothelial growth factor A (VEGFA), and gremlin-1 (GREM1) were measured in PD effluents, and except GREM1, showed significant differences between early and advanced stages of MMT, and their expression was associated with a high peritoneal transport status. The results establish a proof of concept about the feasibility of measuring MMT-associated secreted protein levels as potential biomarkers in PD. PMID:28327551

Identification of candidate diagnostic serum biomarkers for Kawasaki disease using proteomic analysis

PubMed Central

Kimura, Yayoi; Yanagimachi, Masakatsu; Ino, Yoko; Aketagawa, Mao; Matsuo, Michie; Okayama, Akiko; Shimizu, Hiroyuki; Oba, Kunihiro; Morioka, Ichiro; Imagawa, Tomoyuki; Kaneko, Tetsuji; Yokota, Shumpei; Hirano, Hisashi; Mori, Masaaki

2017-01-01

Kawasaki disease (KD) is a systemic vasculitis and childhood febrile disease that can lead to cardiovascular complications. The diagnosis of KD depends on its clinical features, and thus it is sometimes difficult to make a definitive diagnosis. In order to identify diagnostic serum biomarkers for KD, we explored serum KD-related proteins, which differentially expressed during the acute and recovery phases of two patients by mass spectrometry (MS). We identified a total of 1,879 proteins by MS-based proteomic analysis. The levels of three of these proteins, namely lipopolysaccharide-binding protein (LBP), leucine-rich alpha-2-glycoprotein (LRG1), and angiotensinogen (AGT), were higher in acute phase patients. In contrast, the level of retinol-binding protein 4 (RBP4) was decreased. To confirm the usefulness of these proteins as biomarkers, we analyzed a total of 270 samples, including those collected from 55 patients with acute phase KD, by using western blot analysis and microarray enzyme-linked immunosorbent assays (ELISAs). Over the course of this experiment, we determined that the expression level of these proteins changes specifically in the acute phase of KD, rather than the recovery phase of KD or other febrile illness. Thus, LRG1 could be used as biomarkers to facilitate KD diagnosis based on clinical features. PMID:28262744

Combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancers.

PubMed

Cohen, Joshua D; Javed, Ammar A; Thoburn, Christopher; Wong, Fay; Tie, Jeanne; Gibbs, Peter; Schmidt, C Max; Yip-Schneider, Michele T; Allen, Peter J; Schattner, Mark; Brand, Randall E; Singhi, Aatur D; Petersen, Gloria M; Hong, Seung-Mo; Kim, Song Cheol; Falconi, Massimo; Doglioni, Claudio; Weiss, Matthew J; Ahuja, Nita; He, Jin; Makary, Martin A; Maitra, Anirban; Hanash, Samir M; Dal Molin, Marco; Wang, Yuxuan; Li, Lu; Ptak, Janine; Dobbyn, Lisa; Schaefer, Joy; Silliman, Natalie; Popoli, Maria; Goggins, Michael G; Hruban, Ralph H; Wolfgang, Christopher L; Klein, Alison P; Tomasetti, Cristian; Papadopoulos, Nickolas; Kinzler, Kenneth W; Vogelstein, Bert; Lennon, Anne Marie

2017-09-19

The earlier diagnosis of cancer is one of the keys to reducing cancer deaths in the future. Here we describe our efforts to develop a noninvasive blood test for the detection of pancreatic ductal adenocarcinoma. We combined blood tests for KRAS gene mutations with carefully thresholded protein biomarkers to determine whether the combination of these markers was superior to any single marker. The cohort tested included 221 patients with resectable pancreatic ductal adenocarcinomas and 182 control patients without known cancer. KRAS mutations were detected in the plasma of 66 patients (30%), and every mutation found in the plasma was identical to that subsequently found in the patient's primary tumor (100% concordance). The use of KRAS in conjunction with four thresholded protein biomarkers increased the sensitivity to 64%. Only one of the 182 plasma samples from the control cohort was positive for any of the DNA or protein biomarkers (99.5% specificity). This combinatorial approach may prove useful for the earlier detection of many cancer types.

Screening and identification of potential protein biomarkers for evaluating the efficacy of intensive therapy in pulmonary tuberculosis.

PubMed

Jiang, Ting-Ting; Shi, Li-Ying; Chen, Jing; Wei, Li-Liang; Li, Meng; Hu, Yu-Ting; Gan, Lin; Liu, Chang-Ming; Tu, Hui-Hui; Li, Zhi-Bin; Yi, Wen-Jing; Li, Ji-Cheng

2018-06-27

This research aimed to discover potential biomarkers for evaluating the therapeutic efficacy of intensive therapy in pulmonary tuberculosis (TB). Protein profiles in 2-months intensively treated TB patients, untreated TB patients, and healthy controls were investigated with iTRAQ-2DLC-MS/MS technique. 71 differential proteins were identified in 2-months intensively treated TB patients. Significant differences in complement component C7 (CO7), apolipoprotein A-IV (APOA4), apolipoprotein C-II (APOC2), and angiotensinogen (ANGT) were found by ELISA validation. CO7 and ANGT were also found significantly different in sputum negative patients, compared with sputum positive patients after intensive treatment. Clinical analysis showed that after 2-months intensive treatment several indicators were significantly changed, and the one-year cure rate of sputum negative patients were significantly higher than sputum positive patients. Diagnostic models consisting of APOC2, CO7 and APOA4 were established to distinguish intensively treated TB patients from untreated TB patients and healthy controls with the AUC value of 0.910 and 0.935. Meanwhile, ANGT and CO7 were combined to identify sputum negative and sputum positive TB patients after intensive treatment with 89.36% sensitivity, 71.43% specificity, and the AUC value of 0.853. The results showed that APOC2, CO7, APOA4, and ANGT may be potential biomarkers for evaluating the efficacy of intensive anti-TB therapy. Copyright © 2018. Published by Elsevier Inc.

Characterization of biomarkers in stroke based on ego-networks and pathways.

PubMed

Li, Haixia; Guo, Qianqian

2017-12-01

To explore potential biomarkers in stroke based on ego-networks and pathways. EgoNet method was applied to search for the underlying biomarkers in stroke using transcription profiling of E-GEOD-58294 and protein-protein interaction (PPI) data. Eight ego-genes were identified from PPI network according to the degree characteristics at the criteria of top 5% ranked z-sore and degree >1. Eight candidate ego-networks with classification accuracy ≥0.9 were selected. After performed randomization test, seven significant ego-networks with adjusted p value < 0.05 were identified. Pathway enrichment analysis was then conducted with these ego-networks to search for the significant pathways. Finally, two significant pathways were identified, and six of seven ego-networks were enriched to "3'-UTR-mediated translational regulation" pathway, indicating that this pathway performs an important role in the development of stroke. Seven ego-networks were constructed using EgoNet and two significant enriched by pathways were identified. These may provide new insights into the potential biomarkers for the development of stroke.

Cohort profile of BIOMArCS: the BIOMarker study to identify the Acute risk of a Coronary Syndrome—a prospective multicentre biomarker study conducted in the Netherlands

PubMed Central

Oemrawsingh, Rohit M; Akkerhuis, K Martijn; Umans, Victor A; Kietselaer, Bas; Schotborgh, Carl; Ronner, Eelko; Lenderink, Timo; Liem, Anho; Haitsma, David; van der Harst, Pim; Asselbergs, Folkert W; Maas, Arthur; Oude Ophuis, Anton J; Ilmer, Ben; Dijkgraaf, Rene; de Winter, Robbert-Jan; The, S Hong Kie; Wardeh, Alexander J; Hermans, Walter; Cramer, Etienne; van Schaik, Ron H; Hoefer, Imo E; Doevendans, Pieter A; Simoons, Maarten L; Boersma, Eric

2016-01-01

Purpose Progression of stable coronary artery disease (CAD) towards acute coronary syndrome (ACS) is a dynamic and heterogeneous process with many intertwined constituents, in which a plaque destabilising sequence could lead to ACS within short time frames. Current CAD risk assessment models, however, are not designed to identify increased vulnerability for the occurrence of coronary events within a precise, short time frame at the individual patient level. The BIOMarker study to identify the Acute risk of a Coronary Syndrome (BIOMArCS) was designed to evaluate whether repeated measurements of multiple biomarkers can predict such ‘vulnerable periods’. Participants BIOMArCS is a multicentre, prospective, observational study of 844 patients presenting with ACS, either with or without ST-elevation and at least one additional cardiovascular risk factor. Methods and analysis We hypothesised that patterns of circulating biomarkers that reflect the various pathophysiological components of CAD, such as distorted lipid metabolism, vascular inflammation, endothelial dysfunction, increased thrombogenicity and ischaemia, diverge in the days to weeks before a coronary event. Divergent biomarker patterns, identified by serial biomarker measurements during 1-year follow-up might then indicate ‘vulnerable periods’ during which patients with CAD are at high short-term risk of developing an ACS. Venepuncture was performed every fortnight during the first half-year and monthly thereafter. As prespecified, patient enrolment was terminated after the primary end point of cardiovascular death or hospital admission for non-fatal ACS had occurred in 50 patients. A case–cohort design will explore differences in temporal patterns of circulating biomarkers prior to the repeat ACS. Future plans and dissemination Follow-up and event adjudication have been completed. Prespecified biomarker analyses are currently being performed and dissemination through peer-reviewed publications and

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data

PubMed Central

2015-01-01

Background Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machine learning pipelines for omics data is feature selection, which is used to reduce the raw high-dimensional data into a tractable number of features. Feature selection needs to balance the objective of using as few features as possible, while maintaining high predictive power. This balance is crucial when the goal of data analysis is the identification of highly accurate but small panels of biomarkers with potential clinical utility. In this paper we propose a heuristic for the selection of very small feature subsets, via an iterative feature elimination process that is guided by rule-based machine learning, called RGIFE (Rule-guided Iterative Feature Elimination). We use this heuristic to identify putative biomarkers of osteoarthritis (OA), articular cartilage degradation and synovial inflammation, using both proteomic and transcriptomic datasets. Results and discussion Our RGIFE heuristic increased the classification accuracies achieved for all datasets when no feature selection is used, and performed well in a comparison with other feature selection methods. Using this method the datasets were reduced to a smaller number of genes or proteins, including those known to be relevant to OA, cartilage degradation and joint inflammation. The results have shown the RGIFE feature reduction method to be suitable for analysing both proteomic and transcriptomics data. Methods that generate large ‘omics’ datasets are increasingly being used in the area of rheumatology. Conclusions Feature reduction methods are advantageous for the analysis of omics data in the field of rheumatology, as the applications of such techniques are likely to result in improvements in diagnosis, treatment and drug discovery. PMID:25923811

Blood biomarkers for brain injury: What are we measuring?

PubMed Central

Kawata, Keisuke; Liu, Charles Y.; Merkel, Steven F.; Ramirez, Servio H.; Tierney, Ryan T.; Langford, Dianne

2016-01-01

Accurate diagnosis for mild traumatic brain injury (mTBI) remains challenging, as prognosis and return-to-play/work decisions are based largely on patient reports. Numerous investigations have identified and characterized cellular factors in the blood as potential biomarkers for TBI, in the hope that these factors may be used to gauge the severity of brain injury. None of these potential biomarkers have advanced to use in the clinical setting. Some of the most extensively studied blood biomarkers for TBI include S100β, neuron-specific enolase, glial fibrillary acidic protein, and Tau. Understanding the biological function of each of these factors may be imperative to achieve progress in the field. We address the basic question: what are we measuring? This review will discuss blood biomarkers in terms of cellular origin, normal and pathological function, and possible reasons for increased blood levels. Considerations in the selection, evaluation, and validation of potential biomarkers will also be addressed, along with mechanisms that allow brain-derived proteins to enter the bloodstream after TBI. Lastly, we will highlight perspectives and implications for repetitive neurotrauma in the field of blood biomarkers for brain injury. PMID:27181909

Comprehensive and integrative analysis identifies microRNA-106 as a novel non-invasive biomarker for detection of gastric cancer.

PubMed

Peng, Qiliang; Shen, Yi; Lin, Kaisu; Zou, Li; Shen, Yuntian; Zhu, Yaqun

2018-05-15

Recently, accumulating evidences have revealed that microRNA-106 (miR-106) may serve as a non-invasive and cost-effective biomarker in gastric cancer (GC) detection. However, inconsistent results have prevented its application to clinical practice. As a result of this, a comprehensive meta-analysis was conducted to evaluate the diagnostic performance of miR-106 alone and miR-106-related combination markers for GC detection. Meanwhile, an integrative bioinformatics analysis was performed to explore the function of miR-106 at the systems biology level. The results in our work showed that sensitivity of 0.71 (95% CI 0.65-0.76) and specificity of 0.82 (0.72-0.88), with the under area AUC (area under the curve) value of 0.80 (0.76-0.83) for miR-106 alone. Prospectively, miR-106-related combination markers improved the combined sensitivity, specificity and AUC, describing the discriminatory ability of 0.78 (0.65-0.87), 0.83 (0.77-0.89) and 0.88 (0.85-0.90) in the present analysis. Furthermore, targets of miR-106 were obtained and enriched by gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, revealing their associations with the occurrence and development of GC. Hub genes and significant modules were identified from the protein-protein interaction networks constructed by miR-106 targets and found closely associated with the initiation and progression of GC again. Our comprehensive and integrative analysis revealed that miR-106 may be suitable as a diagnostic biomarker for GC while microRNA combination biomarkers may provide a new alternative for clinical application. However, it is necessary to conduct large-scale population-based studies and biological experiments to further investigate the diagnostic value of miR-106.

Protein Biomarkers of Periodontitis in Saliva

PubMed Central

Taylor, John J.

2014-01-01

Periodontitis is a chronic inflammatory condition of the tissues that surround and support the teeth and is initiated by inappropriate and excessive immune responses to bacteria in subgingival dental plaque leading to loss of the integrity of the periodontium, compromised tooth function, and eventually tooth loss. Periodontitis is an economically important disease as it is time-consuming and expensive to treat. Periodontitis has a worldwide prevalence of 5–15% and the prevalence of severe disease in western populations has increased in recent decades. Furthermore, periodontitis is more common in smokers, in obesity, in people with diabetes, and in heart disease patients although the pathogenic processes underpinning these links are, as yet, poorly understood. Diagnosis and monitoring of periodontitis rely on traditional clinical examinations which are inadequate to predict patient susceptibility, disease activity, and response to treatment. Studies of the immunopathogenesis of periodontitis and analysis of mediators in saliva have allowed the identification of many potentially useful biomarkers. Convenient measurement of these biomarkers using chairside analytical devices could form the basis for diagnostic tests which will aid the clinician and the patient in periodontitis management; this review will summarise this field and will identify the experimental, technical, and clinical issues that remain to be addressed before such tests can be implemented. PMID:24944840

Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery

PubMed Central

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N.; Carter, Jeff; Dalby, Andrew B.; Eaton, Bruce E.; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R.; Kim, Nancy; Koch, Tad H.; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K.; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M.; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I.; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D.; Vrkljan, Mike; Walker, Jeffrey J.; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K.; Wolfson, Alexey; Wolk, Steven K.; Zhang, Chi; Zichi, Dom

2010-01-01

Background The interrogation of proteomes (“proteomics”) in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. Methodology/Principal Findings We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (∼100 fM–1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. Conclusions/Significance We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of

Aptamer-based multiplexed proteomic technology for biomarker discovery.

PubMed

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

2010-12-07

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study.

PubMed

Larkin, S E T; Johnston, H E; Jackson, T R; Jamieson, D G; Roumeliotis, T I; Mockridge, C I; Michael, A; Manousopoulou, A; Papachristou, E K; Brown, M D; Clarke, N W; Pandha, H; Aukim-Hastie, C L; Cragg, M S; Garbis, S D; Townsend, P A

2016-10-25

Prostate cancer (PCa) is the most common male cancer in the United Kingdom and we aimed to identify clinically relevant biomarkers corresponding to stage progression of the disease. We used enhanced proteomic profiling of PCa progression using iTRAQ 3D LC mass spectrometry on high-quality serum samples to identify biomarkers of PCa. We identified >1000 proteins. Following specific inclusion/exclusion criteria we targeted seven proteins of which two were validated by ELISA and six potentially interacted forming an 'interactome' with only a single protein linking each marker. This network also includes accepted cancer markers, such as TNF, STAT3, NF-κB and IL6. Our linked and interrelated biomarker network highlights the potential utility of six of our seven markers as a panel for diagnosing PCa and, critically, in determining the stage of the disease. Our validation analysis of the MS-identified proteins found that SAA alongside KLK3 may improve categorisation of PCa than by KLK3 alone, and that TSR1, although not significant in this model, might also be a clinically relevant biomarker.

Potential biomarkers in psychiatry: focus on the cholesterol system

PubMed Central

Woods, Alisa G; Sokolowska, Izabela; Taurines, Regina; Gerlach, Manfred; Dudley, Edward; Thome, Johannes; Darie, Costel C

2012-01-01

Abstract Measuring biomarkers to identify and assess illness is a strategy growing in popularity and relevance. Although already in clinical use for treating and predicting cancer, no biological measurement is used clinically for any psychiatric disorder. Biomarkers could predict the course of a medical problem, and aid in determining how and when to treat. Several studies have indicated that of candidate psychiatric biomarkers detected using proteomic techniques, cholesterol and associated proteins, specifically apolipoproteins (Apos), may be of interest. Cholesterol is necessary for brain development and its synthesis continues at a lower rate in the adult brain. Apos are the protein component of lipoproteins responsible for lipid transport. There is extensive evidence that the levels of cholesterol and Apos may be disturbed in psychiatric disorders, including autistic spectrum disorders (ASD). Here, we describe putative serum biomarkers for psychiatric disorders, and the role of cholesterol and Apos in central nervous system (CNS) disorders. PMID:22304330

Computational systems biology analysis of biomarkers in lung cancer; unravelling genomic regions which frequently encode biomarkers, enriched pathways, and new candidates.

PubMed

Alanazi, Ibrahim O; AlYahya, Sami A; Ebrahimie, Esmaeil; Mohammadi-Dehcheshmeh, Manijeh

2018-06-15

Exponentially growing scientific knowledge in scientific publications has resulted in the emergence of a new interdisciplinary science of literature mining. In text mining, the machine reads the published literature and transfers the discovered knowledge to mathematical-like formulas. In an integrative approach in this study, we used text mining in combination with network discovery, pathway analysis, and enrichment analysis of genomic regions for better understanding of biomarkers in lung cancer. Particular attention was paid to non-coding biomarkers. In total, 60 MicroRNA biomarkers were reported for lung cancer, including some prognostic biomarkers. MIR21, MIR155, MALAT1, and MIR31 were the top non-coding RNA biomarkers of lung cancer. Text mining identified 447 proteins which have been studied as biomarkers in lung cancer. EGFR (receptor), TP53 (transcription factor), KRAS, CDKN2A, ENO2, KRT19, RASSF1, GRP (ligand), SHOX2 (transcription factor), and ERBB2 (receptor) were the most studied proteins. Within small molecules, thymosin-a1, oestrogen, and 8-OHdG have received more attention. We found some chromosomal bands, such as 7q32.2, 18q12.1, 6p12, 11p15.5, and 3p21.3 that are highly involved in deriving lung cancer biomarkers. Copyright © 2018 Elsevier B.V. All rights reserved.

An update on the LIM and SH3 domain protein 1 (LASP1): a versatile structural, signaling, and biomarker protein

PubMed Central

Orth, Martin F.; Cazes, Alex; Butt, Elke; Grunewald, Thomas G. P.

2015-01-01

The gene encoding the LIM and SH3 domain protein (LASP1) was cloned two decades ago from a cDNA library of breast cancer metastases. As the first protein of a class comprising one N-terminal LIM and one C-terminal SH3 domain, LASP1 founded a new LIM-protein subfamily of the nebulin group. Since its discovery LASP1 proved to be an extremely versatile protein because of its exceptional structure allowing interaction with various binding partners, its ubiquitous expression in normal tissues, albeit with distinct expression patterns, and its ability to transmit signals from the cytoplasm into the nucleus. As a result, LASP1 plays key roles in cell structure, physiological processes, and cell signaling. Furthermore, LASP1 overexpression contributes to cancer aggressiveness hinting to a potential value of LASP1 as a cancer biomarker. In this review we summarize published data on structure, regulation, function, and expression pattern of LASP1, with a focus on its role in human cancer and as a biomarker protein. In addition, we provide a comprehensive transcriptome analysis of published microarrays (n=2,780) that illustrates the expression profile of LASP1 in normal tissues and its overexpression in a broad range of human cancer entities. PMID:25622104

High Mobility Group Box 1 Protein as an Auxiliary Biomarker for Dengue Diagnosis

PubMed Central

Allonso, Diego; Vázquez, Susana; Guzmán, Maria G.; Mohana-Borges, Ronaldo

2013-01-01

Despite the availability of many methods for rapid and early diagnosis of dengue, there is still a need to develop new approaches that not only combine low cost, specificity, and sensitivity, but also are capable of accurately detecting secondary infection in the early stages of the disease. We report the potential of the high mobility group box 1 protein as an auxiliary biomarker for early dengue diagnosis. We tested a 205-sample serum panel that included negative and positive samples from primary and secondary dengue cases, as well as samples from patients with dengue-like symptoms. We observed that high mobility group box 1 protein was generally detected only in dengue-positive samples for persons with primary and secondary infections. These results highlight the possibility of using this endogenous molecule as an auxiliary biomarker to aid in dengue detection and improve current methods for early diagnosis of dengue. PMID:23269659

Overcoming biofluid protein complexity during targeted mass spectrometry detection and quantification of protein biomarkers by MRM cubed (MRM3).

PubMed

Jeudy, Jeremy; Salvador, Arnaud; Simon, Romain; Jaffuel, Aurore; Fonbonne, Catherine; Léonard, Jean-François; Gautier, Jean-Charles; Pasquier, Olivier; Lemoine, Jerome

2014-02-01

Targeted mass spectrometry in the so-called multiple reaction monitoring mode (MRM) is certainly a promising way for the precise, accurate, and multiplexed measurement of proteins and their genetic or posttranslationally modified isoforms. MRM carried out on a low-resolution triple quadrupole instrument faces a lack of specificity when addressing the quantification of weakly concentrated proteins. In this case, extensive sample fractionation or immunoenrichment alleviates signal contamination by interferences, but in turn decreases assay performance and throughput. Recently, MRM(3) was introduced as an alternative to MRM to improve the limit of quantification of weakly concentrated protein biomarkers. In the present work, we compare MRM and MRM(3) modes for the detection of biomarkers in plasma and urine. Calibration curves drawn with MRM and MRM(3) showed a similar range of linearity (R(2) > 0.99 for both methods) with protein concentrations above 1 μg/mL in plasma and a few nanogram per milliliter in urine. In contrast, optimized MRM(3) methods improve the limits of quantification by a factor of 2 to 4 depending on the targeted peptide. This gain arises from the additional MS(3) fragmentation step, which significantly removes or decreases interfering signals within the targeted transition channels.

Biomarkers of oxidative stress study V: ozone exposure of rats and its effect on lipids, proteins, and DNA in plasma and urine.

PubMed

Kadiiska, Maria B; Basu, Samar; Brot, Nathan; Cooper, Christopher; Saari Csallany, A; Davies, Michael J; George, Magdalene M; Murray, Dennis M; Jackson Roberts, L; Shigenaga, Mark K; Sohal, Rajindar S; Stocker, Roland; Van Thiel, David H; Wiswedel, Ingrid; Hatch, Gary E; Mason, Ronald P

2013-08-01

Ozone exposure effect on free radical-catalyzed oxidation products of lipids, proteins, and DNA in the plasma and urine of rats was studied as a continuation of the international Biomarker of Oxidative Stress Study (BOSS) sponsored by NIEHS/NIH. The goal was to identify a biomarker for ozone-induced oxidative stress and to assess whether inconsistent results often reported in the literature might be due to the limitations of the available methods for measuring the various types of oxidative products. The time- and dose-dependent effects of ozone exposure on rat plasma lipid hydroperoxides, malondialdehyde, F2-isoprostanes, protein carbonyls, methionine oxidation, and tyrosine- and phenylalanine oxidation products, as well as urinary malondialdehyde and F2-isoprostanes were investigated with various techniques. The criterion used to recognize a marker in the model of ozone exposure was that a significant effect could be identified and measured in a biological fluid seen at both doses at more than one time point. No statistically significant differences between the experimental and the control groups at either ozone dose and time point studied could be identified in this study. Tissue samples were not included. Despite all the work accomplished in the BOSS study of ozone, no available product of oxidation in biological fluid has yet met the required criteria of being a biomarker. The current negative findings as a consequence of ozone exposure are of great importance, because they document that in complex systems, as the present in vivo experiment, the assays used may not provide meaningful data of ozone oxidation, especially in human studies. Published by Elsevier Inc.

Monocyte Chemotactic Protein 1 in Plasma from Soluble Leishmania Antigen-Stimulated Whole Blood as a Potential Biomarker of the Cellular Immune Response to Leishmania infantum

PubMed Central

Ibarra-Meneses, Ana V.; Sanchez, Carmen; Alvar, Jorge; Moreno, Javier; Carrillo, Eugenia

2017-01-01

New biomarkers are needed to identify asymptomatic Leishmania infection as well as immunity following vaccination or treatment. With the aim of finding a robust biomarker to assess an effective cellular immune response, monocyte chemotactic protein 1 (MCP-1) was examined in plasma from soluble Leishmania antigen (SLA)-stimulated whole blood collected from subjects living in a Leishmania infantum-endemic area. MCP-1, expressed 110 times more strongly than IL-2, identified 87.5% of asymptomatic subjects and verified some asymptomatic subjects close to the cutoff. MCP-1 was also significantly elevated in all patients cured of visceral leishmaniasis (VL), unlike IL-2, indicating the specific memory response generated against Leishmania. These results show MCP-1 to be a robust candidate biomarker of immunity that could be used as a marker of cure and to both select and follow the population in vaccine phase I–III human clinical trials with developed rapid, easy-to-use field tools. PMID:29033933

Design of a novel class of protein-based magnetic resonance imaging contrast agents for the molecular imaging of cancer biomarkers

PubMed Central

Xue, Shenghui; Qiao, Jingjuan; Pu, Fan; Cameron, Mathew; Yang, Jenny J.

2014-01-01

Magnetic resonance imaging (MRI) of disease biomarkers, especially cancer biomarkers, could potentially improve our understanding of the disease and drug activity during preclinical and clinical drug treatment and patient stratification. MRI contrast agents with high relaxivity and targeting capability to tumor biomarkers are highly required. Extensive work has been done to develop MRI contrast agents. However, only a few limited literatures report that protein residues can function as ligands to bind Gd3+ with high binding affinity, selectivity, and relaxivity. In this paper, we focus on reporting our current progress on designing a novel class of protein-based Gd3+ MRI contrast agents (ProCAs) equipped with several desirable capabilities for in vivo application of MRI of tumor biomarkers. We will first discuss our strategy for improving the relaxivity by a novel protein-based design. We then discuss the effect of increased relaxivity of ProCAs on improving the detection limits for MRI contrast agent, especially for in vivo application. We will further report our efforts to improve in vivo imaging capability and our achievement in molecular imaging of cancer biomarkers with potential preclinical and clinical applications. PMID:23335551

S100A12 and S100A8/9 proteins are biomarkers of articular disease activity in Blau syndrome.

PubMed

Wang, Lin; Rosé, Carlos D; Foley, Kevin P; Anton, Jordi; Bader-Meunier, Brigitte; Brissaud, Philippe; Chédeville, Gaelle; Cimaz, Rolando; Fernández-Martín, Jorge; Guly, Catherine; Hachulla, Eric; Harjacek, Miroslav; Mackensen, Friederike; Merino, Rosa; Modesto, Consuelo; Naranjo Hernández, Antonio; Pajot, Christine; Ramanan, Athimalaipet V; Thatayatikom, Akaluck; Thomée, Caroline; Vastert, Sebastiaan; Votta, Bart J; Bertin, John; Wouters, Carine H

2018-04-07

To identify biomarkers of articular and ocular disease activity in patients with Blau syndrome (BS). Multiplex plasma protein arrays were performed in five BS patients and eight normal healthy volunteers (NHVs). Plasma S100A12 and S100A8/9 were subsequently measured by ELISA at baseline and 1-year follow-up in all patients from a prospective multicentre cohort study. CRP was measured using Meso Scale Discovery immunoassay. Active joint counts, standardization uveitis nomenclature for anterior uveitis cells and vitreous haze by Nussenblatt scale were the clinical parameters. Multiplex Luminex arrays identified S100A12 as the most significantly elevated protein in five selected BS vs eight NHVs and this was confirmed by ELISA on additional samples from the same five BS patients. In the patient cohort, S100A12 (n = 39) and S100A8/9 (n = 33) were significantly higher compared with NHVs (n = 44 for S100A12, n = 40 for S100A8/9) (P = 0.0000004 and P = 0.0003, respectively). Positive correlations between active joint counts and S100 levels were significant for S100A12 (P = 0.0008) and S100A8/9 (P = 0.015). CRP levels did not correlate with active joint count. Subgroup analysis showed significant association of S100 proteins with active arthritis (S100A12 P = 0.01, S100A8/9 P = 0.008). Active uveitis was not associated with increased S100 levels. S100 proteins are biomarkers of articular disease activity in BS and potential outcome measures in future clinical trials. As secreted neutrophil and macrophage products, S100 proteins may reflect the burden of granulomatous tissue in BS.

Profiling signaling proteins in human spermatozoa: biomarker identification for sperm quality evaluation.

PubMed

Silva, Joana Vieira; Freitas, Maria João; Correia, Bárbara Regadas; Korrodi-Gregório, Luís; Patrício, António; Pelech, Steven; Fardilha, Margarida

2015-10-01

To determine the correlation between semen basic parameters and the expression and activity of signaling proteins. In vitro studies with human spermatozoa. Academic research institute. Thirty-seven men provided semen samples for routine analysis. None. Basic semen parameters tracked included sperm DNA fragmentation (SDF), the expression levels of 75 protein kinases, and the phosphorylation/cleavage patterns of 18 signaling proteins in human spermatozoa. The results indicated that the phosphorylated levels of several proteins (Bad, GSK-3β, HSP27, JNK/SAPK, mTOR, p38 MAPK, and p53), as well as cleavage of PARP (at D214) and Caspase-3 (at D175), were significantly correlated with motility parameters. Additionally, the percentage of morphologically normal spermatozoa demonstrated a significant positive correlation with the phosphorylated levels of p70 S6 kinase and, in turn, head defects and the teratozoospermia index (TZI) showed a significant negative correlation with the phosphorylated levels of Stat3. There was a significant positive correlation between SDF and the teratozoospermia index, as well as the presence of head defects. In contrast, SDF negatively correlated with the percentage of morphologically normal spermatozoa and the phosphorylation of Akt and p70 S6 kinase. Subjects with varicocele demonstrated a significant negative correlation between head morphological defects and the phosphorylated levels of Akt, GSK3β, p38 MAPK, and Stat1. Additionally, 34 protein kinases were identified as expressed in their total protein levels in normozoospermic samples. This study contributed toward establishing a biomarker "fingerprint" to assess sperm quality on the basis of molecular parameters. Copyright © 2015 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Peptide and protein biomarkers for type 1 diabetes mellitus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Qibin; Metz, Thomas O.

A method for identifying persons with increased risk of developing type 1 diabetes mellitus, or having type I diabetes mellitus, utilizing selected biomarkers described herein either alone or in combination. The present disclosure allows for broad based, reliable, screening of large population bases. Also provided are arrays and kits that can be used to perform such methods.

Peptide and protein biomarkers for type 1 diabetes mellitus

DOEpatents

Zhang, Qibin; Metz, Thomas O.

2014-06-10

A method for identifying persons with increased risk of developing type 1 diabetes mellitus, or having type I diabetes mellitus, utilizing selected biomarkers described herein either alone or in combination. The present disclosure allows for broad based, reliable, screening of large population bases. Also provided are arrays and kits that can be used to perform such methods.

A putative OTU domain-containing protein 1 deubiquitinating enzyme is differentially expressed in thyroid cancer and identifies less-aggressive tumours

PubMed Central

Carneiro, A P; Reis, C F; Morari, E C; Maia, Y C P; Nascimento, R; Bonatto, J M C; de Souza, M A; Goulart, L R; Ward, L S

2014-01-01

Background: This study aimed to identify novel biomarkers for thyroid carcinoma diagnosis and prognosis. Methods: We have constructed a human single-chain variable fragment (scFv) antibody library that was selected against tumour thyroid cells using the BRASIL method (biopanning and rapid analysis of selective interactive ligands) and phage display technology. Results: One highly reactive clone, scFv-C1, with specific binding to papillary thyroid tumour proteins was confirmed by ELISA, which was further tested against a tissue microarray that comprised of 229 thyroid tissues, including: 110 carcinomas (38 papillary thyroid carcinomas (PTCs), 42 follicular carcinomas, 30 follicular variants of PTC), 18 normal thyroid tissues, 49 nodular goitres (NG) and 52 follicular adenomas. The scFv-C1 was able to distinguish carcinomas from benign lesions (P=0.0001) and reacted preferentially against T1 and T2 tumour stages (P=0.0108). We have further identified an OTU domain-containing protein 1, DUBA-7 deubiquitinating enzyme as the scFv-binding antigen using two-dimensional polyacrylamide gel electrophoresis and mass spectrometry. Conclusions: The strategy of screening and identifying a cell-surface-binding antibody against thyroid tissues was highly effective and resulted in a useful biomarker that recognises malignancy among thyroid nodules and may help identify lower-risk cases that can benefit from less-aggressive management. PMID:24937664

Combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancers

PubMed Central

Cohen, Joshua D.; Javed, Ammar A.; Thoburn, Christopher; Wong, Fay; Tie, Jeanne; Gibbs, Peter; Schmidt, C. Max; Yip-Schneider, Michele T.; Allen, Peter J.; Schattner, Mark; Brand, Randall E.; Singhi, Aatur D.; Petersen, Gloria M.; Hong, Seung-Mo; Kim, Song Cheol; Falconi, Massimo; Doglioni, Claudio; Weiss, Matthew J.; Ahuja, Nita; He, Jin; Makary, Martin A.; Maitra, Anirban; Hanash, Samir M.; Dal Molin, Marco; Wang, Yuxuan; Li, Lu; Ptak, Janine; Dobbyn, Lisa; Schaefer, Joy; Silliman, Natalie; Popoli, Maria; Goggins, Michael G.; Hruban, Ralph H.; Wolfgang, Christopher L.; Klein, Alison P.; Tomasetti, Cristian; Papadopoulos, Nickolas; Kinzler, Kenneth W.; Vogelstein, Bert; Lennon, Anne Marie

2017-01-01

The earlier diagnosis of cancer is one of the keys to reducing cancer deaths in the future. Here we describe our efforts to develop a noninvasive blood test for the detection of pancreatic ductal adenocarcinoma. We combined blood tests for KRAS gene mutations with carefully thresholded protein biomarkers to determine whether the combination of these markers was superior to any single marker. The cohort tested included 221 patients with resectable pancreatic ductal adenocarcinomas and 182 control patients without known cancer. KRAS mutations were detected in the plasma of 66 patients (30%), and every mutation found in the plasma was identical to that subsequently found in the patient’s primary tumor (100% concordance). The use of KRAS in conjunction with four thresholded protein biomarkers increased the sensitivity to 64%. Only one of the 182 plasma samples from the control cohort was positive for any of the DNA or protein biomarkers (99.5% specificity). This combinatorial approach may prove useful for the earlier detection of many cancer types. PMID:28874546

A systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.

PubMed

Yu, Chenggang; Boutté, Angela; Yu, Xueping; Dutta, Bhaskar; Feala, Jacob D; Schmid, Kara; Dave, Jitendra; Tawa, Gregory J; Wallqvist, Anders; Reifman, Jaques

2015-02-01

The multifactorial nature of traumatic brain injury (TBI), especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior, has confounded attempts to elucidate the pathology underlying the progression of TBI. Here, systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury. To this end, we performed a meta-analysis of four distinct high-throughput gene expression studies involving different animal models of TBI. By using canonical pathways and a large human protein-interaction network as a scaffold, we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies. At 24 hr after injury, the significantly activated molecular signatures were nonspecific to TBI, whereas the significantly suppressed molecular signatures were specific to the nervous system. In particular, we identified a suppressed subnetwork consisting of 58 highly interacting, coregulated proteins associated with synaptic function. We selected three proteins from this subnetwork, postsynaptic density protein 95, nitric oxide synthase 1, and disrupted in schizophrenia 1, and hypothesized that their abundance would be significantly reduced after TBI. In a penetrating ballistic-like brain injury rat model of severe TBI, Western blot analysis confirmed our hypothesis. In addition, our analysis recovered 12 previously identified protein biomarkers of TBI. The results suggest that systems biology may provide an efficient, high-yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI. © 2014 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Cohort profile of BIOMArCS: the BIOMarker study to identify the Acute risk of a Coronary Syndrome-a prospective multicentre biomarker study conducted in the Netherlands.

PubMed

Oemrawsingh, Rohit M; Akkerhuis, K Martijn; Umans, Victor A; Kietselaer, Bas; Schotborgh, Carl; Ronner, Eelko; Lenderink, Timo; Liem, Anho; Haitsma, David; van der Harst, Pim; Asselbergs, Folkert W; Maas, Arthur; Oude Ophuis, Anton J; Ilmer, Ben; Dijkgraaf, Rene; de Winter, Robbert-Jan; The, S Hong Kie; Wardeh, Alexander J; Hermans, Walter; Cramer, Etienne; van Schaik, Ron H; Hoefer, Imo E; Doevendans, Pieter A; Simoons, Maarten L; Boersma, Eric

2016-12-23

Progression of stable coronary artery disease (CAD) towards acute coronary syndrome (ACS) is a dynamic and heterogeneous process with many intertwined constituents, in which a plaque destabilising sequence could lead to ACS within short time frames. Current CAD risk assessment models, however, are not designed to identify increased vulnerability for the occurrence of coronary events within a precise, short time frame at the individual patient level. The BIOMarker study to identify the Acute risk of a Coronary Syndrome (BIOMArCS) was designed to evaluate whether repeated measurements of multiple biomarkers can predict such 'vulnerable periods'. BIOMArCS is a multicentre, prospective, observational study of 844 patients presenting with ACS, either with or without ST-elevation and at least one additional cardiovascular risk factor. We hypothesised that patterns of circulating biomarkers that reflect the various pathophysiological components of CAD, such as distorted lipid metabolism, vascular inflammation, endothelial dysfunction, increased thrombogenicity and ischaemia, diverge in the days to weeks before a coronary event. Divergent biomarker patterns, identified by serial biomarker measurements during 1-year follow-up might then indicate 'vulnerable periods' during which patients with CAD are at high short-term risk of developing an ACS. Venepuncture was performed every fortnight during the first half-year and monthly thereafter. As prespecified, patient enrolment was terminated after the primary end point of cardiovascular death or hospital admission for non-fatal ACS had occurred in 50 patients. A case-cohort design will explore differences in temporal patterns of circulating biomarkers prior to the repeat ACS. Follow-up and event adjudication have been completed. Prespecified biomarker analyses are currently being performed and dissemination through peer-reviewed publications and conference presentations is expected from the third quarter of 2016. Should

Deciphering metabonomics biomarkers-targets interactions for psoriasis vulgaris by network pharmacology.

PubMed

Gu, Jiangyong; Li, Li; Wang, Dongmei; Zhu, Wei; Han, Ling; Zhao, Ruizhi; Xu, Xiaojie; Lu, Chuanjian

2018-06-01

Psoriasis vulgaris is a chronic inflammatory and immune-mediated skin disease. 44 metabonomics biomarkers were identified by high-throughput liquid chromatography coupled to mass spectrometry in our previous work, but the roles of metabonomics biomarkers in the pathogenesis of psoriasis is unclear. The metabonomics biomarker-enzyme network was constructed. The key metabonomics biomarkers and enzymes were screened out by network analysis. The binding affinity between each metabonomics biomarker and target was calculated by molecular docking. A binding energy-weighted polypharmacological index was introduced to evaluate the importance of target-related pathways. Long-chain fatty acids, phospholipids, Estradiol and NADH were the most important metabonomics biomarkers. Most key enzymes belonged hydrolase, thioesterase and acyltransferase. Six proteins (TNF-alpha, MAPK3, iNOS, eNOS, COX2 and mTOR) were extensively involved in inflammatory reaction, immune response and cell proliferation, and might be drug targets for psoriasis. PI3K-Akt signaling pathway and five other pathways had close correlation with the pathogenesis of psoriasis and could deserve further research. The inflammatory reaction, immune response and cell proliferation are mainly involved in psoriasis. Network pharmacology provide a new insight into the relationships between metabonomics biomarkers and the pathogenesis of psoriasis. KEY MESSAGES   • Network pharmacology was adopted to identify key metabonomics biomarkers and enzymes.   • Six proteins were screened out as important drug targets for psoriasis.   • A binding energy-weighted polypharmacological index was introduced to evaluate the importance of target-related pathways.

Derivation and Validation of a Serum Biomarker Panel to Identify Infants With Acute Intracranial Hemorrhage.

PubMed

Berger, Rachel Pardes; Pak, Brian J; Kolesnikova, Mariya D; Fromkin, Janet; Saladino, Richard; Herman, Bruce E; Pierce, Mary Clyde; Englert, David; Smith, Paul T; Kochanek, Patrick M

2017-06-05

Abusive head trauma is the leading cause of death from physical abuse. Missing the diagnosis of abusive head trauma, particularly in its mild form, is common and contributes to increased morbidity and mortality. Serum biomarkers may have potential as quantitative point-of-care screening tools to alert physicians to the possibility of intracranial hemorrhage. To identify and validate a set of biomarkers that could be the basis of a multivariable model to identify intracranial hemorrhage in well-appearing infants using the Ziplex System. Binary logistic regression was used to develop a multivariable model incorporating 3 serum biomarkers (matrix metallopeptidase-9, neuron-specific enolase, and vascular cellular adhesion molecule-1) and 1 clinical variable (total hemoglobin). The model was then prospectively validated. Multiplex biomarker measurements were performed using Flow-Thru microarray technology on the Ziplex System, which has potential as a point-of-care system. The model was tested at 3 pediatric emergency departments in level I pediatric trauma centers (Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania; Primary Children's Hospital, Salt Lake City, Utah; and Lurie Children's Hospital, Chicago, Illinois) among well-appearing infants who presented for care owing to symptoms that placed them at increased risk of abusive head trauma. The study took place from November 2006 to April 2014 at Children's Hospital of Pittsburgh, June 2010 to August 2013 at Primary Children's Hospital, and January 2011 to August 2013 at Lurie Children's Hospital. A mathematical model that can predict acute intracranial hemorrhage in infants at increased risk of abusive head trauma. The multivariable model, Biomarkers for Infant Brain Injury Score, was applied prospectively to 599 patients. The mean (SD) age was 4.7 (3.1) months. Fifty-two percent were boys, 78% were white, and 8% were Hispanic. At a cutoff of 0.182, the model was 89

Non-invasive identification of protein biomarkers for early pregnancy diagnosis in the cheetah (Acinonyx jubatus).

PubMed

Koester, Diana C; Wildt, David E; Maly, Morgan; Comizzoli, Pierre; Crosier, Adrienne E

2017-01-01

Approximately 80% of cheetahs living in typical zoological collections never reproduce. In more than 60% of breedings, the female is confirmed to ovulate, but parturition fails to occur. It is unknown if these non-pregnant intervals of elevated progesterone (deemed luteal phases) are conception failures or a pregnancy terminating in embryonic/fetal loss. There have been recent advances in metabolic profiling and proteome analyses in many species with mass spectrometry used to identify 'biomarkers' and mechanisms indicative of specific physiological states (including pregnancy). Here, we hypothesized that protein expression in voided cheetah feces varied depending on pregnancy status. We: 1) identified the expansive protein profile present in fecal material of females; and 2) isolated proteins that may be candidates playing a role in early pregnancy establishment and diagnosis. Five hundred and seventy unique proteins were discovered among samples from pregnant (n = 8), non-pregnant, luteal phase (n = 5), and non-ovulatory control (n = 5) cheetahs. Four protein candidates were isolated that were significantly up-regulated and two were down-regulated in samples from pregnant compared to non-pregnant or control counterparts. One up-regulated candidate, immunoglobulin J chain (IGJ; an important component of the secretory immune system) was detected using a commercially available antibody via immunoblotting. Findings revealed that increased IGJ abundance could be used to detect pregnancy successfully in >80% of 23 assessed females within 4 weeks after mating. The discovery of a novel fecal pregnancy marker improves the ability to determine reproductive, especially gestational, status in cheetahs managed in an ex situ insurance and source population.

Proteoglycan 4 is a diagnostic biomarker for COPD.

PubMed

Lee, Kang-Yun; Chuang, Hsiao-Chi; Chen, Tzu-Tao; Liu, Wen-Te; Su, Chien-Ling; Feng, Po-Hao; Chiang, Ling-Ling; Bien, Mauo-Ying; Ho, Shu-Chuan

2015-01-01

The measurement of C-reactive protein (CRP) to confirm the stability of COPD has been reported. However, CRP is a systemic inflammatory biomarker that is related to many other diseases. The objective of this study is to discover a diagnostic biomarker for COPD. Sixty-one subjects with COPD and 15 healthy controls (10 healthy non-smokers and 5 smokers) were recruited for a 1-year follow-up study. Data regarding the 1-year acute exacerbation frequency and changes in lung function were collected. CRP and the identified biomarkers were assessed in the validation COPD cohort patients and healthy subjects. Receiver operating characteristic values of CRP and the identified biomarkers were determined. A validation COPD cohort was used to reexamine the identified biomarker. Correlation of the biomarker with 1-year lung function decline was determined. Proteoglycan 4 (PRG4) was identified as a biomarker in COPD. The serum concentrations of PRG4 in COPD Global initiative for chronic Obstructive Lung Disease (GOLD) stages 1+2 and 3+4 were 10.29 ng/mL and 13.20 ng/mL, respectively; 4.99 ng/mL for healthy controls (P<0.05); and 4.49 ng/mL for healthy smokers (P<0.05). PRG4 was more sensitive and specific than CRP for confirming COPD severity and acute exacerbation frequency. There was no correlation between CRP and PRG4 levels, and PRG4 was negatively correlated with the 1-year change in predicted forced vital capacity percent (R (2)=0.91, P=0.013). PRG4 may be a biomarker for identification of severity in COPD. It was related to the 1-year forced vital capacity decline in COPD patients.

Mass Spectrometry-based Assay for High Throughput and High Sensitivity Biomarker Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Xuejiang; Tang, Keqi

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers wouldmore » ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM

Morph-X-Select: Morphology-based tissue aptamer selection for ovarian cancer biomarker discovery

PubMed Central

Wang, Hongyu; Li, Xin; Volk, David E.; Lokesh, Ganesh L.-R.; Elizondo-Riojas, Miguel-Angel; Li, Li; Nick, Alpa M.; Sood, Anil K.; Rosenblatt, Kevin P.; Gorenstein, David G.

2016-01-01

High affinity aptamer-based biomarker discovery has the advantage of simultaneously discovering an aptamer affinity reagent and its target biomarker protein. Here, we demonstrate a morphology-based tissue aptamer selection method that enables us to use tissue sections from individual patients and identify high-affinity aptamers and their associated target proteins in a systematic and accurate way. We created a combinatorial DNA aptamer library that has been modified with thiophosphate substitutions of the phosphate ester backbone at selected 5′dA positions for enhanced nuclease resistance and targeting. Based on morphological assessment, we used image-directed laser microdissection (LMD) to dissect regions of interest bound with the thioaptamer (TA) library and further identified target proteins for the selected TAs. We have successfully identified and characterized the lead candidate TA, V5, as a vimentin-specific sequence that has shown specific binding to tumor vasculature of human ovarian tissue and human microvascular endothelial cells. This new Morph-X-Select method allows us to select high-affinity aptamers and their associated target proteins in a specific and accurate way, and could be used for personalized biomarker discovery to improve medical decision-making and to facilitate the development of targeted therapies to achieve more favorable outcomes. PMID:27839510

Development of a multi-biomarker disease activity test for rheumatoid arthritis.

PubMed

Centola, Michael; Cavet, Guy; Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A; Turner, Mary; Sutton, Chris; Smith, Dustin R; Haney, Douglas J; Chernoff, David; Hesterberg, Lyndal K; Carulli, John P; Taylor, Peter C; Shadick, Nancy A; Weinblatt, Michael E; Curtis, Jeffrey R

2013-01-01

Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. We followed a stepwise approach to

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD.

PubMed

Sun, Wei; Kechris, Katerina; Jacobson, Sean; Drummond, M Bradley; Hawkins, Gregory A; Yang, Jenny; Chen, Ting-Huei; Quibrera, Pedro Miguel; Anderson, Wayne; Barr, R Graham; Basta, Patricia V; Bleecker, Eugene R; Beaty, Terri; Casaburi, Richard; Castaldi, Peter; Cho, Michael H; Comellas, Alejandro; Crapo, James D; Criner, Gerard; Demeo, Dawn; Christenson, Stephanie A; Couper, David J; Curtis, Jeffrey L; Doerschuk, Claire M; Freeman, Christine M; Gouskova, Natalia A; Han, MeiLan K; Hanania, Nicola A; Hansel, Nadia N; Hersh, Craig P; Hoffman, Eric A; Kaner, Robert J; Kanner, Richard E; Kleerup, Eric C; Lutz, Sharon; Martinez, Fernando J; Meyers, Deborah A; Peters, Stephen P; Regan, Elizabeth A; Rennard, Stephen I; Scholand, Mary Beth; Silverman, Edwin K; Woodruff, Prescott G; O'Neal, Wanda K; Bowler, Russell P

2016-08-01

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p < 8 X 10-10) pQTLs in 38 (43%) of blood proteins tested. Most pQTL SNPs were novel with low overlap to eQTL SNPs. The pQTL SNPs explained >10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10-392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

PubMed Central

Drummond, M. Bradley; Hawkins, Gregory A.; Yang, Jenny; Chen, Ting-huei; Quibrera, Pedro Miguel; Anderson, Wayne; Barr, R. Graham; Bleecker, Eugene R.; Beaty, Terri; Casaburi, Richard; Castaldi, Peter; Cho, Michael H.; Comellas, Alejandro; Crapo, James D.; Criner, Gerard; Demeo, Dawn; Christenson, Stephanie A.; Couper, David J.; Doerschuk, Claire M.; Freeman, Christine M.; Gouskova, Natalia A.; Han, MeiLan K.; Hanania, Nicola A.; Hansel, Nadia N.; Hersh, Craig P.; Hoffman, Eric A.; Kaner, Robert J.; Kanner, Richard E.; Kleerup, Eric C.; Lutz, Sharon; Martinez, Fernando J.; Meyers, Deborah A.; Peters, Stephen P.; Regan, Elizabeth A.; Rennard, Stephen I.; Scholand, Mary Beth; Silverman, Edwin K.; Woodruff, Prescott G.; O’Neal, Wanda K.; Bowler, Russell P.

2016-01-01

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p < 8 X 10−10) pQTLs in 38 (43%) of blood proteins tested. Most pQTL SNPs were novel with low overlap to eQTL SNPs. The pQTL SNPs explained >10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In

Identification of novel diagnostic biomarkers for thyroid carcinoma.

PubMed

Wang, Xiliang; Zhang, Qing; Cai, Zhiming; Dai, Yifan; Mou, Lisha

2017-12-19

Thyroid carcinoma (THCA) is the most universal endocrine malignancy worldwide. Unfortunately, a limited number of large-scale analyses have been performed to identify biomarkers for THCA. Here, we conducted a meta-analysis using 505 THCA patients and 59 normal controls from The Cancer Genome Atlas. After identifying differentially expressed long non-coding RNA (lncRNA) and protein coding genes (PCG), we found vast difference in various lncRNA-PCG co-expressed pairs in THCA. A dysregulation network with scale-free topology was constructed. Four molecules (LA16c-380H5.2, RP11-203J24.8, MLF1 and SDC4) could potentially serve as diagnostic biomarkers of THCA with high sensitivity and specificity. We further represent a diagnostic panel with expression cutoff values. Our results demonstrate the potential application of those four molecules as novel independent biomarkers for THCA diagnosis.

Genome-Wide Association Analysis of Blood Biomarkers in Chronic Obstructive Pulmonary Disease

PubMed Central

Kim, Deog Kyeom; Cho, Michael H.; Hersh, Craig P.; Lomas, David A.; Miller, Bruce E.; Kong, Xiangyang; Bakke, Per; Gulsvik, Amund; Agustí, Alvar; Wouters, Emiel; Celli, Bartolome; Coxson, Harvey; Vestbo, Jørgen; MacNee, William; Yates, Julie C.; Rennard, Stephen; Litonjua, Augusto; Qiu, Weiliang; Beaty, Terri H.; Crapo, James D.; Riley, John H.; Tal-Singer, Ruth

2012-01-01

Rationale: A genome-wide association study (GWAS) for circulating chronic obstructive pulmonary disease (COPD) biomarkers could identify genetic determinants of biomarker levels and COPD susceptibility. Objectives: To identify genetic variants of circulating protein biomarkers and novel genetic determinants of COPD. Methods: GWAS was performed for two pneumoproteins, Clara cell secretory protein (CC16) and surfactant protein D (SP-D), and five systemic inflammatory markers (C-reactive protein, fibrinogen, IL-6, IL-8, and tumor necrosis factor-α) in 1,951 subjects with COPD. For genome-wide significant single nucleotide polymorphisms (SNPs) (P < 1 × 10−8), association with COPD susceptibility was tested in 2,939 cases with COPD and 1,380 smoking control subjects. The association of candidate SNPs with mRNA expression in induced sputum was also elucidated. Measurements and Main Results: Genome-wide significant susceptibility loci affecting biomarker levels were found only for the two pneumoproteins. Two discrete loci affecting CC16, one region near the CC16 coding gene (SCGB1A1) on chromosome 11 and another locus approximately 25 Mb away from SCGB1A1, were identified, whereas multiple SNPs on chromosomes 6 and 16, in addition to SNPs near SFTPD, had genome-wide significant associations with SP-D levels. Several SNPs affecting circulating CC16 levels were significantly associated with sputum mRNA expression of SCGB1A1 (P = 0.009–0.03). Several SNPs highly associated with CC16 or SP-D levels were nominally associated with COPD in a collaborative GWAS (P = 0.001–0.049), although these COPD associations were not replicated in two additional cohorts. Conclusions: Distant genetic loci and biomarker-coding genes affect circulating levels of COPD-related pneumoproteins. A subset of these protein quantitative trait loci may influence their gene expression in the lung and/or COPD susceptibility. Clinical trial registered with www.clinicaltrials.gov (NCT 00292552). PMID

Non-invasive detection of candidate pregnancy protein biomarkers in the feces of captive polar bears (Ursus maritimus).

PubMed

Curry, E; Stoops, M A; Roth, T L

2012-07-15

Currently, there is no method of accurately and non-invasively diagnosing pregnancy in polar bears. Specific proteins may exhibit altered profiles in the feces of pregnant bears, but predicting appropriate candidate proteins to investigate is speculative at best. The objective of this study was to identify potential pregnancy biomarker proteins based on their increased abundance in the feces of pregnant polar bears compared to pseudopregnant females (controls) using two-dimensional in-gel electrophoresis (2D-DIGE) and mass spectrometry (MS). Three 2D-DIGE gels were performed to evaluate fecal protein profiles from controls (n=3) and pregnant polar bears (n=3). There were 2224.67±52.39 (mean±SEM) spots resolved per gel. Of these, only five proteins were elevated in the pregnant group (P<0.05), and seven additional spots tended to be higher (0.0599.9% confidence interval. The 11 spots represented seven distinct proteins, five of which were significantly more abundant in the pregnant group: IgGFc-binding protein, filamin-C, carboxypeptidase B, transthyretin, and immunoglobulin heavy chain variable region. To our knowledge, this was the first study that employed 2D-DIGE to identify differentially expressed proteins in fecal samples to characterize a physiological condition other than those related to gastrointestinal disorders. These promising results provided a strong foundation for ensuing efforts to develop a non-invasive pregnancy assay for use in both captive and wild polar bears. Copyright © 2012 Elsevier Inc. All rights reserved.

Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents

DTIC Science & Technology

1997-11-01

status can sometimes be reflected in the infectious potential or drug resistance of those pathogens. For example, in Mycobacterium tuberculosis ... Mycobacterium tuberculosis , its antibiotic resistance and prediction of pathogenicity amongst Mycobacterium spp. based on signature lipid biomarkers ...TITLE AND SUBTITLE Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents 5a. CONTRACT NUMBER 5b

A standardized kit for automated quantitative assessment of candidate protein biomarkers in human plasma.

PubMed

Percy, Andrew J; Mohammed, Yassene; Yang, Juncong; Borchers, Christoph H

2015-12-01

An increasingly popular mass spectrometry-based quantitative approach for health-related research in the biomedical field involves the use of stable isotope-labeled standards (SIS) and multiple/selected reaction monitoring (MRM/SRM). To improve inter-laboratory precision and enable more widespread use of this 'absolute' quantitative technique in disease-biomarker assessment studies, methods must be standardized. Results/methodology: Using this MRM-with-SIS-peptide approach, we developed an automated method (encompassing sample preparation, processing and analysis) for quantifying 76 candidate protein markers (spanning >4 orders of magnitude in concentration) in neat human plasma. The assembled biomarker assessment kit - the 'BAK-76' - contains the essential materials (SIS mixes), methods (for acquisition and analysis), and tools (Qualis-SIS software) for performing biomarker discovery or verification studies in a rapid and standardized manner.

An integrated proteomics and metabolomics approach for defining oncofetal biomarkers in the colorectal cancer.

PubMed

Ma, Yanlei; Zhang, Peng; Wang, Feng; Liu, Weijie; Yang, Jianjun; Qin, Huanlong

2012-04-01

The present study was designed to search for potential diagnostic biomarkers in the serum of colorectal cancer (CRC). CRC is the third most common cancer worldwide, and its prognosis is poor at early stages. A panel of novel biomarkers is urgently needed for early diagnosis of CRC. An integrated proteomics and metabolomics approach was performed to define oncofetal biomarkers in CRC by protein and metabolite profiling of serum samples from CRC patients, healthy control adults, and fetus. The differentially expressed proteins were identified by a 2-D DIGE (2-Dimensional Difference Gel Electrophoresis) coupled with a Finnigan LTQ-based proteomics approach. Meanwhile, the serum metabolome was analyzed using gas chromatography-mass spectrometry integrated with a commercial mass spectral library for peak identification. Of the 28 identified proteins and the 34 analyzed metabolites, only 5 protein spots and 6 metabolites were significantly increased or decreased in both CRC and fetal serum groups compared with the healthy adult group. Data from supervised predictive models allowed a separation of 93.5% of CRC patients from the healthy controls using the 6 metabolites. Finally, correlation analysis was applied to establish quantitative linkages between the 5 individual metabolite 3-hydroxybutyric acid, L-valine, L-threonine, 1-deoxyglucose, and glycine and the 5 individual proteins MACF1, APOH, A2M, IGL@, and VDB. Furthermore, 10 potential oncofetal biomarkers were characterized and their potential for CRC diagnosis was validated. The integrated approach we developed will promote the translation of biomarkers with clinical value into routine clinical practice.

Sweetening the pot: adding glycosylation to the biomarker discovery equation.

PubMed

Drake, Penelope M; Cho, Wonryeon; Li, Bensheng; Prakobphol, Akraporn; Johansen, Eric; Anderson, N Leigh; Regnier, Fred E; Gibson, Bradford W; Fisher, Susan J

2010-02-01

Cancer has profound effects on gene expression, including a cell's glycosylation machinery. Thus, tumors produce glycoproteins that carry oligosaccharides with structures that are markedly different from the same protein produced by a normal cell. A single protein can have many glycosylation sites that greatly amplify the signals they generate compared with their protein backbones. In this article, we survey clinical tests that target carbohydrate modifications for diagnosing and treating cancer. We present the biological relevance of glycosylation to disease progression by highlighting the role these structures play in adhesion, signaling, and metastasis and then address current methodological approaches to biomarker discovery that capitalize on selectively capturing tumor-associated glycoforms to enrich and identify disease-related candidate analytes. Finally, we discuss emerging technologies--multiple reaction monitoring and lectin-antibody arrays--as potential tools for biomarker validation studies in pursuit of clinically useful tests. The future of carbohydrate-based biomarker studies has arrived. At all stages, from discovery through verification and deployment into clinics, glycosylation should be considered a primary readout or a way of increasing the sensitivity and specificity of protein-based analyses.

Analysis of 320 gastroenteropancreatic neuroendocrine tumors identifies TS expression as independent biomarker for survival.

PubMed

Lee, Hye Seung; Chen, Min; Kim, Ji Hun; Kim, Woo Ho; Ahn, Soyeon; Maeng, Kyungah; Allegra, Carmen J; Kaye, Frederic J; Hochwald, Steven N; Zajac-Kaye, Maria

2014-07-01

Thymidylate synthase (TS), a critical enzyme for DNA synthesis and repair, is both a potential tumor prognostic biomarker as well as a tumorigenic oncogene in animal models. We have now studied the clinical implications of TS expression in gastroenteropancreatic (GEP) neuroendocrine tumors (NETs) and compared these results to other cell cycle biomarker genes. Protein tissue arrays were used to study TS, Ki-67, Rb, pRb, E2F1, p18, p21, p27 and menin expression in 320 human GEP-NETs samples. Immunohistochemical expression was correlated with univariate and multivariate predictors of survival utilizing Kaplan Meier and Cox proportional hazards models. Real time RT-PCR was used to validate these findings. We found that 78 of 320 GEP-NETs (24.4%) expressed TS. NETs arising in the colon, stomach and pancreas showed the highest expression of TS (47.4%, 42.6% and 37.3%, respectively), whereas NETs of the appendix, rectum and duodenum displayed low TS expression (3.3%, 12.9% and 15.4%, respectively). TS expression in GEP-NETs was associated with poorly differentiated endocrine carcinoma, angiolymphatic invasion, lymph node metastasis and distant metastasis (p < 0.05). Patients with TS-positive NETs had markedly worse outcomes than TS-negative NETs as shown by univariate (p < 0.001) and multivariate (p = 0.01) survival analyses. Expression of p18 predicted survival in TS-positive patients that received chemotherapy (p = 0.015). In conclusion, TS protein expression was an independent prognostic biomarker for GEP-NETs. The strong association of increased TS expression with aggressive disease and early death supports the role of TS as a cancer promoting agent in these tumors. © 2013 UICC.

A new biomarker panel in bronchoalveolar lavage for an improved lung cancer diagnosis.

PubMed

Uribarri, María; Hormaeche, Itsaso; Zalacain, Rafael; Lopez-Vivanco, Guillermo; Martinez, Antonio; Nagore, Daniel; Ruiz-Argüello, M Begoña

2014-10-01

The enormous biological complexity and high mortality rate of lung cancer highlights the need for new global approaches for the discovery of reliable early diagnostic biomarkers. The study of bronchoalveolar lavage samples by proteomic techniques could identify new lung cancer biomarkers and may provide promising noninvasive diagnostic tools able to enhance the sensitivity of current methods. First, an observational prospective study was designed to assess protein expression differences in bronchoalveolar lavages from patients with (n = 139) and without (n = 49) lung cancer, using two-dimensional gel electrophoresis and subsequent protein identification by mass spectrometry. Second, validation of candidate biomarkers was performed by bead-based immunoassays with a different patient cohort (204 patients, 48 controls). Thirty-two differentially expressed proteins were identified in bronchoalveolar lavages, 10 of which were confirmed by immunoassays. The expression levels of APOA1, CO4A, CRP, GSTP1, and SAMP led to a lung cancer diagnostic panel that reached 95% sensitivity and 81% specificity, and the quantification of STMN1 and GSTP1 proteins allowed the two main lung cancer subtypes to be discriminated with 90% sensitivity and 57% specificity. Bronchoalveolar lavage represents a promising noninvasive source of lung cancer specific protein biomarkers with high diagnostic accuracy. Measurement of APOA1, CO4A, CRP, GSTP1, SAMP, and STMN1 in this fluid may be a useful tool for lung cancer diagnosis, although a further validation in a larger clinical set is required for early stages.

Analytical Pipeline for Discovery and Verification of Glycoproteins from Plasma-Derived Extracellular Vesicles as Breast Cancer Biomarkers.

PubMed

Chen, I-Hsuan; Aguilar, Hillary Andaluz; Paez Paez, J Sebastian; Wu, Xiaofeng; Pan, Li; Wendt, Michael K; Iliuk, Anton B; Zhang, Ying; Tao, W Andy

2018-05-15

Glycoproteins comprise more than half of current FDA-approved protein cancer markers, but the development of new glycoproteins as disease biomarkers has been stagnant. Here we present a pipeline to develop glycoproteins from extracellular vesicles (EVs) through integrating quantitative glycoproteomics with a novel reverse phase glycoprotein array and then apply it to identify novel biomarkers for breast cancer. EV glycoproteomics show promise in circumventing the problems plaguing current serum/plasma glycoproteomics and allowed us to identify hundreds of glycoproteins that have not been identified in blood. We identified 1,453 unique glycopeptides representing 556 glycoproteins in EVs, among which 20 were verified significantly higher in individual breast cancer patients. We further applied a novel glyco-specific reverse phase protein array to quantify a subset of the candidates. Together, this study demonstrates the great potential of this integrated pipeline for biomarker discovery.

Investigating the clinical potential for 14-3-3 zeta protein to serve as a biomarker for epithelial ovarian cancer

PubMed Central

2013-01-01

Objective Recently, 14-3-3 zeta protein was identified as a potential serum biomarker of epithelial ovarian cancer (EOC). The goal of this study was to investigate the clinical potential of 14-3-3 zeta protein for monitoring EOC progression compared with CA-125 and HE4. Design Prospective follow-up study. Setting University of Pecs Medical Center Department of Obstetrics and Gynecology/Oncology (Pecs, Hungary). Population Thirteen EOC patients with advanced stage (FIGO IIb-IIIc) epithelial ovarian cancer that underwent radical surgery and received six consecutive cycles of first line chemotherapy (paclitaxel, carboplatin) in 21-day intervals. Methods Pre- and post-chemotherapy computed tomography (CT) scans were performed. Serum levels of CA-125, HE4, and 14-3-3 zeta protein were detected by enzyme-linked immunosorbent assay (ELISA) and quantitative electrochemiluminescence assay (ECLIA). Main outcome measures Serum levels of CA-125, HE4, and 14-3-3 zeta protein, as well as lesion size according to pre- and post-chemotherapy CT scans. Results Serum levels of CA-125 and HE4 were found to significantly decrease following chemotherapy, and this was consistent with the decrease in lesion size detected post-chemotherapy. In contrast, 14-3-3 zeta protein levels did not significantly differ in healthy postmenopausal patients versus EOC patients. Conclusions Determination of CA-125 and HE4 serum levels for the determination of the risk of ovarian malignancy algorithm (ROMA) represents a useful tool for the prediction of chemotherapy efficacy for EOC patients. However, levels of 14-3-3 zeta protein were not found to vary significantly as a consequence of treatment. Therefore we question if 14-3-3 zeta protein is a reliable biomarker, which correlates with the clinical behavior of EOC. PMID:24238270

Progression Rate Associated Peripheral Blood Biomarkers of Parkinson's Disease.

PubMed

Fan, Yanxia; Xiao, Shuping

2018-06-23

Parkinson disease (PD) is one of the most frequent neurodegenerative disorders. The aim of this study was to identify blood biomarkers capable to discriminate PD patients with different progression rates. Differentially expressed genes (DEGs) were acquired by comparing the expression profiles of PD patients with rapid and slow progression rates, using an expression dataset from Gene Expression Omnibus (GEO) under accession code of GSE80599. Altered biological processes and pathways were revealed by functional annotation. Potential biomarkers of PD were identified by protein-protein interaction (PPI) network analysis. Critical transcription factors (TFs) and miRNAs regulating DEGs were predicted by TF analysis and miRNA analysis. A total of 225 DEGs were identified between PD patients with rapid and slow progression profiles. These genes were significantly enriched in biological processes and pathways related to fatty acid metabolism. Among these DEGs, ZFAND4, SRMS, UBL4B, PVALB, DIRAS1, PDP2, LRCH1, and MYL4 were potential progression rate associated biomarkers of PD. Additionally, these DEGs may be regulated by miRNAs of the miR-30 family and TFs STAT1 and GRHL3. Our results may contribute to our understanding of the molecular mechanisms underlying different PD progression profiles.

Increased liver-specific proteins in circulating extracellular vesicles as potential biomarkers for drug- and alcohol-induced liver injury

PubMed Central

Cho, Young-Eun; Im, Eun-Ju; Moon, Pyong-Gon; Mezey, Esteban; Song, Byoung-Joon; Baek, Moon-Chang

2017-01-01

Drug- and alcohol-induced liver injury are a leading cause of liver failure and transplantation. Emerging evidence suggests that extracellular vesicles (EVs) are a source of biomarkers because they contain unique proteins reflecting the identity and tissue-specific origin of the EV proteins. This study aimed to determine whether potentially hepatotoxic agents, such as acetaminophen (APAP) and binge alcohol, can increase the amounts of circulating EVs and evaluate liver-specific EV proteins as potential biomarkers for liver injury. The circulating EVs, isolated from plasma of APAP-exposed, ethanol-fed mice, or alcoholic hepatitis patients versus normal control counterparts, were characterized by proteomics and biochemical methods. Liver specific EV proteins were analyzed by immunoblots and ELISA. The amounts of total and liver-specific proteins in circulating EVs from APAP-treated mice significantly increased in a dose- and time-dependent manner. Proteomic analysis of EVs from APAP-exposed mice revealed that the amounts of liver-specific and/or hepatotoxic proteins were increased compared to those of controls. Additionally, the increased protein amounts in EVs following APAP exposure returned to basal levels when mice were treated with N-acetylcysteine or glutathione. Similar results of increased amounts and liver-specific proteins in circulating EVs were also observed in mice exposed to hepatotoxic doses of thioacetamide or d-galactosamine but not by non-hepatotoxic penicillin or myotoxic bupivacaine. Additionally, binge ethanol exposure significantly elevated liver-specific proteins in circulating EVs from mice and alcoholics with alcoholic hepatitis, compared to control counterparts. These results indicate that circulating EVs in drug- and alcohol-mediated hepatic injury contain liver-specific proteins that could serve as specific biomarkers for hepatotoxicity. PMID:28225807

Protocol for Standardizing High-to-Moderate Abundance Protein Biomarker Assessments Through an MRM-with-Standard-Peptides Quantitative Approach.

PubMed

Percy, Andrew J; Yang, Juncong; Chambers, Andrew G; Mohammed, Yassene; Miliotis, Tasso; Borchers, Christoph H

2016-01-01

Quantitative mass spectrometry (MS)-based approaches are emerging as a core technology for addressing health-related queries in systems biology and in the biomedical and clinical fields. In several 'omics disciplines (proteomics included), an approach centered on selected or multiple reaction monitoring (SRM or MRM)-MS with stable isotope-labeled standards (SIS), at the protein or peptide level, has emerged as the most precise technique for quantifying and screening putative analytes in biological samples. To enable the widespread use of MRM-based protein quantitation for disease biomarker assessment studies and its ultimate acceptance for clinical analysis, the technique must be standardized to facilitate precise and accurate protein quantitation. To that end, we have developed a number of kits for assessing method/platform performance, as well as for screening proposed candidate protein biomarkers in various human biofluids. Collectively, these kits utilize a bottom-up LC-MS methodology with SIS peptides as internal standards and quantify proteins using regression analysis of standard curves. This chapter details the methodology used to quantify 192 plasma proteins of high-to-moderate abundance (covers a 6 order of magnitude range from 31 mg/mL for albumin to 18 ng/mL for peroxidredoxin-2), and a 21-protein subset thereof. We also describe the application of this method to patient samples for biomarker discovery and verification studies. Additionally, we introduce our recently developed Qualis-SIS software, which is used to expedite the analysis and assessment of protein quantitation data in control and patient samples.

Circulating exosomes and exosomal microRNAs as biomarkers in gastrointestinal cancer.

PubMed

Nedaeinia, R; Manian, M; Jazayeri, M H; Ranjbar, M; Salehi, R; Sharifi, M; Mohaghegh, F; Goli, M; Jahednia, S H; Avan, A; Ghayour-Mobarhan, M

2017-02-01

The most important biological function of exosomes is their possible use as biomarkers in clinical diagnosis. Compared with biomarkers identified in conventional specimens such as serum or urine, exosomal biomarkers provide the highest amount of sensitivity and specificity, which can be attributed to their excellent stability. Exosomes, which harbor different types of proteins, nucleic acids and lipids, are present in almost all bodily fluids. The molecular constituents of exosomes, especially exosomal proteins and microRNAs (miRNAs), are promising as biomarkers in clinical diagnosis. This discovery that exosomes also contain messenger RNAs and miRNAs shows that they could be carriers of genetic information. Although the majority of RNAs found in exosomes are degraded RNA fragments with a length of <200 nucleotides, some full-length RNAs might be present that may affect protein production in the recipient cell. In addition, exosomal miRNAs have been found to be associated with certain diseases. Several studies have pointed out miRNA contents of circulating exosomes that are similar to those of originating cancer cells. In this review, the recent advances in circulating exosomal miRNAs as biomarkers in gastrointestinal cancers are discussed. These studies indicated that miRNAs can be detected in exosomes isolated from body fluids such as saliva, which suggests potential advantages of using exosomal miRNAs as noninvasive novel biomarkers.

Identification and localization of trauma-related biomarkers using matrix assisted laser desorption/ionization imaging mass spectrometry

NASA Astrophysics Data System (ADS)

Jones, Kirstin; Reilly, Matthew A.; Glickman, Randolph D.

2017-02-01

Current treatments for ocular and optic nerve trauma are largely ineffective and may have adverse side effects; therefore, new approaches are needed to understand trauma mechanisms. Identification of trauma-related biomarkers may yield insights into the molecular aspects of tissue trauma that can contribute to the development of better diagnostics and treatments. The conventional approach for protein biomarker measurement largely relies on immunoaffinity methods that typically can only be applied to analytes for which antibodies or other targeting means are available. Matrix assisted laser-assisted desorption/ionization imaging mass spectrometry (MALDI-IMS) is a specialized application of mass spectrometry that not only is well suited to the discovery of novel or unanticipated biomarkers, but also provides information about the spatial localization of biomarkers in tissue. We have been using MALDI-IMS to find traumarelated protein biomarkers in retina and optic nerve tissue from animal models subjected to ocular injury produced by either blast overpressure or mechanical torsion. Work to date by our group, using MALDI-IMS, found that the pattern of protein expression is modified in the injured ocular tissue as soon as 24 hr post-injury, compared to controls. Specific proteins may be up- or down-regulated by trauma, suggesting different tissue responses to a given injury. Ongoing work is directed at identifying the proteins affected and mapping their expression in the ocular tissue, anticipating that systematic analysis can be used to identify targets for prospective therapies for ocular trauma.

Identification of Tetranectin as a Potential Biomarker for Metastatic Oral Cancer

PubMed Central

Arellano-Garcia, Martha E.; Li, Roger; Liu, Xiaojun; Xie, Yongming; Yan, Xiaofei; Loo, Joseph A.; Hu, Shen

2010-01-01

Lymph node involvement is the most important predictor of survival rates in patients with oral squamous cell carcinoma (OSCC). A biomarker that can indicate lymph node metastasis would be valuable to classify patients with OSCC for optimal treatment. In this study, we have performed a serum proteomic analysis of OSCC using 2-D gel electrophoresis and liquid chromatography/tandem mass spectrometry. One of the down-regulated proteins in OSCC was identified as tetranectin, which is a protein encoded by the CLEC3B gene (C-type lectin domain family 3, member B). We further tested the protein level in serum and saliva from patients with lymph-node metastatic and primary OSCC. Tetranectin was found significantly under-expressed in both serum and saliva of metastatic OSCC compared to primary OSCC. Our results suggest that serum or saliva tetranectin may serve as a potential biomarker for metastatic OSCC. Other candidate serum biomarkers for OSCC included superoxide dismutase, ficolin 2, CD-5 antigen-like protein, RalA binding protein 1, plasma retinol-binding protein and transthyretin. Their clinical utility for OSCC detection remains to be further tested in cancer patients. PMID:20957082

Biomarkers of One-Carbon Metabolism Are Associated with Biomarkers of Inflammation in Women123

PubMed Central

Abbenhardt, Clare; Miller, Joshua W.; Song, Xiaoling; Brown, Elissa C.; Cheng, Ting-Yuan David; Wener, Mark H.; Zheng, Yingye; Toriola, Adetunji T.; Neuhouser, Marian L.; Beresford, Shirley A. A.; Makar, Karen W.; Bailey, Lynn B.; Maneval, David R.; Green, Ralph; Manson, JoAnn E.; Van Horn, Linda; Ulrich, Cornelia M.

2014-01-01

Folate-mediated one-carbon metabolism is essential for DNA synthesis, repair, and methylation. Perturbations in one-carbon metabolism have been implicated in increased risk of some cancers and may also affect inflammatory processes. We investigated these interrelated pathways to understand their relation. The objective was to explore associations between inflammation and biomarkers of nutritional status and one-carbon metabolism. In a cross-sectional study in 1976 women selected from the Women’s Health Initiative Observational Study, plasma vitamin B-6 [pyridoxal-5′-phosphate (PLP)], plasma vitamin B-12, plasma folate, and RBC folate were measured as nutritional biomarkers; serum C-reactive protein (CRP) and serum amyloid A (SAA) were measured as biomarkers of inflammation; and homocysteine and cysteine were measured as integrated biomarkers of one-carbon metabolism. Student’s t, chi-square, and Spearman rank correlations, along with multiple linear regressions, were used to explore relations between biomarkers; additionally, we tested stratification by folic acid fortification period and multivitamin use. With the use of univariate analysis, plasma PLP was the only nutritional biomarker that was modestly significantly correlated with serum CRP and SAA (ρ = −0.22 and −0.12, respectively; P < 0.0001). Homocysteine (μmol/L) showed significant inverse correlations with all nutritional biomarkers (ranging from ρ = −0.30 to ρ = −0.46; all P < 0.0001). With the use of multiple linear regression, plasma PLP, RBC folate, homocysteine, and cysteine were identified as independent predictors of CRP; and PLP, vitamin B-12, RBC folate, and homocysteine were identified as predictors of SAA. When stratified by folic acid fortification period, nutrition-homocysteine correlations were generally weaker in the postfortification period, whereas associations between plasma PLP and serum CRP increased. Biomarkers of inflammation are associated with PLP, RBC folate, and

Peptidome Analysis Reveals Novel Serum Biomarkers for Children with Autism Spectrum Disorder in China.

PubMed

Yang, Juan; Chen, Yanni; Xiong, Xiaofan; Zhou, Xiaobo; Han, Lin; Ni, Ei; Wang, Wenjing; Wang, Xiaofei; Zhao, Lingyu; Shao, Dongdong; Huang, Chen

2018-05-13

Autism spectrum disorder (ASD) is a neurological and developmental disorder that begins early in childhood and lasts throughout one's life. Early diagnosis is essential for ASD since early treatment can enable children with ASD to make significant gains in language and social skills, but remains challenging since there are currently no specific biomarkers of ASD. The study aimed to identify serum biomarkers for ASD. Serum of Han Chinese children with ASD (n = 68) and age-matched healthy controls (n = 80) was analyzed using magnetic bead-based separation combined with mass spectrum. Eight potential ASD serum biomarker peaks (m/z: 3886.69, 7775.12, 2381.71, 6638.63, 3319.17, 894.34, 4968.59, and 5910.53) with higher expression in ASD group were further identified as peptide regions of Plasma Serine Protease Inhibitor Precursor (SERPINA5), Platelet Factor 4 (PF4), Fatty Acid Binding Protein 1(FABP1), Apolipoprotein C-I Precursor (APOC1), Alpha-fetoprotein Precursor (AFP), Carboxypeptidase B2 (CPB2), Trace Amine-associated Receptor 6 (TAAR6) and Isoform1 of Fibrinogen Alpha Chain Precursor (FGA). The expression of identified proteins was validated by enzyme-linked immunosorbent assay (ELISA). Our findings reveal the exceptional disease etiology of ASD from a serum proteomic perspective, and the identified proteins might be potential biomarkers for ASD diagnosis. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Plasma Protein Turnover Rates in Rats Using Stable Isotope Labeling, Global Proteomics, and Activity-Based Protein Profiling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Jordan Ned; Tyrrell, Kimberly J.; Hansen, Joshua R.

Protein turnover is important for general health on cellular and organism scales providing a strategy to replace old, damaged, or dysfunctional proteins. Protein turnover also informs of biomarker kinetics, as a better understanding of synthesis and degradation of proteins increases the clinical utility of biomarkers. Here, turnover rates of plasma proteins in rats were measured in vivo using a pulse-chase stable isotope labeling experiment. During the pulse, rats (n=5) were fed 13C6-labeled lysine (“heavy”) feed for 23 days to label proteins. During the chase, feed was changed to an unlabeled equivalent feed (“light”), and blood was repeatedly sampled from ratsmore » over 10 time points for 28 days. Plasma samples were digested with trypsin, and analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS). MaxQuant was used to identify peptides and proteins, and quantify heavy:light lysine ratios. A system of ordinary differential equations was used to calculate protein turnover rates. Using this approach, 273 proteins were identified, and turnover rates were quantified for 157 plasma proteins with half-lives ranging 0.3-103 days. For the ~70 most abundant proteins, variability in turnover rates among rats was low (median coefficient of variation: 0.09). Activity-based protein profiling was applied to pooled plasma samples to enrich serine hydrolases using a fluorophosphonate (FP2) activity-based probe. This enrichment resulted in turnover rates for an additional 17 proteins. This study is the first to measure global plasma protein turnover rates in rats in vivo, measure variability of protein turnover rates in any animal model, and utilize activity-based protein profiling for enhancing measurements of targeted, low-abundant proteins, such as those commonly used as biomarkers. Measured protein turnover rates will be important for understanding of the role of protein turnover in cellular and organism health as well as increasing the utility of

Identifying DNA Methylation Biomarkers for Non-Endoscopic Detection of Barrett’s Esophagus

PubMed Central

Moinova, Helen R.; LaFramboise, Thomas; Lutterbaugh, James D.; Chandar, Apoorva Krishna; Dumot, John; Faulx, Ashley; Brock, Wendy; De la Cruz Cabrera, Omar; Guda, Kishore; Barnholtz-Sloan, Jill S.; Iyer, Prasad G.; Canto, Marcia I.; Wang, Jean S.; Shaheen, Nicholas J.; Thota, Prashanti N.; Willis, Joseph E.; Chak, Amitabh; Markowitz, Sanford D.

2018-01-01

We report a biomarker-based non-endoscopic method for detecting Barrett’s esophagus (BE), based on detecting methylated DNAs retrieved via a swallowable balloon-based esophageal sampling device. BE is the precursor of, and a major recognized risk factor for, developing esophageal adenocarcinoma (EAC). Endoscopy, the current standard for BE detection, is not cost-effective for population screening. We performed genome-wide screening to ascertain regions targeted for recurrent aberrant cytosine methylation in BE, identifying high-frequency methylation within the CCNA1 locus. We tested CCNA1 DNA methylation as a BE biomarker in cytology brushings of the distal esophagus from 173 individuals with or without BE. CCNA1 DNA methylation demonstrated an area under the curve (AUC)=0.95 for discriminating BE-related metaplasia and neoplasia cases versus normal individuals, performing identically to methylation of VIM DNA, an established BE biomarker. When combined, the resulting two biomarker panel was 95% sensitive and 91% specific. These results were replicated in an independent validation cohort of 149 individuals, who were assayed using the same cutoff values for test positivity established in the training population. To progress toward non-endoscopic esophageal screening, we engineered a well-tolerated, swallowable, encapsulated balloon device able to selectively sample the distal esophagus within 5 minutes. In balloon samples from 86 individuals, tests of CCNA1 plus VIM DNA methylation detected BE metaplasia with 90.3% sensitivity and 91.7% specificity. Combining the balloon sampling device with molecular assays of CCNA1 plus VIM DNA methylation enables an efficient, well-tolerated, sensitive, and specific method of screening at-risk populations for BE. PMID:29343623

Identification of novel diagnostic biomarkers for thyroid carcinoma

PubMed Central

Wang, Xiliang; Zhang, Qing; Cai, Zhiming; Dai, Yifan; Mou, Lisha

2017-01-01

Thyroid carcinoma (THCA) is the most universal endocrine malignancy worldwide. Unfortunately, a limited number of large-scale analyses have been performed to identify biomarkers for THCA. Here, we conducted a meta-analysis using 505 THCA patients and 59 normal controls from The Cancer Genome Atlas. After identifying differentially expressed long non-coding RNA (lncRNA) and protein coding genes (PCG), we found vast difference in various lncRNA-PCG co-expressed pairs in THCA. A dysregulation network with scale-free topology was constructed. Four molecules (LA16c-380H5.2, RP11-203J24.8, MLF1 and SDC4) could potentially serve as diagnostic biomarkers of THCA with high sensitivity and specificity. We further represent a diagnostic panel with expression cutoff values. Our results demonstrate the potential application of those four molecules as novel independent biomarkers for THCA diagnosis. PMID:29340074

Plasma Protein Pentosidine and Carboxymethyllysine, Biomarkers for Age-related Macular Degeneration*

PubMed Central

Ni, Jiaqian; Yuan, Xianglin; Gu, Jiayin; Yue, Xiuzhen; Gu, Xiaorong; Nagaraj, Ram H.; Crabb, John W.

2009-01-01

Age-related macular degeneration (AMD) causes severe vision loss in the elderly; early identification of AMD risk could help slow or prevent disease progression. Toward the discovery of AMD biomarkers, we quantified plasma protein Nε-carboxymethyllysine (CML) and pentosidine from 58 AMD and 32 control donors. CML and pentosidine are advanced glycation end products that are abundant in Bruch membrane, the extracellular matrix separating the retinal pigment epithelium from the blood-bearing choriocapillaris. We measured CML and pentosidine by LC-MS/MS and LC-fluorometry, respectively, and found higher mean levels of CML (∼54%) and pentosidine (∼64%) in AMD (p < 0.0001) relative to normal controls. Plasma protein fructosyl-lysine, a marker of early glycation, was found by amino acid analysis to be in equal amounts in control and non-diabetic AMD donors, supporting an association between AMD and increased levels of CML and pentosidine independent of other diseases like diabetes. Carboxyethylpyrrole (CEP), an oxidative modification from docosahexaenoate-containing lipids and also abundant in AMD Bruch membrane, was elevated ∼86% in the AMD cohort, but autoantibody titers to CEP, CML, and pentosidine were not significantly increased. Compellingly higher mean levels of CML and pentosidine were present in AMD plasma protein over a broad age range. Receiver operating curves indicate that CML, CEP adducts, and pentosidine alone discriminated between AMD and control subjects with 78, 79, and 88% accuracy, respectively, whereas CML in combination with pentosidine provided ∼89% accuracy, and CEP plus pentosidine provided ∼92% accuracy. Pentosidine levels appeared slightly altered in AMD patients with hypertension and cardiovascular disease, indicating further studies are warranted. Overall this study supports the potential utility of plasma protein CML and pentosidine as biomarkers for assessing AMD risk and susceptibility, particularly in combination with CEP

Do classic blood biomarkers of JSLE identify active lupus nephritis? Evidence from the UK JSLE Cohort Study.

PubMed

Smith, E M D; Jorgensen, A L; Beresford, M W

2017-10-01

Background Lupus nephritis (LN) affects up to 80% of juvenile-onset systemic lupus erythematosus (JSLE) patients. The value of commonly available biomarkers, such as anti-dsDNA antibodies, complement (C3/C4), ESR and full blood count parameters in the identification of active LN remains uncertain. Methods Participants from the UK JSLE Cohort Study, aged <16 years at diagnosis, were categorized as having active or inactive LN according to the renal domain of the British Isles Lupus Assessment Group score. Classic biomarkers: anti-dsDNA, C3, C4, ESR, CRP, haemoglobin, total white cells, neutrophils, lymphocytes, platelets and immunoglobulins were assessed for their ability to identify active LN using binary logistic regression modeling, with stepAIC function applied to select a final model. Receiver-operating curve analysis was used to assess diagnostic accuracy. Results A total of 370 patients were recruited; 191 (52%) had active LN and 179 (48%) had inactive LN. Binary logistic regression modeling demonstrated a combination of ESR, C3, white cell count, neutrophils, lymphocytes and IgG to be best for the identification of active LN (area under the curve 0.724). Conclusions At best, combining common classic blood biomarkers of lupus activity using multivariate analysis provides a 'fair' ability to identify active LN. Urine biomarkers were not included in these analyses. These results add to the concern that classic blood biomarkers are limited in monitoring discrete JSLE manifestations such as LN.

Biomarkers in Japanese Encephalitis: A Review

PubMed Central

Kant Upadhyay, Ravi

2013-01-01

JE is a flavivirus generated dreadful CNS disease which causes high mortality in various pediatric groups. JE disease is currently diagnosed by measuring the level of viral antigens and virus neutralization IgM antibodies in blood serum and CSF by ELISA. However, it is not possible to measure various disease-identifying molecules, structural and molecular changes occurred in tissues, and cells by using such routine methods. However, few important biomarkers such as cerebrospinal fluid, plasma, neuro-imaging, brain mapping, immunotyping, expression of nonstructural viral proteins, systematic mRNA profiling, DNA and protein microarrays, active caspase-3 activity, reactive oxygen species and reactive nitrogen species, levels of stress-associated signaling molecules, and proinflammatory cytokines could be used to confirm the disease at an earlier stage. These biomarkers may also help to diagnose mutant based environment specific alterations in JEV genotypes causing high pathogenesis and have immense future applications in diagnostics. There is an utmost need for the development of new more authentic, appropriate, and reliable physiological, immunological, biochemical, biophysical, molecular, and therapeutic biomarkers to confirm the disease well in time to start the clinical aid to the patients. Hence, the present review aims to discuss new emerging biomarkers that could facilitate more authentic and fast diagnosis of JE disease and its related disorders in the future. PMID:24455705

Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

PubMed

Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

2015-11-01

Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2017-10-13

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis...TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-15-2-0032 5b. GRANT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI...Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad goal is

Identification of Tengfu Jiangya Tablet Target Biomarkers with Quantitative Proteomic Technique

PubMed Central

Xu, Jingwen; Zhang, Shijun; Jiang, Haiqiang; Wang, Nan; Lin, Haiqing

2017-01-01

Tengfu Jiangya Tablet (TJT) is a well accepted antihypertension drug in China and its major active components were Uncaria total alkaloids and Semen Raphani soluble alkaloid. To further explore treatment effects mechanism of TJT on essential hypertension, a serum proteomic study was performed. Potential biomarkers were quantified in serum of hypertension individuals before and after taking TJT with isobaric tags for relative and absolute quantitation (iTRAQ) coupled two-dimensional liquid chromatography followed electrospray ionization-tandem mass spectrometry (2D LC-MS/MS) proteomics technique. Among 391 identified proteins with high confidence, 70 proteins were differentially expressed (fold variation criteria, >1.2 or <0.83) between two groups (39 upregulated and 31 downregulated). Combining with Gene Ontology annotation, KEGG pathway analysis, and literature retrieval, 5 proteins were chosen as key target biomarkers during TJT therapeutic process. And the alteration profiles of these 5 proteins were verified by ELISA and Western Blot. Proteins Kininogen 1 and Keratin 1 are members of Kallikrein system, while Myeloperoxidase, Serum Amyloid protein A, and Retinol binding protein 4 had been reported closely related to vascular endothelial injury. Our study discovered 5 target biomarkers of the compound Chinese medicine TJT. Secondly, this research initially revealed the antihypertension therapeutic mechanism of this drug from a brand-new aspect. PMID:28408942

Inflammation and hemostasis biomarkers for predicting stroke in postmenopausal women: The Women’s Health Initiative Observational Study

PubMed Central

Kaplan, Robert C; McGinn, Aileen P; Baird, Alison E; Hendrix, Susan L; Kooperberg, Charles; Lynch, John; Rosenbaum, Daniel M; Johnson, Karen C; Strickler, Howard D; Wassertheil-Smoller, Sylvia

2009-01-01

Background Inflammatory and hemostasis-related biomarkers may identify women at risk of stroke. Methods Hormones and Biomarkers Predicting Stroke is a study of ischemic stroke among postmenopausal women participating in the Women’s Health Initiative Observational Study (n = 972 case-control pairs). A Biomarker Risk Score was derived from levels of seven inflammatory and hemostasis-related biomarkers that appeared individually to predict risk of ischemic stroke: C-reactive protein, interleukin-6, tissue plasminogen activator, D-dimer, white blood cell count, neopterin, and homocysteine. The c index was used to evaluate discrimination. Results Of all the individual biomarkers examined, C-reactive protein emerged as the only independent single predictor of ischemic stroke (adjusted odds ratio comparing Q4 versus Q1 = 1.64, 95% confidence interval: 1.15–2.32, p = 0.01) after adjustment for other biomarkers and standard stroke risk factors. The Biomarker Risk Score identified a gradient of increasing stroke risk with a greater number of elevated inflammatory/hemostasis biomarkers, and improved the c index significantly compared with standard stroke risk factors (p = 0.02). Among the subset of individuals who met current criteria for “high risk” levels of C-reactive protein (> 3.0 mg/L), the Biomarker Risk Score defined an approximately two-fold gradient of risk. We found no evidence for a relationship between stroke and levels of E-selectin, fibrinogen, tumor necrosis factor-alpha, vascular cell adhesion molecule-1, prothrombin fragment 1+2, Factor VIIC, or plasminogen activator inhibitor-1 antigen (p >0.15). Discussion The findings support the further exploration of multiple-biomarker panels to develop approaches for stratifying an individual’s risk of stroke. PMID:18984425

A Resource for Discovering Specific and Universal Biomarkers for Distributed Stem Cells

PubMed Central

Noh, Minsoo; Smith, Janet L.; Huh, Yang Hoon; Sherley, James L.

2011-01-01

Specific and universal biomarkers for distributed stem cells (DSCs) have been elusive. A major barrier to discovery of such ideal DSC biomarkers is difficulty in obtaining DSCs in sufficient quantity and purity. To solve this problem, we used cell lines genetically engineered for conditional asymmetric self-renewal, the defining DSC property. In gene microarray analyses, we identified 85 genes whose expression is tightly asymmetric self-renewal associated (ASRA). The ASRA gene signature prescribed DSCs to undergo asymmetric self-renewal to a greater extent than committed progenitor cells, embryonic stem cells, or induced pluripotent stem cells. This delineation has several significant implications. These include: 1) providing experimental evidence that DSCs in vivo undergo asymmetric self-renewal as individual cells; 2) providing an explanation why earlier attempts to define a common gene expression signature for DSCs were unsuccessful; and 3) predicting that some ASRA proteins may be ideal biomarkers for DSCs. Indeed, two ASRA proteins, CXCR6 and BTG2, and two other related self-renewal pattern associated (SRPA) proteins identified in this gene resource, LGR5 and H2A.Z, display unique asymmetric patterns of expression that have a high potential for universal and specific DSC identification. PMID:21818293

Identifying Protein-Calorie Malnutrition Workshop.

ERIC Educational Resources Information Center

Walker, Susan S.; Barker, Ellen M.

Instructional materials are provided for a workshop to enable participants to assist in identifying patients at risk with protein-calorie malnutrition and in corrrecting this nutritional deficiency. Representative topics are nutrients; protein, mineral, and vitamin sources, functions, and deficiency symptoms; malnutrition; nutritional deficiency…

Sweetening the pot: adding glycosylation to the biomarker discovery equation

PubMed Central

Drake, Penelope M.; Cho, Wonryeon; Li, Bensheng; Prakobphol, Akraporn; Johansen, Eric; Anderson, N. Leigh; Regnier, Fred E.; Gibson, Bradford W.; Fisher, Susan J.

2010-01-01

Background Cancer has profound effects on gene expression, including a cell’s glycosylation machinery. Thus, tumors produce glycoproteins that carry oligosaccharides with structures that are markedly different from the same protein produced by a normal cell. A single protein can have many glycosylation sites that greatly amplify the signals they generate as compared to their protein backbones. Content We survey clinical tests that target carbohydrate modifications. for diagnosing and treating cancer. Next, we present the biological relevance of glycosylation to disease progression by highlighting the role these structures play in adhesion, signaling and metastasis, and then address current methodological approaches to biomarker discovery that capitalize on selectively capturing tumor-associated glycoforms to enrich and identify disease-related candidate analytes. Finally, we discuss emerging technologies—multiple reaction monitoring and lectin-antibody arrays—as potential tools for biomarker validation studies in pursuit of clinically useful tests. Summary The future of carbohydrate-based biomarker studies has arrived. At all stages, from discovery through verification and deployment into clinics, glycosylation should be considered a primary readout or a way of increasing the sensitivity and specificity of protein-based analyses. PMID:19959616

Development of a Multi-Biomarker Disease Activity Test for Rheumatoid Arthritis

PubMed Central

Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A.; Turner, Mary; Sutton, Chris; Smith, Dustin R.; Haney, Douglas J.; Chernoff, David; Hesterberg, Lyndal K.; Carulli, John P.; Taylor, Peter C.; Shadick, Nancy A.; Weinblatt, Michael E.; Curtis, Jeffrey R.

2013-01-01

Background Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. Objectives To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Methods Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. Results 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities

Discovery of Colorectal Cancer Biomarker Candidates by Membrane Proteomic Analysis and Subsequent Verification using Selected Reaction Monitoring (SRM) and Tissue Microarray (TMA) Analysis*

PubMed Central

Kume, Hideaki; Muraoka, Satoshi; Kuga, Takahisa; Adachi, Jun; Narumi, Ryohei; Watanabe, Shio; Kuwano, Masayoshi; Kodera, Yoshio; Matsushita, Kazuyuki; Fukuoka, Junya; Masuda, Takeshi; Ishihama, Yasushi; Matsubara, Hisahiro; Nomura, Fumio; Tomonaga, Takeshi

2014-01-01

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the

Discovery of colorectal cancer biomarker candidates by membrane proteomic analysis and subsequent verification using selected reaction monitoring (SRM) and tissue microarray (TMA) analysis.

PubMed

Kume, Hideaki; Muraoka, Satoshi; Kuga, Takahisa; Adachi, Jun; Narumi, Ryohei; Watanabe, Shio; Kuwano, Masayoshi; Kodera, Yoshio; Matsushita, Kazuyuki; Fukuoka, Junya; Masuda, Takeshi; Ishihama, Yasushi; Matsubara, Hisahiro; Nomura, Fumio; Tomonaga, Takeshi

2014-06-01

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the

Identifying biomarkers of dietary patterns by using metabolomics123

PubMed Central

Derkach, Andriy; Reedy, Jill; Subar, Amy F; Sampson, Joshua N; Albanes, Demetrius; Gu, Fangyi; Kontto, Jukka; Lassale, Camille; Liao, Linda M; Männistö, Satu; Mondul, Alison M; Weinstein, Stephanie J; Irwin, Melinda L; Mayne, Susan T; Stolzenberg-Solomon, Rachael

2017-01-01

Background: Healthy dietary patterns that conform to national dietary guidelines are related to lower chronic disease incidence and longer life span. However, the precise mechanisms involved are unclear. Identifying biomarkers of dietary patterns may provide tools to validate diet quality measurement and determine underlying metabolic pathways influenced by diet quality. Objective: The objective of this study was to examine the correlation of 4 diet quality indexes [the Healthy Eating Index (HEI) 2010, the Alternate Mediterranean Diet Score (aMED), the WHO Healthy Diet Indicator (HDI), and the Baltic Sea Diet (BSD)] with serum metabolites. Design: We evaluated dietary patterns and metabolites in male Finnish smokers (n = 1336) from 5 nested case-control studies within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study cohort. Participants completed a validated food-frequency questionnaire and provided a fasting serum sample before study randomization (1985–1988). Metabolites were measured with the use of mass spectrometry. We analyzed cross-sectional partial correlations of 1316 metabolites with 4 diet quality indexes, adjusting for age, body mass index, smoking, energy intake, education, and physical activity. We pooled estimates across studies with the use of fixed-effects meta-analysis with Bonferroni correction for multiple comparisons, and conducted metabolic pathway analyses. Results: The HEI-2010, aMED, HDI, and BSD were associated with 23, 46, 23, and 33 metabolites, respectively (17, 21, 11, and 10 metabolites, respectively, were chemically identified; r-range: −0.30 to 0.20; P = 6 × 10−15 to 8 × 10−6). Food-based diet indexes (HEI-2010, aMED, and BSD) were associated with metabolites correlated with most components used to score adherence (e.g., fruit, vegetables, whole grains, fish, and unsaturated fat). HDI correlated with metabolites related to polyunsaturated fat and fiber components, but not other macro- or micronutrients (e

Comparison of Pancreas Juice Proteins from Cancer Versus Pancreatitis Using Quantitative Proteomic Analysis

PubMed Central

Chen, Ru; Pan, Sheng; Cooke, Kelly; Moyes, Kara White; Bronner, Mary P.; Goodlett, David R.; Aebersold, Ruedi; Brentnall, Teresa A.

2008-01-01

Objectives Pancreatitis is an inflammatory condition of the pancreas. However, it often shares many molecular features with pancreatic cancer. Biomarkers present in pancreatic cancer frequently occur in the setting of pancreatitis. The efforts to develop diagnostic biomarkers for pancreatic cancer have thus been complicated by the false-positive involvement of pancreatitis. Methods In an attempt to develop protein biomarkers for pancreatic cancer, we previously use quantitative proteomics to identify and quantify the proteins from pancreatic cancer juice. Pancreatic juice is a rich source of proteins that are shed by the pancreatic ductal cells. In this study, we used a similar approach to identify and quantify proteins from pancreatitis juice. Results In total, 72 proteins were identified and quantified in the comparison of pancreatic juice from pancreatitis patients versus pooled normal control juice. Nineteen of the juice proteins were overexpressed, and 8 were underexpressed in pancreatitis juice by at least 2-fold compared with normal pancreatic juice. Of these 27 differentially expressed proteins in pancreatitis, 9 proteins were also differentially expressed in the pancreatic juice from pancreatic cancer patient. Conclusions Identification of these differentially expressed proteins from pancreatitis juice provides useful information for future study of specific pancreatitis-associated proteins and to eliminate potential false-positive biomarkers for pancreatic cancer. PMID:17198186

Comparison of pancreas juice proteins from cancer versus pancreatitis using quantitative proteomic analysis.

PubMed

Chen, Ru; Pan, Sheng; Cooke, Kelly; Moyes, Kara White; Bronner, Mary P; Goodlett, David R; Aebersold, Ruedi; Brentnall, Teresa A

2007-01-01

Pancreatitis is an inflammatory condition of the pancreas. However, it often shares many molecular features with pancreatic cancer. Biomarkers present in pancreatic cancer frequently occur in the setting of pancreatitis. The efforts to develop diagnostic biomarkers for pancreatic cancer have thus been complicated by the false-positive involvement of pancreatitis. In an attempt to develop protein biomarkers for pancreatic cancer, we previously use quantitative proteomics to identify and quantify the proteins from pancreatic cancer juice. Pancreatic juice is a rich source of proteins that are shed by the pancreatic ductal cells. In this study, we used a similar approach to identify and quantify proteins from pancreatitis juice. In total, 72 proteins were identified and quantified in the comparison of pancreatic juice from pancreatitis patients versus pooled normal control juice. Nineteen of the juice proteins were overexpressed, and 8 were underexpressed in pancreatitis juice by at least 2-fold compared with normal pancreatic juice. Of these 27 differentially expressed proteins in pancreatitis, 9 proteins were also differentially expressed in the pancreatic juice from pancreatic cancer patient. Identification of these differentially expressed proteins from pancreatitis juice provides useful information for future study of specific pancreatitis-associated proteins and to eliminate potential false-positive biomarkers for pancreatic cancer.

Comparison of Protein Immunoprecipitation-Multiple Reaction Monitoring with ELISA for Assay of Biomarker Candidates in Plasma

PubMed Central

2013-01-01

Quantitative analysis of protein biomarkers in plasma is typically done by ELISA, but this method is limited by the availability of high-quality antibodies. An alternative approach is protein immunoprecipitation combined with multiple reaction monitoring mass spectrometry (IP-MRM). We compared IP-MRM to ELISA for the analysis of six colon cancer biomarker candidates (metalloproteinase inhibitor 1 (TIMP1), cartilage oligomeric matrix protein (COMP), thrombospondin-2 (THBS2), endoglin (ENG), mesothelin (MSLN) and matrix metalloproteinase-9 (MMP9)) in plasma from colon cancer patients and noncancer controls. Proteins were analyzed by multiplex immunoprecipitation from plasma with the ELISA capture antibodies, further purified by SDS-PAGE, digested and analyzed by stable isotope dilution MRM. IP-MRM provided linear responses (r = 0.978–0.995) between 10 and 640 ng/mL for the target proteins spiked into a “mock plasma” matrix consisting of 60 mg/mL bovine serum albumin. Measurement variation (coefficient of variation at the limit of detection) for IP-MRM assays ranged from 2.3 to 19%, which was similar to variation for ELISAs of the same samples. IP-MRM and ELISA measurements for all target proteins except ENG were highly correlated (r = 0.67–0.97). IP-MRM with high-quality capture antibodies thus provides an effective alternative method to ELISA for protein quantitation in biological fluids. PMID:24224610

The study of protein biomarkers to understand the biochemical processes underlying beef color development in young bulls.

PubMed

Gagaoua, Mohammed; Terlouw, E M Claudia; Picard, Brigitte

2017-12-01

This study investigates relationships between 21 biomarkers and meat color traits of Longissimus thoracis muscles of young Aberdeen Angus and Limousin bulls. The relationships found allowed to propose metabolic processes underlying meat color. The color coordinates were related with several biomarkers. The relationships were in some cases breed-dependent and the variability explained in the regression models varied between 31 and 56%. The correlations between biomarkers and color parameters were sometimes opposite between breeds. The PCA using the 21 biomarkers and the instrumental color coordinates showed that these variables discriminated efficiently between the two studied breeds. Results are coherent with earlier studies on other beef breeds showing that several proteins belonging to different but partly related biological pathways involved in muscle contraction, metabolism, heat stress and apoptosis are related to beef color. The results suggest that in future, biomarkers may be used to classify meat cuts sampled early post-mortem according to their forthcoming color. Copyright © 2017 Elsevier Ltd. All rights reserved.

Biomarker Analysis of Samples Visually Identified as Microbial in the Eocene Green River Formation: An Analogue for Mars.

PubMed

Olcott Marshall, Alison; Cestari, Nicholas A

2015-09-01

One of the major exploration targets for current and future Mars missions are lithofacies suggestive of biotic activity. Although such lithofacies are not confirmation of biotic activity, they provide a way to identify samples for further analyses. To test the efficacy of this approach, we identified carbonate samples from the Eocene Green River Formation as "microbial" or "non-microbial" based on the macroscale morphology of their laminations. These samples were then crushed and analyzed by gas chromatography/mass spectroscopy (GC/MS) to determine their lipid biomarker composition. GC/MS analysis revealed that carbonates visually identified as "microbial" contained a higher concentration of more diverse biomarkers than those identified as "non-microbial," suggesting that this could be a viable detection strategy for selecting samples for further analysis or caching on Mars.

Identification of head and neck squamous cell carcinoma biomarker candidates through proteomic analysis of cancer cell secretome.

PubMed

Marimuthu, Arivusudar; Chavan, Sandip; Sathe, Gajanan; Sahasrabuddhe, Nandini A; Srikanth, Srinivas M; Renuse, Santosh; Ahmad, Sartaj; Radhakrishnan, Aneesha; Barbhuiya, Mustafa A; Kumar, Rekha V; Harsha, H C; Sidransky, David; Califano, Joseph; Pandey, Akhilesh; Chatterjee, Aditi

2013-11-01

Protein biomarker discovery for early detection of head and neck squamous cell carcinoma (HNSCC) is a crucial unmet need to improve patient outcomes. Mass spectrometry-based proteomics has emerged as a promising tool for identification of biomarkers in different cancer types. Proteins secreted from cancer cells can serve as potential biomarkers for early diagnosis. In the current study, we have used isobaric tag for relative and absolute quantitation (iTRAQ) labeling methodology coupled with high resolution mass spectrometry to identify and quantitate secreted proteins from a panel of head and neck carcinoma cell lines. In all, we identified 2,472 proteins, of which 225 proteins were secreted at higher or lower abundance in HNSCC-derived cell lines. Of these, 148 were present in higher abundance and 77 were present in lower abundance in the cancer-cell derived secretome. We detected a higher abundance of some previously known markers for HNSCC including insulin like growth factor binding protein 3, IGFBP3 (11-fold) and opioid growth factor receptor, OGFR (10-fold) demonstrating the validity of our approach. We also identified several novel secreted proteins in HNSCC including olfactomedin-4, OLFM4 (12-fold) and hepatocyte growth factor activator, HGFA (5-fold). IHC-based validation was conducted in HNSCC using tissue microarrays which revealed overexpression of IGFBP3 and OLFM4 in 70% and 75% of the tested cases, respectively. Our study illustrates quantitative proteomics of secretome as a robust approach for identification of potential HNSCC biomarkers. This article is part of a Special Issue entitled: An Updated Secretome. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterization of the liver tissue interstitial fluid (TIF) proteome indicates potential for application in liver disease biomarker discovery.

PubMed

Sun, Wei; Ma, Jie; Wu, Songfeng; Yang, Dong; Yan, Yujuan; Liu, Kehui; Wang, Jinglan; Sun, Longqin; Chen, Ning; Wei, Handong; Zhu, Yunping; Xing, Baocai; Zhao, Xiaohang; Qian, Xiaohong; Jiang, Ying; He, Fuchu

2010-02-05

Tissue interstitial fluid (TIF) forms the interface between circulating body fluids and intracellular fluid. Pathological alterations of liver cells could be reflected in TIF, making it a promising source of liver disease biomarkers. Mouse liver TIF was extracted, separated by SDS-PAGE, analyzed by linear ion trap mass spectrometer, and 1450 proteins were identified. These proteins may be secreted, shed from membrane vesicles, or represent cellular breakdown products. They show different profiling patterns, quantities, and possibly modification/cleavage of intracellular proteins. The high solubility and even distribution of liver TIF supports its suitability for proteome analysis. Comparison of mouse liver TIF data with liver tissue and plasma proteome data identified major proteins that might be released from liver to plasma and serve as blood biomarkers of liver origin. This result was partially supported by comparison of human liver TIF data with human liver and plasma proteome data. Paired TIFs from tumor and nontumor liver tissues of a hepatocellular carcinoma patient were analyzed and the profile of subtracted differential proteins supports the potential for biomarker discovery in TIF. This study is the first analysis of the liver TIF proteome and provides a foundation for further application of TIF in liver disease biomarker discovery.

Inflammatory and fibrotic proteins proteomically identified as key protein constituents in urine and stone matrix of patients with kidney calculi.

PubMed

Boonla, Chanchai; Tosukhowong, Piyaratana; Spittau, Björn; Schlosser, Andreas; Pimratana, Chaowat; Krieglstein, Kerstin

2014-02-15

To uncover whether urinary proteins are incorporated into stones, the proteomic profiles of kidney stones and urine collected from the same patients have to be explored. We employed 1D-PAGE and nanoHPLC-ESI-MS/MS to analyze the proteomes of kidney stone matrix (n=16), nephrolithiatic urine (n=14) and healthy urine (n=3). We identified 62, 66 and 22 proteins in stone matrix, nephrolithiatic urine and healthy urine, respectively. Inflammation- and fibrosis-associated proteins were frequently detected in the stone matrix and nephrolithiatic urine. Eighteen proteins were exclusively found in the stone matrix and nephrolithiatic urine, considered as candidate biomarkers for kidney stone formation. S100A8 and fibronectin, representatives of inflammation and fibrosis, respectively, were up-regulated in nephrolithiasis renal tissues. S100A8 was strongly expressed in infiltrated leukocytes. Fibronectin was over-expressed in renal tubular cells. S100A8 and fibronectin were immunologically confirmed to exist in nephrolithiatic urine and stone matrix, but in healthy urine they were undetectable. Conclusion, both kidney stones and urine obtained from the same patients greatly contained inflammatory and fibrotic proteins. S100A8 and fibronectin were up-regulated in stone-baring kidneys and nephrolithiatic urine. Therefore, inflammation and fibrosis are suggested to be involved in the formation of kidney calculi. Copyright © 2013 Elsevier B.V. All rights reserved.

Quantitative phase-digital holographic microscopy: a new imaging modality to identify original cellular biomarkers of diseases

NASA Astrophysics Data System (ADS)

Marquet, P.; Rothenfusser, K.; Rappaz, B.; Depeursinge, C.; Jourdain, P.; Magistretti, P. J.

2016-03-01

Quantitative phase microscopy (QPM) has recently emerged as a powerful label-free technique in the field of living cell imaging allowing to non-invasively measure with a nanometric axial sensitivity cell structure and dynamics. Since the phase retardation of a light wave when transmitted through the observed cells, namely the quantitative phase signal (QPS), is sensitive to both cellular thickness and intracellular refractive index related to the cellular content, its accurate analysis allows to derive various cell parameters and monitor specific cell processes, which are very likely to identify new cell biomarkers. Specifically, quantitative phase-digital holographic microscopy (QP-DHM), thanks to its numerical flexibility facilitating parallelization and automation processes, represents an appealing imaging modality to both identify original cellular biomarkers of diseases as well to explore the underlying pathophysiological processes.

Identification of ovarian cancer-associated proteins in symptomatic women: A novel method for semi-quantitative plasma proteomics.

PubMed

Shield-Artin, Kristy L; Bailey, Mark J; Oliva, Karen; Liovic, Ana K; Barker, Gillian; Dellios, Nicole L; Reisman, Simone; Ayhan, Mustafa; Rice, Gregory E

2012-04-01

To evaluate the utility of an enhanced biomarker discovery approach in order to identify potential biomarkers relevant to ovarian cancer detection. We combined immuno-depletion, liquid-phase IEF, 1D-DIGE, MALDI-TOF/MS and LC-MS/MS to identify differentially expressed proteins in the plasma of symptomatic ovarian cancer patients, stratified by stage, compared to samples obtained from normal subjects. We demonstrate that this approach is a practical alternative to traditional 2D gel techniques and that it has some advantages, most notably increased protein capacity. Proteins were identified in all 76 bands excised from the gels in this project and confirmed the cancer-associated expression of several well-established biomarkers of ovarian cancer. These included C-reactive protein (CRP), haptoglobin, alpha-2 macroglobulin and A1A2. We also identified new ovarian cancer candidate biomarkers, Protein S100-A9 (S100A9) and multimerin-2. The cancer-associated differential expression of CRP and S100A9 was further confirmed by Western blot and ELISA. The methods developed in this study allow for the increased loading of plasma proteins into the analytical stream when compared to traditional 2D-DIGE. This increased protein identification sensitivity allowed us to identify new putative ovarian cancer biomarkers. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

IL-11 and CCL-1: Novel Protein Diagnostic Biomarkers of Lung Adenocarcinoma in Bronchoalveolar Lavage Fluid (BALF).

PubMed

Pastor, Maria Delores; Nogal, Ana; Molina-Pinelo, Sonia; Quintanal-Villalonga, Álvaro; Meléndez, Ricardo; Ferrer, I; Romero-Romero, Beatrice; De Miguel, Maria José; López-Campos, José Luis; Corral, Jesús; García-Carboner, Rocío; Carnero, Amancio; Paz-Ares, Luis

2016-12-01

Lung cancer (LC) and chronic obstructive pulmonary disease (COPD) are smoking-related diseases, with the presence of COPD itself increasing the risk for development of LC, probably owing to underlying inflammation. LC is typically detected at late stages of the disease and carries a poor prognosis. There is an unmet need for methods to facilitate the early detection of LC in high-risk subjects such as smokers. The expression of inflammatory proteins in bronchoalveolar lavage fluid (BALF) samples was studied by antibody arrays in a prospective cohort of 60 smokers of more than 30 pack-years divided into four groups (control, patients with LC, patients with COPD, and patients with LC plus COPD). Relevant biomarkers were validated by Western blot. Additional validation with enzyme-linked immunosorbent assay (ELISA) was carried out on two independent controlled cohorts of 139 patients (control, patients with LC, patients with COPD, and patients with LC plus COPD) and 160 patients (control and patients with LC of all histological types). A total of 16 differentially expressed proteins in samples from patients with LC, COPD, and LC plus COPD were identified by antibody arrays and validated by Western blot and ELISA. C-C motif chemokine ligand 1 (CCL-1) and interleukin-11 (IL)-11 were selectively expressed in samples from patients with adenocarcinoma with or without COPD (p < 0.005). These proteins exhibited a remarkable diagnostic performance for lung adenocarcinoma in an independent cohort of 139 patients. Receiver operating characteristic curves showed that the optimum diagnostic cutoff value for IL-11 was 42 pg/mL (area under the curve = 0.93 [95% confidence interval: 0.896-0.975], sensitivity 90%, specificity 86%), whereas for CCL-1 it was 39.5 pg/mL (0.83 [95% confidence interval: 0.749-0.902], sensitivity 83%, and specificity 74%). Further validation of the ELISA biomarkers at the aforementioned cutoffs was performed in an additional cohort of 160 patients (20

Biomarkers of systemic inflammation in farmers with musculoskeletal disorders; a plasma proteomic study.

PubMed

Ghafouri, Bijar; Carlsson, Anders; Holmberg, Sara; Thelin, Anders; Tagesson, Christer

2016-05-10

Farmers have an increased risk for musculoskeletal disorders (MSD) such as osteoarthritis of the hip, low back pain, and neck and upper limb complaints. The underlying mechanisms are not fully understood. Work-related exposures and inflammatory responses might be involved. Our objective was to identify plasma proteins that differentiated farmers with MSD from rural referents. Plasma samples from 13 farmers with MSD and rural referents were included in the investigation. Gel based proteomics was used for protein analysis and proteins that differed significantly between the groups were identified by mass spectrometry. In total, 15 proteins differed significantly between the groups. The levels of leucine-rich alpha-2-glycoprotein, haptoglobin, complement factor B, serotransferrin, one isoform of kininogen, one isoform of alpha-1-antitrypsin, and two isoforms of hemopexin were higher in farmers with MSD than in referents. On the other hand, the levels of alpha-2-HS-glycoprotein, alpha-1B-glycoprotein, vitamin D- binding protein, apolipoprotein A1, antithrombin, one isoform of kininogen, and one isoform of alpha-1-antitrypsin were lower in farmers than in referents. Many of the identified proteins are known to be involved in inflammation. Farmers with MSD had altered plasma levels of protein biomarkers compared to the referents, indicating that farmers with MSD may be subject to a more systemic inflammation. It is possible that the identified differences of proteins may give clues to the biochemical changes occurring during the development and progression of MSD in farmers, and that one or several of these protein biomarkers might eventually be used to identify and prevent work-related MSD.

Sepsis biomarkers in neutropaenic systemic inflammatory response syndrome patients on standard care wards.

PubMed

Ratzinger, Franz; Haslacher, Helmuth; Perkmann, Thomas; Schmetterer, Klaus G; Poeppl, Wolfgang; Mitteregger, Dieter; Dorffner, Georg; Burgmann, Heinz

2015-08-01

Neutropaenic patients are at a high risk of contracting severe infections. In particular, in these patients, parameters with a high negative predictive value are desirable for excluding infection or bacteraemia. This study evaluated sepsis biomarkers in neutropaenic patients suffering from systemic inflammatory response syndrome (SIRS). Further, the predictive capacities of evaluated biomarkers in neutropaenic SIRS patients were compared to non-neutropaenic SIRS patients. In this prospective observational cohort study, patients with clinically suspected sepsis were screened. The predictive capacities of procalcitonin (PCT), C-reactive protein and lipopolysaccharide-binding protein (LBP) in neutropaenic SIRS patients were evaluated in terms of their potential to identify infection or bacteraemia and were compared to results for non-neutropaenic SIRS patients. To select an appropriate control cohort, propensity score matching was applied, balancing confounding factors between neutropaenic and non-neutropaenic SIRS patients. Of 3370 prospectively screened patients with suspected infection, 51 patients suffered from neutropaenic SIRS. For the identification of infection, none of the assessed biomarkers presented a clinically relevant discriminatory potency. Lipopolysaccharide-binding protein and PCT demonstrated discriminatory capacity to discriminate between nonbacteraemic and bacteraemic SIRS in patients with neutropaenia [receiver-operating characteristics-area under the curves (ROC-AUCs): 0.860, 0.818]. In neutropaenic SIRS patients, LBP had a significantly better ROC-AUC than in a comparable non-neutropaenic patient cohort for identifying bacteraemia (P = 0.01). In neutropaenic SIRS patients, none of the evaluated biomarkers was able to adequately identify infection. LBP and PCT presented a good performance in identifying bacteraemia. Therefore, these markers could be used for screening purposes to increase the pretest probability of blood culture analysis. �

Multiplexing of miniaturized planar antibody arrays for serum protein profiling--a biomarker discovery in SLE nephritis.

PubMed

Petersson, Linn; Dexlin-Mellby, Linda; Bengtsson, Anders A; Sturfelt, Gunnar; Borrebaeck, Carl A K; Wingren, Christer

2014-06-07

In the quest to decipher disease-associated biomarkers, miniaturized and multiplexed antibody arrays may play a central role in generating protein expression profiles, or protein maps, of crude serum samples. In this conceptual study, we explored a novel, 4-times larger pen design, enabling us to, in a unique manner, simultaneously print 48 different reagents (antibodies) as individual 78.5 μm(2) (10 μm in diameter) sized spots at a density of 38,000 spots cm(-2) using dip-pen nanolithography technology. The antibody array set-up was interfaced with a high-resolution fluorescent-based scanner for sensitive sensing. The performance and applicability of this novel 48-plex recombinant antibody array platform design was demonstrated in a first clinical application targeting SLE nephritis, a severe chronic autoimmune connective tissue disorder, as the model disease. To this end, crude, directly biotinylated serum samples were targeted. The results showed that the miniaturized and multiplexed array platform displayed adequate performance, and that SLE-associated serum biomarker panels reflecting the disease process could be deciphered, outlining the use of miniaturized antibody arrays for disease proteomics and biomarker discovery.

Schizophrenia proteomics: biomarkers on the path to laboratory medicine?

PubMed Central

Lakhan, Shaheen Emmanuel

2006-01-01

Over two million Americans are afflicted with schizophrenia, a debilitating mental health disorder with a unique symptomatic and epidemiological profile. Genomics studies have hinted towards candidate schizophrenia susceptibility chromosomal loci and genes. Modern proteomic tools, particularly mass spectrometry and expression scanning, aim to identify both pathogenic-revealing and diagnostically significant biomarkers. Only a few studies on basic proteomics have been conducted for psychiatric disorders relative to the plethora of cancer specific experiments. One such proteomic utility enables the discovery of proteins and biological marker fingerprinting profiling techniques (SELDI-TOF-MS), and then subjects them to tandem mass spectrometric fragmentation and de novo protein sequencing (MALDI-TOF/TOF-MS) for the accurate identification and characterization of the proteins. Such utilities can explain the pathogenesis of neuro-psychiatric disease, provide more objective testing methods, and further demonstrate a biological basis to mental illness. Although clinical proteomics in schizophrenia have yet to reveal a biomarker with diagnostic specificity, methods that better characterize the disorder using endophenotypes can advance findings. Schizophrenia biomarkers could potentially revolutionize its psychopharmacology, changing it into a more hypothesis and genomic/proteomic-driven science. PMID:16846510

Proteomic Workflows for Biomarker Identification Using Mass Spectrometry — Technical and Statistical Considerations during Initial Discovery

PubMed Central

Orton, Dennis J.; Doucette, Alan A.

2013-01-01

Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification. PMID:28250400

Differential representation of liver proteins in obese human subjects suggests novel biomarkers and promising targets for drug development in obesity.

PubMed

Caira, Simonetta; Iannelli, Antonio; Sciarrillo, Rosaria; Picariello, Gianluca; Renzone, Giovanni; Scaloni, Andrea; Addeo, Pietro

2017-12-01

The proteome of liver biopsies from human obese (O) subjects has been compared to those of nonobese (NO) subjects using two-dimensional gel electrophoresis (2-DE). Differentially represented proteins were identified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS)-based peptide mass fingerprinting (PMF) and nanoflow-liquid chromatography coupled to electrospray-tandem mass spectrometry (nLC-ESI-MS/MS). Overall, 61 gene products common to all of the liver biopsies were identified within 65 spots, among which 25 ones were differently represented between O and NO subjects. In particular, over-representation of short-chain acyl-CoA dehydrogenase, Δ(3,5)-Δ(2,4)dienoyl-CoA isomerase, acetyl-CoA acetyltransferase, glyoxylate reductase/hydroxypyruvate reductase, fructose-biphosphate aldolase B, peroxiredoxin I, protein DJ-1, catalase, α- and β-hemoglobin subunits, 3-mercaptopyruvate S-transferase, calreticulin, aminoacylase 1, phenazine biosynthesis-like domain-containing protein and a form of fatty acid-binding protein, together with downrepresentation of glutamate dehydrogenase, glutathione S-transferase A1, S-adenosylmethionine synthase 1A and a form of apolipoprotein A-I, was associated with the obesity condition. Some of these metabolic enzymes and antioxidant proteins have already been identified as putative diagnostic markers of liver dysfunction in animal models of steatosis or obesity, suggesting additional investigations on their role in these syndromes. Their differential representation in human liver was suggestive of their consideration as obesity human biomarkers and for the development of novel antiobesity drugs.

The clinical performance evaluation of novel protein chips for eleven biomarkers detection and the diagnostic model study.

PubMed

Luo, Yuan; Zhu, Xu; Zhang, Pengjun; Shen, Qian; Wang, Zi; Wen, Xinyu; Wang, Ling; Gao, Jing; Dong, Jin; Yang, Caie; Wu, Tangming; Zhu, Zheng; Tian, Yaping

2015-01-01

We aimed to develop and validate two novel protein chips, which are based on microarray chemiluminescence immunoassay and can simultaneously detected 11 biomarkers, and then to evaluate their clinical diagnostic value by comparing with the traditional methods. Protein chips were evaluated for limit of detection, specificity, common interferences, linearity, precision and accuracy. 11 biomarkers were simultaneously detected by traditional methods and protein chips in 3683 samples, which included 1723 cancer patients, 1798 benign diseases patients and 162 healthy controls. After assay validation, protein chips demonstrated high sensitivity, high specificity, good linearity, low imprecision and were free of common interferences. Compared with the traditional methods, protein chips have good correlation in the detection of all the 13 kinds of biomarkers (r≥0.935, P<0.001). For specific cancer detection, there were no statistically significant differences between the traditional method and novel protein chips, except that male protein chip showed significantly better diagnostic value on NSE detection (P=0.004) but significantly worse value on pro-GRP detection (P=0.012), female chip showed significantly better diagnostic value on pro-GRP detection (P=0.005). Furthermore, both male and female multivariate diagnostic models had significantly better diagnostic value than single detection of PGI, PG II, pro-GRP, NSE and CA125 (P<0.05). In addition, male models had significantly better diagnostic value than single CA199 and free-PSA (P<0.05), while female models observed significantly better diagnostic value than single CA724 and β-HCG (P<0.05). For total disease or cancer detection, the AUC of multivariate logistic regression for the male and female disease detection was 0.981 (95% CI: 0.975-0.987) and 0.836 (95% CI: 0.798-0.874), respectively. While, that for total cancer detection was 0.691 (95% CI: 0.666-0.717) and 0.753 (95% CI: 0.731-0.775), respectively. The new

The clinical performance evaluation of novel protein chips for eleven biomarkers detection and the diagnostic model study

PubMed Central

Luo, Yuan; Zhu, Xu; Zhang, Pengjun; Shen, Qian; Wang, Zi; Wen, Xinyu; Wang, Ling; Gao, Jing; Dong, Jin; Yang, Caie; Wu, Tangming; Zhu, Zheng; Tian, Yaping

2015-01-01

We aimed to develop and validate two novel protein chips, which are based on microarray chemiluminescence immunoassay and can simultaneously detected 11 biomarkers, and then to evaluate their clinical diagnostic value by comparing with the traditional methods. Protein chips were evaluated for limit of detection, specificity, common interferences, linearity, precision and accuracy. 11 biomarkers were simultaneously detected by traditional methods and protein chips in 3683 samples, which included 1723 cancer patients, 1798 benign diseases patients and 162 healthy controls. After assay validation, protein chips demonstrated high sensitivity, high specificity, good linearity, low imprecision and were free of common interferences. Compared with the traditional methods, protein chips have good correlation in the detection of all the 13 kinds of biomarkers (r≥0.935, P<0.001). For specific cancer detection, there were no statistically significant differences between the traditional method and novel protein chips, except that male protein chip showed significantly better diagnostic value on NSE detection (P=0.004) but significantly worse value on pro-GRP detection (P=0.012), female chip showed significantly better diagnostic value on pro-GRP detection (P=0.005). Furthermore, both male and female multivariate diagnostic models had significantly better diagnostic value than single detection of PGI, PG II, pro-GRP, NSE and CA125 (P<0.05). In addition, male models had significantly better diagnostic value than single CA199 and free-PSA (P<0.05), while female models observed significantly better diagnostic value than single CA724 and β-HCG (P<0.05). For total disease or cancer detection, the AUC of multivariate logistic regression for the male and female disease detection was 0.981 (95% CI: 0.975-0.987) and 0.836 (95% CI: 0.798-0.874), respectively. While, that for total cancer detection was 0.691 (95% CI: 0.666-0.717) and 0.753 (95% CI: 0.731-0.775), respectively. The new

A DNA aptamer recognising a malaria protein biomarker can function as part of a DNA origami assembly

PubMed Central

Godonoga, Maia; Lin, Ting-Yu; Oshima, Azusa; Sumitomo, Koji; Tang, Marco S. L.; Cheung, Yee-Wai; Kinghorn, Andrew B.; Dirkzwager, Roderick M.; Zhou, Cunshan; Kuzuya, Akinori; Tanner, Julian A.; Heddle, Jonathan G.

2016-01-01

DNA aptamers have potential for disease diagnosis and as therapeutics, particularly when interfaced with programmable molecular technology. Here we have combined DNA aptamers specific for the malaria biomarker Plasmodium falciparum lactate dehydrogenase (PfLDH) with a DNA origami scaffold. Twelve aptamers that recognise PfLDH were integrated into a rectangular DNA origami and atomic force microscopy demonstrated that the incorporated aptamers preserve their ability to specifically bind target protein. Captured PfLDH retained enzymatic activity and protein-aptamer binding was observed dynamically using high-speed AFM. This work demonstrates the ability of DNA aptamers to recognise a malaria biomarker whilst being integrated within a supramolecular DNA scaffold, opening new possibilities for malaria diagnostic approaches based on DNA nanotechnology. PMID:26891622

Protein S100B in umbilical cord blood as a potential biomarker of hypoxic-ischemic encephalopathy in asphyxiated newborns.

PubMed

Zaigham, Mehreen; Lundberg, Fredrik; Olofsson, Per

2017-09-01

Neonatal hypoxic ischemic encephalopathy (HIE) is a devastating condition resulting from a sustained lack of oxygen during birth. The interest in identifying a relevant biomarker of HIE has thrown into limelight the role of protein S100B as a clinical diagnostic marker of hypoxic brain damage in neonates. To evaluate the diagnostic value of protein S100B, measured in umbilical cord blood immediately after birth, as a useful biomarker in the diagnosis of HIE Sarnat stages II-III as well as a marker for long-term mortality and morbidity. Protein S100B was analyzed in cord blood sampled at birth from 13 newborns later diagnosed with stage II-III HIE and compared with 21 healthy controls. S100B concentrations were related to cord artery pH, amplitude-integrated electroencephalography (aEEG), stage of HIE, and death/sequelae up to an age of 6years. Both parametric and non-parametric statistics were used with a two-sided P<0.05 considered significant. The difference in S100B concentration was marginally statistically significant between HIE cases and controls (P=0.056). Cord blood acidosis (P=0.046), aEEG pattern severity (P=0.030), HIE severity (P=0.027), and condition at 6-year follow-up (healthy/permanent sequelae/death; P=0.027) were all related to an increase in S100B concentration. Protein S100B in neonates suffering from HIE stages II-III appeared elevated in umbilical cord blood at birth. The S100B concentrations were positively associated to the severity of disease and the risk of suffering from neurodevelopmental sequelae and even death. Copyright © 2017. Published by Elsevier B.V.

Proteomic analysis of cerebrospinal fluid from children with central nervous system tumors identifies candidate proteins relating to tumor metastatic spread.

PubMed

Spreafico, Filippo; Bongarzone, Italia; Pizzamiglio, Sara; Magni, Ruben; Taverna, Elena; De Bortoli, Maida; Ciniselli, Chiara M; Barzanò, Elena; Biassoni, Veronica; Luchini, Alessandra; Liotta, Lance A; Zhou, Weidong; Signore, Michele; Verderio, Paolo; Massimino, Maura

2017-07-11

Central nervous system (CNS) tumors are the most common solid tumors in childhood. Since the sensitivity of combined cerebrospinal fluid (CSF) cytology and radiological neuroimaging in detecting meningeal metastases remains relatively low, we sought to characterize the CSF proteome of patients with CSF tumors to identify biomarkers predictive of metastatic spread. CSF samples from 27 children with brain tumors and 13 controls (extra-CNS non-Hodgkin lymphoma) were processed using core-shell hydrogel nanoparticles, and analyzed with reverse-phase liquid chromatography/electrospray tandem mass spectrometry (LC-MS/MS). Candidate proteins were identified with Fisher's exact test and/or a univariate logistic regression model. Reverse phase protein array (RPPA), Western blot (WB), and ELISA were used in the training set and in an independent set of CFS samples (60 cases, 14 controls) to validate our discovery findings. Among the 558 non-redundant proteins identified by LC-MS/MS, 147 were missing from the CSF database at http://www.biosino.org. Fourteen of the 26 final top-candidate proteins were chosen for validation with WB, RPPA and ELISA methods. Six proteins (type 1 collagen, insulin-like growth factor binding protein 4, procollagen C-endopeptidase enhancer 1, glial cell-line derived neurotrophic factor receptor α2, inter-alpha-trypsin inhibitor heavy chain 4, neural proliferation and differentiation control protein-1) revealed the ability to discriminate metastatic cases from controls. Combining a unique dataset of CSFs from pediatric CNS tumors with a novel enabling nanotechnology led us to identify CSF proteins potentially related to metastatic status.

Identification of specific bovine blood biomarkers with a non-targeted approach using HPLC ESI tandem mass spectrometry.

PubMed

Lecrenier, M C; Marbaix, H; Dieu, M; Veys, P; Saegerman, C; Raes, M; Baeten, V

2016-12-15

Animal by-products are valuable protein sources in animal nutrition. Among them are blood products and blood meal, which are used as high-quality material for their beneficial effects on growth and health. Within the framework of the feed ban relaxation, the development of complementary methods in order to refine the identification of processed animal proteins remains challenging. The aim of this study was to identify specific biomarkers that would allow the detection of bovine blood products and processed animal proteins using tandem mass spectrometry. Seventeen biomarkers were identified: nine peptides for bovine plasma powder; seven peptides for bovine haemoglobin powder, including six peptides for bovine blood meal; and one peptide for porcine blood. They were not detected in several commercial compound feed or feed materials, such as blood by-products of other animal origins, milk-derived products and fish meal. These biomarkers could be used for developing a species-specific and blood-specific detection method. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of MicroRNA as Sepsis Biomarker Based on miRNAs Regulatory Network Analysis

PubMed Central

Huang, Jie; Sun, Zhandong; Yan, Wenying; Zhu, Yujie; Lin, Yuxin; Chen, Jiajai; Shen, Bairong

2014-01-01

Sepsis is regarded as arising from an unusual systemic response to infection but the physiopathology of sepsis remains elusive. At present, sepsis is still a fatal condition with delayed diagnosis and a poor outcome. Many biomarkers have been reported in clinical application for patients with sepsis, and claimed to improve the diagnosis and treatment. Because of the difficulty in the interpreting of clinical features of sepsis, some biomarkers do not show high sensitivity and specificity. MicroRNAs (miRNAs) are small noncoding RNAs which pair the sites in mRNAs to regulate gene expression in eukaryotes. They play a key role in inflammatory response, and have been validated to be potential sepsis biomarker recently. In the present work, we apply a miRNA regulatory network based method to identify novel microRNA biomarkers associated with the early diagnosis of sepsis. By analyzing the miRNA expression profiles and the miRNA regulatory network, we obtained novel miRNAs associated with sepsis. Pathways analysis, disease ontology analysis, and protein-protein interaction network (PIN) analysis, as well as ROC curve, were exploited to testify the reliability of the predicted miRNAs. We finally identified 8 novel miRNAs which have the potential to be sepsis biomarkers. PMID:24809055

Identifying Key Attributes for Protein Beverages.

PubMed

Oltman, A E; Lopetcharat, K; Bastian, E; Drake, M A

2015-06-01

This study identified key attributes of protein beverages and evaluated effects of priming on liking of protein beverages. An adaptive choice-based conjoint study was conducted along with Kano analysis to gain insight on protein beverage consumers (n = 432). Attributes evaluated included label claim, protein type, amount of protein, carbohydrates, sweeteners, and metabolic benefits. Utility scores for levels and importance scores for attributes were determined. Subsequently, two pairs of clear acidic whey protein beverages were manufactured that differed by age of protein source or the amount of whey protein per serving. Beverages were evaluated by 151 consumers on two occasions with or without priming statements. One priming statement declared "great flavor," the other priming statement declared 20 g protein per serving. A two way analysis of variance was applied to discern the role of each priming statement. The most important attribute for protein beverages was sweetener type, followed by amount of protein, followed by type of protein followed by label claim. Beverages with whey protein, naturally sweetened, reduced sugar and ≥15 g protein per serving were most desired. Three consumer clusters were identified, differentiated by their preferences for protein type, sweetener and amount of protein. Priming statements positively impacted concept liking (P < 0.05) but had no effect on overall liking (P > 0.05). Consistent with trained panel profiles of increased cardboard flavor with higher protein content, consumers liked beverages with 10 g protein more than beverages with 20 g protein (6.8 compared with 5.7, P < 0.05). Protein beverages must have desirable flavor for wide consumer appeal. © 2015 Institute of Food Technologists®

Collecting Protein Biomarkers in Breath Using Electret Filters: A Preliminary Method on New Technical Model and Human Study.

PubMed

Li, Wang; Pi, Xitian; Qiao, Panpan; Liu, Hongying

2016-01-01

Biomarkers in exhaled breath are useful for respiratory disease diagnosis in human volunteers. Conventional methods that collect non-volatile biomarkers, however, necessitate an extensive dilution and sanitation processes that lowers collection efficiencies and convenience of use. Electret filter emerged in recent decade to collect virus biomarkers in exhaled breath given its simplicity and effectiveness. To investigate the capability of electret filters to collect protein biomarkers, a model that consists of an atomizer that produces protein aerosol and an electret filter that collects albumin and carcinoembryonic antigen-a typical biomarker in lung cancer development- from the atomizer is developed. A device using electret filter as the collecting medium is designed to collect human albumin from exhaled breath of 6 volunteers. Comparison of the collecting ability between the electret filter method and other 2 reported methods is finally performed based on the amounts of albumin collected from human exhaled breath. In conclusion, a decreasing collection efficiency ranging from 17.6% to 2.3% for atomized albumin aerosol and 42% to 12.5% for atomized carcinoembryonic antigen particles is found; moreover, an optimum volume of sampling human exhaled breath ranging from 100 L to 200 L is also observed; finally, the self-designed collecting device shows a significantly better performance in collecting albumin from human exhaled breath than the exhaled breath condensate method (p<0.05) but is not significantly more effective than reported 3-stage impactor method (p>0.05). In summary, electret filters are potential in collecting non-volatile biomarkers in human exhaled breath not only because it was simpler, cheaper and easier to use than traditional methods but also for its better collecting performance.

Integration of co-localized glandular morphometry and protein biomarker expression in immunofluorescent images for prostate cancer prognosis

NASA Astrophysics Data System (ADS)

Scott, Richard; Khan, Faisal M.; Zeineh, Jack; Donovan, Michael; Fernandez, Gerardo

2015-03-01

Immunofluorescent (IF) image analysis of tissue pathology has proven to be extremely valuable and robust in developing prognostic assessments of disease, particularly in prostate cancer. There have been significant advances in the literature in quantitative biomarker expression as well as characterization of glandular architectures in discrete gland rings. However, while biomarker and glandular morphometric features have been combined as separate predictors in multivariate models, there is a lack of integrative features for biomarkers co-localized within specific morphological sub-types; for example the evaluation of androgen receptor (AR) expression within Gleason 3 glands only. In this work we propose a novel framework employing multiple techniques to generate integrated metrics of morphology and biomarker expression. We demonstrate the utility of the approaches in predicting clinical disease progression in images from 326 prostate biopsies and 373 prostatectomies. Our proposed integrative approaches yield significant improvements over existing IF image feature metrics. This work presents some of the first algorithms for generating innovative characteristics in tissue diagnostics that integrate co-localized morphometry and protein biomarker expression.

Development of protein biomarkers in cerebrospinal fluid for secondary progressive multiple sclerosis using selected reaction monitoring mass spectrometry (SRM-MS)

PubMed Central

2012-01-01

Background Multiple sclerosis (MS) is a chronic inflammatory disorder of the central nervous system (CNS). It involves damage to the myelin sheath surrounding axons and to the axons themselves. MS most often presents with a series of relapses and remissions but then evolves over a variable period of time into a slowly progressive form of neurological dysfunction termed secondary progressive MS (SPMS). The reasons for this change in clinical presentation are unclear. The absence of a diagnostic marker means that there is a lag time of several years before the diagnosis of SPMS can be established. At the same time, understanding the mechanisms that underlie SPMS is critical to the development of rational therapies for this untreatable stage of the disease. Results Using high performance liquid chromatography-coupled mass spectrometry (HPLC); we have established a highly specific and sensitive selected reaction monitoring (SRM) assay. Our multiplexed SRM assay has facilitated the simultaneous detection of surrogate peptides originating from 26 proteins present in cerebrospinal fluid (CSF). Protein levels in CSF were generally ~200-fold lower than that in human sera. A limit of detection (LOD) was determined to be as low as one femtomol. We processed and analysed CSF samples from a total of 22 patients with SPMS, 7 patients with SPMS treated with lamotrigine, 12 patients with non-inflammatory neurological disorders (NIND) and 10 healthy controls (HC) for the levels of these 26 selected potential protein biomarkers. Our SRM data found one protein showing significant difference between SPMS and HC, three proteins differing between SPMS and NIND, two proteins between NIND and HC, and 11 protein biomarkers showing significant difference between a lamotrigine-treated and untreated SPMS group. Principal component analysis (PCA) revealed that these 26 proteins were correlated, and could be represented by four principal components. Overall, we established an efficient platform

Use of a Combination Biomarker Algorithm To Identify Medical Intensive Care Unit Patients with Suspected Sepsis at Very Low Likelihood of Bacterial Infection

PubMed Central

Nachamkin, Irving; Coffin, Susan E.; Gerber, Jeffrey S.; Fuchs, Barry; Garrigan, Charles; Han, Xiaoyan; Bilker, Warren B.; Wise, Jacqueleen; Tolomeo, Pam; Lautenbach, Ebbing

2015-01-01

Sepsis remains a diagnostic challenge in the intensive care unit (ICU), and the use of biomarkers may help in differentiating bacterial sepsis from other causes of systemic inflammatory syndrome (SIRS). The goal of this study was to assess test characteristics of a number of biomarkers for identifying ICU patients with a very low likelihood of bacterial sepsis. A prospective cohort study was conducted in a medical ICU of a university hospital. Immunocompetent patients with presumed bacterial sepsis were consecutively enrolled from January 2012 to May 2013. Concentrations of nine biomarkers (α-2 macroglobulin, C-reactive protein [CRP], ferritin, fibrinogen, haptoglobin, procalcitonin [PCT], serum amyloid A, serum amyloid P, and tissue plasminogen activator) were determined at baseline and at 24 h, 48 h, and 72 h after enrollment. Performance characteristics were calculated for various combinations of biomarkers for discrimination of bacterial sepsis from other causes of SIRS. Seventy patients were included during the study period; 31 (44%) had bacterial sepsis, and 39 (56%) had other causes of SIRS. PCT and CRP values were significantly higher at all measured time points in patients with bacterial sepsis. A number of combinations of PCT and CRP, using various cutoff values and measurement time points, demonstrated high negative predictive values (81.1% to 85.7%) and specificities (63.2% to 79.5%) for diagnosing bacterial sepsis. Combinations of PCT and CRP demonstrated a high ability to discriminate bacterial sepsis from other causes of SIRS in medical ICU patients. Future studies should focus on the use of these algorithms to improve antibiotic use in the ICU setting. PMID:26239984

Serum Antibody Biomarkers for ASD

DTIC Science & Technology

2015-10-01

autism blood biomarker. In addition, we have identified two new proteins that are linked to ASD. 15. SUBJECT TERMS ASD, autism spectrum disorders . TD...4 8. Appendices…………………………………………………………. 5 3 Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental disorder ...immune responses in young children with autism spectrum disorders : their relationship to gastrointestinal symptoms and dietary intervention

Melanoma Biomolecules: Independently Identified but Functionally Intertwined

PubMed Central

Dye, Danielle E.; Medic, Sandra; Ziman, Mel; Coombe, Deirdre R.

2013-01-01

The majority of patients diagnosed with melanoma present with thin lesions and generally these patients have a good prognosis. However, 5% of patients with early melanoma (<1 mm thick) will have recurrence and die within 10 years, despite no evidence of local or metastatic spread at the time of diagnosis. Thus, there is a need for additional prognostic markers to help identify those patients that may be at risk of recurrent disease. Many studies and several meta-analyses have compared gene and protein expression in melanocytes, naevi, primary, and metastatic melanoma in an attempt to find informative prognostic markers for these patients. However, although a large number of putative biomarkers have been described, few of these molecules are informative when used in isolation. The best approach is likely to involve a combination of molecules. We believe one approach could be to analyze the expression of a group of interacting proteins that regulate different aspects of the metastatic pathway. This is because a primary lesion expressing proteins involved in multiple stages of metastasis may be more likely to lead to secondary disease than one that does not. This review focuses on five putative biomarkers – melanoma cell adhesion molecule (MCAM), galectin-3 (gal-3), matrix metalloproteinase 2 (MMP-2), chondroitin sulfate proteoglycan 4 (CSPG4), and paired box 3 (PAX3). The goal is to provide context around what is known about the contribution of these biomarkers to melanoma biology and metastasis. Although each of these molecules have been independently identified as likely biomarkers, it is clear from our analyses that each are closely linked with each other, with intertwined roles in melanoma biology. PMID:24069584

Detecting Blood-Based Biomarkers in Metastatic Breast Cancer: A Systematic Review of Their Current Status and Clinical Utility

PubMed Central

Berghuis, A. M. Sofie; Koffijberg, Hendrik; Prakash, Jai; Terstappen, Leon W. M. M.; IJzerman, Maarten J.

2017-01-01

Reviews on circulating biomarkers in breast cancer usually focus on one single biomarker or a selective group of biomarkers. An overview summarizing the discovery and evaluation of all blood-based biomarkers in metastatic breast cancer is lacking. This systematic review aims to identify the available evidence of known blood-based biomarkers in metastatic breast cancer, regarding their clinical utility and state-of-the-art position in the validation process. The initial search yielded 1078 original studies, of which 420 were assessed for eligibility. A total of 320 studies were included in the final synthesis. A Development, Evaluation and Application Chart (DEAC) of all biomarkers was developed. Most studies focus on identifying new biomarkers and search for relations between these biomarkers and traditional molecular characteristics. Biomarkers are usually investigated in only one study (68.8%). Only 9.8% of all biomarkers was investigated in more than five studies. Circulating tumor cells, gene expression within tumor cells and the concentration of secreted proteins are the most frequently investigated biomarkers in liquid biopsies. However, there is a lack of studies focusing on identifying the clinical utility of these biomarkers, by which the additional value still seems to be limited according to the investigated evidence. PMID:28208771

Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

NASA Astrophysics Data System (ADS)

Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.; Baker, Erin S.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

2018-05-01

In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. [Figure not available: see fulltext.

Development of Diagnostic Biomarkers for Detecting Diabetic Retinopathy at Early Stages Using Quantitative Proteomics

PubMed Central

Min, Hophil; Kim, Sang Jin; Oh, Sohee; Kim, Kyunggon; Yu, Hyeong Gon; Park, Taesung; Kim, Youngsoo

2016-01-01

Diabetic retinopathy (DR) is a common microvascular complication caused by diabetes mellitus (DM) and is a leading cause of vision impairment and loss among adults. Here, we performed a comprehensive proteomic analysis to discover biomarkers for DR. First, to identify biomarker candidates that are specifically expressed in human vitreous, we performed data-mining on both previously published DR-related studies and our experimental data; 96 proteins were then selected. To confirm and validate the selected biomarker candidates, candidates were selected, confirmed, and validated using plasma from diabetic patients without DR (No DR) and diabetics with mild or moderate nonproliferative diabetic retinopathy (Mi or Mo NPDR) using semiquantitative multiple reaction monitoring (SQ-MRM) and stable-isotope dilution multiple reaction monitoring (SID-MRM). Additionally, we performed a multiplex assay using 15 biomarker candidates identified in the SID-MRM analysis, which resulted in merged AUC values of 0.99 (No DR versus Mo NPDR) and 0.93 (No DR versus Mi and Mo NPDR). Although further validation with a larger sample size is needed, the 4-protein marker panel (APO4, C7, CLU, and ITIH2) could represent a useful multibiomarker model for detecting the early stages of DR. PMID:26665153

Quantitative Proteomic Analysis of Differentially Expressed Protein Profiles Involved in Pancreatic Ductal Adenocarcinoma

PubMed Central

Kuo, Kung-Kai; Kuo, Chao-Jen; Chiu, Chiang-Yen; Liang, Shih-Shin; Huang, Chun-Hao; Chi, Shu-Wen; Tsai, Kun-Bow; Chen, Chiao-Yun; Hsi, Edward; Cheng, Kuang-Hung; Chiou, Shyh-Horng

2016-01-01

Objectives The aim of this study was to identify differentially expressed proteins among various stages of pancreatic ductal adenocarcinoma (PDAC) by shotgun proteomics using nano-liquid chromatography coupled tandem mass spectrometry and stable isotope dimethyl labeling. Methods Differentially expressed proteins were identified and compared based on the mass spectral differences of their isotope-labeled peptide fragments generated from protease digestion. Results Our quantitative proteomic analysis of the differentially expressed proteins with stable isotope (deuterium/hydrogen ratio, ≥2) identified a total of 353 proteins, with at least 5 protein biomarker proteins that were significantly differentially expressed between cancer and normal mice by at least a 2-fold alteration. These 5 protein biomarker candidates include α-enolase, α-catenin, 14-3-3 β, VDAC1, and calmodulin with high confidence levels. The expression levels were also found to be in agreement with those examined by Western blot and histochemical staining. Conclusions The systematic decrease or increase of these identified marker proteins may potentially reflect the morphological aberrations and diseased stages of pancreas carcinoma throughout progressive developments leading to PDAC. The results would form a firm foundation for future work concerning validation and clinical translation of some identified biomarkers into targeted diagnosis and therapy for various stages of PDAC. PMID:26262590

iTRAQ-Based Proteomics Reveals Novel Biomarkers for Idiopathic Pulmonary Fibrosis

PubMed Central

Niu, Rui; Liu, Ying; Zhang, Ying; Zhang, Yuan; Wang, Hui; Wang, Yongbin; Wang, Wei; Li, Xiaohui

2017-01-01

Idiopathic pulmonary fibrosis (IPF) is a gradual lung disease with a survival of less than 5 years post-diagnosis for most patients. Poor molecular description of IPF has led to unsatisfactory interpretation of the pathogenesis of this disease, resulting in the lack of successful treatments. The objective of this study was to discover novel noninvasive biomarkers for the diagnosis of IPF. We employed a coupled isobaric tag for relative and absolute quantitation (iTRAQ)-liquid chromatography–tandem mass spectrometry (LC–MS/MS) approach to examine protein expression in patients with IPF. A total of 97 differentially expressed proteins (38 upregulated proteins and 59 downregulated proteins) were identified in the serum of IPF patients. Using String software, a regulatory network containing 87 nodes and 244 edges was built, and the functional enrichment showed that differentially expressed proteins were predominantly involved in protein activation cascade, regulation of response to wounding and extracellular components. A set of three most significantly upregulated proteins (HBB, CRP and SERPINA1) and four most significantly downregulated proteins (APOA2, AHSG, KNG1 and AMBP) were selected for validation in an independent cohort of IPF and other lung diseases using ELISA test. The results confirmed the iTRAQ profiling results and AHSG, AMBP, CRP and KNG1 were found as specific IPF biomarkers. ROC analysis indicated the diagnosis potential of the validated biomarkers. The findings of this study will contribute in understanding the pathogenesis of IPF and facilitate the development of therapeutic targets. PMID:28122020

iTRAQ-Based Proteomics Reveals Novel Biomarkers for Idiopathic Pulmonary Fibrosis.

PubMed

Niu, Rui; Liu, Ying; Zhang, Ying; Zhang, Yuan; Wang, Hui; Wang, Yongbin; Wang, Wei; Li, Xiaohui

2017-01-01

Idiopathic pulmonary fibrosis (IPF) is a gradual lung disease with a survival of less than 5 years post-diagnosis for most patients. Poor molecular description of IPF has led to unsatisfactory interpretation of the pathogenesis of this disease, resulting in the lack of successful treatments. The objective of this study was to discover novel noninvasive biomarkers for the diagnosis of IPF. We employed a coupled isobaric tag for relative and absolute quantitation (iTRAQ)-liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach to examine protein expression in patients with IPF. A total of 97 differentially expressed proteins (38 upregulated proteins and 59 downregulated proteins) were identified in the serum of IPF patients. Using String software, a regulatory network containing 87 nodes and 244 edges was built, and the functional enrichment showed that differentially expressed proteins were predominantly involved in protein activation cascade, regulation of response to wounding and extracellular components. A set of three most significantly upregulated proteins (HBB, CRP and SERPINA1) and four most significantly downregulated proteins (APOA2, AHSG, KNG1 and AMBP) were selected for validation in an independent cohort of IPF and other lung diseases using ELISA test. The results confirmed the iTRAQ profiling results and AHSG, AMBP, CRP and KNG1 were found as specific IPF biomarkers. ROC analysis indicated the diagnosis potential of the validated biomarkers. The findings of this study will contribute in understanding the pathogenesis of IPF and facilitate the development of therapeutic targets.

A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma.

PubMed

Liu, Wan-Ting; Wang, Yang; Zhang, Jing; Ye, Fei; Huang, Xiao-Hui; Li, Bin; He, Qing-Yu

2018-07-01

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA + /CDK1 + and CENPA + /CDC20 + were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Proteomic Characterization of Annexin l (ANX1) and Heat Shock Protein 27 (HSP27) as Biomarkers for Invasive Hepatocellular Carcinoma Cells.

PubMed

Wang, Ruo-Chiau; Huang, Chien-Yu; Pan, Tai-Long; Chen, Wei-Yu; Ho, Chun-Te; Liu, Tsan-Zon; Chang, Yu-Jia

2015-01-01

To search for reliable biomarkers and drug targets for management of hepatocellular carcinoma (HCC), we performed a global proteomic analysis of a pair of HCC cell lines with distinct differentiation statuses using 2-DE coupled with MALDI-TOF MS. In total, 106 and 55 proteins were successfully identified from the total cell lysate and the cytosolic, nuclear and membrane fractions in well-differentiated (HepG2) and poorly differentiated (SK-Hep-1) HCC clonal variants, respectively. Among these proteins, nine spots corresponding to proteins differentially expressed between HCC cell types were selected and confirmed by immunofluorescence staining and western blotting. Notably, Annexin 1 (ANX1), ANX-2, vimentin and stress-associated proteins, such as GRP78, HSP75, HSC-70, protein disulfide isomerase (PDI), and heat shock protein-27 (HSP27), were exclusively up-regulated in SK-Hep-1 cells. Elevated levels of ANX-4 and antioxidant/metabolic enzymes, such as MnSOD, peroxiredoxin, NADP-dependent isocitrate dehydrogenase, α-enolase and UDP-glucose dehydrogenase, were observed in HepG2 cells. We functionally demonstrated that ANX1 and HSP27 were abundantly overexpressed only in highly invasive types of HCC cells, such as Mahlavu and SK-Hep-1. Knockdown of ANX1 or HSP27 in HCC cells resulted in a severe reduction in cell migration. The in-vitro observations of ANX1 and HSP27 expressions in HCC sample was demonstrated by immunohistochemical stains performed on HCC tissue microarrays. Poorly differentiated HCC tended to have stronger ANX1 and HSP27 expressions than well-differentiated or moderately differentiated HCC. Collectively, our findings suggest that ANX1 and HSP27 are two novel biomarkers for predicting invasive HCC phenotypes and could serve as potential treatment targets.

A lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform for identification of multiple liver cancer biomarkers in human plasma.

PubMed

Ahn, Yeong Hee; Shin, Park Min; Oh, Na Ree; Park, Gun Wook; Kim, Hoguen; Yoo, Jong Shin

2012-09-18

Aberrantly glycosylated proteins related to liver cancer progression were captured with specific lectin and identified from human plasma by multiple reaction monitoring (MRM) mass spectrometry as multiple biomarkers for hepatocellular carcinoma (HCC). The lectin fractionation for fucosylated protein glycoforms in human plasma was conducted with a fucose-specific aleuria aurantia lectin (AAL). Following tryptic digestion of the lectin-captured fraction, plasma samples from 30 control cases (including 10 healthy, 10 hepatitis B virus [HBV], and 10 cirrhosis cases) and 10 HCC cases were quantitatively analyzed by MRM to identify which glycoproteins are viable HCC biomarkers. A1AG1, AACT, A1AT, and CERU were found to be potent biomarkers to differentiate HCC plasma from control plasmas. The AUROC generated independently from these four biomarker candidates ranged from 0.73 to 0.92. However, the lectin-coupled MRM assay with multiple combinations of biomarker candidates is superior statistically to those generated from the individual candidates with AUROC more than 0.95, which can be an alternative to the immunoassay inevitably requiring tedious development of multiple antibodies against biomarker candidates to be verified. Eventually the lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform was found to be efficient to identify multiple biomarkers from human plasma according to cancer progression. Copyright © 2012 Elsevier B.V. All rights reserved.

Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics.

PubMed

Kirwan, Alan; Utratna, Marta; O'Dwyer, Michael E; Joshi, Lokesh; Kilcoyne, Michelle

2015-01-01

Cancer is the second most common cause of death in developed countries with approximately 14 million newly diagnosed individuals and over 6 million cancer-related deaths in 2012. Many cancers are discovered at a more advanced stage but better survival rates are correlated with earlier detection. Current clinically approved cancer biomarkers are most effective when applied to patients with widespread cancer. Single biomarkers with satisfactory sensitivity and specificity have not been identified for the most common cancers and some biomarkers are ineffective for the detection of early stage cancers. Thus, novel biomarkers with better diagnostic and prognostic performance are required. Aberrant protein glycosylation is well known hallmark of cancer and represents a promising source of potential biomarkers. Glycoproteins enter circulation from tissues or blood cells through active secretion or leakage and patient serum is an attractive option as a source for biomarkers from a clinical and diagnostic perspective. A plethora of technical approaches have been developed to address the challenges of glycosylation structure detection and determination. This review summarises currently utilised glycoprotein biomarkers and novel glycosylation-based biomarkers from the serum glycoproteome under investigation as cancer diagnostics and for monitoring and prognostics and includes details of recent high throughput and other emerging glycoanalytical techniques.

Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics

PubMed Central

Kirwan, Alan; Utratna, Marta; O'Dwyer, Michael E.; Joshi, Lokesh

2015-01-01

Cancer is the second most common cause of death in developed countries with approximately 14 million newly diagnosed individuals and over 6 million cancer-related deaths in 2012. Many cancers are discovered at a more advanced stage but better survival rates are correlated with earlier detection. Current clinically approved cancer biomarkers are most effective when applied to patients with widespread cancer. Single biomarkers with satisfactory sensitivity and specificity have not been identified for the most common cancers and some biomarkers are ineffective for the detection of early stage cancers. Thus, novel biomarkers with better diagnostic and prognostic performance are required. Aberrant protein glycosylation is well known hallmark of cancer and represents a promising source of potential biomarkers. Glycoproteins enter circulation from tissues or blood cells through active secretion or leakage and patient serum is an attractive option as a source for biomarkers from a clinical and diagnostic perspective. A plethora of technical approaches have been developed to address the challenges of glycosylation structure detection and determination. This review summarises currently utilised glycoprotein biomarkers and novel glycosylation-based biomarkers from the serum glycoproteome under investigation as cancer diagnostics and for monitoring and prognostics and includes details of recent high throughput and other emerging glycoanalytical techniques. PMID:26509158

Development of a Multiplexed Liquid Chromatography Multiple-Reaction-Monitoring Mass Spectrometry (LC-MRM/MS) Method for Evaluation of Salivary Proteins as Oral Cancer Biomarkers.

PubMed

Chen, Yi-Ting; Chen, Hsiao-Wei; Wu, Chun-Feng; Chu, Lichieh Julie; Chiang, Wei-Fang; Wu, Chih-Ching; Yu, Jau-Song; Tsai, Cheng-Han; Liang, Kung-Hao; Chang, Yu-Sun; Wu, Maureen; Ou Yang, Wei-Ting

2017-05-01

Multiple (selected) reaction monitoring (MRM/SRM) of peptides is a growing technology for target protein quantification because it is more robust, precise, accurate, high-throughput, and multiplex-capable than antibody-based techniques. The technique has been applied clinically to the large-scale quantification of multiple target proteins in different types of fluids. However, previous MRM-based studies have placed less focus on sample-preparation workflow and analytical performance in the precise quantification of proteins in saliva, a noninvasively sampled body fluid. In this study, we evaluated the analytical performance of a simple and robust multiple reaction monitoring (MRM)-based targeted proteomics approach incorporating liquid chromatography with mass spectrometry detection (LC-MRM/MS). This platform was used to quantitatively assess the biomarker potential of a group of 56 salivary proteins that have previously been associated with human cancers. To further enhance the development of this technology for assay of salivary samples, we optimized the workflow for salivary protein digestion and evaluated quantification performance, robustness and technical limitations in analyzing clinical samples. Using a clinically well-characterized cohort of two independent clinical sample sets (total n = 119), we quantitatively characterized these protein biomarker candidates in saliva specimens from controls and oral squamous cell carcinoma (OSCC) patients. The results clearly showed a significant elevation of most targeted proteins in saliva samples from OSCC patients compared with controls. Overall, this platform was capable of assaying the most highly multiplexed panel of salivary protein biomarkers, highlighting the clinical utility of MRM in oral cancer biomarker research. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Development of a Multiplexed Liquid Chromatography Multiple-Reaction-Monitoring Mass Spectrometry (LC-MRM/MS) Method for Evaluation of Salivary Proteins as Oral Cancer Biomarkers*

PubMed Central

Chen, Hsiao-Wei; Wu, Chun-Feng; Chu, Lichieh Julie; Chiang, Wei-Fang; Wu, Chih-Ching; Yu, Jau-Song; Tsai, Cheng-Han; Liang, Kung-Hao; Chang, Yu-Sun; Wu, Maureen; Ou Yang, Wei-Ting

2017-01-01

Multiple (selected) reaction monitoring (MRM/SRM) of peptides is a growing technology for target protein quantification because it is more robust, precise, accurate, high-throughput, and multiplex-capable than antibody-based techniques. The technique has been applied clinically to the large-scale quantification of multiple target proteins in different types of fluids. However, previous MRM-based studies have placed less focus on sample-preparation workflow and analytical performance in the precise quantification of proteins in saliva, a noninvasively sampled body fluid. In this study, we evaluated the analytical performance of a simple and robust multiple reaction monitoring (MRM)-based targeted proteomics approach incorporating liquid chromatography with mass spectrometry detection (LC-MRM/MS). This platform was used to quantitatively assess the biomarker potential of a group of 56 salivary proteins that have previously been associated with human cancers. To further enhance the development of this technology for assay of salivary samples, we optimized the workflow for salivary protein digestion and evaluated quantification performance, robustness and technical limitations in analyzing clinical samples. Using a clinically well-characterized cohort of two independent clinical sample sets (total n = 119), we quantitatively characterized these protein biomarker candidates in saliva specimens from controls and oral squamous cell carcinoma (OSCC) patients. The results clearly showed a significant elevation of most targeted proteins in saliva samples from OSCC patients compared with controls. Overall, this platform was capable of assaying the most highly multiplexed panel of salivary protein biomarkers, highlighting the clinical utility of MRM in oral cancer biomarker research. PMID:28235782

Identification and Quantification of Preterm Birth Biomarkers in Human Cervicovaginal Fluid by Liquid Chromatography/Tandem Mass Spectrometry

PubMed Central

Shah, Sumit J.; Yu, Kenneth H.; Sangar, Vineet; Parry, Samuel I.; Blair, Ian A.

2009-01-01

Spontaneous preterm birth (PTB) before 37 completed weeks of gestation resulting from preterm labor (PTL) is a leading contributor of perinatal morbidity and mortality. Early identification of at-risk women by reliable screening tests could alleviate this health issue; however, conventional methods such as obstetric history and clinical risk factors, uterine activity monitoring, biochemical markers, and cervical sonography for screening women at risk for PTB have proven unsuccessful in lowering the rate of PTB. Cervicovaginal fluid (CVF) might prove to be a useful, readily available biological fluid for identifying diagnostic PTB biomarkers. Human columnar epithelial endocervical-1 (End1) and vaginal (Vk2) cell secretomes were employed to generate a stable isotope labeled proteome (SILAP) standard to facilitate characterization and relative quantification of proteins present in CVF. The SILAP standard was prepared using stable isotope labeling by amino acids in cell culture (SILAC) of End1 and Vk2 through seven passages. The labeled secreted proteins from both cell lines were combined and characterized by liquid-chromatography-tandem mass spectrometry (LC-MS/MS). 1211 proteins were identified in the End1-Vk2 SILAP standard, with 236 proteins being consistently identified in each of the replicates analyzed. Individual proteins were found to contain < 0.5 % of the endogenous unlabeled forms. Identified proteins were screened to provide a set of fifteen candidates that have either previously been identified as potential PTB biomarkers or could be linked mechanistically to PTB. Stable isotope dilution LC-multiple reaction monitoring (MRM/MS) assays were then developed for conducting relative quantification of the fifteen candidate biomarkers in human CVF samples from term and PTB cases. Three proteins were significantly elevated in PTB cases (desmoplakin isoform 1, stratifin, and thrombospondin 1 precursor), providing a foundation for further validation in larger

Identification and quantification of preterm birth biomarkers in human cervicovaginal fluid by liquid chromatography/tandem mass spectrometry.

PubMed

Shah, Sumit J; Yu, Kenneth H; Sangar, Vineet; Parry, Samuel I; Blair, Ian A

2009-05-01

Spontaneous preterm birth (PTB) before 37 completed weeks of gestation resulting from preterm labor (PTL) is a leading contributor of perinatal morbidity and mortality. Early identification of at-risk women by reliable screening tests could alleviate this health issue; however, conventional methods such as obstetric history and clinical risk factors, uterine activity monitoring, biochemical markers, and cervical sonography for screening women at risk for PTB have proven unsuccessful in lowering the rate of PTB. Cervicovaginal fluid (CVF) might prove to be a useful, readily available biological fluid for identifying diagnostic PTB biomarkers. Human columnar epithelial endocervical-1 (End1) and vaginal (Vk2) cell secretomes were employed to generate a stable isotope labeled proteome (SILAP) standard to facilitate characterization and relative quantification of proteins present in CVF. The SILAP standard was prepared using stable isotope labeling by amino acids in cell culture (SILAC) of End1 and Vk2 through seven passages. The labeled secreted proteins from both cell lines were combined and characterized by liquid-chromatography-tandem mass spectrometry (LC-MS/MS). In total, 1211 proteins were identified in the End1-Vk2 SILAP standard, with 236 proteins being consistently identified in each of the replicates analyzed. Individual proteins were found to contain <0.5% of the endogenous unlabeled forms. Identified proteins were screened to provide a set of 15 candidates that have either previously been identified as potential PTB biomarkers or could be linked mechanistically to PTB. Stable isotope dilution LC-multiple reaction monitoring (MRM/MS) assays were then developed for conducting relative quantification of the 15 candidate biomarkers in human CVF samples from term and PTB cases. Three proteins were significantly elevated in PTB cases (desmoplakin isoform 1, stratifin, and thrombospondin 1 precursor), providing a foundation for further validation in larger patient

Dithiothreitol-based protein equalization technology to unravel biomarkers for bladder cancer.

PubMed

Araújo, J E; López-Fernández, H; Diniz, M S; Baltazar, Pedro M; Pinheiro, Luís Campos; da Silva, Fernando Calais; Carrascal, Mylène; Videira, Paula; Santos, H M; Capelo, J L

2018-04-01

This study aimed to assess the benefits of dithiothreitol (DTT)-based sample treatment for protein equalization to assess potential biomarkers for bladder cancer. The proteome of plasma samples of patients with bladder carcinoma, patients with lower urinary tract symptoms (LUTS) and healthy volunteers, was equalized with dithiothreitol (DTT) and compared. The equalized proteomes were interrogated using two-dimensional gel electrophoresis and matrix assisted laser desorption ionization time of flight mass spectrometry. Six proteins, namely serum albumin, gelsolin, fibrinogen gamma chain, Ig alpha-1 chain C region, Ig alpha-2 chain C region and haptoglobin, were found dysregulated in at least 70% of bladder cancer patients when compared with a pool of healthy individuals. One protein, serum albumin, was found overexpressed in 70% of the patients when the equalized proteome of the healthy pool was compared with the equalized proteome of the LUTS patients. The pathways modified by the proteins differentially expressed were analyzed using Cytoscape. The method here presented is fast, cheap, of easy application and it matches the analytical minimalism rules as outlined by Halls. Orthogonal validation was done using western-blot. Overall, DTT-based protein equalization is a promising methodology in bladder cancer research. Copyright © 2017 Elsevier B.V. All rights reserved.

Biomarkers in Scleroderma: Progressing from Association to Clinical Utility.

PubMed

Ligon, Colin; Hummers, Laura K

2016-03-01

Scleroderma is a heterogenous disease characterized by autoimmunity, a characteristic vasculopathy, and often widely varying extents of deep organ fibrosis. Recent advances in the understanding of scleroderma's evolution have improved the ability to identify subgroups of patients with similar prognosis in order to improve risk stratification, enrich clinical trials for patients likely to benefit from specific therapies, and identify promising therapeutic targets for intervention. High-throughput technologies have recently identified fibrotic and inflammatory effectors in scleroderma that exhibit strong prognostic ability and may be tied to disease evolution. Increasingly, the use of collections of assayed circulating proteins and patterns of gene expression in tissue has replaced single-marker investigations in understanding the evolution of scleroderma and in objectively characterizing disease extent. Lastly, identification of shared patterns of disease evolution has allowed classification of patients into latent disease subtypes, which may allow rapid clinical prognostication and targeted management in both clinical and research settings. The concept of biomarkers in scleroderma is expanding to include nontraditional measures of aggregate protein signatures and disease evolution. This review examines the recent advances in biomarkers with a focus on those approaches poised to guide prospective management or themselves serve as quantitative surrogate disease outcomes.

Development of an Immunoassay for the Kidney Specific Protein myo-Inositol Oxygenase, a Potential Biomarker of Acute Kidney Injury

PubMed Central

Gaut, Joseph P.; Crimmins, Dan L.; Ohlendorf, Matt F.; Lockwood, Christina M.; Griest, Terry A.; Brada, Nancy A.; Hoshi, Masato; Sato, Bryan; Hotchkiss, Richard S.; Jain, Sanjay; Ladenson, Jack H.

2014-01-01

Background Acute kidney injury (AKI) affects 45% of critically ill patients resulting in increased morbidity and mortality. The diagnostic standard, serum creatinine (SCr), is non-specific and may not increase until days after injury. There is significant need for a renal specific AKI biomarker detectable early enough that there would be a potential window for therapeutic intervention. In this study, we sought to identify a renal specific biomarker of AKI. Methods Gene expression data was analyzed from normal mouse tissues to identify kidney specific genes, one of which was Miox. Monoclonal antibodies were generated to recombinant myo-inositol oxygenase (MIOX), and an immunoassay was developed to quantify MIOX in plasma. The immunoassay was tested in animals and retrospectively in patients with and without AKI. Results Kidney tissue specificity of MIOX was supported by Western blot. Immunohistochemistry localized MIOX to the proximal renal tubule. Plasma MIOX, undetectable at baseline, increased 24 hours following AKI in mice. Plasma MIOX was increased in critically ill patients with AKI (12.4 ± 4.3 ng/mL, n=42) compared with patients without AKI (0.5 ± 0.3 ng/mL, n=17) and was highest in patients with oliguric AKI (20.2 ± 7.5 ng/mL, n=23). Plasma MIOX increased 54.3 ± 3.8 hours before the increase in SCr. Conclusions MIOX is a renal specific, proximal tubule protein that is increased in plasma of animals and critically ill patients with AKI. MIOX preceded the elevation in SCr by approximately two days in human patients. Large-scale studies are warranted to further investigate MIOX as an AKI biomarker. PMID:24486646

Neo-epitope Peptides as Biomarkers of Disease Progression for Muscular Dystrophies and Other Myopathies

PubMed Central

Arvanitidis, A.; Henriksen, K.; Karsdal, M.A.; Nedergaard, A.

2016-01-01

For several decades, serological biomarkers of neuromuscular diseases as dystrophies, myopathies and myositis have been limited to routine clinical biochemistry panels. Gauging the pathological progression is a prerequisite for proper treatment and therefore identifying accessible, easy to monitor biomarkers that can predict the disease progression would be an important advancement. Most muscle diseases involve accelerated muscle fiber degradation, inflammation, fatty tissue substitution and/or fibrosis. All these pathological traits have been shown to give rise to serological peptide biomarkers in other tissues, underlining the potential application of existing biomarkers of such traits in muscle disorders. A significant quantity of tissue is involved in these pathological mechanisms alongside with qualitative changes in protein turnover in myofibrillar, extra-cellular matrix and immunological cell protein fractions accompanied by alterations in body fluids. We propose that protein and peptides can leak out of the afflicted muscles and can be of use in diagnosis, prediction of pathology trajectory and treatment efficacy. Proteolytic cleavage systems are especially modulated during a range of muscle pathologies, thereby giving rise to peptides that are differentially released during disease manifestation. Therefore, we believe that pathology-specific post-translational modifications like cleavages can give rise to neoepitope peptides that may represent a promising class of peptides for discovery of biomarkers pertaining to neuromuscular diseases. PMID:27854226

Minimally-invasive biomarker studies in eosinophilic esophagitis: a systematic review.

PubMed

Hines, Brittany T; Rank, Matthew A; Wright, Benjamin L; Marks, Lisa A; Hagan, John B; Straumann, Alex; Greenhawt, Matthew; Dellon, Evan S

2018-05-10

Eosinophilic esophagitis (EoE) is a chronic, inflammatory disease of the esophagus which currently requires repeated endoscopic biopsies for diagnosis and monitoring as no reliable non-invasive markers have been identified. To identify promising minimally-invasive EoE biomarkers and remaining gaps in biomarker validation. We performed a systematic review of EMBASE, Ovid Medline, PubMed, and Web of Science from inception to June 6, 2017. Studies were included if subjects met the 2007 consensus criteria for EoE diagnosis, a minimally-invasive biomarker was assessed, and the study included at least 1 control for comparison. The search identified 2094 studies, with 234 reviewed at full text level, and 49 included in the analysis (20 adult, 19 pediatric, 7 pediatric and adult, and 3 not stated). The majority (26 of 49) were published after 2014. Thirty-five studies included normal controls, 9 analyzed atopic controls, and 29 compared samples from subjects with active and inactive EoE. Minimally-invasive biomarkers were obtained from peripheral blood (n=41 studies), sponge/string samples (3), oral/throat swab secretions (2), breath condensate (2), stool (2), and urine (2). The most commonly reported biomarkers were peripheral blood eosinophils (16), blood and string eosinophil granule proteins (14), and eosinophil surface or intracellular markers (12). EoE biomarkers distinguished active EoE from normal controls in 23 studies, atopic controls in 2 studies, and inactive EoE controls in 20 studies. Several promising minimally-invasive biomarkers for EoE have emerged; however, few are able to differentiate EoE from other atopic diseases. Copyright © 2018. Published by Elsevier Inc.

Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers.

PubMed

Irigoyen, Antonio; Jimenez-Luna, Cristina; Benavides, Manuel; Caba, Octavio; Gallego, Javier; Ortuño, Francisco Manuel; Guillen-Ponce, Carmen; Rojas, Ignacio; Aranda, Enrique; Torres, Carolina; Prados, Jose

2018-01-01

Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

Cytoskeletal proteins in the cerebrospinal fluid as biomarker of multiple sclerosis.

PubMed

Madeddu, Roberto; Farace, Cristiano; Tolu, Paola; Solinas, Giuliana; Asara, Yolande; Sotgiu, Maria Alessandra; Delogu, Lucia Gemma; Prados, Jose Carlos; Sotgiu, Stefano; Montella, Andrea

2013-02-01

The axonal cytoskeleton is a finely organized system, essential for maintaining the integrity of the axon. Axonal degeneration is implicated in the pathogenesis of unremitting disability of multiple sclerosis (MS). Purpose of this study is to evaluate levels of cytoskeletal proteins such as neurofilament light protein (NFL), glial fibrillary acidic protein (GFAP), and β-tubulin (β-Tub) isoforms II and III in the cerebrospinal fluid (CSF) of MS patients and their correlation with MS clinical indices. CSF levels of cytoskeletal proteins were determined in 51 patients: 33 with MS and 18 with other neurological diseases (OND). NFL, GFAP and β-Tub II proteins were significantly higher (p < 0.0001) in MS than in OND group; no significant difference (p > 0.05) was found between MS and OND with regard to β-Tub III. Interestingly, levels of β-Tub III and NFL were higher in progressive than in remitting MS forms; on the contrary, higher levels of β-Tub II and GFAP were found in remitting MS forms. However, with the exception of β-Tub III, all proteins tend to decrease their CSF levels concomitantly with the increasing disability (EDSS) score. Overall, our results might indicate β-Tub II as a potential candidate for diagnostic and β-Tub III as a possible prognostic biomarker of MS. Therefore, further analyses are legitimated and desirable.

Serum Protein KNG1, APOC3, and PON1 as Potential Biomarkers for Yin-Deficiency-Heat Syndrome.

PubMed

Liu, Changming; Mao, Liangen; Ping, Zepeng; Jiang, Tingting; Wang, Chong; Chen, Zhongliang; Li, Zhongjie; Li, Jicheng

2016-01-01

Yin-deficiency-heat (YDH) syndrome is a concept in Traditional Chinese Medicine (TCM) for describing subhealth status. However, there are few efficient diagnostic methods available for confirming YDH syndrome. To explore the novel method for diagnosing YDH syndrome, we applied iTRAQ to observe the serum protein profiles in YDH syndrome rats and confirmed protein levels by ELISA. A total of 92 differentially expressed proteins (63 upregulated proteins and 29 downregulated proteins), which were mainly involved in complement and coagulation cascades and glucose metabolism pathway, were identified by the proteomic experiments. Kininogen 1 (KNG1) was significantly increased ( p < 0.0001), while apolipoprotein C-III (APOC3, p < 0.005) and paraoxonase 1 (PON1, p < 0.001) were significantly decreased in the serum of YDH syndrome rats. The combination of KNG1, APOC3, and PON1 constituted a diagnostic model with 100.0% sensitivity and 85.0% specificity. The results indicated that KNG1, APOC3, and PON1 may act as potential biomarkers for diagnosing YDH syndrome. KNG1 may regulate cytokines and chemokines release in YDH syndrome, and the low levels of PON1 and APOC3 may increase oxidative stress and lipolysis in YDH syndrome, respectively. Our work provides a novel method for YDH syndrome diagnosis and also provides valuable experimental basis to understand the molecular mechanism of YDH syndrome.

Microarray expression analysis and identification of serum biomarkers for Niemann-Pick disease, type C1.

PubMed

Cluzeau, Celine V M; Watkins-Chow, Dawn E; Fu, Rao; Borate, Bhavesh; Yanjanin, Nicole; Dail, Michelle K; Davidson, Cristin D; Walkley, Steven U; Ory, Daniel S; Wassif, Christopher A; Pavan, William J; Porter, Forbes D

2012-08-15

Niemann-Pick disease type C (NPC) is a lysosomal storage disorder characterized by liver disease and progressive neurodegeneration. Deficiency of either NPC1 or NPC2 leads to the accumulation of cholesterol and glycosphingolipids in late endosomes and early lysosomes. In order to identify pathological mechanisms underlying NPC and uncover potential biomarkers, we characterized liver gene expression changes in an Npc1 mouse model at six ages spanning the pathological progression of the disease. We identified altered gene expression at all ages, including changes in asymptomatic, 1-week-old mice. Biological pathways showing early altered gene expression included: lipid metabolism, cytochrome P450 enzymes involved in arachidonic acid and drug metabolism, inflammation and immune responses, mitogen-activated protein kinase and G-protein signaling, cell cycle regulation, cell adhesion and cytoskeleton remodeling. In contrast, apoptosis and oxidative stress appeared to be late pathological processes. To identify potential biomarkers that could facilitate monitoring of disease progression, we focused on a subset of 103 differentially expressed genes that encode secreted proteins. Further analysis identified two secreted proteins with increased serum levels in NPC1 patients: galectin-3 (LGALS3), a pro-inflammatory molecule, and cathepsin D (CTSD), a lysosomal aspartic protease. Elevated serum levels of both proteins correlated with neurological disease severity and appeared to be specific for NPC1. Expression of Lgals3 and Ctsd was normalized following treatment with 2-hydroxypropyl-β-cyclodextrin, a therapy that reduces pathological findings and significantly increases Npc1(-/-) survival. Both LGALS3 and CTSD have the potential to aid in diagnosis and serve as biomarkers to monitor efficacy in therapeutic trials.

Sporadic Inclusion Body Myositis: Possible pathogenesis inferred from biomarkers

PubMed Central

Weihl, Conrad C.; Pestronk, Alan

2013-01-01

Purpose of review The relevance of proteins that accumulate and aggregate in the muscle fibers of patients with sporadic inclusion body myositis (sIBM) is unknown. Many of these proteins also aggregate in other disorders, including Alzheimer’s disease, leading to speculation that sIBM pathogenesis has similarities to neurodegenerative disorders. Our review will discuss current studies on these protein biomarkers and any utility in sIBM diagnosis. Recent findings Two “classical” components of sIBM aggregates (Aβ and phospho-tau) have been re-evaluated. Three additional components of aggregates (TDP-43, p62, and LC3) have been identified. The sensitivity and specificity of these biomarkers has been explored. Two studies suggest that TDP-43 may have clinical utility in distinguishing sIBM from other inflammatory myopathies. Summary The fact that sIBM muscle accumulates multiple protein aggregates with no single protein appearing in every sIBM patient biopsy suggests that it is not presently possible to place pathogenic blame on any single protein (i.e. Aβ or TDP-43). Instead changes in protein homeostasis may lead to the accumulation of different proteins that have a propensity to aggregate in skeletal muscle. Therapies aimed at improving protein homeostasis, instead of targeting a specific protein that may or may not accumulate in all sIBM patients, could be useful future strategies for this devastating and enigmatic disorder. PMID:20664349

High-sensitive factor I and C-reactive protein based biomarkers for coronary artery disease.

PubMed

Zhao, Qing; Du, Jian-Shi; Han, Dong-Mei; Ma, Ying

2014-01-01

An analysis of high-sensitive factor I and C-reactive proteins as biomarkers for coronary artery disease has been performed from 19 anticipated cohort studies that included 21,567 participants having no information about coronary artery disease. Besides, the clinical implications of statin therapy initiated due to assessment of factor I and C-reactive proteins have also been modeled during studies. The measure of risk discrimination (C-index) was increased (by 0.0101) as per the prognostic model for coronary artery disease with respect to sex, smoking status, age, blood pressure, total cholesterol level along with diabetic history characteristic parameters. The C-index was further raised by 0.0045 and 0.0053 when factor I and C-reactive proteins based information were added, respectively which finally predicted 10-year risk categories as: high (> 20%), medium (10% to < 20%), and low (< 10%) risks. We found 2,254 persons (among 15,000 adults (age ≥ 45 years)) would initially be classified as being at medium risk for coronary artery disease when only conventional risk factors were used as calculated risk. Besides, persons with a predicted risk of more than 20% as well as for persons suffering from other risk factors (i.e. diabetes), statin therapy was initiated (irrespective of their decade old predicted risk). We conclude that under current treatment guidelines assessment of factor I and C-reactive proteins levels (as biomarker) in people at medium risk for coronary artery disease could prevent one additional coronary artery disease risk over a period a decade for every 390-500 people screened.

Plasma soluble prion protein, a potential biomarker for sport-related concussions: a pilot study.

PubMed