Search PubMedSearch

PubMed · 42685115

Integrative proteomics reveals MSH6 to modulate PARP inhibitor sensitivity in BRCA1/2-proficient ovarian cancer.

Abstract

Ovarian cancer remains a leading cause of gynecologic cancer-related deaths worldwide. Deficiencies in BRCA1/2 are well-established biomarkers that predict sensitivity to poly(ADP-ribose) polymerase inhibitors (PARPis). However, emerging evidence indicates that a subset of BRCA-proficient tumors also responds to PARPi therapy, suggesting the presence of additional molecular mechanisms. We hypothesized that the composition of the PARP1 protein complex and PARylation-mediated signaling contribute to PARPi response in BRCA-proficient HGSOC. We assessed PARPi response across a panel of BRCA-proficient ovarian cancer cell lines and identified distinct sensitive and resistant groups. Chemical proteomics with rucaparib revealed different PARP1 complexes including higher enrichment of MSH6 in sensitive cells. Co-immunoprecipitation analyses further confirmed differential assembly of PARP1-MSH6-PARP2 complexes between sensitive and resistant models. To explore PARylation signaling, we performed ADP-ribosylation proteomics using clickable NAD⁺ analogs, revealing distinct PARylation profiles between sensitive and resistant cell lines. CHAF1A, a known MSH6 interactor and PARP1 substrate, showed more pronounced reduction in ADP-ribosylation in PARPi-sensitive cells. Targeting MSH6 using CRISPR or siRNA decreased PARPi sensitivity. In addition, mTOR signaling was reduced in sensitive, but increased in resistant cells, following rucaparib treatment. Notably, MSH6 knockdown led to increased CHAF1A expression regardless of rucaparib treatment. Importantly, knockdown of CHAF1A significantly impaired cell viability, especially in A2780 cells, and suppressed mTOR signaling, suggesting that CHAF1A acts downstream of MSH6 to regulate the mTOR axis. Furthermore, co-treatment with mTORC1 inhibitors enhanced the cellular effects of rucaparib in resistant cells, suggesting a therapeutic potential of targeting downstream mTOR effectors to overcome intrinsic resistance. In conclusion, this study identifies the PARP1-MSH6 interaction to modulate PARPi sensitivity via CHAF1A-mTOR signaling in BRCA-proficient ovarian cancer. By integrating chemical proteomics and ADP-ribosylation proteomics, we delineate the interplay between PARP1 complex composition and signaling dynamics, highlighting MSH6 as a critical modulator of PARPi response and potential biomarker to enhance therapeutic efficacy in BRCA-proficient HGSOC.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ou Deng, Thales Da Costa Nepomuceno, Bin Fang, Eric A Welsh, Victoria Izumi, Rachael H Martin, Erin M George, John M Koomen, Alvaro N Monteiro, Uwe Rix. 2026-09-02. Integrative proteomics reveals MSH6 to modulate PARP inhibitor sensitivity in BRCA1/2-proficient ovarian cancer.. https://doi.org/10.1371/journal.pone.0357365

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans