Pharmacoproteomic characterisation of human colon and rectal cancer

• Published in: Molecular systems biology 2017-11, Vol.13 (11), p.951-n/a
• Main Authors: Frejno, Martin, Zenezini Chiozzi, Riccardo, Wilhelm, Mathias, Koch, Heiner, Zheng, Runsheng, Klaeger, Susan, Ruprecht, Benjamin, Meng, Chen, Kramer, Karl, Jarzab, Anna, Heinzlmeir, Stephanie, Johnstone, Elaine, Domingo, Enric, Kerr, David, Jesinghaus, Moritz, Slotta‐Huspenina, Julia, Weichert, Wilko, Knapp, Stefan, Feller, Stephan M, Kuster, Bernhard
• Format: Article
• Language: English
• Subjects: Antineoplastic Agents - therapeutic use; Biomarkers, Tumor - antagonists & inhibitors; Biomarkers, Tumor - genetics; Biomarkers, Tumor - metabolism; Biotechnology; c-Mer Tyrosine Kinase - antagonists & inhibitors; c-Mer Tyrosine Kinase - genetics; c-Mer Tyrosine Kinase - metabolism; Cancer; Cell Line, Tumor; Clinical trials; Colon; Colon cancer; Colorectal cancer; Colorectal carcinoma; Colorectal Neoplasms - diagnosis; Colorectal Neoplasms - drug therapy; Colorectal Neoplasms - genetics; Colorectal Neoplasms - mortality; CPTAC; CRC65; Depth profiling; Drug development; Drug Resistance, Neoplasm - genetics; drug response; Drugs; EMBO03; EMBO28; EMBO31; Gene Expression Regulation, Neoplastic; Gene Regulatory Networks; Humans; Immunohistochemistry; Inhibitors; MAP Kinase Kinase 1 - antagonists & inhibitors; MAP Kinase Kinase 1 - genetics; MAP Kinase Kinase 1 - metabolism; MAP Kinase Kinase 2 - antagonists & inhibitors; MAP Kinase Kinase 2 - genetics; MAP Kinase Kinase 2 - metabolism; Mass spectrometry; Mass spectroscopy; Mathematical models; Medical research; MEK inhibitors; patient stratification; Patients; Pharmacogenetics - methods; Pharmacology; Prognosis; Protein Kinase Inhibitors - therapeutic use; Proteins; Proteomics; Proteomics - methods; Rectum; Scientific imaging; Sensitivity; Signal Transduction; Spectroscopy; Survival; Survival Analysis; Tumor cell lines; Tumors
• ISSN: 1744-4292; 1744-4292
• DOI: 10.15252/msb.20177701

Most molecular cancer therapies act on protein targets but data on the proteome status of patients and cellular models for proteome‐guided pre‐clinical drug sensitivity studies are only beginning to emerge. Here, we profiled the proteomes of 65 colorectal cancer (CRC) cell lines to a depth of > 10,000 proteins using mass spectrometry. Integration with proteomes of 90 CRC patients and matched transcriptomics data defined integrated CRC subtypes, highlighting cell lines representative of each tumour subtype. Modelling the responses of 52 CRC cell lines to 577 drugs as a function of proteome profiles enabled predicting drug sensitivity for cell lines and patients. Among many novel associations, MERTK was identified as a predictive marker for resistance towards MEK1/2 inhibitors and immunohistochemistry of 1,074 CRC tumours confirmed MERTK as a prognostic survival marker. We provide the proteomic and pharmacological data as a resource to the community to, for example, facilitate the design of innovative prospective clinical trials. Synopsis Deep proteome profiling of colorectal cancer (CRC) cell lines is used to identify cell lines matching to molecular subtypes of CRC patients. The subsequent identification of molecular signatures predicting the response to specific drugs is a useful resource for clinical trial design. The proteomes of 65 CRC cell lines are characterized by quantitative mass spectrometry to a depth of > 10,000 proteins. A combined analysis of proteomes and transcriptomes of cell lines and patients reveals integrated CRC subtypes. Integration with phenotypic drug sensitivity data predicts subtype‐specific drug response. MERTK protein levels in patients predict response to MEK inhibitors and patient survival. Graphical Abstract Deep proteome profiling of colorectal cancer (CRC) cell lines is used to identify cell lines matching to molecular subtypes of CRC patients. The subsequent identification of molecular signatures predicting the response to specific drugs is a useful resource for clinical trial design.