Evidence map›Paper›PMID 41793107›Full record

ArticleCancer science2026

Systematic Multiplatform Discovery of Methylation Markers Enables Non-Invasive Early Detection of Endometrial Cancer.

Yan Cai, Shuchao Chen, Zhen Wu, Jinxia Guan, Jie Zhao, Jianwei Ye, Baochen Du, Xiaoliang Han, Tong Shu, Guangpeng Zhou and 1 more

Abstract read
In one paragraph

Article in Cancer science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yan CaiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gynecologic Oncology, Peking University Cancer Hospital & Institute, Beijing, China.
Shuchao ChenBioChain (Beijing) Science & Technology Inc., Beijing, China.
Zhen WuBioChain (Beijing) Science & Technology Inc., Beijing, China.
Jinxia GuanBioChain (Beijing) Science & Technology Inc., Beijing, China.
Jie ZhaoBioChain (Beijing) Science & Technology Inc., Beijing, China.ORCID https://orcid.org/0000-0001-7254-761X
Jianwei YeBioChain (Beijing) Science & Technology Inc., Beijing, China.
Baochen DuBioChain (Beijing) Science & Technology Inc., Beijing, China.
Xiaoliang HanBioChain (Beijing) Science & Technology Inc., Beijing, China.
Tong ShuKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gynecologic Oncology, Peking University Cancer Hospital & Institute, Beijing, China.
Guangpeng ZhouBioChain (Beijing) Science & Technology Inc., Beijing, China.
Hong ZhengKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gynecologic Oncology, Peking University Cancer Hospital & Institute, Beijing, China.

Funding

Clinical Research Fund For Distinguished Young Scholars of Peking University Cancer Hospital. QNJJ202325
6 · The paper itself

Abstract

Endometrial cancer, the most common gynecological malignancy with an annual increase of 1%-3%, lacks suitable noninvasive diagnostic tools, as current methods like hysteroscopy and biopsy are invasive and impractical for routine screening. We conducted a comprehensive, multilayered marker discovery workflow integrating whole-genome bisulfite sequencing and targeted methylation panels in tumor and control tissues, then prioritized and optimized candidates for detection in cervical exfoliated cells. Using a two-stage design, we built and tested a quantitative methylation-specific PCR (qMSP) model in ThinPrep Cytology Test (TCT) samples, with 148 samples for discovery/model construction and an independent cohort of 80 TCT samples for validation. We identified a three-gene methylation panel-ZNF626, GRIA4, and SPDYA-that demonstrated high accuracy for early endometrial cancer detection from cervical cytology. In the validation cohort, the model showed strong performance across menopausal subgroups: in premenopausal women, sensitivity was 90.91% and specificity for benign endometrial disease was 92.59%; in postmenopausal women, sensitivity and specificity were 96.55% and 84.62%, respectively. Notably, the approach achieved a 92.86% detection rate for stage I endometrial cancer. These results support a robust, noninvasive diagnostic strategy that leverages simple cervical cytology sampling to enable early detection, facilitate clinical decision-making, and potentially improve outcomes for patients at risk of endometrial cancer.

Indexed as

Biomarkers, TumorDNA MethylationEarly Detection of CancerEndometrial NeoplasmsAdultAgedFemaleHumansMiddle AgedSensitivity and SpecificityBiomarkers, TumorDNA methylationearly detectionEC diagnostic modelendometrial cancerTCT sample

Identifiers

PMID41793107
PMCPMC13134521

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.