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Mutant RAS has remained recalcitrant to targeted therapy efforts. We demonstrate that combined treatment with poly(adenosine diphosphate-ribose) polymerase (PARP) inhibitors and mitogen-activated protein kinase (MAPK) kinase (MEK) inhibitors evokes unanticipated, synergistic cytotoxic effects in vitro and in vivo in multiple RAS mutant tumor models across tumor lineages where RAS mutations are prevalent. The effects of PARP and MEK inhibitor combinations are independent of BRCA1/2 and p53 mutation status, suggesting that the synergistic activity is likely to be generalizable. Synergistic activity of PARP and MEK inhibitor combinations in RAS mutant tumors is associated with (i) induction of BIM-mediated apoptosis, (ii) decrease in expression of components of the homologous recombination DNA repair pathway, (iii) decrease in homologous recombination DNA damage repair capacity, (iv) decrease in DNA damage checkpoint activity, (v) increase in PARP inhibitor-induced DNA damage, (vi) decrease in vascularity that could increase PARP inhibitor efficacy by inducing hypoxia, and (vii) elevated PARP1 protein, which increases trapping activity of PARP inhibitors. Mechanistically, enforced expression of FOXO3a, which is a target of the RAS/MAPK pathway, was sufficient to recapitulate the functional consequences of MEK inhibitors including synergy with PARP inhibitors. Thus, the ability of mutant RAS to suppress FOXO3a and its reversal by MEK inhibitors accounts, at least in part, for the synergy of PARP and MEK inhibitors in RAS mutant tumors. The rational combination of PARP and MEK inhibitors warrants clinical investigation in patients with RAS mutant tumors where there are few effective therapeutic options.

Identification of cancer driver mutations is critical for advancing cancer research and personalized medicine. Due to inter-tumor genetic heterogeneity, many driver mutations occur at low frequencies, which make it challenging to distinguish them from passenger mutations. Here, we show that a novel Bayesian hierarchical modeling approach, named rDriver can achieve enhanced prediction accuracy by identifying mutations that not only have high functional impact scores but also are associated with systemic variation in gene expression levels. In examining 3,080 tumor samples from 8 cancer types in The Cancer Genome Atlas, rDriver predicted 1,389 driver mutations. Compared with existing tools, rDriver identified more low frequency mutations associated with lineage specific functional properties, timing of occurrence and patient survival. Evaluation of rDriver predictions using engineered cell-line models resulted in a positive predictive value of 0.94 in PIK3CA genes. Our study highlights the importance of integrating multi-omic data in predicting cancer driver mutations and provides a statistically rigorous solution for cancer target discovery and development. [ABSTRACT FROM AUTHOR]

Summary: Clinical and genomic evidence suggests that the metastatic potential of a primary tumor may be dictated by prometastatic events that have additional oncogenic capability. To test this “deterministic” hypothesis, we adopted a comparative oncogenomics-guided function-based strategy involving: (1) comparison of global transcriptomes of two genetically engineered mouse models with contrasting metastatic potential, (2) genomic and transcriptomic profiles of human melanoma, (3) functional genetic screen for enhancers of cell invasion, and (4) evidence of expression selection in human melanoma tissues. This integrated effort identified six genes that are potently proinvasive and oncogenic. Furthermore, we show that one such gene, ACP5, confers spontaneous metastasis in vivo, engages a key pathway governing metastasis, and is prognostic in human primary melanomas. [Copyright &y& Elsevier]

A cardinal feature of malignant melanoma is its metastatic propensity. An incomplete view of the genetic events driving metastatic progression has been a major barrier to rational development of effective therapeutics and prognostic diagnostics for melanoma patients. In this study, we conducted global genomic characterization of primary and metastatic melanomas to examine the genomic landscape associated with metastatic progression. In addition to uncovering three genomic subclasses of metastastic melanomas, we delineated 39 focal and recurrent regions of amplification and deletions, many of which encompassed resident genes that have not been implicated in cancer or metastasis. To identify progression-associated metastasis gene candidates, we applied a statistical approach, Integrative Genome Comparison (IGC), to define 32 genomic regions of interest that were significantly altered in metastatic relative to primary melanomas, encompassing 30 resident genes with statistically significant expression deregulation. Functional assays on a subset of these candidates, including MET, ASPM, AKAP9, IMP3, PRKCA, RPA3, and SCAP2, validated their pro-invasion activities in human melanoma cells. Validity of the IGC approach was further reinforced by tissue microarray analysis of Survivin showing significant increased protein expression in thick versus thin primary cutaneous melanomas, and a progression correlation with lymph node metastases. Together, these functional validation results and correlative analysis of human tissues support the thesis that integrated genomic and pathological analyses of staged melanomas provide a productive entry point for discovery of melanoma metastases genes.