Clinical BRCA1/2 Reversion Analysis Identifies Hotspot Mutations and Predicted Neoantigens Associated with Therapy Resistance.

Reversion mutations in BRCA1 or BRCA2 are associated with resistance to PARP inhibitors and platinum. To better understand the nature of these mutations, we collated, codified, and analyzed more than 300 reversions. This identified reversion "hotspots" and "deserts" in regions encoding the N and C terminus, respectively, of BRCA2, suggesting that pathogenic mutations in these regions may be at higher or lower risk of reversion. Missense and splice-site pathogenic mutations in BRCA1/2 also appeared less likely to revert than truncating mutations. Most reversions were <100 bp deletions. Although many deletions exhibited microhomology, this was not universal, suggesting that multiple DNA-repair processes cause reversion. Finally, we found that many reversions were predicted to encode immunogenic neopeptides, suggesting a route to the treatment of reverted disease. As well as providing a freely available database for the collation of future reversion cases, these observations have implications for how drug resistance might be managed in BRCA-mutant cancers. SIGNIFICANCE: Reversion mutations in BRCA genes are a major cause of clinical platinum and PARP inhibitor resistance. This analysis of all reported clinical reversions suggests that the position of BRCA2 mutations affects the risk of reversion. Many reversions are also predicted to encode tumor neoantigens, providing a potential route to targeting resistance.This article is highlighted in the In This Issue feature, p. 1426.

DNA repair deficiency sensitizes lung cancer cells to NAD+ biosynthesis blockade.

Synthetic lethality is an efficient mechanism-based approach to selectively target DNA repair defects. Excision repair cross-complementation group 1 (ERCC1) deficiency is frequently found in non-small-cell lung cancer (NSCLC), making this DNA repair protein an attractive target for exploiting synthetic lethal approaches in the disease. Using unbiased proteomic and metabolic high-throughput profiling on a unique in-house-generated isogenic model of ERCC1 deficiency, we found marked metabolic rewiring of ERCC1-deficient populations, including decreased levels of the metabolite NAD+ and reduced expression of the rate-limiting NAD+ biosynthetic enzyme nicotinamide phosphoribosyltransferase (NAMPT). We also found reduced NAMPT expression in NSCLC samples with low levels of ERCC1. These metabolic alterations were a primary effect of ERCC1 deficiency, and caused selective exquisite sensitivity to small-molecule NAMPT inhibitors, both in vitro - ERCC1-deficient cells being approximately 1,000 times more sensitive than ERCC1-WT cells - and in vivo. Using transmission electronic microscopy and functional metabolic studies, we found that ERCC1-deficient cells harbor mitochondrial defects. We propose a model where NAD+ acts as a regulator of ERCC1-deficient NSCLC cell fitness. These findings open therapeutic opportunities that exploit a yet-undescribed nuclear-mitochondrial synthetic lethal relationship in NSCLC models, and highlight the potential for targeting DNA repair/metabolic crosstalks for cancer therapy.

Genome-wide profiling of genetic synthetic lethality identifies CDK12 as a novel determinant of PARP1/2 inhibitor sensitivity.

Small-molecule inhibitors of PARP1/2, such as olaparib, have been proposed to serve as a synthetic lethal therapy for cancers that harbor BRCA1 or BRCA2 mutations. Indeed, in clinical trials, PARP1/2 inhibitors elicit sustained antitumor responses in patients with germline BRCA gene mutations. In hypothesizing that additional genetic determinants might direct use of these drugs, we conducted a genome-wide synthetic lethal screen for candidate olaparib sensitivity genes. In support of this hypothesis, the set of identified genes included known determinants of olaparib sensitivity, such as BRCA1, RAD51, and Fanconi's anemia susceptibility genes. In addition, the set included genes implicated in established networks of DNA repair, DNA cohesion, and chromatin remodeling, none of which were known previously to confer sensitivity to PARP1/2 inhibition. Notably, integration of the list of candidate sensitivity genes with data from tumor DNA sequencing studies identified CDK12 deficiency as a clinically relevant biomarker of PARP1/2 inhibitor sensitivity. In models of high-grade serous ovarian cancer (HGS-OVCa), CDK12 attenuation was sufficient to confer sensitivity to PARP1/2 inhibition, suppression of DNA repair via homologous recombination, and reduced expression of BRCA1. As one of only nine genes known to be significantly mutated in HGS-OVCa, CDK12 has properties that should confirm interest in its use as a biomarker, particularly in ongoing clinical trials of PARP1/2 inhibitors and other agents that trigger replication fork arrest.

Cross-platform pathway-based analysis identifies markers of response to the PARP inhibitor olaparib.

Poly(ADP-ribose) polymerase (PARP) is an enzyme involved in DNA repair. PARP inhibitors can act as chemosensitizers, or operate on the principle of synthetic lethality when used as single agent. Clinical trials have shown drugs in this class to be promising for BRCA mutation carriers. We postulated that inability to demonstrate response in non-BRCA carriers in which BRCA is inactivated by other mechanisms or with deficiency in homologous recombination for DNA repair is due to lack of molecular markers that define a responding subpopulation. We identified candidate markers for this purpose for olaparib (AstraZeneca) by measuring inhibitory effects of nine concentrations of olaparib in 22 breast cancer cell lines and identifying features in transcriptional and genome copy number profiles that were significantly correlated with response. We emphasized in this discovery process genes involved in DNA repair. We found that the cell lines that were sensitive to olaparib had a significant lower copy number of BRCA1 compared to the resistant cell lines (p value 0.012). In addition, we discovered seven genes from DNA repair pathways whose transcriptional levels were associated with response. These included five genes (BRCA1, MRE11A, NBS1, TDG, and XPA) whose transcript levels were associated with resistance and two genes (CHEK2 and MK2) whose transcript levels were associated with sensitivity. We developed an algorithm to predict response using the seven-gene transcription levels and applied it to 1,846 invasive breast cancer samples from 8 U133A/plus 2 (Affymetrix) data sets and found that 8-21 % of patients would be predicted to be responsive to olaparib. A similar response frequency was predicted in 536 samples analyzed on an Agilent platform. Importantly, tumors predicted to respond were enriched in basal subtype tumors. Our studies support clinical evaluation of the utility of our seven-gene signature as a predictor of response to olaparib.

Functional viability profiles of breast cancer.

UNLABELLED: The design of targeted therapeutic strategies for cancer has largely been driven by the identification of tumor-specific genetic changes. However, the large number of genetic alterations present in tumor cells means that it is difficult to discriminate between genes that are critical for maintaining the disease state and those that are merely coincidental. Even when critical genes can be identified, directly targeting these is often challenging, meaning that alternative strategies such as exploiting synthetic lethality may be beneficial. To address these issues, we have carried out a functional genetic screen in >30 commonly used models of breast cancer to identify genes critical to the growth of specific breast cancer subtypes. In particular, we describe potential new therapeutic targets for PTEN-mutated cancers and for estrogen receptor-positive breast cancers. We also show that large-scale functional profiling allows the classification of breast cancers into subgroups distinct from established subtypes. SIGNIFICANCE: Despite the wealth of molecular profiling data that describe breast tumors and breast tumor cell models, our understanding of the fundamental genetic dependencies in this disease is relatively poor. Using high-throughput RNA interference screening of a series of pharmacologically tractable genes, we have generated comprehensive functional viability profiles for a wide panel of commonly used breast tumor cell models. Analysis of these profiles identifies a series of novel genetic dependencies, including that of PTEN-null breast tumor cells upon mitotic checkpoint kinases, and provides a framework upon which additional dependencies and candidate therapeutic targets may be identified.

Germline mutations in RAD51D confer susceptibility to ovarian cancer.

Recently, RAD51C mutations were identified in families with breast and ovarian cancer. This observation prompted us to investigate the role of RAD51D in cancer susceptibility. We identified eight inactivating RAD51D mutations in unrelated individuals from 911 breast-ovarian cancer families compared with one inactivating mutation identified in 1,060 controls (P = 0.01). The association found here was principally with ovarian cancer, with three mutations identified in the 59 pedigrees with three or more individuals with ovarian cancer (P = 0.0005). The relative risk of ovarian cancer for RAD51D mutation carriers was estimated to be 6.30 (95% CI 2.86-13.85, P = 4.8 × 10(-6)). By contrast, we estimated the relative risk of breast cancer to be 1.32 (95% CI 0.59-2.96, P = 0.50). These data indicate that RAD51D mutation testing may have clinical utility in individuals with ovarian cancer and their families. Moreover, we show that cells deficient in RAD51D are sensitive to treatment with a PARP inhibitor, suggesting a possible therapeutic approach for cancers arising in RAD51D mutation carriers.

Searching for synthetic lethality in cancer.

The incentive to develop personalised therapy for cancer treatment is driven by the premise that it will increase therapeutic efficacy and reduce toxicity. Understanding the underlying cellular and molecular basis of the disease has been extremely important in the design of these novel therapies; however, identifying new drug targets for personalised therapies remains problematic. This review describes how the biological concept of synthetic lethality has been successfully implemented to identify new therapeutic approaches and targets in models from yeast through to human cells. We also discuss how recent technical advances combined with an increased understanding of the complexity of cellular networks may facilitate therapeutic advances in the future.