Precision Medicine is an approach that takes into account the influence of individuals' genes, environment and lifestyle exposures to tailor interventions. Here, we describe the development of a robust precision cancer care platform, which integrates whole exome sequencing (WES) with a living biobank that enables high throughput drug screens on patient-derived tumor organoids. To date, 56 tumor-derived organoid cultures, and 19 patient-derived xenograft (PDX) models have been established from the 769 patients enrolled in an IRB approved clinical trial. Because genomics alone was insufficient to identify therapeutic options for the majority of patients with advanced disease, we used high throughput drug screening effective strategies. Analysis of tumor derived cells from four cases, two uterine malignancies and two colon cancers, identified effective drugs and drug combinations that were subsequently validated using 3D cultures and PDX models. This platform thereby promotes the discovery of novel therapeutic approaches that can be assessed in clinical trials and provides personalized therapeutic options for individual patients where standard clinical options have been exhausted.

A major hurdle in the study of rare tumors is a lack of existing preclinical models. Neuroendocrine prostate cancer is an uncommon and aggressive histologic variant of prostate cancer that may arise de novo or as a mechanism of treatment resistance in patients with pre-existing castration-resistant prostate cancer. There are few available models to study neuroendocrine prostate cancer. Here, we report the generation and characterization of tumor organoids derived from needle biopsies of metastatic lesions from four patients. We demonstrate genomic, transcriptomic, and epigenomic concordance between organoids and their corresponding patient tumors. We utilize these organoids to understand the biologic role of the epigenetic modifier EZH2 in driving molecular programs associated with neuroendocrine prostate cancer progression. High-throughput organoid drug screening nominated single agents and drug combinations suggesting repurposing opportunities. This proof of principle study represents a strategy for the study of rare cancer phenotypes.

Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified. In contrast, the MYC antagonists MGA and MNT were the most frequently mutated or deleted members, proposing a role as tumor suppressors. MYC alterations were mutually exclusive with PIK3CA, PTEN, APC, or BRAF alterations, suggesting that MYC is a distinct oncogenic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such as immune response and growth factor signaling; chromatin, translation, and DNA replication/repair were conserved pan-cancer. This analysis reveals insights into MYC biology and is a reference for biomarkers and therapeutics for cancers with alterations of MYC or the PMN.

Background Homologous recombination deficiencies (HRD) are present in approximately half of epithelial ovarian cancers, for which PARP inhibitors (PARPi) are becoming a preferred treatment option. However, a considerable proportion of these carcinomas acquire resistance or harbour de novo resistance, posing a significant challenge to treatment. Methods To identify new combinatorial therapeutics to overcome resistance to PARPi, we employed high-throughput conditional RNAi and drug screening of patient-derived ovarian cancer cells. To prioritise clinically relevant drug combinations, we integrated empirical validation with analysis of The Cancer Genome Atlas (TCGA) and Genomics of Drug Sensitivity in Cancer (GDSC) datasets to nominate candidate targets and drugs, reaching three main findings. Findings Firstly, we found that the PARPi rucaparib enhanced the effect of BET inhibitors (CPI-203 & CPI-0610) irrespective of clinical subtype or HRD status. Additional drug combination screens identified that dasatinib, a non-receptor tyrosine kinase inhibitor, augmented the effects of rucaparib and BET inhibitors, proposing a potential broadly applicable triple-drug combination for high-grade serous and clear cell ovarian carcinomas. Secondly, rucaparib synergised with the BCL2 family inhibitor navitoclax, with preferential activity in ovarian carcinomas that harbour alterations in BRCA1/2, BARD1, or MSH2/6. Thirdly, we identified potentially antagonistic drug combinations between the PARPi rucaparib and vinca alkaloids, anthracyclines, and antimetabolites, cautioning their use in the clinic. Interpretation These findings propose therapeutic strategies to address PARP inhibitor resistance using agents that are already approved or are in clinical development, with the potential for rapid translation to benefit a broad population of ovarian cancer patients.

Ovarian clear cell carcinoma (OCCC) is a rare, chemo-resistant subtype of ovarian cancer. To identify novel therapeutic targets and combination therapies for OCCC, we subjected a set of patient-derived ovarian cancer cell lines to arrayed high throughput siRNA and drug screening. The results indicated OCCC cells are vulnerable to knockdown of epigenetic gene targets such as bromodomain and extra-terminal domain (BET) proteins BRD2 and BRD3. Subsequent RNA interference assays, as well as BET inhibitor treatments validated these BET proteins as potential therapeutic targets. Because development of resistance to single targeted agents is common, we next performed sensitizer drug screens to identify potential combination therapies with the BET inhibitor CPI0610. Several PI3K or AKT inhibitors were among the top drug combinations identified and subsequent work showed CPI0610 synergized with alpelisib or MK2206 by inducing p53-independent apoptosis. We further verified synergy between CPI0610 and