Abstract LB-27: Dissecting signaling transduction network to infer master regulators of non small cell lung cancer

Abstract

Abstract Abstract The dissection of signal transduction networks is lagging significantly with respect to their transcriptional and protein-complex counterparts. Innovative use of multiplex and microarray-based approaches, where multiple antibodies can be used to probe an ensemble of phosphoproteins, is starting to become sufficiently mature to allow characterization of small pathways. Yet, this is still far from providing an unbiased, genome-wide view of signal-transduction processes. Using data from the first genome-wide profiling of phosphopeptide abundance in normal and tumor related lung tissue1, we have designed a novel algorithm, pARACNe, to generate an unbiased, genome-wide network representing tyrosine kinase signal transduction pathways. Specifically, pARACNe was used to infer tyrosine kinase substrates in non-small cell lung cancer (NSCLC) from tandem mass-spec abundance profiling of phosphotyrosine enriched peptides from ∼250 samples derived from primary tumors, cell lines, and normal lung tissue. SILAC validation of EGFR, MET and ALK substrates, confirmed >80% of the pARACNe inferred interactions. Further analysis of large-scale NSCLC microarray expression profile data, using the MINDy algorithm2, showed significant convergence between the signal transduction pathways inferred by proteomics and gene expression based methods. The availability of an accurate NSCLC Tyrosine Kinase Interaction Network (TKIN) has significant implications for our ability to elucidate master regulators of oncogenesis and tumor progression and for the identification and prioritization of druggable targets. We used the MARINa algorithm and the TKIN to infer a complete repertoire of master regulator (MRs) kinases of 46 cell lines. Initial validation shows that the method could recapitulate both cancer specific MRs, such as EGFR, as well as cell line specific ones, such as ALK and PTK2 in H2228 cells. Follow up experimental assays have shown that the PTK2, which is active in tumor-related but not in normal cells, is required for H2228 cell viability and may constitute a novel oncogene addiction in NSCLC and a candidate therapeutic target. The TKI suggests that current pathway models are incomplete and sets the stage for quantitative, network-based methods to identify key regulators of physiologic and pathologic cell phenotypes.