MLMP: A Methylation‐Associated lncRNA‐mRNA Prognostic Signature for Endometrial Carcinoma
- 1Department of Gynecological Radiotherapy Harbin Medical University Cancer Hospital Harbin China
- 2School of Life Science and Technology Harbin Institute of Technology Harbin China
Abstract
Background: Endometrial carcinoma (EC) is one of the most common gynecological malignancies. Aberrant DNA methylation (DNAm) is an important epigenetic alteration involved in cancer progression. Long non‐coding RNAs (LncRNAs) play critical roles in gene regulation and pathological processes. However, the biological and prognostic significance of lncRNA‐mRNA pairs associated with methylation remains unclear.
Methods: Transcriptomic, DNA methylation, and clinical data from The Cancer Genome Atlas were integrated to construct a differentially methylated sites (DMSs)‐lncRNA‐mRNA network. After mapping DMSs to their corresponding differentially methylated genes (DMGs), the DMS‐mediated network was further represented as a DMG‐lncRNA‐mRNA tripartite network. After removal of DMG nodes, a DMG‐associated lncRNA‐mRNA background network was constructed, and key lncRNA‐mRNA pairs were prioritized according to their topological importance using weighted shortest‐path calculation and PageRank‐based random walk algorithms. The methylation‐associated lncRNA‐ mRNA pair (MLMP) model was then established based on univariate Cox, LASSO Cox, and multivariate Cox regression analyses.
Results: Eight DMG‐associated lncRNA‐mRNA pairs were selected to construct the MLMP model. Under a common analysis framework, the MLMP model achieved higher area under the curve (AUC) values than 17 previously published prognostic signatures for overall survival prediction. Patients in the low‐MLMP group had significantly better overall survival than those in the high‐MLMP group. Functional enrichment and immune microenvironment analyses indicated that the MLMP model was associated with immune‐related pathways and distinct tumor immune microenvironment characteristics. Predictive analyses suggested that patients in the low‐MLMP group exhibited higher predicted responsiveness to CTLA‐4/PD‐1 blockade and differential predicted sensitivity to several therapeutic agents.
Conclusions: The MLMP model may serve as a potential tool for prognostic stratification in EC and provide insights into methylation‐associated lncRNA‐mRNA interactions. The predicted associations with immunotherapy response and therapeutic sensitivity may generate hypotheses for future treatment‐related studies. These findings require further validation in independent clinical cohorts and experimental studies before clinical application.
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BibTeX
@article{kou2026mlmp,
title = {{MLMP: A Methylation‐Associated lncRNA‐mRNA Prognostic Signature for Endometrial Carcinoma}},
author = {Hong Kou and Mu Su and Jie Zhou and Yujie Liu and Yuan Wang and Jie Xing and Hongli Wang and Xueting Liu and Xinwen Wang and Yunyan Zhang and Sijia Liu},
journal = {Cancer Medicine},
year = {2026},
month = oct,
doi = {10.1002/cam4.72425},
url = {https://doi.org/10.1002/cam4.72425},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - MLMP: A Methylation‐Associated lncRNA‐mRNA Prognostic Signature for Endometrial Carcinoma
AU - Hong Kou
AU - Mu Su
AU - Jie Zhou
AU - Yujie Liu
AU - Yuan Wang
AU - Jie Xing
AU - Hongli Wang
AU - Xueting Liu
AU - Xinwen Wang
AU - Yunyan Zhang
AU - Sijia Liu
PY - 2026
DA - 2026/10/25
JO - Cancer Medicine
DO - 10.1002/cam4.72425
UR - https://doi.org/10.1002/cam4.72425
AB - Background: Endometrial carcinoma (EC) is one of the most common gynecological malignancies. Aberrant DNA methylation (DNAm) is an important epigenetic alteration involved in cancer progression. Long non‐coding RNAs (LncRNAs) play critical roles in gene regulation and pathological processes. However, the biological and prognostic significance of lncRNA‐mRNA pairs associated with methylation remains unclear. Methods: Transcriptomic, DNA methylation, and clinical data from The Cancer Genome Atlas were integrated to construct a differentially methylated sites (DMSs)‐lncRNA‐mRNA network. After mapping DMSs to their corresponding differentially methylated genes (DMGs), the DMS‐mediated network was further represented as a DMG‐lncRNA‐mRNA tripartite network. After removal of DMG nodes, a DMG‐associated lncRNA‐mRNA background network was constructed, and key lncRNA‐mRNA pairs were prioritized according to their topological importance using weighted shortest‐path calculation and PageRank‐based random walk algorithms. The methylation‐associated lncRNA‐ mRNA pair (MLMP) model was then established based on univariate Cox, LASSO Cox, and multivariate Cox regression analyses. Results: Eight DMG‐associated lncRNA‐mRNA pairs were selected to construct the MLMP model. Under a common analysis framework, the MLMP model achieved higher area under the curve (AUC) values than 17 previously published prognostic signatures for overall survival prediction. Patients in the low‐MLMP group had significantly better overall survival than those in the high‐MLMP group. Functional enrichment and immune microenvironment analyses indicated that the MLMP model was associated with immune‐related pathways and distinct tumor immune microenvironment characteristics. Predictive analyses suggested that patients in the low‐MLMP group exhibited higher predicted responsiveness to CTLA‐4/PD‐1 blockade and differential predicted sensitivity to several therapeutic agents. Conclusions: The MLMP model may serve as a potential tool for prognostic stratification in EC and provide insights into methylation‐associated lncRNA‐mRNA interactions. The predicted associations with immunotherapy response and therapeutic sensitivity may generate hypotheses for future treatment‐related studies. These findings require further validation in independent clinical cohorts and experimental studies before clinical application.
SN - 2045-7634
ER -