bims-dinmec 2025-08-10 papers

Issue of 2025–08–10
three papers selected by
Lorena Ancona, Humanitas Research

PLoS One. 2025 ;20(8): e0329593

A comparison of DNA methylation detection between HiFi sequencing and whole genome bisulfite sequencing in monozygotic twins with Down syndrome.

Kanyanee Promsawan, Chalurmpon Srichomthong, Monnat Pongpanich, Vorasuk Shotelersuk.

DNA methylation, a key epigenetic modification, regulates gene expression and diverse cellular functions. Bisulfite sequencing (BS) remains the gold standard for methylation detection, while PacBio HiFi sequencing enables direct detection without chemical conversion. Although both technologies are increasingly used, few studies have directly compared their concordance, particularly in clinically relevant settings such as Down syndrome (DS). We performed a comparative analysis of DNA methylation profiles using whole-genome bisulfite sequencing (WGBS) and PacBio high-fidelity (HiFi) whole-genome sequencing (WGS) in a pair of monozygotic twins with DS. WGBS data were processed with two pipelines, wg-blimp and Bismark, while HiFi WGS data were analyzed using pb-CpG-tools. Our analysis focused on four key aspects: CpG site detection, genomic distribution of methylated CpGs (mCs), average methylation levels, and inter-platform concordance. HiFi WGS detected a greater number of mCs-particularly in repetitive elements and regions with low WGBS coverage-while WGBS reported higher average methylation levels than HiFi WGS. Both platforms exhibited methylation patterns consistent with known biological principles, such as low methylation in CpG islands, and the relative methylation patterns across genomic features were largely concordant. Pearson correlation coefficients indicated strong agreement between platforms (r ≈ 0.8), with higher concordance in GC-rich regions and at increased sequencing depths. Depth-matched comparisons and site-level down-sampling revealed that methylation concordance improves with increasing coverage, with stronger agreement observed beyond 20 × . Our findings support the reliability of HiFi WGS for methylation detection and highlight its advantages in regions that are challenging for bisulfite-based methods. This study demonstrates that HiFi WGS can serve as a robust alternative for genome-wide methylation profiling.

DOI: https://doi.org/10.1371/journal.pone.0329593

Clin Epigenetics. 2025 Aug 07. 17(1): 140

BRCA1 promoter methylation predicts PARPi response in ovarian cancer: insights from the KOMET study.

Léna Nougarede, Florence Hazane-Puch, Florence de Fraipont, Emmanuelle Jacquet, Marie Bidart.

OBJECTIVES: PARP inhibitors (PARPi) have become the new standard maintenance treatment for patients with advanced homologous recombination deficiency (HRD) ovarian cancer; they are also used upon platinum-sensitive relapse. HRD in ovarian cancer is primarily assessed through BRCA genes mutations and genomic scar scores, which are key biomarkers forecasting PARPi benefit. However, the role of BRCA1 promoter methylation in guiding clinical management is unclear. Evidence is needed to improve patient selection before initiating PARPi and to minimize PARPi-related toxicities. Our study aimed to determine the clinical relevance of BRCA1 promoter methylation for patients with ovarian carcinoma.
METHOD: The KOMET (Ovarian Cancer Methylation) study is a single-center retrospective study involving 88 ovarian cancer patients treated between January 2021 and July 2024. Methylation was assessed using Methylation specific high-resolution melting (MS-HRM). Outcomes were measured based on progression-free survival (PFS) from diagnosis and from the initiation of PARPi treatment, as well as overall survival (OS).
RESULTS: A methylated BRCA1 promoter was detected in 17 out of 88 (19%) tumor tissues. Statistically, PFS from PARPi initiation was significantly different between the BRCA1 methylated promoter (BRCA1mp) group and the BRCA1 unmethylated promoter and HRD negative (BRCA1up HRD-) group (p value = 0.0003 log rank test; Hazard Ratio (HR), 95% CI 0.04-0.40). OS was also significantly different between these groups (p value = 0.047 log rank test; HR = 0.30, 95% CI 0.10-0.84), as was PFS from diagnosis (p value = 0.02 log rank test; HR = 0.43, 95% CI 0.21-0.89).
CONCLUSION: BRCA1 promoter methylation in ovarian cancer is associated with a better response to PARPi and platinum salt chemotherapy than tumors without promoter methylation or classical homologous recombination deficiency. Patients with unmethylated BRCA1 promoters and HRD-negative tumors appeared to have a poorer prognosis in terms of PFS from diagnosis. BRCA1 methylation should be considered as a theragnostic biomarker for initiation of PARPi.

DOI: https://doi.org/10.1186/s13148-025-01917-w

Front Med (Lausanne). 2025 ;12 1630788

Applications and advances of multi-omics technologies in gastrointestinal tumors.

Yuqing Liu, Feng Gao, Yang Cheng, Liang Qi, Haining Yu.

Gastrointestinal tumors pose a significant clinical challenge due to their high heterogeneity and the difficulties in early diagnosis. The article systematically reviews the latest advances in multi-omics technologies in gastrointestinal tumor research, focusing on their contributions to early screening, biomarker discovery, and treatment optimization. Genomics reveals genetic characteristics and heterogeneity of tumors; transcriptomics helps identify molecular subtypes and potential therapeutic targets; proteomics provides important information on core proteins and the immune microenvironment; and metabolomics offers promising biomarkers for early diagnosis. Furthermore, emerging fields such as epigenomics, metagenomics, and lipidomics, through the construction of multi-scale frameworks, have opened new paths for molecular subtyping and targeted therapy. By integrating these multi-dimensional data, multi-omics integration enables a panoramic dissection of driver mutations, dynamic signaling pathways, and metabolic-immune interactions. However, challenges such as data heterogeneity, insufficient algorithm generalization, and high costs limit clinical translation. In the future, the integration of single-cell multi-omics, artificial intelligence, and deep learning technologies with multi-omics may offer more efficient strategies for the precise diagnosis and personalized treatment of gastrointestinal tumors.

Keywords: biomarkers; early screening; gastrointestinal tumors; multi-omics technologies; single-cell genomics; treatment optimization

DOI: https://doi.org/10.3389/fmed.2025.1630788