SILAC-based quantitative proteomic analysis of gastric cancer secretome

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.

An integrated mRNA and microRNA expression signature for glioblastoma multiforme prognosis

Although patients with Glioblastoma multiforme (GBM) have grave prognosis, significant variability in patient outcome is observed. The objective of this study is to identify a molecular signature for GBM prognosis. We subjected 355 mRNA and microRNA expression profiles to elastic net-regulated Cox regression for identification of an integrated RNA signature for GBM prognosis. A prognostic index (PI) was generated for patient stratification. Survival comparison was conducted by Kaplan-Meier method and a general multivariate Cox regression procedure was applied to evaluate the independence of the PI. The abilities and efficiencies of signatures to predict GBM patient outcome was assessed and compared by the area under the curve (AUC) of the receiver-operator characteristic (ROC). An integrated RNA prognostic signature consisted by 4 protective mRNAs, 12 risky mRNAs, and 1 risky microRNA was identified. Decreased survival was associated with being in the high-risk group (hazard ratio = 2.864, P<0.0001). The prognostic value of the integrated signature was validated in five independent GBM expression datasets (n = 201, hazard ratio = 2.453, P<0.0001). The PI outperformed the known clinical factors, mRNA-only, and miRNA-only prognostic signatures for GBM prognosis (area under the ROC curve for the integrated RNA, mRNA-only, and miRNA-only signatures were 0.828, 0.742, and 0.757 at 3 years of overall survival, respectively, P<0.0001 by permutation test). We describe the first, to our knowledge, robust transcriptome-based integrated RNA signature that improves the current GBM prognosis based on clinical variables, mRNA-only, and miRNA-only signatures.

Divide and conquer: subproteomic approaches toward gastric cancer biomarker and drug target discovery

The discovery of biomarkers for early detection and treatment for gastric cancer are two important gaps that proteomics have the potential to fill. Advancements in mass spectrometry, sample preparation and separation strategies are crucial to proteomics-based discoveries and subsequent translations from bench to bedside. A great number of studies exploiting various subproteomic approaches have emerged for higher-resolution analysis (compared with shotgun proteomics) that permit interrogation of different post-translational and subcellular compartmentalized forms of the same proteins as determinants of disease phenotypes. This is a unique and key strength of proteomics over genomics. In this review, the salient features, competitive edges and pitfalls of various subproteomic approaches are discussed. We also highlight valuable insights from several subproteomic studies that have increased our understanding of the molecular etiology of gastric cancer and the findings that led to the discovery of potential biomarkers/drug targets that were otherwise not revealed by conventional shotgun expression proteomics.

Cancer secretomes and their place in supplementing other hallmarks of cancer

The secretome includes all macromolecules secreted by cells, in particular conditions at defined times, allowing cell-cell communication. Cancer cell secretomes that are altered compared to normal cells have shown significant potential for elucidating cancer biology. Proteins of secretomes are secreted by various secretory pathways and can be studied using different methods. Cancer secretomes seem to play an important role in known hallmarks of cancers such as excessive proliferation, reduced apoptosis, immune invasion, angioneogenesis, alteration in energy metabolism, and development of resistance against anti-cancer therapy [1, 2]. If a significant role of an altered secretome can be identified in cancer cells, using advanced mass spectrometry-based techniques, this may allow researchers to screen and characterize the secretome proteins involved in cancer progression and open up new opportunities to develop new therapies. We aim to elaborate upon recent advances in cancer cell secretome analysis using different proteomics techniques. In this review, we highlight the role of the altered secretome in contributing to already recognized and emerging hallmarks of cancer and we discuss new challenges in the field of secretome analysis.

Mapping proteolytic processing in the secretome of gastric cancer-associated myofibroblasts reveals activation of MMP-1, MMP-2, and MMP-3

Cancer progression involves changes in extracellular proteolysis, but the contribution of stromal cell secretomes to the cancer degradome remains uncertain. We have now defined the secretome of a specific stromal cell type, the myofibroblast, in gastric cancer and its modification by proteolysis. SILAC labeling and COFRADIC isolation of methionine containing peptides allowed us to quantify differences in gastric cancer-derived myofibroblasts compared with myofibroblasts from adjacent tissue, revealing increased abundance of several proteases in cancer myofibroblasts including matrix metalloproteinases (MMP)-1 and -3. Moreover, N-terminal COFRADIC analysis identified cancer-restricted proteolytic cleavages, including liberation of the active forms of MMP-1, -2, and -3 from their inactive precursors. In vivo imaging confirmed increased MMP activity when gastric cancer cells were xenografted in mice together with gastric cancer myofibroblasts. Western blot and enzyme activity assays confirmed increased MMP-1, -2, and -3 activity in cancer myofibroblasts, and cancer cell migration assays indicated stimulation by MMP-1, -2, and -3 in cancer-associated myofibroblast media. Thus, cancer-derived myofibroblasts differ from their normal counterparts by increased production and activation of MMP-1, -2, and -3, and this may contribute to the remodelling of the cancer cell microenvironment.

The human secretome atlas initiative: implications in health and disease conditions

Proteomic analysis of human body fluids is highly challenging, therefore many researchers are redirecting efforts toward secretome profiling. The goal is to define potential biomarkers and therapeutic targets in the secretome that can be traced back in accessible human body fluids. However, currently there is a lack of secretome profiles of normal human primary cells making it difficult to assess the biological meaning of current findings. In this study we sought to establish secretome profiles of human primary cells obtained from healthy donors with the goal of building a human secretome atlas. Such an atlas can be used as a reference for discovery of potential disease associated biomarkers and eventually novel therapeutic targets. As a preliminary study, secretome profiles were established for six different types of human primary cell cultures and checked for overlaps with the three major human body fluids including plasma, cerebrospinal fluid and urine. About 67% of the 1054 identified proteins in the secretome of these primary cells occurred in at least one body fluid. Furthermore, comparison of the secretome profiles of two human glioblastoma cell lines to this new human secretome atlas enabled unambiguous identification of potential brain tumor biomarkers. These biomarkers can be easily monitored in different body fluids using stable isotope labeled standard proteins. The long term goal of this study is to establish a comprehensive online human secretome atlas for future use as a reference for any disease related secretome study. This article is part of a Special Issue entitled: An Updated Secretome.