Development of an Immunogenic Cell Death-related LncRNAs Signature for Prognostic Risk Assessment in Gastric Cancer

Overview

Journal Transl Cancer Res

Specialty Oncology

Date 2024 Sep 12

PMID 39262480

Authors

Wen Li

Fan Ding

Jie Zhang

Affiliations

Soon will be listed here.

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. functional experiments were conducted to assess the impact of lncRNAs on the proliferation, migration, and invasion capabilities of GC cells.

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 functional experiments revealed that AP002954.1 and AP000695.1 can promote the proliferation, migration, and invasion of GC cells.

Conclusions: In conclusion, our ICDlncSig model has significant predictive value for the prognosis of GC patients and may provide clinical guidance for individualized immunotherapy.

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