Search PubMedSearch

PubMed · 42091345

Homologous recombination-deficient high-grade serous ovarian cancers exhibit distinct morphological features.

Abstract

OBJECTIVE: Access to homologous recombination testing remains limited in many centers. We aim to correlate the morphology and immunophenotype of high-grade serous ovarian carcinoma with homologous recombination statuses. METHODS: A retrospective analysis of a high-grade serous ovarian carcinoma tumors with known homologous recombination status. A pathological review of morphology was performed for each tumor, along with immunohistochemical profiling. Tumor morphology was classified as (1) solid, pseudo-endometrioid, or transitional (2) micropapillary or nested. RESULTS: Overall, 81 tumors were included. The median age was 62 (interquartile range; 52-71). Of those, 27 (33.3%) tumors were BRCA1mut, 19 (23.5%) were BRCA2mut, 15 (18.5%) tumors had no BRCA1 or BRCA2 mutations but exhibited a genomic instability score &#x2265;42 and were classified as BRCA1/2-wild-type with homologous recombinant deficient. The remainder 20 (24.7%) cases were homologous recombinant proficient. The proportion of tumors with solid transitional-like morphology was higher in BRCA1 (12/21, 57%) and BRCA2 (12/18, 67%) compared to the tumors with homologous recombinant proficient (3/17, 18%), p =.019. When stratified by genomic instability score, tumors with low score (genomic instability score <26) exhibited 0% solid transitional-like morphology versus 43% solid transitional-like morphology in high-score (genomic instability score >26), p =.03. PAX8 diffuse expression was detected in 71% of BRCA1, 65% of BRCA2, 92% of BRCA-wild-type homologous recombinant deficient tumors, and 100% of homologous recombinant proficient tumors, p =.071. The proportion of diffuse expression was higher in homologous recombinant proficient (100%) versus BRCA2 (65%) (Bonferroni-adjusted pairwise comparisons). CONCLUSIONS: Homologous recombinant deficient tumors are associated with the solid transitional-like morphology, with the BRCA1/2-mutated homologous recombinant deficient cases showing the strongest correlation. Genomic instability score alone may not fully capture the spectrum of homologous recombinant deficient-related phenotypes. The variation in solid transitional-like morphology features among BRCA1- or BRCA2-mutated, BRCA1/2- wild-type with homologous recombinant deficient, and homologous recombinant proficient cases may reflect the diverse biological spectrum of different homologous recombination alterations.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kattreen Hanna, Gabriel Levin, Miryam Al Nasir, Roxanne Lacouline-Boulanger, Lawrie Shahbazian, Sarah-Slim Diwan, Joyce Li, Denia Hamidi, L&#xe9;a Stephan, Mina Hmimas, Nicole Zhang, Phuong-Nam Nathalie Nguyen, Lara Richer, Karine Jacob, Andrea Gomez, Reitan Ribeiro, Victoria Mandilaras, Laurence Bernard, Xing Zeng, Robert A Soslow, Lucy Gilbert, Shuk On Annie Leung, Basile Tessier-Cloutier. 2026-04-09. Homologous recombination-deficient high-grade serous ovarian cancers exhibit distinct morphological features.. https://doi.org/10.1016/j.ijgc.2026.104690

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