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Wakefield, M. J.

Publications and source records attributed to Wakefield, M. J..

8 recordsLinked to original sources

Genomic alterations enable BRCA1 methylation loss and promoter bypass to drive resistance in high-grade serous ovarian cancer

BRCA1 promoter methylation predicts sensitivity to PARP inhibitors in high-grade serous ovarian cancer, yet therapeutic resistance is common and mechanistically unresolved. Using long-read direct DNA sequencing of patient-derived xenografts and cell lines, we resolved BRCA1 methylation at single-molecule resolution with structural and transcriptomic analyses. We revealed two convergent PARP inhibitor and platinum resistance mechanisms, validated in patient tumors. First, focal, allele-specific loss of BRCA1 methylation arose through local cis-acting genomic alterations, instead of global epigenetic reprogramming. Engineered in cis sequence alterations near the methylated BRCA1 promoter were sufficient to induce methylation loss, restore homologous recombination, and confer resistance. Similar associations were observed across the genome, suggesting this mechanism extends beyond BRCA1. Second, BRCA1 expression was restored despite intact promoter methylation via structural variant-mediated promoter bypass or alternative transcription initiation. Together, these findings redefine BRCA1 methylation loss as a locus-restricted process and reveal multiple routes by which tumors escape PARP inhibitor therapy. Statement of SignificanceWe show that high-grade serous ovarian cancers can restore BRCA1 expression after therapy through multiple genomic mechanisms, including local methylation loss and promoter bypass, thereby re-establishing homologous recombination and driving PARP inhibitor resistance. These findings challenge reliance on BRCA1 methylation alone as a predictive biomarker and support rational combination therapies for more durable responses.

cancer biology↗

CountESS: a flexible, graphical pipeline tool for deep mutational scanning analysis

Deep Mutational Scanning (DMS) experiments generate large volumes of sequencing data that must be processed through multi-step computational pipelines to yield interpretable variant scores. At least twelve dedicated tools have been published for this purpose, yet the diversity of experimental designs, scoring strategies, and software implementations has produced a fragmented landscape in which no single tool accommodates the full range of workflows encountered in practice. Here we present CountESS (Count-based Experiment Scoring and Statistics), an open-source pipeline tool that provides a modular, graphical interface for constructing flexible DMS analysis workflows. CountESS supports a wide range of input formats, barcode translation, HGVS variant calling, and user-defined scoring functions, enabling it to accommodate diverse experimental designs including selection assays, time-series experiments, and bin-based assays such as VAMP-seq. Implemented in Python with DuckDB as a computational backend, the software provides high-performance, memory-efficient processing suitable for large datasets. CountESS is freely available at https://github.com/CountESS-Project/CountESS under the 3-Clause BSD Licence. Supplementary data, including demonstration pipelines and example datasets, are available at https://github.com/CountESS-Project/countess-demo.

bioinformatics↗

Demethylating agents drive PARP inhibitor resistance in ovarian carcinomas with BRCA1 gene silencing

DNA methyltransferase 1 inhibitor (DNMT1i) therapy is a promising option for increasing immune response as part of combination cancer therapy. High-grade serous ovarian carcinoma (HGSOC) is a highly aggressive cancer with poor survival outcomes, where DNMT1i therapy is being increasingly explored. HGSOC with epigenetically silenced BRCA1 has been shown to respond to PARP inhibitor (PARPi) treatment - a core targeted therapy for HGSOC. However, loss of silencing of even a single BRCA1 allele causes PARPi and platinum chemotherapy resistance. We tested whether BRCA1 silencing was robust to DNMT1i therapy, or would be reversed, thus driving PARPi resistance. We previously generated two homozygously silenced BRCA1 HGSOC cell lines: WEHI-CS62 and an OVCAR8 derivative. DNMT1i treatment caused sustained BRCA1 promoter methylation loss, gene re-expression and PARPi resistance in both of these silenced BRCA1 lines, but not in mutated BRCA1/2 or RAD51C lines. Methylation arrays confirmed transient global CpG methylation losses following DNMT1i. CRISPR deletion of the re-expressed BRCA1 copy in WEHI-CS62 restored silencing and PARPi sensitivity. Furthermore, DNMT1i treatment of a silenced BRCA1 PDX caused heterogeneous BRCA1 promoter methylation loss. In summary, DNMT1 inhibitors caused sustained reduction of BRCA1 promoter methylation in HGSOC cells. This resulted in BRCA1 re-expression and PARP inhibitor resistance, presenting a significant risk for up to 17% of HGSOC patients with BRCA1 gene silencing who could benefit from PARP inhibitor therapy. We conclude that DNA demethylation therapy should be avoided for HGSOC patients with epigenetically silenced BRCA1.

cancer biology↗

Generation of a PARPi-sensitive homozygous BRCA1-methylated OVCAR8 cell line using targeted CRISPR gene editing

Up to 17% of high grade serous ovarian carcinomas (HGSOC) harbour BRCA1 promoter methylation (meBRCA1), making them susceptible to treatment with targeted PARP inhibitor (PARPi) therapy. Unfortunately, meBRCA1 loss can be acquired following PARPi or platinum chemotherapy, resulting in BRCA1 re-expression and PARPi resistance. Our understanding of meBRCA1 stability in HGSOC is currently limited, in part due to a paucity of pre-clinical models with homozygous meBRCA1. Herein, we describe the generation of a several OVCAR8 cell line derivatives containing landing pad constructs, for future functional studies, and representing various BRCA1 states, including a homozygous meBRCA1 variant. Our PARPi resistant OVCAR8 has two methylated BRCA1 copies and one unmethylated copy, enabling BRCA1 expression. CRISPR-Cas9 gene editing was used to delete copies of the BRCA1 gene in landing pad-containing clones of this cell line (A6 and H4). We produced one variant with deletion of all BRCA1 copies (H4-53), and another with two copies deleted and only a single methylated gene copy remaining (A6-30 - validated further using nanopore long-read sequencing). These both lacked BRCA1 gene expression and were sensitive to PARPi treatment. The A6-30 line was transplanted into immunocompromised mice to generate a xenograft model that retained homozygous meBRCA1 and demonstrated some response to PARPi in vivo. Thus, using CRISPR gene editing we have created several novel isogenic HGSOC cell line models, including one with homozygous meBRCA1, that will support future studies of meBRCA1 stability and PARPi resistance.

cancer biology↗

MaveDB v2: a curated community database with over three million variant effects from multiplexed functional assays

A central problem in genomics is understanding the effect of individual DNA variants. Multiplexed Assays of Variant Effect (MAVEs) can help address this challenge by measuring all possible single nucleotide variant effects in a gene or regulatory sequence simultaneously. Here we describe MaveDB v2, which has become the database of record for MAVEs. MaveDB now contains a large fraction of published studies, comprising over two hundred datasets and three million variant effect measurements. We created tools and APIs to streamline data submission and access, transforming MaveDB into a hub for the analysis and dissemination of these impactful datasets.

genomics↗

Characterization of a RAD51C-Silenced High Grade Serous Ovarian Cancer Model During PARP Inhibitor Resistance Development

Acquired PARP inhibitor (PARPi) resistance in BRCA1- or BRCA2-mutant ovarian cancer often results from secondary mutations that restore expression of functional protein. RAD51C is a less commonly studied ovarian cancer susceptibility gene whose promoter is sometimes methylated in the tumor, leading to homologous recombination deficiency and PARPi sensitivity. For this study, the PARPi-sensitive patient-derived xenograft PH039, which lacks demonstrable repair gene mutations but harbors RAD51C promoter methylation, was selected for PARPi resistance by repeated 21-day niraparib treatments in vivo. PH039 acquired PARPi resistance by the third cycle of treatment and demonstrated unimpeded growth during subsequent exposure to either niraparib or rucaparib. Transcriptional profiling throughout the time course of resistance development showed widespread pathway level changes along with a marked increase in RAD51C mRNA, which reflected loss of RAD51C promoter methylation. Analysis of RAD51C methylation in patient tumor samples from the ARIEL2 Part 1 clinical trial of rucaparib monotherapy likewise indicated that loss of RAD51C methylation prior to on-study biopsy was associated with limited response. Interestingly, the PARPi resistant PH039 model remained platinum sensitive. Collectively, these results not only indicate that PARPi treatment pressure can reverse RAD51C methylation and restore RAD51C expression, but also provide an important model for studying the clinical observation that PARPi and platinum sensitivity are sometimes dissociated.

cancer biology↗

Acquired RAD51C promoter methylation loss causes PARP inhibitor resistance in high grade serous ovarian carcinoma

While loss of BRCA1 promoter methylation has been shown to cause PARP inhibitor (PARPi) resistance in high-grade serous ovarian carcinoma (HGSC), the impacts of RAD51C methylation (meRAD51C) remain unresolved. In this study, three PARPi-responsive HGSC patient-derived xenografts (PDX) with RAD51C gene silencing and homologous recombination deficiency were found to have either homogeneous or heterogeneous patterns of meRAD51C. PDX could lose meRAD51C following PARPi treatment (rucaparib/niraparib), where a single unmethylated RAD51C copy was sufficient to drive PARPi-resistance. Genomic profiling revealed this resistance was acquired independently in two distinct PDX lineages. Furthermore, we describe a patient sample where 1/3 RAD51C gene copies lost methylation following neoadjuvant chemotherapy. We show meRAD51C is a positive predictive biomarker for PARPi response and should be screened for routinely in patients. However, methylation loss in a single gene copy is sufficient to cause PARPi resistance and should be carefully assessed in previously treated patients considering PARPi therapy.

cancer biology↗

Inhibition of RNA Polymerase I Transcription Activates Targeted DNA Damage Response and Enhances the Efficacy of PARP Inhibitors in High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) accounts for the majority of ovarian cancer and has a dismal prognosis. PARP inhibitors (PARPi) have revolutionized disease management of patients with homologous recombination (HR) DNA repair-deficient HGSOC. However, acquired resistance to PARPi by complex mechanisms including HR restoration and stabilisation of replication forks is a major challenge in the clinic. Here, we demonstrate CX-5461, an inhibitor of RNA polymerase I transcription of ribosomal RNA genes (rDNA), induces replication stress at rDNA leading to activation of DNA damage response and DNA damage involving MRE11-dependent degradation of replication forks. CX-5461 cooperates with PARPi in exacerbating DNA damage and enhances synthetic lethal interactions of PARPi with HR deficiency in HGSOC-patient-derived xenograft (PDX) in vivo. We demonstrate CX-5461 has a different sensitivity spectrum to PARPi and destabilises replication forks irrespective of HR pathway status, overcoming two well-known mechanisms of resistance to PARPi. Importantly, CX-5461 exhibits single agent efficacy in PARPi-resistant HGSOC-PDX. Further, we identify CX-5461-sensitivity gene expression signatures in primary and relapsed HGSOC. Therefore, CX-5461 is a promising therapy alone and in combination therapy with PARPi in HR-deficient HGSOC. CX-5461 is also an exciting treatment option for patients with relapsed HGSOC tumors that have poor clinical outcome.

cancer biology↗