Assessment of ABT-263 activity across a cancer cell line collection leads to a potent combination therapy for small-cell lung cancer.

BH3 mimetics such as ABT-263 induce apoptosis in a subset of cancer models. However, these drugs have shown limited clinical efficacy as single agents in small-cell lung cancer (SCLC) and other solid tumor malignancies, and rational combination strategies remain underexplored. To develop a novel therapeutic approach, we examined the efficacy of ABT-263 across >500 cancer cell lines, including 311 for which we had matched expression data for select genes. We found that high expression of the proapoptotic gene Bcl2-interacting mediator of cell death (BIM) predicts sensitivity to ABT-263. In particular, SCLC cell lines possessed greater BIM transcript levels than most other solid tumors and are among the most sensitive to ABT-263. However, a subset of relatively resistant SCLC cell lines has concomitant high expression of the antiapoptotic myeloid cell leukemia 1 (MCL-1). Whereas ABT-263 released BIM from complexes with BCL-2 and BCL-XL, high expression of MCL-1 sequestered BIM released from BCL-2 and BCL-XL, thereby abrogating apoptosis. We found that SCLCs were sensitized to ABT-263 via TORC1/2 inhibition, which led to reduced MCL-1 protein levels, thereby facilitating BIM-mediated apoptosis. AZD8055 and ABT-263 together induced marked apoptosis in vitro, as well as tumor regressions in multiple SCLC xenograft models. In a Tp53; Rb1 deletion genetically engineered mouse model of SCLC, the combination of ABT-263 and AZD8055 significantly repressed tumor growth and induced tumor regressions compared with either drug alone. Furthermore, in a SCLC patient-derived xenograft model that was resistant to ABT-263 alone, the addition of AZD8055 induced potent tumor regression. Therefore, addition of a TORC1/2 inhibitor offers a therapeutic strategy to markedly improve ABT-263 activity in SCLC.

mTOR inhibition specifically sensitizes colorectal cancers with KRAS or BRAF mutations to BCL-2/BCL-XL inhibition by suppressing MCL-1.

Colorectal cancers harboring KRAS or BRAF mutations are refractory to current targeted therapies. Using data from a high-throughput drug screen, we have developed a novel therapeutic strategy that targets the apoptotic machinery using the BCL-2 family inhibitor ABT-263 (navitoclax) in combination with a TORC1/2 inhibitor, AZD8055. This combination leads to efficient apoptosis specifically in KRAS- and BRAF-mutant but not wild-type (WT) colorectal cancer cells. This specific susceptibility results from TORC1/2 inhibition leading to suppression of MCL-1 expression in mutant, but not WT, colorectal cancers, leading to abrogation of BIM/MCL-1 complexes. This combination strategy leads to tumor regressions in both KRAS-mutant colorectal cancer xenograft and genetically engineered mouse models of colorectal cancer, but not in the corresponding KRAS-WT colorectal cancer models. These data suggest that the combination of BCL-2/BCL-XL inhibitors with TORC1/2 inhibitors constitutes a promising targeted therapy strategy to treat these recalcitrant cancers.

Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells.

Alterations in cancer genomes strongly influence clinical responses to treatment and in many instances are potent biomarkers for response to drugs. The Genomics of Drug Sensitivity in Cancer (GDSC) database (www.cancerRxgene.org) is the largest public resource for information on drug sensitivity in cancer cells and molecular markers of drug response. Data are freely available without restriction. GDSC currently contains drug sensitivity data for almost 75 000 experiments, describing response to 138 anticancer drugs across almost 700 cancer cell lines. To identify molecular markers of drug response, cell line drug sensitivity data are integrated with large genomic datasets obtained from the Catalogue of Somatic Mutations in Cancer database, including information on somatic mutations in cancer genes, gene amplification and deletion, tissue type and transcriptional data. Analysis of GDSC data is through a web portal focused on identifying molecular biomarkers of drug sensitivity based on queries of specific anticancer drugs or cancer genes. Graphical representations of the data are used throughout with links to related resources and all datasets are fully downloadable. GDSC provides a unique resource incorporating large drug sensitivity and genomic datasets to facilitate the discovery of new therapeutic biomarkers for cancer therapies.

Systematic identification of genomic markers of drug sensitivity in cancer cells.

Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. Here, to uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines--which represent much of the tissue-type and genetic diversity of human cancers--with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing's sarcoma cells harbouring the EWS (also known as EWSR1)-FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

A genome-wide RNAi screen identifies multiple RSK-dependent regulators of cell migration.

To define the functional pathways regulating epithelial cell migration, we performed a genome-wide RNAi screen using 55,000 pooled lentiviral shRNAs targeting ∼11,000 genes, selecting for transduced cells with increased motility. A stringent validation protocol generated a set of 31 genes representing diverse pathways whose knockdown dramatically enhances cellular migration. Some of these pathways share features of epithelial-to-mesenchymal transition (EMT), and together they implicate key regulators of transcription, cellular signaling, and metabolism, as well as novel modulators of cellular trafficking, such as DLG5. In delineating downstream pathways mediating these migration phenotypes, we observed universal activation of ERKs and a profound dependence on their RSK effectors. Pharmacological inhibition of RSK dramatically suppresses epithelial cell migration induced by knockdown of all 31 genes, suggesting that convergence of diverse migratory pathways on this kinase may provide a therapeutic opportunity in disorders of cell migration, including cancer metastasis.

Modeling cancer progression via pathway dependencies.

Cancer is a heterogeneous disease often requiring a complexity of alterations to drive a normal cell to a malignancy and ultimately to a metastatic state. Certain genetic perturbations have been implicated for initiation and progression. However, to a great extent, underlying mechanisms often remain elusive. These genetic perturbations are most likely reflected by the altered expression of sets of genes or pathways, rather than individual genes, thus creating a need for models of deregulation of pathways to help provide an understanding of the mechanisms of tumorigenesis. We introduce an integrative hierarchical analysis of tumor progression that discovers which a priori defined pathways are relevant either throughout or in particular steps of progression. Pathway interaction networks are inferred for these relevant pathways over the steps in progression. This is followed by the refinement of the relevant pathways to those genes most differentially expressed in particular disease stages. The final analysis infers a gene interaction network for these refined pathways. We apply this approach to model progression in prostate cancer and melanoma, resulting in a deeper understanding of the mechanisms of tumorigenesis. Our analysis supports previous findings for the deregulation of several pathways involved in cell cycle control and proliferation in both cancer types. A novel finding of our analysis is a connection between ErbB4 and primary prostate cancer.