The cancer cell secretome: A good source for discovering biomarkers?

Cancer is a leading cause of death. Early detection is usually associated with better clinical outcomes. Recent advances in genomics and proteomics raised hopes that new biomarkers for diagnosis, prognosis or monitoring therapeutic response will soon be discovered. Proteins secreted by cancer cells, referred also as “the cancer cell secretome”, is a promising source for biomarker discovery. In this review we will summarize recent advances in cancer cell secretome analysis, focusing on the five most fatal cancers (lung, breast, prostate, colorectal, and pancreatic). For each cancer type we will describe the proteomic approaches utilized for the identification of novel biomarkers. Despite progress, identification of markers that are superior to those currently used has proven to be a difficult task and very few, if any, newly discovered biomarker has entered the clinic the last 10 years.     

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.     

Application of proteomics in non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is a heterogeneous disease with diverse pathological features. Clinical proteomics allows the discovery of molecular markers and new therapeutic targets for this most prevalent type of lung cancer. Some of them may be used to detect early lung cancer, while others may serve as predictive markers of resistance to different therapies. Therapeutic targets and prognostic markers in NSCLC have also been discovered. These proteomics biomarkers may help to pair the individual NSCLC patient with the best treatment option. Despite the fact that implementation of these biomarkers in the clinic appears to be scarce, the recently launched Precision Medicine Initiative may encourage their translation into clinical practice.     

Proteomic profiling of pancreatic cancer for biomarker discovery

Pancreatic cancer is a uniformly lethal disease that is difficult to diagnose at early stage and even more difficult to cure. In recent years, there has been a substantial interest in applying proteomics technologies to identify protein biomarkers for early detection of cancer. Quantitative proteomic profiling of body fluids, tissues, or other biological samples to identify differentially expressed proteins represents a very promising approach for improving the outcome of this disease. Proteins associated with pancreatic cancer identified through proteomic profiling technologies could be useful as biomarkers for the early diagnosis, therapeutic targets, and disease response markers. In this article, we discuss recent progress and challenges for applying quantitative proteomics technologies for biomarker discovery in pancreatic cancer.     

Discovery and Validation of Clinical Biomarkers of Cancer: A Review Combining Metabolomics and Proteomics

Early detection and diagnosis of cancer can allow timely medical intervention, which greatly improves chances of survival and enhances quality of life. Biomarkers play an important role in assisting clinicians and health care providers in cancer diagnosis and treatment follow‐up. In spite of years of research and the discovery of thousands of candidate cancer biomarkers, only a few have transitioned to routine usage in the clinic. This review highlights advances in proteomics technologies that have enabled high rates of discovery of candidate cancer biomarkers and evaluates integration with other omics technologies to improve their progress through to validation and clinical translation. Furthermore, it gauges the role of metabolomics technology in cancer biomarker research and assesses it as a complementary tool in aiding cancer biomarker discovery and validation.     

Protein biomarker discovery for head and neck cancer

Squamous cell carcinoma of the head and neck (HNSCC) is the sixth most common cancer worldwide. Despite improvements in diagnosis and treatment, the five-year-survival rate of advanced HNSCC has only moderately increased, which is largely due to the high proportion of patients that present with advanced disease stage and the frequent development of relapse and second primary tumors. Protein biomarkers allowing early detection of primary HNSCC or relapse may aid to improve clinical outcome. Screening for precursor changes in the mucosal linings preceding the development of invasive tumors and for accurate prediction of risk of malignant transformation, may be propitious opportunities, which are as yet difficult. This review summarizes recent results in HNSCC proteomics for biomarker research. Despite the wide diversity of experimental designs, a few common markers have been detected. Although some of these potential biomarkers are very promising, they still have to be further clinically validated. Finally, treatment of advanced cancers of several sites within the head and neck has shifted significantly during the last decade, and also, targeted drugs have entered the clinic. This has major consequences for the research questions in HNSCC research and accordingly for the future direction of proteome research in HNSCC biomarker discovery.     

Proteome profiling for the identification of lung cancer signatures

Comprehensive and in-depth discovery of the disease proteome is an important issue in recent proteomics developments. Previous studies have shown a number of biomarkers discovered in various diseases, including lung cancer. Some of them are potentially useful in lung cancer diagnostics and prognostics. However, few of them can act as organ-specific biomarkers to extensively compare multiple cancer models. This article evaluates a recently published study employing comparative proteomics on multiple genetically engineered mouse models and sheds light on the usefulness and application of the discovered marker panel for human lung cancer diagnostics.     

Proteomic analysis of colorectal cancer: discovering novel biomarkers

Colorectal cancer is one of the most common cancers in the Western world. When detected at an early stage, the majority of cancers can be cured with current treatment modalities. However, most cancers present at an intermediate stage. The discovery of sensitive and specific biomarkers has the potential to improve preclinical diagnosis of primary and recurrent colorectal cancer, and holds the promise of prognostic and therapeutic application. Current biomarkers such as carcinoembryonic antigen lack sensitivity and specificity for general population screening. This review aims to highlight the role of current proteomic technologies in the discovery and validation of potential biomarkers with a view to translation to the clinic.     

Proteomic analysis of colorectal cancer: discovering novel biomarkers

Colorectal cancer is one of the most common cancers in the Western world. When detected at an early stage, the majority of cancers can be cured with current treatment modalities. However, most cancers present at an intermediate stage. The discovery of sensitive and specific biomarkers has the potential to improve preclinical diagnosis of primary and recurrent colorectal cancer, and holds the promise of prognostic and therapeutic application. Current biomarkers such as carcinoembryonic antigen lack sensitivity and specificity for general population screening. This review aims to highlight the role of current proteomic technologies in the discovery and validation of potential biomarkers with a view to translation to the clinic.     

Proteomics in prostate cancer biomarker discovery

Despite advances in molecular medicine, genomics, proteomics and translational research, prostate cancer remains the second most common cause of cancer-related mortality for men in the Western world. Clearly, early detection, targeted treatment and post-treatment monitoring are vital tools to combat this disease. Tumor markers can be useful for diagnosis and early detection of cancer, assessment of prognosis, prediction of therapeutic effect and treatment monitoring. Such tumor markers include prostate-specific antigen (prostate), cancer antigen (CA)15.3 (breast), CA125 (ovarian), CA19.9 (gastrointestinal) and serum α-fetoprotein (testicular cancer). However, all of these biomarkers lack sensitivity and specificity and, therefore, there is a large drive towards proteomic biomarker discovery. Current research efforts are directed towards discovering biosignatures from biological samples using novel proteomic technologies that provide high-throughput, in-depth analysis and quantification of the proteome. Several of these studies have revealed promising biomarkers for use in diagnosis, assessment of prognosis, and targeting treatment of prostate cancer. This review focuses on prostate cancer proteomic biomarker discovery and its future potential.     

Use of DNA methylation for cancer detection: promises and challenges

DNA methylation is an important and reversible epigenetic modification, which regulates genomic stability and cellular plasticity. Faithful DNA methylation is essential for mammalian development and health, and perturbation of methylation dynamics contributes to the development of disease, including cancer. The discovery and validation of the biological indicators (biomarkers) for human cancers are essential steps in the development of methods for accurate subtype classification and outcome prediction in clinic oncology. While genetics (SNP, LOH and mutation) and expression profiling (mRNA and protein) of biomarkers have been extensively assessed for cancer diagnosis and prognosis, the potential for using epigenetic fingerprints for early diagnosis and outcome prediction in clinic oncology propels the exploration of using DNA methylation as a biomarker for cancer prognosis. Both the promises and challenges to realizing the clinical utility of the DNA methylation in cancer management are discussed in this review.     

Proteome profiling for the identification of lung cancer signatures

Evaluation of: Taguchi A, Politi K, Pitteri SJ et al. Lung cancer signatures in plasma based on proteome profiling of mouse tumor models. Cancer Cell 20(3), 289–299 (2011).

Comprehensive and in-depth discovery of the disease proteome is an important issue in recent proteomics developments. Previous studies have shown a number of biomarkers discovered in various diseases, including lung cancer. Some of them are potentially useful in lung cancer diagnostics and prognostics. However, few of them can act as organ-specific biomarkers to extensively compare multiple cancer models. This article evaluates a recently published study employing comparative proteomics on multiple genetically engineered mouse models and sheds light on the usefulness and application of the discovered marker panel for human lung cancer diagnostics.     

临床蛋白质组学———蛋白质组学在临床研究中的应用

临床蛋白质组学是将蛋白质组学技术应用于临床医学研究,它主要围绕疾病的预防、早期诊断和治疗等方面开展研究,其中,恶性肿瘤是临床蛋白质组学研究的一个重点研究对象.由于肿瘤生物标志物对早期诊断具有重要价值,所以临床蛋白质组学的主要目标之一是寻找合适的肿瘤生物标志物,多分子生物标志物已成为寻找肿瘤生物标志物的一个研究趋势.简要介绍了临床蛋白质组学的基本概念,实验设计,临床样本收集与预处理以及蛋白质组学技术在临床研究中的应用与进展.     

Differential membrane proteomics using 18O-labeling to identify biomarkers for cholangiocarcinoma

Quantitative proteomic methodologies allow profiling of hundreds to thousands of proteins in a high-throughput fashion. This approach is increasingly applied to cancer biomarker discovery to identify proteins that are differentially regulated in cancers. Fractionation of protein samples based on enrichment of cellular subproteomes prior to mass spectrometric analysis can provide increased coverage of certain classes of molecules. We used a membrane protein enrichment strategy coupled with 18O labeling based quantitative proteomics to identify proteins that are highly expressed in cholangiocarcinomas. In addition to identifying several proteins previously known to be overexpressed in cholangiocarcinoma, we discovered a number of molecules that were previously not associated with cholangiocarcinoma. Using immunoblotting and immunohistochemical labeling of tissue microarrays, we validated Golgi membrane protein 1, Annexin IV and Epidermal growth factor receptor pathway substrate 8 (EPS8) as candidate biomarkers for cholangiocarcinomas. Golgi membrane protein 1 was observed to be overexpressed in 89% of cholangiocarcinoma cases analyzed by staining tissue microarrays. In light of recent reports showing that Golgi membrane protein 1 is detectable in serum, further investigation into validation of this protein has the potential to provide a biomarker for early detection of cholangiocarcinomas.     

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

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.     

Targeted proteomics: a bridge between discovery and validation

New technologies in mass spectrometry are beginning to mature and show unique advantages for the identification and quantitation of proteins. In recent years, one of the significant goals of clinical proteomics has been to identify biomarkers that can be used for clinical diagnosis. As technology has progressed, the list of potential biomarkers has grown. However, the verification and validation of these potential biomarkers is increasingly challenging and require high-throughput quantitative assays, targeting specific candidates. Targeted proteomics bridges the gap between biomarker discovery and the development of clinically applicable biomarker assays.     

Advances, challenges, and limitations in serum-proteome-based cancer diagnosis

Recent advances in medicine have dramatically reduced the incidence and mortality of many cardiovascular, infectious, and certain neoplastic diseases; the overall mortality for most malignant solid tumors remains high. The poor prognosis in these cancers is due, in part, to the absence of adequate early screening tests, leading to delays in diagnosis. Three strategies have been applied to fight cancer: analysis of the molecular mechanisms involved in its pathogenesis and progression, improvement of early diagnosis, and the development of novel treatment strategies. There have been major advances in our understanding of cancer biology and pathogenesis and in the development of new (targeted) treatment modalities. However, insufficient progress has been made with respect to improving the methods for the early diagnosis and screening of many cancers. Therefore, cancer is often diagnosed at advanced stages, delaying timely treatment and leading to poor prognosis. Proteome analysis has recently been used for the identification of biomarkers or biomarker patterns that may allow for the early diagnosis of cancer. This tool is of special interest, since it allows for the identification of tumor-derived secretory products in serum or other body fluids. In addition, it may be used to detect reduced levels or loss of proteins in the serum of cancer patients that are present in noncancer individuals. These changes in the serum proteome may result from cancer-specific metabolic or immunological alterations, which are, at least partly, independent of tumor size or mass, thereby facilitating early discovery.     

Targeted and Untargeted Proteomics Approaches in Biomarker Development

An enormous amount of research effort has been devoted to biomarker discovery and validation. With the completion of the human genome, proteomics is now playing an increasing role in this search for new and better biomarkers. Here, what leads to successful biomarker development is reviewed and how these features may be applied in the context of proteomic biomarker research is considered. The “fit‐for‐purpose” approach to biomarker development suggests that untargeted proteomic approaches may be better suited for early stages of biomarker discovery, while targeted approaches are preferred for validation and implementation. A systematic screening of published biomarker articles using MS‐based proteomics reveals that while both targeted and untargeted technologies are used in proteomic biomarker development, most researchers do not combine these approaches. i) The reasons for this discrepancy, (ii) how proteomic technologies can overcome technical challenges that seem to limit their translation into the clinic, and (iii) how MS can improve, complement, or replace existing clinically important assays in the future are discussed.