Hrd in ovarian cancer: Defined today, evolving for the future.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e18052-e18052
Author(s):  
Markus Eckstein ◽  
Kenneth Joel Bloom ◽  
Peter Riccelli ◽  
Frank Policht ◽  
Derry Mae Keeling ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Homologous Recombination ◽  
Genomic Instability ◽  
Large Scale ◽  
Gene Mutations ◽  
Therapy Response ◽  
State Transitions ◽  
Data Set ◽  
Gene Target ◽  
Increased Risk

e18052 Background: Homologous Recombination Repair (HRR) gene mutations result in Homologous Recombination Deficiency (HRD) associated with increased risk of high grade serous ovarian (HGOC) cancer and subsequent response to PARP inhibitors (PARPi). Traditionally, HRD has been determined by testing for germline and/or somatic BRCA1/2 mutations. Today, a growing number of HRR gene mutations are known to result in HRD and genomic instability, thus being a suitable target for PARPi. Therapy response to PARPi is highest in BRCA-mutant followed by HRD+/non-BRCA-mutant HGOC. Today, no standard HRD testing methods exist, causing confusion for physicians, and leading to poor outcomes for missed PARPi eligible patients. Thus, there is need to understand HRD testing utilization and methods in HGOC to inform best practices and optimize HRD testing in the clinic. Methods: We assessed the testing landscape for determining HRD status in ovarian cancer using a data set of 8,400 newly diagnosed and metastatic ovarian cancer patients in the US from Q3-2018 through Q2-2019 identified from Diaceutics’ proprietary Global Diagnostic Index (GDI). Analysis of real-world BRCA1/2 and NGS associated testing data and laboratory profile mapping exercise of 82 US labs was carried out using Diaceutics proprietary methods and data sources to evaluate BRCA1/2 and/or HRD germline/somatic testing rates, test availability, and test panel HRR gene composition. Results: Overall, germline mutation testing rates were 3x greater than somatic testing rates. Excluding BRCA1/2, 67 labs offered comprehensive solid tumor NGS panels capable of measuring HRD with varied HRR gene target composition. Across 34 labs, 5 HRR genes were commonly found on panels: PALB2, ATM, BARD1, BRIP1 and CHEK2. 3 labs currently offering panels explicitly intended for HRD determination only include BRCA1/2 and at least one genomic instability marker (loss of heterozygosity, large-scale state transitions or telomeric allelic imbalance). Conclusions: Lack of standardized HRD panels and low testing rate identifying patients with somatic mutations in BRCA1/2 and other HRR genes is leading to poorer outcomes for missed patients eligible for PARPi’s. As clinical evidence linking HRD status with PARPi efficacy grows in ovarian as well as prostate and pancreatic cancer, Diaceutics recommends organizations such as ASCO, CAP or AMP establish defined universal HRD testing panels including relevant somatic/germline HRR genes and BRCA1/2 as well as genomic instability markers and educate stake holders aiding harmonization and ultimately, better treatment outcomes.

Genomic profiling of biliary tract cancers to reveal clinically actionable genes and therapeutic biomarkers.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16187-e16187
Author(s):  
Yang Shao ◽  
Qiuxiang Ou ◽  
Zhenhao Fang ◽  
Rui Liu ◽  
Hua Bao ◽  
...  
Keyword(s):  
Dna Damage ◽  
Homologous Recombination ◽  
Genomic Instability ◽  
Biliary Tract ◽  
Large Scale ◽  
Excision Repair ◽  
State Transitions ◽  
Pathway Enrichment Analysis ◽  
Distal Cholangiocarcinoma ◽  
Tract Cancer

e16187 Background: Bile tract cancers are genetically and clinically heterogenous with a poor prognosis. Identifying novel biomarkers for targeted therapy is required to improve the clinical outcome of bile tract cancer patients. Methods: Tumor tissue samples of 482 Chinese biliary tract cancer (BTC) patients were genetically profiled using targeted next generation sequencing. Tumor mutation burden (TMB) was calculated by counting all nonsynonymous mutations per megabase of coding sequences. The R package ReactomePA was used in pathway enrichment analysis. Genomic instability was characterized by an in-house developed NGS-based Homologous Recombination Deficiency (HRD) panel and a HRD score was an unweighted sum of loss of heterozygosity (LOH), telomeric allelic imbalance (TAI), and large-scale state transitions (LST) scores. Results: The BTC cohort consisted of 135 gallbladder cancer (GBC), 73 intrahepatic cholangiocarcinoma (iCCA), 18 distal cholangiocarcinoma (dCCA), 14 perihilar cholangiocarcinoma (pCCA), while the remaining 242 BTC patients of no specific subtype information. Most frequently mutated genes included TP53 (56%), KRAS (25%), ARID1A (17%), SMAD4 (11%), and CDKN2A (10%) . A preliminary pathway analysis revealed that mutations of DNA damage repair (DDR) pathway genes were enriched in the cohort ( p< 1e-10), accounting for over 70% of the patients, particularly in homologous recombination repair (HRR), Fanconi anemia (FA), mismatch repair (MMR), and base excision repair (BER) genes. More specifically, approximately 50% of the cohort carried at least one mutation of the HRR genes (43%) or MMR genes (14%). Patients with impaired MMR had increased microsatellite instability status (MSI) comparing to those with wildtype MMR (33% vs. 3.1%, p< 0.0001), and patients harboring HRR mutations demonstrated elevated genomic instability than those without such mutations (median HRD: 18 vs.14, p < 0.05), indicative of potential response to poly (ADP-ribose) polymerase (PARP) inhibitors and other DNA-damage agents. Furthermore, high TMB was found to be highly correlated with DDR gene alterations ( p =0.004). In addition, we observed higher mutation frequencies of BRCA1/2 genes (including somatic and germline) in GBCs in contrast to other BTC subtypes. Conclusions: We herein reported the genomic features of 482 Chinese BTC samples and highlighted the role of DDR pathways including HRR and MMR. These findings could be useful to establish treatment and diagnostic strategies for BTC patients based on genetic information.

Evaluation of BRCA1/2 and homologous recombination defects in ovarian cancer and impact on clinical outcomes.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 5511-5511 ◽  
Author(s):  
Melinda S. Yates ◽  
Kirsten Timms ◽  
Molly S Daniels ◽  
Holly D. Oakley ◽  
Mark F. Munsell ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Homologous Recombination ◽  
Cancer Patients ◽  
Clinical Outcomes ◽  
Germline Mutation ◽  
Large Scale ◽  
Recurrent Ovarian Cancer ◽  
State Transitions ◽  
Cancer Genes ◽  
The Impact

5511 Background: Recent studies show that germline or somatic BRCA1/2 mutations and homologous recombination (HR) defects can be used to predict response to PARP inhibitors in recurrent ovarian cancer. However, the impact of defects in BRCA1/2 and HR genes on overall clinical outcomes are not yet defined for patients undergoing neoadjuvant chemotherapy (NACT) versus upfront surgical debulking (USD). Methods: Previously untreated ovarian cancer patients were prospectively enrolled under approved IRB protocol. Germline and tumor BRCA1/2 mutation testing and methylation were analyzed when sufficient tumor and blood was available. Mutation in 21 additional hereditary cancer genes (including HR genes) was also evaluated. Tumor HR defects were scored on LOH, telomeric allelic imbalance, and large-scale state transitions (as previously described). Presence of germline or somatic BRCA1/2 mutations, BRCA1 methylation, HR score ≥42, or germline mutation in other HR genes were defined together as HRD positive. Results: Of 299 enrolled patients, 129 (43%) received USD and 170 (57%) received NACT. Patients receiving USD had better outcomes compared to NACT, including overall survival (OS, 65.8 vs 45.2 months, p = 0.0003) and event free survival (EFS, 24.8 vs 15.6 months, p < 0.0001). In the overall cohort, EFS was significantly longer for HRD positive patients vs HRD negative (20.5 vs 16.3 months, p = 0.0268). Patients with somatic and germline BRCA1/2 mutations had longer OS vs BRCA1/2 negative (65.3 vs 46.1 months, p = 0.0403). Overall outcomes were worse in NACT compared to USD, but impact of BRCA1/2 mutations and HR defects was stronger in this group. NACT patients with any HR defect had longer EFS (19.7 vs 14.5 months, p = 0.0247). NACT patients with BRCA1/2 germline mutations had longer OS (65.3 vs 38.3 months, p = 0.0230). NACT patients with BRCA1/2 germline mutation had longer EFS (22.6 vs 14.6 months, p = 0.0047). OS and EFS in USD patients were significantly changed based on only debulking status; mutation or HR status did not have a statistically significant effect. Conclusions: While HR defects and BRCA1/2 mutations influence overall outcomes for ovarian cancer patients, the impact is stronger in NACT compared to USD.

scholarly journals The association between XRCC3 rs1799794 polymorphism and cancer risk: a meta-analysis of 34 case–control studies

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Weiqing Liu ◽  
Shumin Ma ◽  
Lei Liang ◽  
Zhiyong Kou ◽  
Hongbin Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Thyroid Cancer ◽  
Cancer Risk ◽  
Large Scale ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Cancer Type ◽  
Increased Risk ◽  
Risk Of Cancer

Abstract Background Studies on the XRCC3 rs1799794 polymorphism show that this polymorphism is involved in a variety of cancers, but its specific relationships or effects are not consistent. The purpose of this meta-analysis was to investigate the association between rs1799794 polymorphism and susceptibility to cancer. Methods PubMed, Embase, the Cochrane Library, Web of Science, and Scopus were searched for eligible studies through June 11, 2019. All analyses were performed with Stata 14.0. Subgroup analyses were performed by cancer type, ethnicity, source of control, and detection method. A total of 37 studies with 23,537 cases and 30,649 controls were included in this meta-analysis. Results XRCC3 rs1799794 increased cancer risk in the dominant model and heterozygous model (GG + AG vs. AA: odds ratio [OR] = 1.04, 95% confidence interval [CI] = 1.00–1.08, P = 0.051; AG vs. AA: OR = 1.05, 95% CI = 1.00–1.01, P = 0.015). The existence of rs1799794 increased the risk of breast cancer and thyroid cancer, but reduced the risk of ovarian cancer. In addition, rs1799794 increased the risk of cancer in the Caucasian population. Conclusion This meta-analysis confirms that XRCC3 rs1799794 is related to cancer risk, especially increased risk for breast cancer and thyroid cancer and reduced risk for ovarian cancer. However, well-designed large-scale studies are required to further evaluate the results.

Frequency of homologous recombination associated gene mutations in Japanese patients with ovarian cancer

2021 ◽  
Vol 162 ◽  
pp. S163-S164
Author(s):  
Kosuke Yoshihara ◽  
Tsukasa Baba ◽  
Mueaki Shimada ◽  
Hiroshi Yoshida ◽  
Aikou Okamoto ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Homologous Recombination ◽  
Gene Mutations ◽  
Japanese Patients

scholarly journals Germline and somatic mutations of homologous recombination-associated genes in Japanese ovarian cancer patients

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kentaro Sugino ◽  
Ryo Tamura ◽  
Hirofumi Nakaoka ◽  
Nozomi Yachida ◽  
Manako Yamaguchi ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Homologous Recombination ◽  
Cancer Patients ◽  
Somatic Mutations ◽  
Clear Cell ◽  
Gene Mutations ◽  
Parp Inhibitors ◽  
Low Grade ◽  
Mmr Genes ◽  
Selection Of

AbstractWe explored the frequency of germline and somatic mutations in homologous recombination (HR)-associated genes in major histological types of ovarian cancer. We performed targeted sequencing to assess germline and somatic mutations of 16 HR-associated genes and 4 mismatch repair (MMR) genes among 207 ovarian cancer patients (50 high-grade serous carcinomas (HGSC), 99 clear cell carcinomas (CCC), 39 endometrioid carcinomas (EC), 13 mucinous carcinomas (MC), and 6 low-grade serous carcinomas (LGSC)). Germline or somatic mutations of HR-associated genes were detected in 44% of HGSC, 28% of CCC, 23% of EC, 16% of MC, and 17% of LGSC patients. The profile of HR-associated gene mutations was remarkably different among each histological type. Germline BRCA1/2 mutations were frequently detected in HGSC and were rarely observed in CCC, EC, and MC patients. ATM somatic mutation was more frequently detected in CCC (9%) and EC patients (18%) than in HGSC patients (4%). There was a positive correlation between MMR gene mutations and HR-associated gene mutations (p = 0.0072). Our findings might be useful in selection of ovarian cancer patients that should be treated with PARP inhibitors.

scholarly journals ERpred: a web server for the prediction of subtype-specific estrogen receptor antagonists

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11716
Author(s):  
Nalini Schaduangrat ◽  
Aijaz Ahmad Malik ◽  
Chanin Nantasenamat
Keyword(s):  
Large Scale ◽  
Cancer Metastasis ◽  
Model Building ◽  
Hormone Replacement ◽  
Web Server ◽  
Breast Cancer Metastasis ◽  
Data Set ◽  
Therapy Targets ◽  
Subtype Specificity ◽  
Increased Risk

Estrogen receptors alpha and beta (ERα and ERβ) are responsible for breast cancer metastasis through their involvement of clinical outcomes. Estradiol and hormone replacement therapy targets both ERs, but this often leads to an increased risk of breast and endometrial cancers as well as thromboembolism. A major challenge is posed for the development of compounds possessing ER subtype specificity. Herein, we present a large-scale classification structure-activity relationship (CSAR) study of inhibitors from the ChEMBL database which consisted of an initial set of 11,618 compounds for ERα and 7,810 compounds for ERβ. The IC50 was selected as the bioactivity unit for further investigation and after the data curation process, this led to a final data set of 1,593 and 1,281 compounds for ERα and ERβ, respectively. We employed the random forest (RF) algorithm for model building and of the 12 fingerprint types, models built using the PubChem fingerprint was the most robust (Ac of 94.65% and 92.25% and Matthews correlation coefficient (MCC) of 89% and 76% for ERα and ERβ, respectively) and therefore selected for feature interpretation. Results indicated the importance of features pertaining to aromatic rings, nitrogen-containing functional groups and aliphatic hydrocarbons. Finally, the model was deployed as the publicly available web server called ERpred at http://codes.bio/erpred where users can submit SMILES notation as the input query for prediction of the bioactivity against ERα and ERβ.

scholarly journals Ovarian Cancer Prediction Using PCA, K-PCA, ICA and Random Forest

2021 ◽  
pp. 103-108
Author(s):  
Asiye Sahin ◽  
Nermin Ozcan ◽  
Gokhan Nur
Keyword(s):  
Ovarian Cancer ◽  
Dimension Reduction ◽  
Large Scale ◽  
Time Saving ◽  
Data Set ◽  
Cancer Prediction ◽  
Reduction Methods ◽  
Advanced Stages ◽  
Model Training ◽  
Post Menopausal

Ovarian cancer, which is the most common in women and occurs mostly in the post-menopausal period, develops with the uncontrolled proliferation of the cells in the ovaries and the formation of tumors. Early diagnosis is very difficult and in most cases, it is a type of cancer that is in advanced stages when first diagnosed. While it tends to be treated successfully in the early stages where it is confined to the ovary, it is more difficult to treat in the advanced stages and is often fatal. For this reason, it has been focused on studies that predict whether people have ovarian cancer. In our study, we designed a RF-based ovarian cancer prediction model using a data set consisting of 49 features including blood routine tests, general chemistry tests and tumor marker data of 349 real patients. Since the data set containing too many dimensions will increase the time and resources that need to be spent, we reduced the dimension of the data with PCA, K-PCA and ICA methods and examined its effect on the result and time saving. The best result was obtained with a score of 0.895 F1 by using the new smaller-sized data obtained by the PCA method, in which the dimension was reduced from 49 to 6, in the RF method, and the training of the model took 18.191 seconds. This result was both better as a success and more economical in terms of time spent during model training compared to the prediction made over larger data with 49 features, where no dimension reduction method was used. The study has shown that in predictions made with machine learning models over large-scale medical data, dimension reduction methods will provide advantages in terms of time and resources by improving the prediction results.

scholarly journals The association between XRCC3 rs1799794 polymorphism and cancer risk: a meta-analysis of 34 case-control studies

2021 ◽  
Author(s):  
Weiqing Liu ◽  
Shumin Ma ◽  
Lei Liang ◽  
Zhiyong Kou ◽  
Hongbin Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Thyroid Cancer ◽  
Cancer Risk ◽  
Large Scale ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Cancer Type ◽  
Increased Risk ◽  
Risk Of Cancer

Abstract Background: Studies on the XRCC3 rs1799794 polymorphism show that this polymorphism is involved in a variety of cancers, but its specific relationships or effects are not consistent. The purpose of this meta-analysis was to investigate the association between rs1799794 polymorphism and susceptibility to cancer. Methods: PubMed, Embase, the Cochrane Library, Web of Science, and Scopus were searched for eligible studies through June 11, 2019. All analyses were performed with Stata 14.0. Subgroup analyses were performed by cancer type, ethnicity, source of control, and detection method. A total of 37 studies with 23,537 cases and 30,649 controls were included in this meta-analysis. Results: XRCC3 rs1799794 increased cancer risk in the dominant model and heterozygous model (GG+AG vs. AA: odds ratio [OR] = 1.04, 95% confidence interval [CI] = 1.00–1.08, P = 0.051; AG vs. AA: OR = 1.05, 95% CI = 1.00–1.01, P = 0.015). The existence of rs1799794 increased the risk of breast cancer and thyroid cancer, but reduced the risk of ovarian cancer. In addition, rs1799794 increased the risk of cancer in the Caucasian population. Conclusion: This meta-analysis confirms that XRCC3 rs1799794 is related to cancer risk, especially increased risk for breast cancer and thyroid cancer and reduced risk for ovarian cancer. However, well-designed large-scale studies are required to further evaluate the results.

scholarly journals Integrated Genomics and Functional Validation Identifies a Global Kinase Gene Signature Impacting Genome Stability in Myeloma

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 363-363
Author(s):  
Subodh Kumar ◽  
Leutz Buon ◽  
Srikanth Talluri ◽  
Chengcheng Liao ◽  
Jialan Shi ◽  
...  
Keyword(s):  
Dna Repair ◽  
Homologous Recombination ◽  
Genomic Instability ◽  
Small Molecule ◽  
Copy Number ◽  
Genome Stability ◽  
Dna Breaks ◽  
Genomic Amplification ◽  
Data Set ◽  
The Impact

Identification of mechanisms underlying genomic instability is necessary to understand disease progression, including development of drug resistance. Our previous data demonstrates that dysregulation of DNA repair and maintenance/modification activities (including homologous recombination (HR), apurinic/apyrimidinic nuclease and APOBEC) significantly contribute to genomic instability in multiple myeloma (MM). However, how these and other pathways involved in genomic instability are dysregulated, remains to be explored. Since kinases play a critical role in the regulation of the maintenance of genomic integrity, we have performed a genome-wide kinome profiling to identify those involved in genomic instability in cancer. First, we analyzed genomic database for ten human cancers (including MM) from TCGA with both tumor cell gene expression and SNP/CGH array-based copy number information for each patient.We assessed genomic instability in each patient based on the total number of amplification and deletion events. We next interrogated all 550 kinases expressed in humans and identified those whose expression correlated with copy number alteration (based on FDR ≤ 0.05) in all tumor types. We identified six kinases whose elevated expression correlated with increased genomic instability defined by genomic amplification/deletion events in all ten cancers, including MM. To demonstrate functional relevance of these kinases, we conducted a CRISPR-based loss of function screen (using 3 guides per gene) in MM cells and evaluated the impact of each gene-knockout on micronuclei, a marker of ongoing genomic rearrangements and instability. For all six kinases, at least one guide resulted in ≥ 65% inhibition of micronuclei formation. Moreover, for five out of the six kinases, at least two guides showed ≥ 60% inhibition of micronuclei. All together, these data establishes a strong relevance of these kinases with genomic instability in MM. PDZ Binding Kinase (PBK) was among top kinases impacting genome stability in this data set with 2 out of 3 guides causing &gt; 88% and 3rdguide causing 35% inhibition of micronuclei formation. We further report that inhibition of PBK, by knockdown or small molecule, inhibits DNA breaks, RAD51 recombinase expression and homologous recombination in MM cells. We further investigated molecular mechanisms involved in PBK-mediated genomic instability in MM. Expression profiling using RNA sequencing of MM cells treated with a specific PBK inhibitor showed that top ten pathways downregulated by treatment were mostly DNA repair/recombination followed by replication and G2/M checkpoint. Interestingly, we identified a notable overlap between PBK-regulated genes with FOXM1 target genes. FOXM1 is a major transcriptional regulator of genes involved in DNA repair, G2/M regulation and chromosomal stability. We, therefore, investigated PBK/FOXM1 interaction and show that PBK interacts with FOXM1 in MM cells. Moreover, the inhibition of PBK, by knockdown or small molecule, inhibits phosphorylation of FOXM1 as well as downregulates FOXM1-regulated HR and cell cycle genes RAD51, EXO1 and CDC25A. These results suggest that PBK-dependent phosphorylation of FOXM1 activity controls transcriptional networks involved in genomic instability in MM. Ongoing work is investigating role of PBK and other kinases in progression of MGUS/SMM to active MM and their impact on ongoing genomic changes with influence on multiple DNA repair pathways including HR. In conclusion, we describe a kinase panel that may have significant role in maintaining genome stability, and their perturbation may allow to improve genome stability in MM. Disclosures Munshi: Adaptive: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Abbvie: Consultancy; Oncopep: Consultancy; Takeda: Consultancy.

Elucidation of PARP inhibitor activity in BRCAwt recurrent ovarian cancer by hrr mutational gene profile analysis.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 5568-5568
Author(s):  
Mansoor Raza Mirza ◽  
Bin Feng ◽  
Ming Shan ◽  
Kaiming Sun ◽  
Ilkar Yalcin ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Homologous Recombination ◽  
Clinical Benefit ◽  
Brca Mutation ◽  
Parp Inhibitor ◽  
Gene Mutations ◽  
Recurrent Ovarian Cancer ◽  
Exploratory Analysis ◽  
Platinum Based Chemotherapy ◽  
Biomarker Analysis

5568 Background: Niraparib is an oral, selective poly(ADP-ribose) polymerase inhibitor (PARPi) approved for maintenance treatment of BRCA mutated ( BRCAmut) and BRCA wild-type ( BRCAwt) recurrent ovarian cancer patients (pts) who are in response to platinum-based chemotherapy. In the non-germline BRCA mutated (non-g BRCAmut) cohort of the ENGOT-OV16/NOVA trial, clinical benefit with niraparib vs placebo was seen in pts regardless of their Myriad myChoice HRD test status ( BRCAmut and homologous recombination deficiency [HRD] score), with a hazard ratio (HR) of 0.38 in HRD-positive (HRDpos) and 0.58 in HRD-negative (HRDneg) pts. To determine if treatment benefit in HRDneg pts may result from mutations in other homologous recombination repair ( HRR) genes, we examined the relationship between progression-free survival and other HRR gene mutations in the NOVA non-gBRCAmut cohort. Methods: A retrospective, exploratory biomarker analysis was conducted using all available tumor samples from 331 pts enrolled in the NOVA non-g BRCAmut cohort. Mutation status of HRR genes was evaluated using a 43-gene NGS assay (Myriad Genetics), including BRCA1/2 and 16 additional HRR genes. Results: In this exploratory analysis of the NOVA non-g BRCAmut cohort, niraparib demonstrated clinical benefit in pts with somatic BRCA mutation (HR, 0.27) and in BRCAwt pts (HR, 0.47). In addition, BRCAwt pts with other HRR gene mutations also derived benefit from niraparib (HR, 0.31), as did BRCAwt/ HRRwt pts (HR, 0.49). When BRCAwt/ HRRwt pts were categorized by HRD score, clinical benefit was also observed in both HRDpos and HRDneg pts, with HRs of 0.33 and 0.60, respectively. These results suggest that, although these biomarkers have good positive predictive value, they are not good negative predictors for niraparib benefit in this indication. Conclusions: This retrospective, exploratory analysis of the ENGOT-OV16/NOVA non-g BRCAmut cohort suggests that although pts with somatic BRCA mutation and other HRR mutations benefit from niraparib treatment, clinical benefit is also seen in HRDneg pts without HRR mutations, perhaps related to other genomic, epigenetic, or functional alterations within ovarian tumors yet to be defined.

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