Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous backbone upon which to study genetic variants, candidate targets, small molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from various lineages and ethnicities. Integrating these data with functional characterizations such as drug-sensitivity data, short hairpin RNA knockdown and CRISPR–Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource to accelerate cancer research using model cancer cell lines.

The stability of the Wnt pathway transcription factor beta-catenin is tightly regulated by the multi-subunit destruction complex. Deregulated Wnt pathway activity has been implicated in many cancers, making this pathway an attractive target for anticancer therapies. However, the development of targeted Wnt pathway inhibitors has been hampered by the limited number of pathway components that are amenable to small molecule inhibition. Here, we used a chemical genetic screen to identify a small molecule, XAV939, which selectively inhibits beta-catenin-mediated transcription. XAV939 stimulates beta-catenin degradation by stabilizing axin, the concentration-limiting component of the destruction complex. Using a quantitative chemical proteomic approach, we discovered that XAV939 stabilizes axin by inhibiting the poly-ADP-ribosylating enzymes tankyrase 1 and tankyrase 2. Both tankyrase isoforms interact with a highly conserved domain of axin and stimulate its degradation through the ubiquitin-proteasome pathway. Thus, our study provides new mechanistic insights into the regulation of axin protein homeostasis and presents new avenues for targeted Wnt pathway therapies.

Although mechanisms of acquired resistance of EGFR mutant non-small cell lung cancers to EGFR inhibitors have been identified, little is known about how resistant clones evolve during drug therapy. Here, we observe that acquired resistance caused by the T790M gatekeeper mutation can occur either by selection of pre-existing T790M clones or via genetic evolution of initially T790M-negative drug tolerant cells. The path to resistance impacts the biology of the resistant clone, as those that evolved from drug tolerant cells had a diminished apoptotic response to third generation EGFR inhibitors that target T790M EGFR; treatment with navitoclax, an inhibitor of BCL-XL and BCL-2 restored sensitivity. We corroborated these findings using cultures derived directly from EGFR inhibitor-resistant patient tumors. These findings provide evidence that clinically relevant drug resistant cancer cells can both pre-exist and evolve from drug tolerant cells, and point to therapeutic opportunities to prevent or overcome resistance in the clinic.

Highlights d Quantified the proteomes of 375 cell lines from diverse lineages in the CCLE d Correlated expression of proteins across many pathways d Downregulation of multiple protein complexes in microsatellite instability d Protein complexes associated with sensitivity to gene knockdown and mutation

Elucidation of the mutational landscape of human cancer has progressed rapidly and been accompanied by the development of therapeutics targeting mutant oncogenes. However, a comprehensive mapping of cancer dependencies has lagged behind and the discovery of therapeutic targets for counteracting tumor suppressor gene loss is needed. To identify vulnerabilities relevant to specific cancer subtypes, we conducted a large-scale RNAi screen in which viability effects of mRNA knockdown were assessed for 7,837 genes using an average of 20 shRNAs per gene in 398 cancer cell lines. We describe findings of this screen, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features. In addition, we describe robust gene-interaction networks recapitulating both protein complexes and functional cooperation among complexes and pathways. This dataset along with a web portal is provided to the community to assist in the discovery and translation of new therapeutic approaches for cancer.