(Carr, Mertins) Genetic alterations in human cancer have been systematically mapped by genomics landscape studies in the past decade, however, the direct consequences of these alterations on the functional proteome are poorly understood. Deep scale, mass spectrometry-based proteomic studies of three tumor types in the current phase of the Clinical Proteomics Tumor Analysis Consortium (CPTAC) program have revealed that integration of proteomic data with genomic data can improve specificity for identifying cancer-relevant pathways triggered by somatic DNA variants or DNA copy number alterations (CNAs) compared to genomic characterization alone, and help narrow target selection for potential therapeutic intervention. Here we propose to extend proteogenomic characterization to additional genetically defined tumor types ? lung, brain and pancreatic cancer ? and preclinical patient-derived tumor xenografts and cell line models. State-of-the-art LC-MS/MS proteomics technology with highly multiplexed stable- isotope mass tagging (TMT 10-plex) will be employed for precise relative quantification of the proteome, phosphoproteome and acetylome with very deep coverage. Improved multiplexing capabilities in these discovery type analyses enable a throughput of over 500 samples per year in conjunction with longitudinal quality control performance measurements. The proteome data produced will be integrated with genomics data in collaboration with the CPTAC Proteogenomics Data Analysis Centers. The goal will be to identify proteins with somatic variants or cancer-specific splice site junctions, correlate effects between copy number alterations and protein expression, and to identify signaling pathways in the phosphoproteome and lysine-acetylome that are activated by genetic alterations. This proteogenomics approach will inform target selection for confirmatory targeted mass spectrometry assays with a particular emphasis on mutated proteins, oncogenic regulators/effectors, and druggable proteins. We will develop and deploy new and existing analytically validated, highly multiplexed targeted MS- based assays (MRM and PRM) to measure cancer-relevant proteins and modified peptides in human biospecimens for candidate verification. Stable isotope-labeled peptides will be used as internal standards for unambiguous identification and quantification at a multiplex level of up to 200 analytes per assay. Existing technology will be further developed to enable comprehensive analysis of rare tumor cell populations, to evaluate tumor heterogeneity, to increase depth and breadth of post-translational modification analysis, and to improve depth, reliability and repeatability of peptide i.d. and quantification in general by intelligent data acquisition.

Public Health Relevance

(Carr, Mertins) Genetic alterations in human cancer have been systematically studied over the past decade, but the impact of a majority of these changes on the proteome ? the functional end of the genome ? are poorly understood. In this project we will use a state-of-the-art, unbiased analysis method, mass spectrometry-based proteomics, to define the protein content and identify key chemical modifications of the proteins that are involved in cell signaling. By integrating the proteomics data with the genomics data for the same samples/tumors we will shed new light on the biology of cancer, the response and resistance to drug treatments and, importantly, help to identify new targets for therapeutic intervention.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
1U24CA210986-01
Application #
9210945
Study Section
Special Emphasis Panel (ZCA1-TCRB-Q (O1))
Program Officer
Rodriguez, Henry
Project Start
2016-09-14
Project End
2021-08-31
Budget Start
2016-09-14
Budget End
2017-08-31
Support Year
1
Fiscal Year
2016
Total Cost
$1,288,045
Indirect Cost
$584,195
Name
Broad Institute, Inc.
Department
Type
DUNS #
623544785
City
Cambridge
State
MA
Country
United States
Zip Code
02142
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Mertins, Philipp; Tang, Lauren C; Krug, Karsten et al. (2018) Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry. Nat Protoc 13:1632-1661
Archer, Tenley C; Ehrenberger, Tobias; Mundt, Filip et al. (2018) Proteomics, Post-translational Modifications, and Integrative Analyses Reveal Molecular Heterogeneity within Medulloblastoma Subgroups. Cancer Cell 34:396-410.e8
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