Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets.
Abdulkadir ElmasSerena TharakanSuraj K JaladankiMatthew D GalskyTao LiuKuan-Lin HuangPublished in: Communications biology (2021)
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.
Keyphrases
- papillary thyroid
- mass spectrometry
- tyrosine kinase
- squamous cell
- transcription factor
- small cell lung cancer
- gene expression
- signaling pathway
- genome wide
- big data
- poor prognosis
- machine learning
- binding protein
- high throughput
- small molecule
- liquid chromatography
- cell cycle
- smoking cessation
- drug delivery
- epithelial mesenchymal transition
- tandem mass spectrometry
- induced apoptosis
- pi k akt