Development of a PANoptosis-related LncRNAs for prognosis predicting and immune infiltration characterization of gastric Cancer

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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Publication Details

Journal
Scientific Reports
Published
2025-03-05
DOI
https://doi.org/10.1038/s41598-025-91534-7
Citations
3
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
2.81

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article

Development of a PANoptosis-related LncRNAs for prognosis predicting and immune infiltration characterization of gastric Cancer

Gaofeng Hu, Jiaming Ge, C. L. Luo, Wenyuan Niu et al.
3 citations
Scientific Reports
Cancer-related molecular mechanisms research
2.81
article

Development of a PANoptosis-related LncRNAs for prognosis predicting and immune infiltration characterization of gastric Cancer

Gaofeng Hu, Jiaming Ge, C. L. Luo, Wenyuan Niu, Bowen Li, Qinglin Li, Jie Xuan, Yanyang Liu, Zeng Wang, Huize Shen, Yangjian Hong, Huangjie Zhang
article en
3 citations

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.

Scientific ReportsVol. 15(1)
Chinese Academy of Sciences (CN), Wenzhou Medical University (CN), Zhejiang Cancer Hospital (CN)
Basic Public Welfare Research Program of Zhejiang Province
Zero hunger
Openalex Percentile: Top 11%
Cancer-related molecular mechanisms research
2.81
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