Proteomics of Colorectal Cancer in a Genomic Context: First Large-scale Mass Spectrometry–Based Analysis from the Cancer Genome Atlas

[摘要] Cancer is a disease caused by DNA alterations that make cells grow in an uncontrolled way. Identifying the alterations in each tumor's complete set of DNA (the genome) and its functionally relevant protein complement (the proteome) is expected to increase our understanding of how such changes interact to drive the disease. This global molecular information will help lay a foundation for improving cancer prevention, early detection, and treatment.In the past decade, mass spectrometry (MS)3 technology and (bio)informatics tools have matured to the extent that they can provide high-throughput, comprehensive protein inventories of cells, tissues, and biofluids, even when present at low concentrations (1), paving the way for large-scale profiling of clinical samples. The integration of proteomic and genomic data in which MS/MS data are searched against customized databases of individually matched DNA/RNA sequence data, referred to as proteogenomics, provides a more comprehensive view of the molecular determinants that drive cancer than genomic analysis alone and may help identify the most important targets for cancer detection and intervention.Six years ago, the first report on the genomic characterization of glioblastoma was published by the Cancer Genome Atlas (TCGA) network. A research team of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has now assembled an MS-based inventory of protein expression and variants in 95 colon and rectal tumors (2) that were previously characterized by the TCGA project. The authors focused on the question of how gene alterations identified in previous analyses of the same samples are expressed at the protein level.To enable a comprehensive and in-depth analysis of colorectal tumors, the CPTAC team used a label-free, next-generation proteomics approach based on basic and reversed-phase nano-liquid chromatography coupled to high-resolution tandem MS (2). The tandem MS data were analyzed by an innovative bioinformatics pipeline that was developed in-house for stringent …

[学科分类] 过敏症与临床免疫学