Evidence map›Paper›PMID 39262480›Full record

ArticleTranslational cancer research2024

Development of an immunogenic cell death-related lncRNAs signature for prognostic risk assessment in gastric cancer.

Wen Li, Fan Ding, Jie Zhang

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Article in Translational cancer research, 2024. 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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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Wen LiDepartment of Immunology, Nantong University School of Medicine, Nantong, China.
Fan DingDepartment of Medical Administration, The People's Hospital of Danyang, Affiliated Danyang Hospital of Nantong University, Zhenjiang, China.
Jie ZhangDepartment of Immunology, Nantong University School of Medicine, Nantong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immunogenic cell death (ICD) is a functionally specialized form of apoptosis induced by endoplasmic reticulum (ER) stress and is associated with a variety of cancers, including gastric cancer (GC). In recent years, long non-coding RNAs (lncRNAs) have been shown to be important mediators in the regulation of ICD. However, the specific role and prognostic value of ICD-related lncRNAs in GC remain unclear. This study aims to develop an ICD-related lncRNAs signature for prognostic risk assessment in GC. Methods: The ICD-related lncRNAs signature (ICDlncSig) of GC was constructed by univariate Cox regression analysis, least absolute shrinkage, and selection operator (LASSO) regression model and multivariate Cox regression analysis, and the signature was correlated with immune infiltration. The potential response of GC patients to immunotherapy was predicted by the tumor immune dysfunction and rejection (TIDE) algorithm. Results: We constructed a novel ICDlncSig and found that this signature could be used as a prognostic risk model to predict survival of GC patients by validating it in the training cohort, testing cohort and entire cohort. The robust predictive power of the signature was demonstrated by building a Nomogram based on ICDlncSig scores and clinical characteristics. Furthermore, immune cell subpopulations, expression of immune checkpoint genes, and response to chemotherapy and immunotherapy differed significantly between the high- and low-risk groups. The Conclusions: In conclusion, our ICDlncSig model has significant predictive value for the prognosis of GC patients and may provide clinical guidance for individualized immunotherapy.

Indexed as

Gastric cancer (GC)immune infiltrationimmunogenic cell death (ICD)immunotherapylong non-coding RNA (lncRNA)

Identifiers

PMID39262480
PMCPMC11385251

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