Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets

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作者
Abdulkadir Elmas
Serena Tharakan
Suraj Jaladanki
Matthew D. Galsky
Tao Liu
Kuan-lin Huang
机构
[1] Tisch Cancer Institute,Center for Transformative Disease Modeling, Department of Genetics and Genomic Sciences
[2] Icahn Institute for Data Science and Genomic Technology,Division of Hematology and Medical Oncology
[3] Icahn School of Medicine at Mount Sinai,Biological Sciences Division
[4] Tisch Cancer Institute,undefined
[5] Icahn School of Medicine at Mount Sinai,undefined
[6] Pacific Northwest National Laboratory,undefined
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Identifying genomic alterations of cancer proteins has guided the development of targeted therapies, but proteomic analyses are required to validate and reveal new treatment opportunities. Herein, we develop a new algorithm, OPPTI, to discover overexpressed kinase proteins across 10 cancer types using global mass spectrometry proteomics data of 1,071 cases. OPPTI outperforms existing methods by leveraging multiple co-expressed markers to identify targets overexpressed in a subset of tumors. OPPTI-identified overexpression of ERBB2 and EGFR proteins correlates with genomic amplifications, while CDK4/6, PDK1, and MET protein overexpression frequently occur without corresponding DNA- and RNA-level alterations. Analyzing CRISPR screen data, we confirm expression-driven dependencies of multiple currently-druggable and new target kinases whose expressions are validated by immunochemistry. Identified kinases are further associated with up-regulated phosphorylation levels of corresponding signaling pathways. Collectively, our results reveal protein-level aberrations—sometimes not observed by genomics—represent cancer vulnerabilities that may be targeted in precision oncology.
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