Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis.

ABSTRACT: To understand drug combination effect, it is necessary to decipher the interactions between drug targets-many of which are signaling molecules. Previously, such signaling pathway models are largely based on the compilation of literature data from heterogeneous cellular contexts. Indeed, de novo reconstruction of signaling interactions from large-scale molecular profiling is still lagging, compared to similar efforts in transcriptional and protein-protein interaction networks. To address this challenge, we introduce a novel algorithm for the systematic inference of protein kinase pathways, and applied it to published mass spectrometry-based phosphotyrosine profile data from 250 lung adenocarcinoma (LUAD) samples. The resulting network includes 43 TKs and 415 inferred, LUAD-specific substrat

SUBMITTER: Bansal M 

PROVIDER: S-EPMC6322741 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature