Evidence map›Paper›PMID 41928513›Full record

ArticleCell reports. Medicine2026

Development and validation of a 5mC-based prognostic model for lung adenocarcinoma survival.

Yifan Wu, Zichen Jiao, Jianchao Xue, Xiaoyi Zheng, Zhicheng Huang, Daoyun Wang, Peipei Chen, Tao Wang, Jian-Qun Chen, Naixin Liang and 3 more

Abstract readValidation Study
In one paragraph

Article in Cell reports. Medicine, 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

13 authors.

Yifan WuThe State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China.
Zichen JiaoThe State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China; Department of Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
Jianchao XueDepartment of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China; Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xiaoyi ZhengThe State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China.
Zhicheng HuangDepartment of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China; Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Daoyun WangDepartment of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China; Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Peipei ChenThe State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China.
Tao WangDepartment of Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
Jian-Qun ChenSchool of Life and Health Science, Fuyao University of Science and Technology, Fuzhou, China.
Naixin LiangDepartment of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China; Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Electronic address: liangnaixin@pumch.cn.
Yao TangDepartment of Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China; Cancer Center, Faculty of Health Sciences, University of Macau, Macau, SAR, China; Center of Precision Medicine Research and Training, Faculty of Health Sciences, University of Macau, Macau, SAR, China. Electronic address: yaotang@um.edu.mo.
Qiang WangThe State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China; Department of Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China. Electronic address: wangq@nju.edu.cn.
Qihan ChenCancer Center, Faculty of Health Sciences, University of Macau, Macau, SAR, China; Center of Precision Medicine Research and Training, Faculty of Health Sciences, University of Macau, Macau, SAR, China. Electronic address: lyonchen@umac.mo.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD) exhibits marked prognostic heterogeneity. Existing methylation-based prognostic models lack robustness, accuracy, or external validation, limiting their clinical utility. We develop MethPro-LUAD, a prognostic model based on eight 5-methylcytosine features, using TCGA-LUAD data (training, N = 269; testing, N = 180), and validate the model across two independent hospital cohorts (Beijing, N = 195; Nanjing, N = 88) and two external GEO datasets (N = 82 and N = 155) to ensure its generalizability and effectiveness. MethPro-LUAD stratifies patients into high- and low-risk groups, with high-risk individuals consistently showing significantly shorter overall survival across all cohorts. In addition, the model's predictive performance remains robust in subgroups defined by age, sex, stage, and EGFR mutation and in disease-free survival analyses. Compared with other reported LUAD prognostic models, MethPro-LUAD demonstrates better performance across cohorts, which offers valuable support for personalized postoperative treatment and follow-up, and warrants further prospective evaluation, highlighting its strong potential for clinical translation through feasible targeted assays.

Indexed as

5-MethylcytosineAdenocarcinoma of LungDNA MethylationLung NeoplasmsAgedBiomarkers, TumorDisease-Free SurvivalFemaleHumansMaleMiddle AgedPrognosis5-MethylcytosineBiomarkers, TumorDNA methylationlung adenocarcinomaprognosis

Identifiers

PMID41928513
PMCPMC13130642

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.