Ovarian cancer is usually diagnosed at late stages when cancer has spread beyond the ovary and patients ultimately succumb to the development of drug-resistant disease. There is an urgent and unmet need to develop therapeutic strategies that effectively treat ovarian cancer and this requires a better understanding of signaling pathways important for ovarian cancer progression. Aurora A kinase (AURKA) plays an important role in ovarian cancer progression by mediating mitosis and chromosomal instability. In the current study, we investigated the role of AURKA in regulating the DNA damage response and DNA repair in ovarian carcinoma cells. We discovered that AURKA modulated the expression and activity of PARP, a crucial mediator of DNA repair that is a target of therapeutic interest for the treatment of ovarian and other cancers. Further, specific inhibition of AURKA activity with the small molecule inhibitor, alisertib, stimulated the non-homologous end-joining (NHEJ) repair pathway by elevating DNA-PKcs activity, a catalytic subunit required for double-strand break (DSB) repair, as well as decreased the expression of PARP and BRCA1/2, which are required for high-fidelity homologous recombination-based DNA repair. Further, AURKA inhibition stimulates error-prone NHEJ repair of DNA double-strand breaks with incompatible ends. Consistent with in vitro findings, alisertib treatment increased phosphorylated DNA-PKcs(pDNA-PKcsT2609) and decreased PARP levels in vivo. Collectively, these results reveal new non-mitotic functions for AURKA in the regulation of DNA repair, which may inform of new therapeutic targets and strategies for treating ovarian cancer.

Tumor-infiltrating lymphocyte (TIL) therapy is a personalized cancer treatment which involves generating ex vivo cultures of tumor-reactive T cells from surgically resected tumors and administering the expanded TILs as a therapeutic infusion. Phase 1 of many TIL production protocols use aldesleukin (IL-2) alone to establish TIL cultures (termed "PreREP" (Pre-Rapid Expansion Protocol)); however, this fails to consistently produce TIL cultures from renal cell carcinoma (RCC) in a timely manner. Adding mitogenic stimulation via anti-CD3/anti-CD28 beads along with IL-2 to the fresh tumor digest (FTD) during TIL generation (termed "FTD+ beads") increases successful TIL culture rates; however, T cells produced by this method may be suboptimal for adoptive transfer. We hypothesize that adherent cell depletion (ACD) before TIL expansion will produce a superior TIL product by removing the immunosuppressive signals originating from adherent tumor and stromal cells. Here we investigate if "panning," a technique for ACD prior to TIL expansion, will impact the phenotype, functionality and/or clonality of ex vivo expanded RCC TILs.

Triple-negative breast cancer (TNBC) patients with residual disease (RD) after neoadjuvant systemic therapy (NAST) are at high risk for recurrence. Biomarkers to risk-stratify patients with RD could help individualize adjuvant therapy and inform future adjuvant therapy trials. We aim to investigate the impact of circulating tumor DNA (ctDNA) status and residual cancer burden (RCB) class on outcomes in TNBC patients with RD. We analyze end-of-treatment ctDNA status in 80 TNBC patients with residual disease who are enrolled in a prospective multisite registry. Among 80 patients, 33% are ctDNA positive (ctDNA+) and RCB class distribution is RCB-I = 26%, RCB-II = 49%, RCB-III = 18% and 7% unknown. ctDNA status is associated with RCB status, with 14%, 31%, and 57% of patients within RCB-I, -II, and -III classes demonstrating ctDNA+ status (P = 0.028). ctDNA+ status is associated with inferior 3-year EFS (48% vs. 82%, P < 0.001) and OS (50% vs. 86%, P = 0.002). ctDNA+ status predicts inferior 3-year EFS among RCB-II patients (65% vs. 87%, P = 0.044) and shows a trend for inferior EFS among RCB-III patients (13% vs. 40%, P = 0.081). On multivariate analysis accounting for T stage and nodal status, RCB class and ctDNA status independently predict EFS (HR = 5.16, P = 0.016 for RCB class; HR = 3.71, P = 0.020 for ctDNA status). End-of-treatment ctDNA is detectable in one-third of TNBC patients with residual disease after NAST. ctDNA status and RCB are independently prognostic in this setting.

Understanding the molecular mechanisms of ultraviolet (UV) induced melanoma formation is becoming crucial with more reported cases each year. Expression of type II nuclear receptor Retinoid-X-Receptor α (RXRα) is lost during melanoma progression in humans. Here, we observed that in mice with melanocyte-specific ablation of RXRα and RXRβ, melanocytes attract fewer IFN-γ secreting immune cells than in wild-type mice following acute UVR exposure, via altered expression of several chemoattractive and chemorepulsive chemokines/cytokines. Reduced IFN-γ in the microenvironment alters UVR-induced apoptosis, and due to this, the survival of surrounding dermal fibroblasts is significantly decreased in mice lacking RXRα/β. Interestingly, post-UVR survival of the melanocytes themselves is enhanced in the absence of RXRα/β. Loss of RXRs α/β specifically in the melanocytes results in an endogenous shift in homeostasis of pro- and anti-apoptotic genes in these cells and enhances their survival compared to the wild type melanocytes. Therefore, RXRs modulate post-UVR survival of dermal fibroblasts in a "non-cell autonomous" manner, underscoring their role in immune surveillance, while independently mediating post-UVR melanocyte survival in a "cell autonomous" manner. Our results emphasize a novel immunomodulatory role of melanocytes in controlling survival of neighboring cell types besides controlling their own, and identifies RXRs as potential targets for therapy against UV induced melanoma.

From March through August 2015, nearly 60 teams from around the world participated in the Prostate Cancer Dream Challenge (PCDC). Participating teams were faced with the task of developing prediction models for patient survival and treatment discontinuation using baseline clinical variables collected on metastatic castrate-resistant prostate cancer (mCRPC) patients in the comparator arm of four phase III clinical trials. In total, over 2,000 mCRPC patients treated with first-line docetaxel comprised the training and testing data sets used in this challenge. In this paper we describe: (a) the sub-challenges comprising the PCDC, (b) the statistical metrics used to benchmark prediction performance, (c) our analytical approach, and finally (d) our team's overall performance in this challenge. Specifically, we discuss our curated, ad-hoc, feature selection (CAFS) strategy for identifying clinically important risk-predictors, the ensemble-based Cox proportional hazards regression framework used in our final submission, and the adaptation of our modeling framework based on the results from the intermittent leaderboard rounds. Strong predictors of patient survival were successfully identified utilizing our model building approach. Several of the identified predictors were new features created by our team via strategically merging collections of weak predictors. In each of the three intermittent leaderboard rounds, our prediction models scored among the top four models across all participating teams and our final submission ranked 9 th place overall with an integrated area under the curve (iAUC) of 0.7711 computed in an independent test set. While the prediction performance of teams placing between 2 nd- 10 th (iAUC: 0.7710-0.7789) was better than the current gold-standard prediction model for prostate cancer survival, the top-performing team, FIMM-UTU significantly outperformed all other contestants with an iAUC of 0.7915.  In summary, our ensemble-based Cox regression framework with CAFS resulted in strong overall performance for predicting prostate cancer survival and represents a promising approach for future prediction problems.

The long-term overall survival of Ewing sarcoma (EWS) patients remains poor; less than 30% of patients with metastatic or recurrent disease survive despite aggressive combinations of chemotherapy, radiation and surgery. To identify new therapeutic options, we employed a multi-pronged approach using in silico predictions of drug activity via an integrated bioinformatics approach in parallel with an in vitro screen of FDA-approved drugs. Twenty-seven drugs and forty-six drugs were identified, respectively, to have anti-proliferative effects for EWS, including several classes of drugs in both screening approaches. Among these drugs, 30 were extensively validated as mono-therapeutic agents and 9 in 14 various combinations in vitro. Two drugs, auranofin, a thioredoxin reductase inhibitor, and ganetespib, an HSP90 inhibitor, were predicted to have anti-cancer activities in silico and were confirmed active across a panel of genetically diverse EWS cells. When given in combination, the survival rate in vivo was superior compared to auranofin or ganetespib alone. Importantly, extensive formulations, dose tolerance, and pharmacokinetics studies demonstrated that auranofin requires alternative delivery routes to achieve therapeutically effective levels of the gold compound. These combined screening approaches provide a rapid means to identify new treatment options for patients with a rare and often-fatal disease.

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer death among women in the United States (5 % of cancer deaths). The standard treatment for patients with advanced EOC is initial debulking surgery followed by carboplatin-paclitaxel combination chemotherapy. Unfortunately, with chemotherapy most patients relapse and die resulting in a five-year overall survival around 45 %. Thus, finding novel therapeutics for treating EOC is essential. Connectivity Mapping (CMAP) has been used widely in cancer drug discovery and generally has relied on cancer cell line gene expression and drug phenotype data. Therefore, we took a CMAP approach based on tumor information and clinical endpoints from high grade serous EOC patients.

Gene fusions play a critical role in some cancers and can serve as important clinical targets. In epithelial ovarian cancer (EOC), the contribution of fusions, especially by histological type, is unclear. We therefore screened for recurrent fusions in a histologically diverse panel of 220 EOCs using RNA sequencing. The Pipeline for RNA-Sequencing Data Analysis (PRADA) was used to identify fusions and allow for comparison with The Cancer Genome Atlas (TCGA) tumors. Associations between fusions and clinical prognosis were evaluated using Cox proportional hazards regression models. Nine recurrent fusions, defined as occurring in two or more tumors, were observed. CRHR1-KANSL1 was the most frequently identified fusion, identified in 6 tumors (2.7% of all tumors). This fusion was not associated with survival; other recurrent fusions were too rare to warrant survival analyses. One recurrent in-frame fusion, UBAP1-TGM7, was unique to clear cell (CC) EOC tumors (in 10%, or 2 of 20 CC tumors). We found some evidence that CC tumors harbor more fusions on average than any other EOC histological type, including high-grade serous (HGS) tumors. CC tumors harbored a mean of 7.4 fusions (standard deviation [sd] = 7.4, N = 20), compared to HGS EOC tumors mean of 2.0 fusions (sd = 3.3, N = 141). Few fusion genes were detected in endometrioid tumors (mean = 0.24, sd = 0.74, N = 55) or mucinous tumors (mean = 0.25, sd = 0.5, N = 4) tumors. To conclude, we identify one fusion at 10% frequency in the CC EOC subtype, but find little evidence for common (> 5% frequency) recurrent fusion genes in EOC overall, or in HGS subtype-specific EOC tumors.

There is a lack of personalized treatment options for women with recurrent platinum-resistant ovarian cancer. Outside of bevacizumab and a group of poly ADP-ribose polymerase inhibitors, few options are available to women that relapse. We propose that efficacious drug combinations can be determined via molecular characterization of ovarian tumors along with pre-established pharmacogenomic profiles of repurposed compounds. To that end, we selectively performed multiple two-drug combination treatments in ovarian cancer cell lines that included reactive oxygen species inducers and HSP90 inhibitors. This allowed us to select cell lines that exhibit disparate phenotypes of proliferative inhibition to a specific drug combination of auranofin and AUY922. We profiled altered mechanistic responses from these agents in both reactive oxygen species and HSP90 pathways, as well as investigated PRKCI and lncRNA expression in ovarian cancer cell line models. Generation of dual multi-gene panels implicated in resistance or sensitivity to this drug combination was produced using RNA sequencing data and the validity of the resistant signature was examined using high-density RT-qPCR. Finally, data mining for the prevalence of these signatures in a large-scale clinical study alluded to the prevalence of resistant genes in ovarian tumor biology. Our results demonstrate that high-throughput viability screens paired with reliable in silico data can promote the discovery of effective, personalized therapeutic options for a currently untreatable disease.

Lung cancer accounts for approximately 14% of all newly diagnosed cancers and is the leading cause of cancer-related deaths. Chimeric RNA resulting from gene fusions (RNA fusions) and other RNA splicing errors are driver events and clinically addressable targets for non-small cell lung cancer (NSCLC). The reliable assessment of these RNA markers by next-generation sequencing requires integrated reagents, protocols, and interpretive software that can harmonize procedures and ensure consistent results across laboratories. We describe the development and verification of a system for targeted RNA sequencing for the analysis of challenging, low-input solid tumor biopsies that includes reagents for nucleic acid quantification and library preparation, run controls, and companion bioinformatics software. Assay development reconciled sequence discrepancies in public databases, created predictive formalin-fixed, paraffin-embedded RNA qualification metrics, and eliminated read misidentification attributable to index hopping events on the next-generation sequencing flow cell. The optimized and standardized system was analytically verified internally and in a multiphase study conducted at five independent laboratories. The results show accurate, reproducible, and sensitive detection of RNA fusions, alternative splicing events, and other expression markers of NSCLC. This comprehensive approach, combining sample quantification, quality control, library preparation, and interpretive bioinformatics software, may accelerate the routine implementation of targeted RNA sequencing of formalin-fixed, paraffin-embedded samples relevant to NSCLC.

The standard treatment for epithelial ovarian cancer (EOC) patients with advanced disease is carboplatin-paclitaxel combination therapy following initial debulking surgery, yet there is wide inter-patient variation in clinical response. We sought to identify pharmacogenomic markers related to carboplatin-paclitaxel therapy.