Large-scale proteomics analysis of human ovarian cancer for biomarkers

Ovarian cancer is usually found at a late stage when the prognosis is often bad. Relative survival rates decrease with tumor stage or grade, and the 5-year survival rate for women with carcinoma is only 38%. Thus, there is a great need to find biomarkers that can be used to carry out routine screening, especially in high-risk patient groups. Here, we present a large-scale study of 64 tissue samples taken from patients at all stages and show that we can identify statistically valid markers using nonsupervised methods that distinguish between normal, benign, borderline, and malignant tissue. We have identified 217 of the significantly changing protein spots. We are expressing and raising antibodies to 35 of these. Currently, we have validated 5 of these antibodies for use in immunohistochemical analysis using tissue microarrays of healthy and diseased ovarian, as well as other, human tissues.     

Discovery of biomarkers for gastric cancer: a proteomics approach

Gastric cancer is the second leading cause of cancer-related deaths worldwide. Although many treatment options exist for patients with gastric tumors, the incidence and mortality rate of gastric cancer are on the rise. The early stages of gastric cancer are non-symptomatic, and the treatment response is unpredictable. This situation is further aggravated by a lack of diagnostic biomarkers that can aid in the early detection and prognosis of gastric cancer and in the prediction of chemoresistance. Moreover, clinical surgical specimens are rarely obtained, and traditional biomarkers of gastric cancer are not very effective. Many studies in the field of proteomics have contributed to the discovery and establishment of powerful diagnostic tools (e.g., ProteinChip array) in the management of cancer. The evolution in proteomic technologies has not only enabled the screening of a large number of samples but also enabled the identification of pathologically significant proteins, such as phosphoproteins, and the quantitation of difference in protein expression under different conditions. Multiplexed assays are used widely to accurately fractionate various complex samples such as blood, tissue, cells, and Helicobacter pylori-infected specimens to identify differentially expressed proteins. Biomarker detection studies have substantially contributed to the areas of secretome, metabolome, and phosphoproteome. Here, we review the development of potential biomarkers in the natural history of gastric cancer, with specific emphasis on the characteristics of target protein convergence.     

Secretome proteomics for discovery of cancer biomarkers

“Secretome” is referred to as the rich, complex set of molecules secreted from living cells. In a less strict definition frequently followed in “secretome” studies, the term also includes molecules shed from the surface of living cells. Proteins of secretome (will be referred to as secreted) play a key role in cell signaling, communication and migration. The need for developing more effective cancer biomarkers and therapeutic modalities has led to the study of cancer cell secretome as a means to identify and characterize diagnostic and prognostic markers and potential drug and therapeutic targets. Significant technological advances in the field of proteomics during the last two decades have greatly facilitated research towards this direction. Nevertheless, secretome analysis still faces some difficulties mainly related to sample collection and preparation. The goal of this article is to provide an overview of the main findings from the analysis of cancer cell secretome. Specifically, we focus on the presentation of main methodological approaches that have been developed for the study of secreted proteins and the results thereof from the analysis of secretome in different types of malignancies; special emphasis is given on correlation of findings with protein expression in body fluids.     

Prostate cancer proteomics: clinically useful protein biomarkers and future perspectives

Introduction: Although prostate cancer constitutes one of the most important, death-related diseases in the male population, there is still a need for identification of sensitive biomarkers that could precociously detect the disease and differentiate aggressive from indolent cancers, in order to decrease overtreatment. Proteomics research has improved understanding on mechanisms underlying tumorigenesis, cancer cells migration and invasion potential, and castration resistance. This review has focused on proteomic studies of prostate cancer published in the recent years, with a special emphasis on determination of biomarkers for cancer progression and diagnosis.

Areas covered: Shotgun and targeted-proteomic studies of prostate cancer in different matrices are reviewed, i.e., prostate tissue, prostate cell lines, blood (serum and plasma), urine, seminal plasma, and exosomes. The most important biomarkers for cancer diagnosis and aggressiveness characterization are highlighted.

Expert commentary: In general, results demonstrate alteration in cell cycle control, DNA repair, proteasomal degradation, and metabolic activity. However, these studies suffer from low reproducibility due to heterogeneity of the cancer itself, as well as to techniques utilized for protein identification/quantification. Downstream confirmatory studies in separate cohorts are warranted in order to demonstrate accuracy of these results.     

Proximal fluid proteomics for the discovery of digestive cancer biomarkers

Most digestive malignancies have asymptomatic course, often progressing to poor outcome stages. Surgical resection usually represents the only potentially curative option but a prior assumption of the malignant nature of the lesion is mandatory to avoid exposing patients to unnecessary risks. Unfortunately, currently available diagnostic tools lack accuracy in many cases, consequently more reliable markers are needed to improve detection of malignant lesions. In this challenging context, fluids surrounding digestive malignancies represent a valuable source for the search of new potential biomarkers and proteomic tools offer the opportunity to achieve this goal. The new field of proximal fluid proteomics is thus emerging in the arena of digestive cancer biomarker discovery.     

Progress and prospects for the discovery of biomarkers for gastric cancer: a focus on proteomics

Introduction: Patient outcomes from gastric cancer vary due to the complexity of stomach carcinogenesis. Recent research using proteomic technologies has targeted components of all of these systems in order to develop biomarkers to aid the early diagnosis of gastric cancer and to assist in prognostic stratification.

Areas covered: This review is comprised of evidence obtained from literature searches from PubMed. It covers the evidence of diagnostic, prognostic, and predictive biomarkers for gastric cancer using proteomic technologies, and provides up-to-date references.

Expert commentary: The proteomic technologies have not only enabled the screening of a large number of samples, but also enabled the identification of diagnostic, prognostic and predictive biomarkers for gastric cancer. While major challenges still remain, to date, proteomic studies in gastric cancer have provided a wealth of information in revealing proteome alterations associated with the disease.     

Identification of candidate biomarkers for early detection of human lung squamous cell cancer by quantitative proteomics

To discover novel biomarkers for early detection of human lung squamous cell cancer (LSCC) and explore possible mechanisms of LSCC carcinogenesis, iTRAQ-tagging combined with two dimensional liquid chromatography tandem MS analysis was used to identify differentially expressed proteins in human bronchial epithelial carcinogenic process using laser capture microdissection-purified normal bronchial epithelium (NBE), squamous metaplasia (SM), atypical hyperplasia (AH), carcinoma in situ (CIS) and invasive LSCC. As a result, 102 differentially expressed proteins were identified, and three differential proteins (GSTP1, HSPB1 and CKB) showing progressively expressional changes in the carcinogenic process were selectively validated by Western blotting. Immunohistochemistry was performed to detect the expression of the three proteins in an independent set of paraffin-embedded archival specimens including various stage tissues of bronchial epithelial carcinogenesis, and their ability for early detection of LSCC was evaluated by receiver operating characteristic analysis. The results showed that the combination of the three proteins could perfectly discriminate NBE from preneoplastic lesions (SM, AH and CIS) from invasive LSCC, achieving a sensitivity of 96% and a specificity of 92% in discriminating NBE from preneoplatic lesions, a sensitivity of 100% and a specificity of 98% in discriminating NBE from invasive LSCC, and a sensitivity of 92% and a specificity of 91% in discriminating preneoplastic lesions from invasive LSCC, respectively. Furthermore, we knocked down GSTP1 in immortalized human bronchial epithelial cell line 16HBE cells, and then measured their susceptibility to carcinogen benzo(a)pyrene-induced cell transformation. The results showed that GSTP1 knockdown significantly increased the efficiency of benzo(a)pyrene-induced 16HBE cell transformation. The present data first time show that GSTP1, HSPB1 and CKB are novel potential biomarkers for early detection of LSCC, and GSTP1 down-regulation is involved in human bronchial epithelial carcinogenesis.     

Towards developing biomarkers for glioblastoma multiforme: a proteomics view

Glioblastoma multiforme (GBM) is one of the most aggressive and lethal forms of the primary brain tumors. With predominance of tumor heterogeneity and emergence of new subtypes, new approaches are needed to develop tissue-based markers for tumor typing or circulatory markers to serve as blood-based assays. Multi-omics data integration for GBM tissues would offer new insights on the molecular view of GBM pathogenesis useful to identify biomarker panels. On the other hand, mapping differentially expressed tissue proteins for their secretory potential through bioinformatics analysis or analysis of the tumor cell secretome or tumor exosomes would enhance our understanding of the tumor microenvironment and prospects for targeting circulatory biomarkers. In this review, the authors first present potential biomarker candidates for GBM that have been reported and then focus on plausible pipelines for multi-omic data integration to identify additional, high-confidence molecular panels for clinical applications in GBM.     

Urinary proteomics: a tool to discover biomarkers of kidney diseases

There is intense interest in applying proteomics to urine analysis in order to promote a better understanding of kidney disease processes, develop new biomarkers for diagnosis and detect early factors that contribute to end-stage renal diseases. This interest creates numerous opportunities as well as challenges. To fulfill this task, proteomics requires, in its different stages of realization, various technological platforms with high sensitivity, high throughput and large automation ability. In this review, we will give an overview of promising proteomic methods that can be used for analyzing urinary proteome and detecting biomarkers for different kidney diseases. Furthermore, we will focus on the current status and future directions in investigating kidney diseases using urinary proteomics.     

Urinary proteomics: a tool to discover biomarkers of kidney diseases

There is intense interest in applying proteomics to urine analysis in order to promote a better understanding of kidney disease processes, develop new biomarkers for diagnosis and detect early factors that contribute to end–stage renal diseases. This interest creates numerous opportunities as well as challenges. To fulfill this task, proteomics requires, in its different stages of realization, various technological platforms with high sensitivity, high throughput and large automation ability. In this review, we will give an overview of promising proteomic methods that can be used for analyzing urinary proteome and detecting biomarkers for different kidney diseases. Furthermore, we will focus on the current status and future directions in investigating kidney diseases using urinary proteomics.     

Defining salivary biomarkers using mass spectrometry-based proteomics: a systematic review

Recent advancements in mass spectrometric proteomics provide a promising result in utilizing saliva to explore biomarkers for diagnostic purposes. However, the issues of specificity or redundancy of disease-associated salivary biomarkers have not been described. This systematic review was therefore aimed to define and summarize disease-related salivary biomarkers identified by mass spectrometry proteomics. Peer-reviewed articles published through July 2009 within three databases were reviewed. Out of 243 articles, 21 studies were selected in this systematic review with conditions including Sj?gren's syndrome, squamous cell carcinoma, dental caries, diabetes, breast cancer, periodontitis, gastric cancer, systemic sclerosis, oral lichen planus, bleeding oral cavity, and graft-versus-host disease. The sample size ranged from 3-41 in both diseased and control subjects, with no consensus on sample collection protocol. One hundred eighty biomarkers were identified in total; 87 upregulated, 63 downregulated, and 30 varying based on disease. Except for Sj?gren's syndrome, the majority of studies with the same disease produce inconsistent biomarkers. Larger sample size and standardization of sample collection/treatment protocol may improve future studies.     

Systemic sclerosis biomarkers discovered using mass-spectrometry-based proteomics: a systematic review

Abstract

Context: Systemic sclerosis (SSc) is an autoimmune disease with incompletely known physiopathology. There is a great challenge to predict its course and therapeutic response using biomarkers.

Objective: To critically review proteomic biomarkers discovered from biological specimens from systemic sclerosis patients using mass spectrometry technologies.

Methods: Medline and Embase databases were searched in February 2014.

Results: Out of the 199 records retrieved, a total of 20 records were included, identifying 116 candidate proteomic biomarkers.

Conclusion: Research in SSc proteomic biomarkers should focus on biomarker validation, as there are valuable mass-spectrometry proteomics studies in the literature.     

Current advances in tumor proteomics and candidate biomarkers for hepatic cancer

Tumor proteomics apply proteomics techniques to tumor biological research, mainly by screening candidate biomarkers for early tumor diagnosis, prognosis and treatment. Hepatocellular carcinoma (HCC) is a type of malignant tumor with one of the highest death rates in the world. With the advent of the post-genomic age, tumor biological research developing the technology of proteomics has become a major focus of researchers. The discovery of novel candidate biomarkers is one of crucial problems for the early diagnosis of HCC. In general, there are three distinct types of candidate biomarkers for HCC based on different areas: biochemical biomarkers, antigenic biomarkers and epigenetic biomarkers. This review mainly discusses current advances in the problems and prospects of candidate biomarker for the early diagnosis of HCC, discovered by technologies of tumor proteomics.     

Advances in ovarian cancer proteomics: the quest for biomarkers and improved therapeutic interventions

Epithelial ovarian cancer is the leading cause of cancer-related death among gynecological cancers due to the asymptomatic nature of the disease, a lack of early detection markers and the development of resistance to current chemotherapeutic agents. Currently available tests (CA-125, transvaginal ultrasound or combination of both) lack the sensitivity and specificity to be useful as an efficient screening tool for surveillance of the general population. Thus, there is an urgent need for the development and validation of new molecular markers that would be both specific and sensitive indicators of disease onset, as well as progression. Proteomic profiling has emerged as a powerful tool to study ovarian cancer in an unbiased way at the molecular level, to monitor the effects of given treatment options and for the discovery of biomarkers. In this review we discuss the challenges associated with proteomics-based biomarker discovery and some recent concepts to potentially overcome these hurdles. Recent proteomics work on ovarian cancer cells and tissues will be discussed in light of obtaining new insights into fundamental biological processes, as well as their potential integration with ongoing biomarker discovery pipelines.     

Advances in ovarian cancer proteomics: the quest for biomarkers and improved therapeutic interventions

Epithelial ovarian cancer is the leading cause of cancer-related death among gynecological cancers due to the asymptomatic nature of the disease, a lack of early detection markers and the development of resistance to current chemotherapeutic agents. Currently available tests (CA-125, transvaginal ultrasound or combination of both) lack the sensitivity and specificity to be useful as an efficient screening tool for surveillance of the general population. Thus, there is an urgent need for the development and validation of new molecular markers that would be both specific and sensitive indicators of disease onset, as well as progression. Proteomic profiling has emerged as a powerful tool to study ovarian cancer in an unbiased way at the molecular level, to monitor the effects of given treatment options and for the discovery of biomarkers. In this review we discuss the challenges associated with proteomics-based biomarker discovery and some recent concepts to potentially overcome these hurdles. Recent proteomics work on ovarian cancer cells and tissues will be discussed in light of obtaining new insights into fundamental biological processes, as well as their potential integration with ongoing biomarker discovery pipelines.     

Mathematical framework for human SLE Nephritis: disease dynamics and urine biomarkers

Background  

Although the prognosis for Lupus Nephritis (LN) has dramatically improved with aggressive immunosuppressive therapies, these drugs carry significant side effects. To improve the effectiveness of these drugs, biomarkers of renal flare cycle could be used to detect the onset, severity, and responsiveness of kidney relapses, and to modify therapy accordingly. However, LN is a complex disease and individual biomarkers have so far not been sufficient to accurately describe disease activity. It has been postulated that biomarkers would be more informative if integrated into a pathogenic-based model of LN.     

Discovery of urine biomarkers for bladder cancer via global metabolomics

Bladder cancer (BC) is latent in its early stage and lethal in its late stage. Therefore, early diagnosis and intervention are essential for successful BC treatment. Considering the limitations of current diagnostic tools, noninvasive biomarkers that are both highly sensitive and specific are needed to improve the overall survival and quality of life of patients. With the advent of systems biology, “-omics” technologies have been developed over the past few decades. As a promising member, global metabolomics has increasingly been found to have clear potential for biomarker discovery. However, urinary metabolomics studies related to BC have lagged behind those of other urinary cancers, and major findings have not been systematically reported. The objective of this review is to comprehensively list the currently identified potential urinary metabolite biomarkers for BC.     

Recent advances in atherosclerosis-based proteomics: new biomarkers and a future perspective

Vascular proteomics is providing two main types of data: proteins that actively participate in vascular pathophysiological processes and novel protein candidates that can potentially serve as useful clinical biomarkers. Although both types of proteins can be identified by similar proteomic strategies and methods, it is important to clearly distinguish biomarkers from mediators of disease. A particular protein, or group of proteins, may participate in a pathogenic process but not serve as an effective biomarker. Alternatively, a useful biomarker may not mediate pathogenic pathways associated with disease (i.e., C-reactive protein). To date, there are no clear successful examples in which discovery proteomics has led to a novel useful clinical biomarker in cardiovascular diseases. Nevertheless, new sources of biomarkers are being explored (i.e., secretomes, circulating cells, exosomes and microparticles), an increasing number of novel proteins involved in atherogenesis are constantly described, and new technologies and analytical strategies (i.e., quantitative proteomics) are being developed to access low abundant proteins. Therefore, this presages a new era of discovery and a further step in the practical application to diagnosis, prognosis and early action by medical treatment of cardiovascular diseases.     

Discovery of Apo-A1 as a potential bladder cancer biomarker by urine proteomics and analysis

Bladder cancer is clinically characterized by high recurrent rate and poor prognosis and thereby patients need regular re-examinations which are invasive, unpleasant, and expensive. A noninvasive and less expensive method for detecting and monitoring bladder cancer would thus be advantageous. In this study, by using the two-dimensional electrophoresis (2-DE) approach with subsequent mass spectrometry (MS), we demonstrated the increased expression of apolipoprotein-A1 (Apo-A1) in individual urine from patients with bladder cancer, which was confirmed by Western blot results. A further analysis of the urinary Apo-A1 levels by an enzyme-linked immunosorbent assay yielded results that were consistent with the Western blot, and suggested Apo-A1 could provide diagnostic utility to distinguish patients with bladder cancer from healthy controls at 19.21 ng/ml. Further validation assay in a larger number of urine samples (n = 379) showed that Apo-A1 could be used as a biomarker to diagnosis bladder cancer with a sensitivity and specificity of 89.2% and 84.6% respectively. Moreover, the application of exfoliative urinary cytology in combination with the urine Apo-A1 detection could significantly increased the sensitivity in detecting bladder cancer. Our data showed a significant relationship of expressed Apo-A1 was established between bladder cancer and normal controls. Apo-A1 could be a potential biomarker for the diagnosis of bladder cancer.