Chromosome 7-Centric Analysis of Proteomics Data from a Panel of Human Colon Carcinoma Cell Lines

Proteomics of Colorectal Cancer: Tumors, Organoids, and Cell Cultures-A Minireview

Proteomics, the study of the complete protein composition of a sample, is an important field for cancer research. Changes in the proteome can serve as a biomarker of cancer or lead to the development of a targeted therapy. This minireview will focus on mass spectrometry-based proteomics studies applied specifically to colorectal cancer, particularly the variety of cancer model systems used, including tumor samples, two-dimensional (2D) and three-dimensional (3D) cell cultures such as spheroids and organoids. A thorough discussion of the application of these systems will accompany the review of the literature, as each provides distinct advantages and disadvantages for colorectal cancer research. Finally, we provide conclusions and future perspectives for the application of these model systems to cancer research as a whole.

Secretome Proteomic Approaches for Biomarker Discovery: An Update on Colorectal Cancer

Searching for new cancer-related biomarkers is a key priority for the early detection of solid tumors, such as colorectal cancer (CRC), in clinically relevant biological fluids. The cell line and/or tumor tissue secretome represents a valuable resource for discovering novel protein markers secreted by cancer cells. The advantage of a secretome analysis is the reduction of the large dynamic range characterizing human plasma/serum, and the simultaneous enrichment of low abundance cancer-secreted proteins, thereby overcoming the technical limitations underlying the direct search in blood samples. In this review, we provided a comprehensive overview of recent studies on the CRC secretome for biomarker discovery, focusing both on methodological and technical aspects of secretome proteomic approaches and on biomarker-independent validation in CRC patient samples (blood and tissues). Secretome proteomics are mainly based on LC-MS/MS analyses for which secretome samples are either in-gel or in-solution trypsin-digested. Adequate numbers of biological and technical replicates are required to ensure high reproducibility and robustness of the secretome studies. Moreover, another major challenge is the accuracy of proteomic quantitative analysis performed by label-free or labeling methods. The analysis of differentially expressed proteins in the CRC secretome by using bioinformatic tools allowed the identification of potential biomarkers for early CRC detection. In this scenario, this review may help to follow-up the recent secretome studies in order to select promising circulating biomarkers to be validated in larger screenings, thereby contributing toward a complete translation in clinical practice.

MOPED enables discoveries through consistently processed proteomics data

The Model Organism Protein Expression Database (MOPED, http://moped.proteinspire.org) is an expanding proteomics resource to enable biological and biomedical discoveries. MOPED aggregates simple, standardized and consistently processed summaries of protein expression and metadata from proteomics (mass spectrometry) experiments from human and model organisms (mouse, worm, and yeast). The latest version of MOPED adds new estimates of protein abundance and concentration as well as relative (differential) expression data. MOPED provides a new updated query interface that allows users to explore information by organism, tissue, localization, condition, experiment, or keyword. MOPED supports the Human Proteome Project's efforts to generate chromosome- and diseases-specific proteomes by providing links from proteins to chromosome and disease information as well as many complementary resources. MOPED supports a new omics metadata checklist to harmonize data integration, analysis, and use. MOPED's development is driven by the user community, which spans 90 countries and guides future development that will transform MOPED into a multiomics resource. MOPED encourages users to submit data in a simple format. They can use the metadata checklist to generate a data publication for this submission. As a result, MOPED will provide even greater insights into complex biological processes and systems and enable deeper and more comprehensive biological and biomedical discoveries.

Proteogenomic analysis of human colon carcinoma cell lines LIM1215, LIM1899, and LIM2405

As part of the genome-wide and chromosome-centric human proteomic project (C-HPP), we have integrated shotgun proteomics approach and a genome-wide transcriptomic approach (RNA-Seq) of a set of human colon cancer cell lines (LIM1215, LIM1899 and LIM2405) that were selected to represent a wide range of pathological states of colorectal cancer. The combination of a standard proteomics approach (1D-gel electrophoresis coupled to LC/ion trap mass spectrometry) and RNA-Seq allowed us to exploit the greater depth of the transcriptomics measurement (∼ 9800 transcripts per cell line) versus the protein observations (∼ 1900 protein identifications per cell line). Conversely, the proteomics data were helpful in identifying both cancer associated proteins with differential expression patterns as well as protein networks and pathways which appear to be deregulated in these cell lines. Examples of potential markers include mortalin, nucleophosmin, ezrin, LASP1, alpha and beta forms of spectrin, exportin, the carcinoembryonic antigen family, EGFR and MET. Interaction analyses identified the large intermediate filament family, the protein folding network and adapter proteins in focal adhesion networks, which included the CDC42 and RHOA signaling pathways that may have potential for identifying phenotypic states representing poorly and moderately differentiated states of CRC, with or without metastases.