Evidence map›Paper›PMID 40895543›Full record

ArticleFrontiers in immunology2025

Construction and validation of a necroptosis-related lncRNA signature for predicting the prognosis of gastrointestinal cancer patients.

Weicheng Huang, Yuchen Liu, Ruyi Liu, Chi Feng, Jiehua Wu, Xing Sun, Pengfei Zhu, Pengxiang Chen, Yufeng Cheng

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Article in Frontiers in immunology, 2025. 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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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Weicheng Huang *Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
Yuchen Liu *Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
Ruyi LiuDepartment of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
Chi FengDepartment of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
Jiehua WuDepartment of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
Xing SunDepartment of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
Pengfei ZhuDepartment of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
Pengxiang ChenDepartment of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
Yufeng ChengDepartment of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Given the high incidence and mortality rates of gastrointestinal (GI) cancer, along with the lack of effective prognostic markers, this study aimed to construct a prognostic signature to identify high-risk patients facilitate precision medicine, and ultimately improve patient outcomes. Methods: We analyzed transcriptomic data for COAD, ESCA, READ, and STAD from the TCGA and GTEx databases. Using co-expression analysis, Cox regression, and least absolute shrinkage and selection operator (LASSO) regression, we developed a necroptosis-related lncRNA signature, termed the Necro-lnc score. The predictive performance of the score was validated and assessed through survival analysis, receiver operating characteristic (ROC) analysis, and Cox regression analysis. Additionally, we conducted gene set enrichment analysis (GSEA), immune landscape profiling, and drug sensitivity prediction based on half-maximal inhibitory concentration (IC50) values. The robustness of the score was further supported by cluster analysis, and the biological functions of the selected lncRNAs were experimentally validated through phenotypic assays. Results: We constructed a prognostic signature comprising five necroptosis-related lncRNAs, referred to as the Necro-lnc score. Calibration plots and areas under the ROC curves (AUCs) confirmed the strong prognostic predictive capability of the score. Kaplan-Meier (K-M) survival curves revealed a significant correlation between the Necro-lnc score and patient outcomes, with high-score patients exhibiting markedly poorer prognoses. Immune landscape and drug susceptibility analyses indicated that the high-score group was characterized by hot tumors and showed greater sensitivity to immunotherapeutic drugs and targeted drugs, while the low-score group associated with cold tumors, was more responsive to chemotherapeutic agents. Furthermore, Conclusion: This study developed the promising Necro-lnc score, which demonstrates potential for predicting prognosis and distinguishing between cold and hot tumors, thereby improving personalized treatment strategies for patients with GI cancer.

Indexed as

Biomarkers, TumorGastrointestinal NeoplasmsNecroptosisRNA, Long NoncodingFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMalePrognosisROC CurveTranscriptomeBiomarkers, TumorRNA, Long Noncodinggastrointestinal cancersimmunotherapynecroptosisprognostic predictiontumor immune microenvironment

Identifiers

PMID40895543
PMCPMC12391139

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