Germline RAD51B variants confer susceptibility to breast and ovarian cancers deficient in homologous recombination

Pathogenic germline mutations in the RAD51 paralog genes RAD51C and RAD51D, are known to confer susceptibility to ovarian and triple-negative breast cancer. Here, we investigated whether germline loss-of-function variants affecting another RAD51 paralog gene, RAD51B, are also associated with breast and ovarian cancer. Among 3422 consecutively accrued breast and ovarian cancer patients consented to tumor/germline sequencing, the observed carrier frequency of loss-of-function germline RAD51B variants was significantly higher than control cases from the gnomAD population database (0.26% vs 0.09%), with an odds ratio of 2.69 (95% CI: 1.4–5.3). Furthermore, we demonstrate that tumors harboring biallelic RAD51B alteration are deficient in homologous recombination DNA repair deficiency (HRD), as evidenced by analysis of sequencing data and in vitro functional assays. Our findings suggest that RAD51B should be considered as an addition to clinical germline testing panels for breast and ovarian cancer susceptibility.

Immune checkpoint inhibitor sensitivity of DNA repair deficient tumors

Faithful DNA replication is necessary to maintain genome stability and implicates a complex network with several pathways depending on DNA damage type: homologous repair, nonhomologous end joining, base excision repair, nucleotide excision repair and mismatch repair. Alteration in components of DNA repair machinery led to DNA damage accumulation and potentially carcinogenesis. Preclinical data suggest sensitivity to immune checkpoint inhibitors in tumors with DNA repair deficiency. Here, we review clinical studies that explored the use of immune checkpoint inhibitor in patient harboring tumor with DNA repair deficiency.

Deep Learning identifies new morphological patterns of Homologous Recombination Deficiency in luminal breast cancers from whole slide images

Homologous Recombination DNA-repair deficiency (HRD) is a well-recognized marker of platinum-salt and PARP inhibitor chemotherapies in ovarian and breast cancers (BC). Causing high genomic instability, HRD is currently determined by BRCA1/2 sequencing or by genomic signatures, but its morphological manifestation is not well understood. Deep Learning (DL) is a powerful machine learning technique that has been recently shown to be capable of predicting genomic signatures from stained tissue slides. However, DL is known to be sensitive to dataset biases and lacks interpretability. Here, we present and evaluate a strategy to control for biases in retrospective cohorts. We train a deep-learning model to predict the HRD in a controlled cohort with unprecedented accuracy (AUC: 0.86) and we develop a new visualization technique that allows for automatic extraction of new morphological features related to HRD. We analyze in detail the extracted morphological patterns that open new hypotheses on the phenotypic impact of HRD.

Optimized detection of somatic allelic imbalances specific for homologous recombination deficiency improves the prediction of clinical outcomes in ovarian cancer

Specific patterns of genomic allelic imbalances (AIs) have been associated with Homologous recombination DNA-repair deficiency (HRD). We performed a systematic pan-cancer characterization of AIs across tumor types, revealing unique patterns in ovarian cancer. Using machine learning on a multi-omics dataset, we generated an optimized algorithm to detect HRD in ovarian cancer (ovaHRDscar). ovaHRDscar improved the prediction of clinical outcomes in three independent validation cohorts (PCAWG, HERCULES, TERVA). Characterization of 98 spatiotemporally distinct tumor samples indicated ovary/adnex as the preferred site to assess HRD. In conclusion, ovaHRDscar improves the detection of HRD in ovarian cancer with the premise to improve patient selection for HR-targeted therapies.

Epigenetic regulation of innate immune memory in microglia

Microglia are the tissue-resident macrophages of the CNS. They originate in the yolk sac, colonize the CNS during embryonic development and form a self-sustaining population with limited turnover. A consequence of their relative slow turnover is that microglia can serve as a long-term memory for inflammatory or neurodegenerative events. We characterized the epigenomes and transcriptomes of microglia exposed to different stimuli; an endotoxin challenge (LPS) and genotoxic stress (DNA repair deficiency-induced accelerated aging). Whereas the enrichment of permissive epigenetic marks at enhancer regions explains training (hyperresponsiveness) of primed microglia to LPS challenge, the tolerized response of microglia seems to be regulated by loss of permissive epigenetic marks. Here, we identify that inflammatory stimuli and accelerated aging because of genotoxic stress activate distinct gene networks. These gene networks and associated biological processes are partially overlapping, which is likely driven by specific transcription factor networks, resulting in altered epigenetic signatures and distinct functional (desensitized vs. primed) microglia phenotypes.

Integrated mutational landscape analysis of uterine leiomyosarcomas

Uterine leiomyosarcomas (uLMS) are aggressive tumors arising from the smooth muscle layer of the uterus. We analyzed 83 uLMS sample genetics, including 56 from Yale and 27 from The Cancer Genome Atlas (TCGA). Among them, a total of 55 Yale samples including two patient-derived xenografts (PDXs) and 27 TCGA samples have whole-exome sequencing (WES) data; 10 Yale and 27 TCGA samples have RNA-sequencing (RNA-Seq) data; and 11 Yale and 10 TCGA samples have whole-genome sequencing (WGS) data. We found recurrent somatic mutations in TP53, MED12, and PTEN genes. Top somatic mutated genes included TP53, ATRX, PTEN, and MEN1 genes. Somatic copy number variation (CNV) analysis identified 8 copy-number gains, including 5p15.33 (TERT), 8q24.21 (C-MYC), and 17p11.2 (MYOCD, MAP2K4) amplifications and 29 copy-number losses. Fusions involving tumor suppressors or oncogenes were deetected, with most fusions disrupting RB1, TP53, and ATRX/DAXX, and one fusion (ACTG2-ALK) being potentially targetable. WGS results demonstrated that 76% (16 of 21) of the samples harbored chromoplexy and/or chromothripsis. Clinically actionable mutational signatures of homologous-recombination DNA-repair deficiency (HRD) and microsatellite instability (MSI) were identified in 25% (12 of 48) and 2% (1 of 48) of fresh frozen uLMS, respectively. Finally, we found olaparib (PARPi; P = 0.002), GS-626510 (C-MYC/BETi; P < 0.000001 and P = 0.0005), and copanlisib (PIK3CAi; P = 0.0001) monotherapy to significantly inhibit uLMS-PDXs harboring derangements in C-MYC and PTEN/PIK3CA/AKT genes (LEY11) and/or HRD signatures (LEY16) compared to vehicle-treated mice. These findings define the genetic landscape of uLMS and suggest that a subset of uLMS may benefit from existing PARP-, PIK3CA-, and C-MYC/BET-targeted drugs.

The utility of homologous recombination deficiency biomarkers across cancer types

BackgroundGenomic alterations in BRCA1/2 and genomic scar signatures are associated with homologous recombination DNA repair deficiency (HRD) and serve as therapeutic biomarkers for platinum and PARP inhibitors in breast and ovarian cancers. However, the clinical significance of these biomarkers in other homologous recombination repair-related genes or other cancer types is not fully understood.ResultsWe analyzed the datasets of all solid cancers from The Cancer Genome Atlas and Cancer Cell Line Encyclopedia, and found that the association between biallelic alterations in the homologous recombination pathway genes and genomic scar signatures differed greatly depending on gender and the presence of somatic TP53 mutation. Additionally, HRD cases identified by a combination of these indicators showed higher sensitivity to DNA-damaging drugs than non-HRD cases both in clinical samples and cell lines.ConclusionOur work provides novel proof of the utility of HRD analysis for all cancer types and will improve the precision and efficacy of chemotherapy selection in clinical oncology.

Association of Germline BRCA Pathogenic Variants with Diminished Ovarian Reserve: A Meta-Analysis of Individual Patient-Level Data

PurposeTo determine whether germline BRCA pathogenic variants (gBRCA) are associated with decreased ovarian reserve.Materials and MethodsAn individual patient-data meta-analysis was performed using 5 datasets on 828 evaluable women who were tested for gBRCA. Of those, 250 carried gBRCA while 578 had tested negative and served as controls. Of the women with gBRCA, four centers studied those affected with breast cancer (n=161) and one studied unaffected individuals (n=89). The data were adjusted for the center, age, body mass index, smoking and oral contraceptive pill use before the final analysis. Anti-mullerian hormone (AMH) levels in affected women were drawn before pre-systemic therapy.ResultsMean ages of women with vs. without gBRCA1/2 (34.1± 4.9 vs. 34.3± 4.8 years; p=0.48), and with gBRCA1 vs gBRCA2 (33.7± 4.9 vs. 34.6± 4.8 years; p=0.16) were similar. After the adjustments, women with gBRCA1/2 had significantly lower AMH levels compared to controls (23% lower; 95% CI: 4-38%, p=0.02). When the adjusted analysis was limited to affected women (157 with gBRCA vs. 524 without, after exclusions), the difference persisted (25% lower; CI: 9-38%, p=0.003). The serum AMH levels were lower in women with gBRCA1 (33% lower; CI: 12-49%, p=0.004) but not gBRCA2 compared to controls (7% lower; CI: 31% lower to 26% higher, p=0.64).ConclusionsYoung women with gBRCA pathogenic variants, particularly of those affected and with gBRCA1, have lower serum AMH levels compared to controls. They may need to be preferentially counselled about the possibility of shortened reproductive lifespan due to diminished ovarian reserve.ContextKey objectiveDNA repair deficiency is emerging as a joint mechanism for breast cancer and reproductive aging. Recent studies showed that ovarian reserve maybe lower in women with BRCA pathogenic variants (gBRCA) due to DNA repair deficiency. However, clinical studies using the most sensitive serum ovarian reserve marker Anti-Mullerian-Hormone (AMH) provided mixed results. Given the heterogeneity of the data from clinical studies, we performed an individual patient data (IPD) meta-analysis to determine if gBRCA are associated with lower ovarian reserve.Knowledge generatedgBRCA are associated with diminished ovarian reserve, as determined by serum AMH and this association is restricted to gBRCA1. This finding is firmer for affected women as this IPD meta-analysis predominantly studied those with breast cancer.RelevanceWomen with gBRCA may have shortened reproductive life span due to diminished ovarian reserve and should be proactively counseled for fertility preservation especially if faced with chemotherapy or delaying childbearing.

Deep Learning Predicts Underlying Features on Pathology Images with Therapeutic Relevance for Breast and Gastric Cancer

DNA repair deficiency (DRD) is an important driver of carcinogenesis and an efficient target for anti-tumor therapies to improve patient survival. Thus, detection of DRD in tumors is paramount. Currently, determination of DRD in tumors is dependent on wet-lab assays. Here we describe an efficient machine learning algorithm which can predict DRD from histopathological images. The utility of this algorithm is demonstrated with data obtained from 1445 cancer patients. Our method performs rather well when trained on breast cancer specimens with homologous recombination deficiency (HRD), AUC (area under curve) = 0.80. Results for an independent breast cancer cohort achieved an AUC = 0.70. The utility of our method was further shown by considering the detection of mismatch repair deficiency (MMRD) in gastric cancer, yielding an AUC = 0.81. Our results demonstrate the capacity of our learning-base system as a low-cost tool for DRD detection.