ArticleFrontiers in oncology2026
Application of ultrasound and methylation omics detection in the diagnosis of endometrial cancer.
Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Endometrial cancer (EC) is a common malignant gynecological tumor with a rising incidence globally. This study aimed to integrate DNA methylation analysis of cervical scrapings with transvaginal ultrasound (TVUS) imaging to develop a more effective non-invasive diagnostic strategy for EC. Methods: Methylated cytosine-guanine dinucleotide (CpG) tandem amplification and sequencing was used for genome-wide methylation profiling on EC tissues, adjacent normal tissues, and cervical scrapings from 20 EC patients and 20 benign endometrial thickening controls. Samples were randomly divided training and validation cohorts at a ratio of 6:4. Sequencing depth was 30× with coverage ≥90%, and repeatability was validated (intraclass correlation coefficient ≥0.85). BWA-Meth was used for alignment and the β-value method for methylation level calculation. Strict quality control was applied (DNA concentration ≥20 ng/μL, OD260/280 = 1.8~2.0) with preset sample criteria (≥5000 cells, ≥40% cell proportion, ≥20 mg weight). TVUS parameters were correlated with methylation findings. Four diagnostic strategies were evaluated: methylation biomarkers alone, TVUS alone, direct combination, and sequential approach (TVUS followed by methylation testing). Results: Significant differences were observed in Adler blood flow grade and endometrial-myometrial border irregularity between EC and control groups ( Conclusion: Cervical scraping-based methylation analysis may serve a useful non-invasive tool for EC detection. The sequential combination of TVUS and methylation testing appears to improve diagnostic accuracy, suggesting a potential strategy for early EC screening. This is a single-center exploratory study with a small sample size, and the results need to be validated in large-scale, multi-center independent cohorts.
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