Supplementary Figure 5 | Clustering (n=106) and survival analysis (n=70) on kinome mutations and CNA. (A) Disease-specific survival of patients (n=70) grouped on ARID1A status, (B) PIK3CA status and (C) ARID1A + PIK3CA status. (D) Consensus clustering, with maximum group count set to 10 and clustering optimization with 1000 repetitions maximum, shows adding of tumors (n=106) as consensus index (horizontally) and empirical cumulative distribution (vertically) for 1-10 clusters. (E) Area under the curve plot of decrease in friction from 1-10 clusters. (F) Heatmap distribution of tumors in 8 clusters. (G) Disease-specific survival of patients (n=70) in 8 clusters, (H) cluster 3 vs. other clusters. (I) Disease-specific survival in advanced stage OCCC patients (FIGO 2C-4), Log rank (Mantel-Cox) was used for statistical analysis. (J) Nonsynonymous mutation distribution in genes involved in the frequently mutated PI3K/AKT/mTOR (blue) and MAPK pathway (yellow), ERBB family of receptor tyrosine kinases (green) and DNA repair pathway (red) as well as ARID1A and PALB2 are shown with OncoPrint. CNA in each mutated gene are added. The 106 OCCC tumors that were both kinome sequenced and SNP arrayed are shown on the horizontal axis grouped on tumor clusters and ordered on total event frequency in the subsequently altered pathways. (K) Oncoprint from advanced stage patients in cluster 3 vs. other clusters, shown on the horizontal axis grouped on tumor clusters and ordered on total event frequency in the subsequent altered pathways, ordered as aforementioned.

Supplementary Figure 4 | Whole genome CNA heatmap. (A) Genome-wide CNA heatmap profiles of all 108 OCCC tumors (above), 63 ARID1A wildtype tumors (middle) and 45 ARID1A mutant tumors (below). (B) Significant CNA plot of only ARID1A wildtype tumors (n=63) and (C) only ARID1A mutant tumors (n=45) as determined by GISTIC analysis. All kinases and cancer-related genes from the kinome sequencing gene panel that were focally significantly amplified (red) or deleted (blue) are indicated along the chromosomes vertically. Chromosomal location and total amount of tumors harboring the event are annotated with each gene name. False-discovery rate (FDR) 0.05 threshold, indicated by the green line, and G-score are shown along the horizontal axis.

Supplementary Table 3 | Binomial testing of kinome sequencing variants.

Supplementary Table 1 | Gene set for kinome sequencing.

Supplementary Figure 7 | PDX alteration status and p-S6 staining. (A) Nonsynonymous mutation distribution in PDX.155, PDX.180 and PDX.247 in genes involved in the frequently mutated PI3K/AKT/mTOR (blue) and MAPK pathway (yellow), ERBB family of receptor tyrosine kinases (green) and DNA repair pathway (red) as well as ARID1A and PALB2 are shown with OncoPrint. CNA in each mutated gene are added. (B) PDX.155, (C) PDX.180 and (D) PDX.247 representative p-S6 expression after 21 days of vehicle or AZD8055 treatment.

Supplementary Figure 2 | Significantly mutated genes AKT1, PIK3R1, ERBB3, FBXW7, ATM, CHEK2 and MYO3A. Schematics of the identified novel significantly mutated genes (A) AKT1, (B) PIK3R1, (C) ERBB3, (D) FBXW7, (E) ATM, (F) CHEK2 and (G) MYO3A in OCCC. Mutation marks are shown in black (truncating), red (SIFT and PolyPhen damaging prediction), yellow (SIFT or PolyPhen damaging prediction) or white (SIFT and PolyPhen benign prediction). Mutation effects are indicated with a black spot when paired control was available and written in black (previously described mutation) or red (novel mutations).

Supplementary Figures 1-5, Tables 1-8. Supplementary Figure 1: Overview of the analytic approach. Supplementary Figure 2: QQ plots of SNPs with MAF ≥0.02 and imputation r2 ≥0.9 associated with Overall Survival in A. Supplementary Figure 3: ‘All OCAC’ histology-adjusted analysis. Supplementary Figure 4: Forest plots of promising SNPs. Supplementary Figure 5: KM-Plotter graphs of significant associations with outcome. Supplementary Table 1: All studies (OCAC & TCGA) eligible for analyses according to first-line chemotherapy. Supplementary Table 2: Description of individual OCAC studies included in the secondary 'all OCAC' analysis. Supplementary Table 3a: Overall Survival estimates for selected SNPs (MAF ≥0.02) comparing iCOGS imputed (r2 ≥0.3) and iPLEX genotyped samples. Supplementary Table 3b: Progression-free Survival estimates for selected SNPs (MAF ≥0.02) comparing iCOGS imputed (r2 ≥0.3) and iPLEX genotyped samples. Supplementary Table 4: SNPs with imputation r2 ≥0.9, EAF ≥0.02 and p ≤ 1E-05 for at least one of four outcomes analyzed in cases selected according to first-line chemotherapy. Supplementary Table 5: Meta-analysis of largest possible sample (TCGA, non-overlapping iCOGS and iplex genotyped) for selected promising SNPs analyzed in cases selected according to first-line chemotherapy. Supplementary Table 6: Significant association between protein-coding genes within 1Mb of promising SNPs and ovarian cancer outcomes. Supplementary Table 7: SNPs with imputation r-sq≥0.9 and p ≤ 1E-05 for Overall Survival in histology-adj 'all OCAC' analysis. Supplementary Table 8: iCOGS estimates for SNPs previously identified to be associated with response to chemotherapy as reported in the aNHGRI GWAS catalog.

Supplementary Figure 3 | Mutation distribution in OCCC. (A) Nonsynonymous mutation distribution in genes involved in the frequently mutated PI3K/AKT/mTOR (blue) and MAPK pathway (yellow), ERBB family of receptor tyrosine kinases (green) and DNA repair (red) pathway is shown. In this OncoPrint, kinome sequenced OCCC tumors are depicted on the horizontal axis and ordered on mutation frequency in the subsequent altered pathways, represented vertically on the right. ARID1A mutant tumors are displayed at the top. (B) BioVenn diagrams demonstrating overlap in ARID1A mutant tumors and PI3K/AKT/mTOR, MAPK and DNA repair pathway and ERBB family of receptor tyrosine kinases mutant tumors (n=103). On the right, PI3K/AKT/mTOR and MAPK pathway, the ERBB family of receptor tyrosine kinases and DNA repair pathway mutations within only ARID1A wildtype tumors (n=49) and only ARID1A mutant tumors (n=44). All data in A and B is derived from 122 kinome-sequenced OCCC tumors, overlap in BioVenn diagram circles is proportional to group overlap.

Legends of supplementary figures and tables

PDF file - 157K, Supplemental Table 1. Regulatory T cell genes included in this study (N=25). Supplemental Table 2. Regulatory T cell SNPs included in this study. Supplemental Table 3. Participating invasive epithelial ovarian cancer studies. Supplemental Table 4. Association between clinical variables and overall survival.

Supplementary Table 4 | Clinicopathological characteristics (n=70 patients).

Supplementary Figure 6 | mTORC1, mTORC1/2 and PI3K-mTORC1/2 inhibitor sensitivities. (A) IC50 of the mTORC1 inhibitor temsirolimus from COSMICs drug screening database in all cancer cell lines vs. ovarian cancer cell lines, horizontal lines indicate geometric mean. (B) MTT assay curves from AZD8055 (left) or everolimus (right) treatment on the aforementioned cell line panel. (C) Expression of p-AKT308, p-AKT473 and p-S6 after 24 (up) and 72h (down) exposure to 100 nM everolimus, AZD8055 or MLN0128 in the OCCC cell lines KOC7C or JHOC5 determined by Western blot. β-Actin was used as loading control. Results are representative from n=2 experiments. (D) Expression of p-AKT308, p-AKT473, p-S6 and (cleaved) PARP after 48h exposure to increasing concentrations of everolimus, AZD8055 and dactolisib in the OCCC cell lines KOC7C (up) and JHOC5 (down) determined by Western blot. β-Actin was used as loading control. Results are representative from n=2 experiments. (E) Everolimus, AZD8055, GDC0941 and selumetinib IC50 determined for 14 OCCC cell lines (ES2, KOC7C, SMOV2, JHOC5, RMG1, OVMANA, HAC2, OV207, OVTOKO, TOV21G, OVAS, OVCA429, TUOC1 and RMG2) and dactolisib IC50 determined for 7 OCCC cell lines (ES2, KOC7C, SMOV2, JHOC5, RMG1, OVMANA and HAC2) by MTT assay. Selumetinib IC50 of KOC7C was not reached at maximum used concentration of 25 uM. Horizontal lines indicate geometric mean. Data is derived from n{greater than or equal to}2 experiments. (F) Long-term proliferation assay after exposure to increasing concentrations of AZD8055 and dactolisib. Results are representative from n=3 experiments.

Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers. Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data. Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10−7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation. Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis. Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

ABSTRACTWe report a meta-analysis of breast, prostate, ovarian, and endometrial cancer genome-wide association data (effective sample size: 237,483 cases/317,006 controls). This identified 465 independent lead variants (P<5×10−8) across 192 genomic regions. Four lead variants were >1Mb from previously identified risk loci for the four cancers and an additional 23 lead variant-cancer associations were novel for one of the cancers. Bayesian models supported pleiotropic effects involving at least two cancers at 222/465 lead variants in 118/192 regions. Gene-level association analysis identified 13 shared susceptibility genes (P<2.6×10−6) in 13 regions not previously implicated in any of the four cancers and not uncovered by our variant-level meta-analysis. Several lead variants had opposite effects across cancers, including a cluster of such variants in the TP53 pathway. Fifty-four lead variants were associated with blood cell traits and suggested genetic overlaps with clonal hematopoiesis. Our study highlights the remarkable pervasiveness of pleiotropy across hormone-related cancers, further illuminating their shared genetic and mechanistic origins at variant- and gene-level resolution.

Abstract Purpose: Advanced-stage ovarian clear cell carcinoma (OCCC) is unresponsive to conventional platinum-based chemotherapy. Frequent alterations in OCCC include deleterious mutations in the tumor suppressor ARID1A and activating mutations in the PI3K subunit PIK3CA. In this study, we aimed to identify currently unknown mutated kinases in patients with OCCC and test druggability of downstream affected pathways in OCCC models. Experimental Design: In a large set of patients with OCCC (n = 124), the human kinome (518 kinases) and additional cancer-related genes were sequenced, and copy-number alterations were determined. Genetically characterized OCCC cell lines (n = 17) and OCCC patient–derived xenografts (n = 3) were used for drug testing of ERBB tyrosine kinase inhibitors erlotinib and lapatinib, the PARP inhibitor olaparib, and the mTORC1/2 inhibitor AZD8055. Results: We identified several putative driver mutations in kinases at low frequency that were not previously annotated in OCCC. Combining mutations and copy-number alterations, 91% of all tumors are affected in the PI3K/AKT/mTOR pathway, the MAPK pathway, or the ERBB family of receptor tyrosine kinases, and 82% in the DNA repair pathway. Strong p-S6 staining in patients with OCCC suggests high mTORC1/2 activity. We consistently found that the majority of OCCC cell lines are especially sensitive to mTORC1/2 inhibition by AZD8055 and not toward drugs targeting ERBB family of receptor tyrosine kinases or DNA repair signaling. We subsequently demonstrated the efficacy of mTORC1/2 inhibition in all our unique OCCC patient–derived xenograft models. Conclusions: These results propose mTORC1/2 inhibition as an effective treatment strategy in OCCC. Clin Cancer Res; 24(16); 3928–40. ©2018 AACR.

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR = 1.33, p = 4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR = 1.07, p = 0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR = 0.90, p = 0.00033; rs927062, OR = 0.94, p = 0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations.

BACKGROUND:Vulvar lichen sclerosus is a chronic and incurable disease that causes various unpleasant symptoms and serious consequences.OBJECTIVE:The purpose of the study was to assess the effectiveness of photodynamic therapy in the treatment of vulvar lichen sclerosus.METHODS:Participants in the study included 102 female patients aged 19-85 suffer from vulvar lichen sclerosus. The patients underwent photodynamic therapy (PDT). In the course of PDT the 5% 5- aminolevulinic acid was used in gel form. The affected areas were irradiated with a halogenic lamp PhotoDyn 501 (590-760nm) during a 10-min radiation treatment. The treatment was repeated weekly for 10 weeks.RESULT:PDT has brought about a good therapeutic effect (complete or partial clinical remission), with 87.25% improvement rate in patients suffering from lichen sclerosus. The greatest vulvoscopic response was observed in the reduction of subepithelial ecchymoses and teleangiectasia (78.95%), and the reduction of erosions and fissures (70.97%). A partial remission of lichenification with hyperkeratosis was observed in 51.61% of cases. The least response was observed in the atrophic lesions reduction (improvement in 37.36% of cases).CONCLUSION:Our patients suffering from vulvar lichen sclerosus demonstrated positive responses to photodynamic therapy and the treatment was well tolerated. Photodynamic therapy used to treat lichen sclerosus yields excellent cosmetic results.

BackgroundOlaparib, a poly(ADP-ribose) polymerase (PARP) inhibitor, has previously shown efficacy in a phase 2 study when given in capsule formulation to all-comer patients with platinum-sensitive, relapsed high-grade serous ovarian cancer. We aimed to confirm these findings in patients with a BRCA1 or BRCA2 (BRCA1/2) mutation using a tablet formulation of olaparib.MethodsThis international, multicentre, double-blind, randomised, placebo-controlled, phase 3 trial evaluated olaparib tablet maintenance treatment in platinum-sensitive, relapsed ovarian cancer patients with a BRCA1/2 mutation who had received at least two lines of previous chemotherapy. Eligible patients were aged 18 years or older with an Eastern Cooperative Oncology Group performance status at baseline of 0–1 and histologically confirmed, relapsed, high-grade serous ovarian cancer or high-grade endometrioid cancer, including …

Objective: Recombinant adeno-associated virus (rAAV) type 2 is a common vector used in gene therapy. However, the presence of anti-AAV2 neutralizing antibodies or other neutralizing factors can significantly limit effective transduction. Intraperitoneal gene therapy could enable local delivery of the target gene directly to ovarian cancer cells. Until now, there have been no reports on the presence of anti-AAV antibodies in ascitic fluid, which might limit the effectiveness of rAAV as a candidate vector for intraperitoneal gene therapy. Thus, the characterization of the preexisting neutralization antibodies in ascitic fluid will provide insight into successful intraperitoneal gene therapy.Methods: The study was conducted on 23 ascitic fluid samples obtained from women with stage 3 and 4 ovarian cancer. The samples were collected to determine the presence of anti-AAV antibodies with ELISA test and the presence of neutralizing antibodies with neutralizing assay.Results: Our results indicate that anti-rAAV antibodies are present in 70%, whereas neutralizing factors/antibodies are present in 78% of analyzed ascitic fluid samples. This correlation provides evidence for the presence of additional, different from antibodies, currently unknown factors in ascites, which are able to inhibit AAV2 infection in the absence of anti-AAV antibodies.Conclusion: The presence of neutralizing antibodies against rAAV or other neutralizing factors in ascitic fluid should be taken into account during intraperitoneal gene therapy, because they might limit effective intraperitoneal gene therapy with rAAV as a vector.