Tumor cell-intrinsic signals promoting tolerance and adaptation to oncogenic kinase inhibition

Abstract

Therapeutics targeting oncogenic kinases have offered longer survival and superior quality of life for cancer patients with particular malignancies compared to the preceding standard of care. However, many patients still fail to show a clinically meaningful response to kinase inhibitors prescribed on the basis of tumor genotype, and nearly all responsive patients eventually develop resistance, limiting the curative potential of these agents. A more complete understanding of the molecular basis underlying therapy failure is required for designing new agents and combinations with improved response rates. In this thesis, I explore these issues using tractable experimental models in which genotype-matched kinase inhibitors fail to kill or durably arrest proliferation of cancer cells, with particular focus on the role of cellular signaling networks. In the first part, I have characterized a panel of human lung cancer cell lines harboring genetic gain-of-function alterations of clinically actionable tyrosine kinases (TKs). Using commonly prescribed TK inhibitors (TKIs), I show that TK genetic status generally predicts whether or not a cell line will show any response to genotype-matched TKI (GM-TKI), but is insufficient to predict drug tolerance, the ability of a cell line to sustain proliferation under drug. In drug combination experiments targeting co-mutated pathways, I show that some degree of tolerance to GM-TKI is explained by oncogenic co-mutations, but not across all lines. By leveraging targeted and untargeted mass spectrometry (MS) of endogenous tyrosine-phosphorylated proteins, which enables phosphosite-specific quantification of TK signaling networks, I report several cell line-specific vulnerabilities not predicted to exist at the genetic level, and the consensus observation that sustained activity of SRC family kinases (SFKs), or of the SRC-like kinases ABL1/2, is an important contributor to GM-TKI tolerance in all lines. In the second part, I have examined the molecular events underlying drug-induced adaptation, the process by which drug exposure inadvertently drives upregulation of pro-survival signaling pathways. In a collaborative effort, we report the signaling and transcriptional dynamics underlying early adaptation to oncogenic BRAF inhibition in a patient-derived cell line model of human BRAF-mutant melanoma. We show by time-resolved MS of mitogenic signaling networks, computationally integrated with matched mRNA sequencing data, that adaptation to BRAF inhibition in our model system is promoted by early drug-induced compensatory SFK signaling, due in part to accumulation of reactive oxygen species via an impaired NRF2 antioxidant response. This concerted adaptive response promotes sensitivity to SFK inhibition across a panel of patient-derived BRAF-mutant melanoma cell lines and in a mouse xenograft model. The work described in both parts was aided by two MS software solutions I developed: one to automate the generation of targeted acquisition methods for protein phosphosites and pathways of interest, and the other to retain quantitative information from fragment ion spectra with missing values. Together, this thesis reports new connections between cell signaling and kinase inhibitor response, and offers the intriguing hypothesis that SFK signaling may be a conserved barrier for maximally effective targeted cancer therapy.