Homologous Recombination Deficiency Associated With Response to Poly (ADP-Ribose) Polymerase Inhibitors in Ovarian Cancer Patients: The First Real-Word Evidence From China

Homologous recombination deficiency (HRD) is an approved predictive biomarker for Poly (ADP-ribose) polymerase inhibitors (PARPi) in ovarian cancer. However, the proportion of positive HRD in the real world and the relationship between HRD status and PARPi in Chinese ovarian cancer patients remain unknown. A total of 67 ovarian cancer patients who underwent PARPi, either olaparib or niraparib, were enrolled and passed inclusion criteria from August 2018 to January 2021 in the Affiliated Cancer Hospital of Nanjing Medical University. HRD status correlation with Progression-free survival (PFS) was analyzed and summarized with a log-rank test. Univariate and multiple cox-regression analyses were conducted to investigate all correlated clinical factors. Approximately 68.7% (46/67) patients were HRD positive and the rest 31.3% (21/67) were HRD negative. The PFS among HRD-positive patients was significantly longer than those HRD-negative patients (medium PFS 9.4 m vs 4.1 m, hazard ratio [HR]: 0.52, 95% CI: [0.38–0.71], p <0.001). Univariate cox-regression found that HRD status, Eastern Cooperative Oncology Group (ECOG) status, BRCA status, previous treatment lines, secondary cytoreductive surgery and R0 resection were significantly associated with PFS after PARPi treatment. After multiple regression correction, HRD status and ECOG were the independent factors to predict PFS (HR: 0.67, 95% CI: [0.49–0.92], p = 0.01; HR: 2.20, 95% CI: [1.14–4.23], p = 0.02, respectively). In platinum sensitivity evaluable subgroup (N = 49), HRD status and platinum sensitivity status remain significant to predict PFS after multiple regression correction (HR: 0.71, 95% CI: [0.51–0.98], p = 0.04; HR: 0.49, 95% CI: [0.24–1.0], p = 0.05, respectively). This is the first real-world study of HRD status in ovarian cancer patients in China, and we demonstrate that HRD is an independent predictive biomarker for PARP inhibitors treatment in Chinese ovarian cancer patients.

Validation of Genomic and Transcriptomic Models of Homologous Recombination Deficiency in a Real-World Pan-Cancer Cohort

Background: With the introduction of DNA-damaging therapies into standard of care cancer treatment, there is a growing need for predictive diagnostics assessing homologous recombination deficiency (HRD) status across tumor types. Following the strong clinical evidence for the utility of DNA-sequencing-based HRD testing in ovarian cancer, and growing evidence in breast cancer, we present analytical validation of the Tempus|HRD-DNA test. We further developed, validated, and explored the Tempus|HRD-RNA model, which uses gene expression data from 16,470 RNA-seq samples to predict HRD status from formalin-fixed paraffin-embedded (FFPE) tumor samples across numerous cancer types. Methods: Genomic and transcriptomic profiling was performed using next-generation sequencing from Tempus|xT, Tempus|xO, Tempus|xE, Tempus|RS, and Tempus|RS.v2 assays on 48,843 samples. Samples were labeled based on their BRCA1, BRCA2 and selected Homologous Recombination Repair (HRR) pathway gene (CDK12, PALB2, RAD51B, RAD51C, RAD51D) mutational status to train and validate HRD-DNA, a genome-wide loss-of-heterozygosity biomarker, and HRD-RNA, a logistic regression model trained on gene expression, using several performance metrics and statistical tests. Results: In a sample of 2,058 breast and 1,216 ovarian tumors, BRCA status was predicted by HRD-DNA with F1-scores of 0.98 and 0.96, respectively. Across an independent set of 1,363 samples across solid tumor types, the HRD-RNA model was predictive of BRCA status in prostate, pancreatic, and non-small cell lung cancer, with F1-scores of 0.88, 0.69, and 0.62, respectively. Conclusions: We predict HRD-positive patients across many cancer types and believe both HRD models may generalize to other mechanisms of HRD outside of BRCA loss. HRD-RNA complements DNA-based HRD detection methods, especially for indications with low prevalence of BRCA alterations.

Inferring Homologous Recombination Deficiency of Ovarian Cancer From the Landscape of Copy Number Variation at Subchromosomal and Genetic Resolutions

BackgroundHomologous recombination deficiency (HRD) is characterized by overall genomic instability and has emerged as an indispensable therapeutic target across various tumor types, particularly in ovarian cancer (OV). Unfortunately, current detection assays are far from perfect for identifying every HRD patient. The purpose of this study was to infer HRD from the landscape of copy number variation (CNV).MethodsGenome-wide CNV landscape was measured in OV patients from the Australian Ovarian Cancer Study (AOCS) clinical cohort and >10,000 patients across 33 tumor types from The Cancer Genome Atlas (TCGA). HRD-predictive CNVs at subchromosomal resolution were identified through exploratory analysis depicting the CNV landscape of HRD versus non-HRD OV patients and independently validated using TCGA and AOCS cohorts. Gene-level CNVs were further analyzed to explore their potential predictive significance for HRD across tumor types at genetic resolution.ResultsAt subchromosomal resolution, 8q24.2 amplification and 5q13.2 deletion were predominantly witnessed in HRD patients (both p < 0.0001), whereas 19q12 amplification occurred mainly in non-HRD patients (p < 0.0001), compared with their corresponding counterparts within TCGA-OV. The predictive significance of 8q24.2 amplification (p < 0.0001), 5q13.2 deletion (p = 0.0056), and 19q12 amplification (p = 0.0034) was externally validated within AOCS. Remarkably, pan-cancer analysis confirmed a cross-tumor predictive role of 8q24.2 amplification for HRD (p < 0.0001). Further analysis of CNV in 8q24.2 at genetic resolution revealed that amplifications of the oncogenes, MYC (p = 0.0001) and NDRG1 (p = 0.0004), located on this fragment were also associated with HRD in a pan-cancer manner.ConclusionsThe CNV landscape serves as a generalized predictor of HRD in cancer patients not limited to OV. The detection of CNV at subchromosomal or genetic resolution could aid in the personalized treatment of HRD patients.

Expanding the Use of PARP Inhibitors as Monotherapy and in Combination in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and is known to be associated with a poor prognosis and limited therapeutic options. Poly (ADP-ribose) polymerase inhibitors (PARPi) are targeted therapeutics that have demonstrated efficacy as monotherapy in metastatic BRCA-mutant (BRCAMUT) TNBC patients. Improved efficacy of PARPi has been demonstrated in BRCAMUT breast cancer patients who have either received fewer lines of chemotherapy or in chemotherapy-naïve patients in the metastatic, adjuvant, and neoadjuvant settings. Moreover, recent trials in smaller cohorts have identified anti-tumor activity of PARPi in TNBC patients, regardless of BRCA-mutation status. While there have been concerns regarding the efficacy and toxicity of the use of PARPi in combination with chemotherapy, these challenges can be mitigated with careful attention to PARPi dosing strategies. To better identify a patient subpopulation that will best respond to PARPi, several genomic biomarkers of homologous recombination deficiency have been tested. However, gene expression signatures associated with PARPi response can integrate different pathways in addition to homologous recombination deficiency and can be implemented in the clinic more readily. Taken together, PARPi have great potential for use in TNBC patients beyond BRCAMUT status, both as a single-agent and in combination.

Race-Specific Genetic Profiles of Homologous Recombination Deficiency in Multiple Cancers

Homologous recombination deficiency (HRD) has been used to predict both cancer prognosis and the response to DNA-damaging therapies in many cancer types. HRD has diverse manifestations in different cancers and even in different populations. Many screening strategies have been designed for detecting the sensitivity of a patient’s HRD status to targeted therapies. However, these approaches suffer from low sensitivity, and are not specific to each cancer type and population group. Therefore, identifying race-specific and targetable HRD-related genes is of clinical importance. Here, we conducted analyses using genomic sequencing data that was generated by the Pan-Cancer Atlas. Collapsing non-synonymous variants with functional damage to HRD-related genes, we analyzed the association between these genes and race within cancer types using the optimal sequencing kernel association test (SKAT-O). We have identified race-specific mutational patterns of curated HRD-related genes across cancers. Overall, more significant mutation sites were found in ATM, BRCA2, POLE, and TOP2B in both the ‘White’ and ‘Asian’ populations, whereas PTEN, EGFG, and RIF1 mutations were observed in both the ‘White’ and ‘African American/Black’ populations. Furthermore, supported by pathogenic tendency databases and previous reports, in the ‘African American/Black’ population, several associations, including BLM with breast invasive carcinoma, ERCC5 with ovarian serous cystadenocarcinoma, as well as PTEN with stomach adenocarcinoma, were newly described here. Although several HRD-related genes are common across cancers, many of them were found to be specific to race. Further studies, using a larger cohort of diverse populations, are necessary to identify HRD-related genes that are specific to race, for guiding gene testing methods.

Identification of molecular subtypes and prognostic signature for hepatocellular carcinoma based on genes associated with homologous recombination deficiency

Hepatocellular carcinoma (HCC) is a rapidly developing digestive tract carcinoma. The prognosis of patients and side effects caused by clinical treatment should be better improved. Nonnegative matrix factorization (NMF) clustering was performed using 109 homologous recombination deficiency (HRD)-related of HCC genes from The Cancer Genome Atlas (TCGA) database. Limma was applied to analyze subtype differences. Immune scores and clinical characteristics of different subtypes were compared. An HRD signature were built with least absolute shrinkage operator (LASSO) and multivariate Cox analysis. Performance of the signature system was then assessed by Kaplan–Meier curves and receiver operating characteristic (ROC) curves. We identified two molecular subtypes (C1 and C2), with C2 showing a significantly better prognosis than C1. C1 contained 3623 differentially expressed genes. A 4-gene prognostic signature for HCC was established, and showed a high predicting accuracy in validation sets, entire TCGA data set, HCCDB18 and GSE14520 queues. Moreover, the risk score was validated as an independent prognostic marker for HCC. Our research identified two molecular subtypes of HCC, and proposed a novel scoring system for evaluating the prognosis of HCC in clinical practice.