ArticleScientific reports2025
Development of a PANoptosis-related LncRNAs for prognosis predicting and immune infiltration characterization of gastric Cancer.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Reprogramming of cell death in gastric cancer: From molecular mechanisms to therapeutic potential (Review).International journal of molecular medicine · 2026Review
- Autophagy determines the fate of immune cells by regulating metabolic remodeling and PANoptosis (Review).International journal of molecular medicine · 2026Review
- Identification of immunogenic cell death-related prognostic genes in gastric cancer.Journal of gastrointestinal oncology · 2026Article
- Epigenetic regulation of PANoptosis: DNA methylation, histone modifications and non-coding RNAs.EXCLI journal · 2026Review
- PANoptosis: potential new targets and therapeutic prospects in digestive diseases.Apoptosis : an international journal on programmed cell death · 2025Review
- A potential strategy to rebuild the tumor immune microenvironment: PANoptosis.Frontiers in immunology · 2025Review
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
PANoptosis is a newly discovered form of programmed cell death (PCD), involving the interaction of cellular pyroptosis, apoptosis, and necroptosis. Although PANoptosis plays a significant role in carcinogenesis process, the impact of PANoptosis-related lncRNAs (PANlncRNAs) on the prognostic value and mechanism of immune infiltration of gastric cancer have not been studied. All information of gastric cancer (GC) patients was downloaded from the TCGA database. PANoptosis-related genes were obtained from molecular characteristic databases, and PANlncRNAs were screened through Pearson correlation analysis. Based on this, PANlncRNAs were subjected to univariate Cox regression analysis using the least absolute shrinkage and selection operator (LASSO) algorithm to obtain lncRNA associated with survival outcomes, which were subsequently used to calculate survival scores and to construct signatures. Through further analysis of clinical subgroups, immune infiltration, drug sensitivity analysis, tumor mutation burden testing, and GSEA enrichment pathway analysis, their clinical significance was comprehensively analyzed. This study constructed a prognosis model for gastric cancer based on 8 PANlncRNAs and validated its prognostic value. The study showed that the survival time and outcome of the high-risk subgroup was significantly worse than that of the low-risk subgroup. The bar graph showed satisfactory predictive results, and the calibration curve showed good consistency between the prognostic model and actual prognostic outcomes. TIDE and drug sensitivity analysis showed significant differences between high and low-risk subgroups. The prognosis model based on PANlncRNAs has important implications for the judgment and precision treatment of gastric cancer.
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Registered trials
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