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Updated: May 22, 2026
Reusable Single Cell for Iterative Epigenomic Analyses
Published on: February 11, 2022
Single-Cell and Computational Epigenomics in HGSOC: A Roadmap to Overcoming Chemoresistance
Samira A Farhadi1, Issa S Al-Amri1
1Department of Biological Sciences and Chemistry, College of Arts and Sciences, University of Nizwa, Nizwa, Sultanate of Oman.
Background:
High-Grade Serous Ovarian Cancer (HGSOC) remains the most lethal gynecologic malignancy, driven by profound molecular heterogeneity and dynamic epigenetic remodeling. Beyond well-characterized genomic alterations, emerging evidence underscores aberrant DNA methylation as a central regulator of lineage plasticity, tumor evolution, and chemoresistance.
Objective:
This review synthesizes recent advances demonstrating how computational deconvolution and single-cell DNA methylation technologies illuminate the epigenetic architecture of HGSOC, revealing cell-type-specific determinants of therapeutic resistance.
Methods:
We integrate findings from reference-based and reference-free deconvolution frameworks, single-cell bisulfite sequencing platforms, and multi-omic integrative tools such as SVA, EpiSCORE, and scDeconv, to provide a unified perspective on cell-resolved DNA methylation patterns in ovarian cancer.
Results:
These high-resolution epigenomic analyses reveal distinct methylation programs within chemoresistant subpopulations, notably cancer stem-like and EMT-associated cell states. Spatially informed methylation profiling further identifies microenvironmental niches that sustain resistance, offering new opportunities to define precise biomarkers and therapeutic vulnerabilities.
Conclusion:
The convergence of computational deconvolution and single-cell epigenomics provides a transformative framework for decoding chemoresistance in HGSOC. Embedding these technologies into clinical research promises to accelerate biomarker discovery, refine patient stratification, and guide the development of personalized therapeutic strategies aimed at overcoming treatment resistance.
