PARP Inhibitors Display Differential Efficacy in Models of BRCA Mutant High-Grade Serous Ovarian Cancer

CRISPR single base-editing: in silico predictions to variant clonal cell lines

Engineering single base edits using CRISPR technology including specific deaminases and single-guide RNA (sgRNA) is a rapidly evolving field. Different types of base edits can be constructed, with cytidine base editors (CBEs) facilitating transition of C-to-T variants, adenine base editors (ABEs) enabling transition of A-to-G variants, C-to-G transversion base editors (CGBEs) and recently adenine transversion editors (AYBE) that create A-to-C and A-to-T variants. The base-editing machine learning algorithm BE-Hive predicts which sgRNA and base editor combinations have the strongest likelihood of achieving desired base edits. We have used BE-Hive and TP53 mutation data from The Cancer Genome Atlas (TCGA) ovarian cancer cohort to predict which mutations can be engineered, or reverted to wild-type (WT) sequence, using CBEs, ABEs or CGBEs. We have developed and automated a ranking system to assist in selecting optimally designed sgRNA that considers the presence of a suitable protospacer adjacent motif (PAM), the frequency of predicted bystander edits, editing efficiency and target base change. We have generated single constructs containing ABE or CBE editing machinery, an sgRNA cloning backbone and an enhanced green fluorescent protein tag (EGFP), removing the need for co-transfection of multiple plasmids. We have tested our ranking system and new plasmid constructs to engineer the p53 mutants Y220C, R282W and R248Q into WT p53 cells and shown that these mutants cannot activate four p53 target genes, mimicking the behaviour of endogenous p53 mutations. This field will continue to rapidly progress, requiring new strategies such as we propose to ensure desired base-editing outcomes.

Olaparib-Resistant BRCA2MUT Ovarian Cancer Cells with Restored BRCA2 Abrogate Olaparib-Induced DNA Damage and G2/M Arrest Controlled by the ATR/CHK1 Pathway for Survival

The PARP inhibitor (PARPi) olaparib is currently the drug of choice for serous ovarian cancer (OC), especially in patients with homologous recombination (HR) repair deficiency associated with deleterious BRCA1/2 mutations. Unfortunately, OC patients who fail to respond to PARPi or relapse after treatment have limited therapeutic options. To elucidate olaparib resistance and enhance the efficacy of olaparib, intracellular factors exploited by OC cells to achieve decreased sensitivity to PARPi were examined. An olaparib-resistant OC cell line, PEO1-OR, was established from BRCA2MUT PEO1 cells. The anticancer activity and action of olaparib combined with inhibitors of the ATR/CHK1 pathway (ceralasertib as ATRi, MK-8776 as CHK1i) in olaparib-sensitive and -resistant OC cell lines were evaluated. Whole-exome sequencing revealed that PEO1-OR cells acquire resistance through subclonal enrichment of BRCA2 secondary mutations that restore functional full-length protein. Moreover, PEO1-OR cells upregulate HR repair-promoting factors (BRCA1, BRCA2, RAD51) and PARP1. Olaparib-inducible activation of the ATR/CHK1 pathway and G2/M arrest is abrogated in olaparib-resistant cells. Drug sensitivity assays revealed that PEO1-OR cells are less sensitive to ATRi and CHK1i agents. Combined treatment is less effective in olaparib-resistant cells considering inhibition of metabolic activity, colony formation, survival, accumulation of DNA double-strand breaks, and chromosomal aberrations. However, synergistic antitumor activity between compounds is achievable in PEO1-OR cells. Collectively, olaparib-resistant cells display co-existing HR repair-related mechanisms that confer resistance to olaparib, which may be effectively utilized to resensitize them to PARPi via combination therapy. Importantly, the addition of ATR/CHK1 pathway inhibitors to olaparib has the potential to overcome acquired resistance to PARPi.

Differences in Durability of PARP Inhibition by Clinically Approved PARP Inhibitors: Implications for Combinations and Scheduling

Six PARP inhibitors (PARPi) are approved for cancer therapy as monotherapy agents in daily or twice-daily continuous dosing schedules to maintain the necessary continuous suppression of PARP activity. Continuous PARP inhibition is required for single-agent anticancer activity. To investigate if such intense schedules are necessary, we determined the durability of PARP inhibition up to 72 h after a 1 h pulse of 1 µM of five of the approved PARPi, rucaparib, olaparib, niraparib, talazoparib and pamiparib, in IGROV-1 and ES-2 (human ovarian cancer) cells. Rucaparib caused the most persistent inhibition of PARP activity when maintained at ≥75% at 72 h after drug withdrawal in both IGROV-1 and ES-2 cells, but inhibition was more rapidly lost with the other PARPi. PARPi are also under clinical investigation with ATR inhibitors, and thus, we evaluated the implications for scheduling with an ATR inhibitor (VE-821). Rucaparib enhanced VE-821 cytotoxicity in co-exposure, sequential and delayed (24 h drug-free) schedules in IGROV-1 and ES-2 cells. Olaparib and niraparib enhanced VE-821 cytotoxicity only in co-exposed cells and not in sequential exposures. These data have clinical implications for the scheduling of PARPi as a monotherapy and in combination with ATR inhibitors and other cytotoxic drugs.

Identification of the most common BRCA alterations through analysis of germline mutation databases: Is droplet digital PCR an additional strategy for the assessment of such alterations in breast and ovarian cancer families?

Breast and ovarian cancer represent two of the most common tumor types in females worldwide. Over the years, several non‑modifiable and modifiable risk factors have been associated with the onset and progression of these tumors, including age, reproductive factors, ethnicity, socioeconomic status and lifestyle factors, as well as family history and genetic factors. Of note, BRCA1 and BRCA2 are two tumor suppressor genes with a key role in DNA repair processes, whose mutations may induce genomic instability and increase the risk of cancer development. Specifically, females with a family history of breast or ovarian cancer harboring BRCA1/2 germline mutations have a 60‑70% increased risk of developing breast cancer and a 15‑40% increased risk for ovarian cancer. Different databases have collected the most frequent germline mutations affecting BRCA1/2. Through the analysis of such databases, it is possible to identify frequent hotspot mutations that may be analyzed with next‑generation sequencing (NGS) and novel innovative strategies. In this context, NGS remains the gold standard method for the assessment of BRCA1/2 mutations, while novel techniques, including droplet digital PCR (ddPCR), may improve the sensitivity to identify such mutations in the hereditary forms of breast and ovarian cancer. On these bases, the present study aimed to provide an update of the current knowledge on the frequency of BRCA1/2 mutations and cancer susceptibility, focusing on the diagnostic potential of the most recent methods, such as ddPCR.

Targeting DNA Damage Response and Immune Checkpoint for Anticancer Therapy

Deficiency in DNA damage response (DDR) genes leads to impaired DNA repair functions that will induce genomic instability and facilitate cancer development. However, alterations of DDR genes can serve as biomarkers for the selection of suitable patients to receive specific therapeutics, such as immune checkpoint blockade (ICB) therapy. In addition, certain altered DDR genes can be ideal therapeutic targets through adapting the mechanism of synthetic lethality. Recent studies indicate that targeting DDR can improve cancer immunotherapy by modulating the immune response mediated by cGAS-STING-interferon signaling. Investigations of the interplay of DDR-targeting and ICB therapies provide more effective treatment options for cancer patients. This review introduces the mechanisms of DDR and discusses their crucial roles in cancer therapy based on the concepts of synthetic lethality and ICB. The contemporary clinical trials of DDR-targeting and ICB therapies in breast, colorectal, and pancreatic cancers are included.

Three-Dimensional Modelling of Ovarian Cancer: From Cell Lines to Organoids for Discovery and Personalized Medicine

Ovarian cancer has the highest mortality of all of the gynecological malignancies. There are several distinct histotypes of this malignancy characterized by specific molecular events and clinical behavior. These histotypes have differing responses to platinum-based drugs that have been the mainstay of therapy for ovarian cancer for decades. For histotypes that initially respond to a chemotherapeutic regime of carboplatin and paclitaxel such as high-grade serous ovarian cancer, the development of chemoresistance is common and underpins incurable disease. Recent discoveries have led to the clinical use of PARP (poly ADP ribose polymerase) inhibitors for ovarian cancers defective in homologous recombination repair, as well as the anti-angiogenic bevacizumab. While predictive molecular testing involving identification of a genomic scar and/or the presence of germline or somatic BRCA1 or BRCA2 mutation are in clinical use to inform the likely success of a PARP inhibitor, no similar tests are available to identify women likely to respond to bevacizumab. Functional tests to predict patient response to any drug are, in fact, essentially absent from clinical care. New drugs are needed to treat ovarian cancer. In this review, we discuss applications to address the currently unmet need of developing physiologically relevant in vitro and ex vivo models of ovarian cancer for fundamental discovery science, and personalized medicine approaches. Traditional two-dimensional (2D) in vitro cell culture of ovarian cancer lacks critical cell-to-cell interactions afforded by culture in three-dimensions. Additionally, modelling interactions with the tumor microenvironment, including the surface of organs in the peritoneal cavity that support metastatic growth of ovarian cancer, will improve the power of these models. Being able to reliably grow primary tumoroid cultures of ovarian cancer will improve the ability to recapitulate tumor heterogeneity. Three-dimensional (3D) modelling systems, from cell lines to organoid or tumoroid cultures, represent enhanced starting points from which improved translational outcomes for women with ovarian cancer will emerge.