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Purpose: Addition of ataxia telangiectasia and Rad3-related kinase inhibitors (ATRi) to poly-ADP ribose polymerase inhibitors (PARPi) overcomes PARPi-resistance in high grade serous ovarian cancer (HGSOC) cell and mouse models. We present the results of an investigator-initiated study of combination PARPi(olaparib) and ATRi(ceralasertib) in patients with acquired PARPi-resistant HGSOC. Patients and Methods: Eligible patients had recurrent, platinum-sensitive BRCA1/2 mutated or homologous recombination (HR) deficient HGSOC and clinically benefited from PARPi (response by imaging/CA-125 or duration of maintenance therapy; >12 months 1st-line or >6 months ≥2nd-line) before progression. No intervening chemotherapy was permitted. Patients received olaparib 300mg twice daily and ceralasertib 160mg daily on days 1-7 of a 28-day cycle. Primary objectives were safety and objective response rate (ORR). Results: Thirteen patients enrolled were evaluable for safety and 12 for efficacy. 62%(n=8) had germline BRCA1/2 mutations, 23% (n=3) somatic BRCA1/2 mutations, and 15%(n=2) HR-deficient tumors. Prior PARPi indication was treatment for recurrence (54%, n=7), 2nd line-maintenance (38%, n=5), and frontline treatment with carboplatin/paclitaxel (8%, n=1). There were 6 partial responses yielding an ORR of 50% (95% CI:0.15, 0.72). Median treatment duration was 8 cycles (range 4-23+). Grade(G) 3/4 toxicities were 38%(n=5); 15%(n=2) G3 anemia, 23%(n=3) G3 thrombocytopenia, 8% (n=1) G4 neutropenia. Four patients required dose-reductions. No patient discontinued treatment due to toxicity. Conclusion: Combination olaparib and ceralasertib is tolerable and shows activity in HR-deficient platinum-sensitive recurrent HGSOC that benefited and then progressed with PARPi as the penultimate regimen. These data suggest that ceralasertib re-sensitizes PARPi resistant HGSOCs to olaparib, warranting further investigation.

Although checkpoint inhibitors that block CTLA-4 and PD-1 have improved cancer immunotherapies, targeting additional checkpoint receptors may be required to broaden patient response to immunotherapy. PVRIG is a coinhibitory receptor of the DNAM/TIGIT/CD96 nectin family that binds to PVRL2. We report that antagonism of PVRIG and TIGIT, but not CD96, increased CD8+ T-cell cytokine production and cytotoxic activity. The inhibitory effect of PVRL2 was mediated by PVRIG and not TIGIT, demonstrating that the PVRIG–PVRL2 pathway is a nonredundant signaling node. A combination of PVRIG blockade with TIGIT or PD-1 blockade further increased T-cell activation. In human tumors, PVRIG expression on T cells was increased relative to normal tissue and trended with TIGIT and PD-1 expression. Tumor cells coexpressing PVR and PVRL2 were observed in multiple tumor types, with highest coexpression in endometrial cancers. Tumor cells expressing either PVR or PVRL2 were also present in numbers that varied with the cancer type, with ovarian cancers having the highest percentage of PVR−PVRL2+ tumor cells and colorectal cancers having the highest percentage of PVR+PVRL2− cells. To demonstrate a role of PVRIG and TIGIT on tumor-derived T cells, we examined the effect of PVRIG and TIGIT blockade on human tumor-infiltrating lymphocytes. For some donors, blockade of PVRIG increased T-cell function, an effect enhanced by combination with TIGIT or PD-1 blockade. In summary, we demonstrate that PVRIG and PVRL2 are expressed in human cancers and the PVRIG–PVRL2 and TIGIT–PVR pathways are nonredundant inhibitory signaling pathways.See related article on p. 244

Supplementary Figure Legends from ARID1A Deficiency Impairs the DNA Damage Checkpoint and Sensitizes Cells to PARP Inhibitors

Supplement 2

Somatic mutations and single nucleotide variants (SNVs) in paired tissue from cervical swabs, serum/plasma and urine from patient TG01

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Supplementary Methods from ARID1A Deficiency Impairs the DNA Damage Checkpoint and Sensitizes Cells to PARP Inhibitors

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Legends for Supplementary Figures 1-4

Supplementary Figures and Tables

Supplementary Figure 1. Proteomic analysis of ATR-interacting proteins. Supplementary Figure 2. ARID1A interacts with ATR in MDA-MB-231 Cells. Supplementary Figure 3. ARID1A recruitment to I-SceI-induced DSBs analyzed by ChIP assay. Supplementary Figure 4. Schematic diagram of KillerRed system in U2OS TRE cells. Supplementary Figure 5. Expression of ARID1A mutants. Supplementary Figure 6. Knockdown BRG1, BRM, or ARID1A in U2OS cells. Supplementary Figure 7. ARID1A depletion did not affect the number of ATM foci after exposure to IR. Supplementary Figure 8. (A) ARID1A depletion did not affect the presence of DSBs after exposure to IR. Supplementary Figure 9. ARID1A depletion did not affect the expression of DSB end resection factors. Supplementary Figure 10. ARID1A depletion did not affect the expression of ATM and MRN complex. Supplementary Figure 11. (A) ARID1A depletion sensitize MDA-MB-231 cells to PARP inhibitor. Supplementary Figure 12. ARID1A knockdown sensitizes ovarian cancer cell line HOC8 to PARP inhibitor. Supplementary Figure 13. Ovarian cancer cells with lower expression levels of ARID1A are more sensitive to PARP inhibitor treatment than cells with higher ARID1A expression levels. Supplementary Figure 14. Rescuing experiments were conducted with ARID1A wild-type and mutant constructs (deletion mutants/patient-derived mutants). Supplementary Figure 15. ATR inhibitor sensitizes cells to PAPR Inhibitor treatment. Supplementary Figure 16. Proposed model for ARID1A function in DSB End Resection and repair.

Survival alleles at SNV level

Supplementary Figure 3

Supplement 3: Baseline characteristics for the 105 women that underwent extensive sampling of thefallopian tube.

Methylation and mutation associations

Molecular alterations that contribute to long-term (LT) and short-term (ST) survival in ovarian high-grade serous carcinoma (HGSC) may be used as precision medicine biomarkers. DNA promoter methylation is an early event in tumorigenesis, which can be detected in blood and urine, making it a feasible companion biomarker to somatic mutations for early detection and targeted treatment workflows. We compared the methylation profile in 12 HGSC tissue samples to 30 fallopian tube epithelium samples, using the Infinium Human Methylation 450K Array. We also used 450K methylation arrays to compare methylation among HGSCs long-term survivors (more than 5 years) and short-term survivors (less than 3 years). We verified the array results using bisulfite sequencing and methylation-specific PCR (qMSP). in another cohort of HGSC patient samples (n = 35). Immunoblot and clonogenic assays after pharmacologic unmasking show that HIST1H2BB and MAGI2 promoter methylation downregulates mRNA expression levels in ovarian cancer cells. We then used qMSP in paired tissue, ascites, plasma/serum, vaginal swabs, and urine from a third cohort of patients with HGSC cancer (n = 85) to test the clinical potential of HIST1H2BB and MAGI2 in precision medicine workflows. We also performed next-generation exome sequencing of 50 frequently mutated in human cancer genes, using the Ion AmpliSeqCancer Hotspot Panel, to show that the somatic mutation profile found in tissue and plasma can be quantified in paired urine samples from patients with HGSC. Our results suggest that HIST1H2BB and MAGI2 have growth-suppressing roles and can be used as HGSC precision medicine biomarkers.

Somatic mutations and single nucleotide variants (SNVs) in paired tissue from cervical swabs, serum/plasma and urine from patient TG05

Purpose:The current paradigm in the development of high-grade serous ovarian carcinoma (HGSC) proposes that the majority of HGSCs arise from precursor serous tubal intraepithelial carcinoma (STIC) lesions of the fallopian tube. Here we survey genome-wide methylation in HGSC precursor lesions to identify genomic regions that exhibit high-specificity differential hypermethylation for potential use as biomarkers for detecting STIC and HGSC at stages when curative intervention likely remains feasible.Experimental Design:We first identified quality control criteria for performing reliable methylomic analysis of DNA-limited tubal precursor lesions with the Illumina Infinium MethylationEPIC array. We then used this platform to compare genome-wide methylation among 12 STICs with paired adjacent-normal epithelia, one p53 signature lesion and two samples of concurrent HGSC. The resulting methylomic data were analyzed by unsupervised hierarchical clustering and multidimensional analysis. Regions of high-confidence STIC-specific differential hypermethylation were identified using selective bioinformatic criteria and compared with published MethylationEPIC data from 23 HGSC tumors and 11 healthy fallopian tube mucosae.Results:Unsupervised analysis showed that STICs largely clustered with HGSCs, but were clearly distinct from adjacent-normal fallopian tube epithelia. Forty-two genomic regions exhibited high-confidence STIC-specific differential hypermethylation, of which 17 (40.5%) directly overlapped with HGSC-specific differentially methylated regions. Methylation at these shared loci was able to completely distinguish STIC and HGSC samples from normal and adjacent-normal specimens.Conclusions:Our results suggest that most STICs are epigenetically similar to HGSCs and share regions of differential hypermethylation that warrant further evaluation for potential use as biomarkers for early detection of ovarian HGSC.See related commentary by Ishak and De Carvalho, p. 6083

Elucidating the earliest pathogenic steps in cancer development is fundamental to improving its early detection and prevention. Ovarian high-grade serous carcinoma (HGSC), a highly aggressive cancer, mostly originates from the fallopian tube epithelium through a precursor stage, serous tubal intraepithelial carcinoma (STIC). In this study, we performed spatial transcriptomic analysis to compare STICs, carcinoma, and their matched normal fallopian tube epithelium. Several differentially expressed genes in STICs and carcinomas were involved in cancer metabolism and detected in a larger independent transcriptomic dataset of ovarian HGSCs. Among these, insulin-like growth factor binding protein-2 (IGFBP2) was found to undergo DNA hypomethylation and to be increased at the protein level in STICs. Pyrosequencing revealed an association of IGFBP2 expression with the methylation state of its proximal enhancer, and 5-azacytidine treatment increased IGFBP2 expression. In postmenopausal fallopian tubes, where most STICs are detected, IGFBP2 immunoreactivity was detected in all 38 proliferatively active STICs but was undetectable in morphologically normal tubal epithelia, including those with TP53 mutations. In premenopausal fallopian tubes, IGFBP2 expression was limited to the secretory epithelium at the proliferative phase, and estradiol treatment increased IGFBP2 expression levels. IGFBP2 knockdown suppressed the growth of IGFBP2-expressing tubal epithelial cells via inactivation of the AKT pathway. Taken together, demethylation of the proximal enhancer of IGFBP2 drives tumor development by maintaining the increased IGFBP2 required for proliferation in an otherwise estrogen-deprived, proliferation-quiescent, and postmenopausal tubal microenvironment.Significance:Molecular studies of the earliest precursor lesions of ovarian cancer reveal a role of IGFBP2 in propelling tumor initiation, providing new insights into ovarian cancer development.

Supplementary Table 2 from Gene Expression Signatures Differentiate Ovarian/Peritoneal Serous Carcinoma from Diffuse Malignant Peritoneal Mesothelioma

Supplementary Figures S1-S5

Supplemental Materials, Supplemental Tables S1, S2,and S5, Supplemental Figures S1-S6

Purpose: Ovarian/primary peritoneal serous carcinoma (OC/PPC) and diffuse peritoneal malignant mesothelioma (DMPM) are highly aggressive tumors that are closely related morphologically and histogenetically. It remains unclear whether both tumors are molecularly distinct neoplasms. The current study compared global gene expression patterns in OC/PPC and DMPM.Experimental Design: Ten OC/PPC and five DMPM effusions were analyzed for gene expression profiles using the Affymetrix U133 Plus 2 arrays and the dCHIP analysis program. Differentially expressed candidate genes were validated using quantitative real-time PCR and immunohistochemistry.Results: Unsupervised hierarchical clustering using all 54,675 genes in the array classified the samples into two groups: DMPM specimens versus OC/PPC specimens. A total of 189 genes that were differentially expressed in these two groups were selected based on statistical significance. Genes overexpressed in DMPM (n = 68) included calretinin, vitronectin, claudin 15, α4 laminin, hyaluronan synthase 1, cadherin 11, RAB7, v-maf, and the epidermal growth factor–containing fibulin-like extracellular matrix protein 1. Genes overexpressed in OC/PPC (n = 121) included insulin-like growth factor II (IGF-II); IGF-II binding protein 3; cyclin E1; folate receptors 1 and 3; RAB25; MUC4; endothelin-1; CD24; kallikreins 6, 7, and 8; claudins 3, 4, and 6; Notch3; and MMP-7. Quantitative real-time PCR validated the differential expression of 13 genes, and immunohistochemistry confirmed the differences for four gene products.Conclusions: Expression profiling separates OC/PPC from DMPM and identifies a number of genes that are differentially expressed in these tumors. The molecular signatures unique to OC/PPC and DMPM should provide a molecular basis to study both tumors and new potential markers for facilitating their differential diagnosis.

Supplementary Tables S1-S8

Supplementary Figures

The evolution of chemoresistance is a fundamental characteristic of cancer that ultimately hampers its clinical management. However, it may be possible to improve patient outcomes significantly by a better understanding of resistance mechanisms, which cancers rely upon during the evolution to an untreatable state. Here we report an essential role of the stem cell reprogramming factor, PBX1, in mediating chemoresistance in ovarian carcinomas. In the clinical setting, high levels of PBX1 expression correlated with shorter survival in post-chemotherapy ovarian cancer patients. In tumor cells with low endogenous levels of PBX1, its enforced expression promoted cancer stem cell-like phenotypes, including most notably an increase in resistance to platinum-based therapy used most commonly for treating this disease. Conversely, silencing PBX1 in platinum-resistant cells that overexpressed PBX1 sensitized them to platinum treatment and reduced their stem-like properties. An analysis of published genome-wide chromatin immunoprecipitation data indicated that PBX1 binds directly to promoters of genes involved in stem cell maintenance and the response to tissue injury. We confirmed direct regulation of one of these genes, STAT3, demonstrating that the PBX1 binding motif at its promoter acted to positively regulate STAT3 transcription. We further demonstrated that a STAT3/JAK2 inhibitor could potently sensitize platinum-resistant cells to carboplatin and suppress their growth in vivo. Our findings offer a mechanistic rationale to target the PBX1/STAT3 axis to antagonize a key mechanism of chemoresistance in ovarian cancers and possibly other human cancers. Cancer Res; 76(21); 6351–61. ©2016 AACR.

Supplementary Tables 1-3, Supplementary Figures 1-7. Supplementary Table 1: Oligonucleotide primers used for qRT-PCR analysis. Supplementary Table 2: GSEA enrichment of KEGG functional pathways in lovastatin-regulated genes. Supplementary Table 3: Lovastatin affects expression of genes in glycolysis/gluconeogenesis pathway. Supplementary Figure 1: Daily administration of lovastatin prevents tumor growth in mogp-TAg transgenic mice. Supplementary Figure 2: Body weight and serum levels of cholesterol and triglyceride in mogp-TAg, SKOV3-IP, and OVCAR5 mouse tumor models. Supplementary Figure 3: Atorvastatin treatment delays growth of ovarian tumor xenografts. Supplementary Figure 4: Statin treatment increases transcript levels of LC3A and LC3B. Supplementary Figure 5: Scheme of the mevalonate pathway. Supplementary Figure 6: Applying GGPP or FPP as a single agent does not affect ovarian cancer cell proliferation. Supplementary Figure 7: Real-time qRT-PCR confirms knockdown efficiency of each siRNA.

Differentially expressed genes between different comparisons

Gene promoters identified by PBX1 ChIP-on-chip.

Supplementary Table 1 from Gene Expression Signatures Differentiate Ovarian/Peritoneal Serous Carcinoma from Diffuse Malignant Peritoneal Mesothelioma

Including Supplementary Figures and Methods