ArticleCurrent oncology (Toronto, Ont.)2022
Immune-Related LncRNAs to Construct a Prognosis Risk-Assessment Model for Gastric Cancer.
Article in Current oncology (Toronto, Ont.), 2022. 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.
- A novel prognostic model based on migrasome-related LncRNAs for gastric cancer.Scientific reports · 2025Article
- Analysis of gene polymorphisms in patients with pulmonary infections based on next-generation sequencing technology and their prognostic predictive value.Frontiers in medicine · 2025Article
- Cell-in-cell associated lncRNA signature predicts prognosis and immunotherapy response in gastric cancer.Frontiers in oncology · 2025Article
- In Silico Identification and Validation of Cuproptosis-Related LncRNA Signature as a Novel Prognostic Model and Immune Function Analysis in Colon Adenocarcinoma.Current oncology (Toronto, Ont.) · 2022Article
- Prognostic value of antitumor drug targets prediction using integrated bioinformatic analysis for immunogenic cell death-related lncRNA model based on stomach adenocarcinoma characteristics and tumor immune microenvironment.Frontiers in pharmacology · 2022Article
- Upregulation of OTX2-AS1 is Associated With Immune Infiltration and Predicts Prognosis of Gastric Cancer.Technology in cancer research & treatmentArticle
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Authors and funding
6 authors.
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Abstract
backgroundGastric cancer is a prevalent cause of tumor death. Tumor immunotherapy aims to reshape the specific immunity to tumors in order to kill the tumor. LncRNAs play a pivotal role in regulating the tumor immune microenvironment. Herein, immune-related lncRNAs were used to establish a prognosis risk-assessment model for gastric cancer and provide personalized predictions while providing insights and targets for gastric cancer treatment to enhance patient prognosis.
methodsGastric adenocarcinoma transcriptome and clinical data were acquired from the The Cancer Genome Atlas (TCGA) database to screen the immune-related lncRNAs. Then, LASSO COX regression was utilized to construct the prognosis risk-assessment model. Afterward, the reliability of the model was evaluated the relationship between immune infiltration, clinical characteristics, and the model was analyzed.
resultsWe identified 13 lncRNAs and constructed the prognosis assessment model. According to the median risk score of the training set, the patients were assigned to different risk groups. Overall survival time was shorter in the high-risk group. In the high-risk group, higher infiltration of mono-macrophages, dendritic cells, CD4+ T cells, and CD8+ T cells was observed. Moreover, the model was positively related to tumor metastasis.
conclusionThe prognosis risk-assessment model developed in this research can effectively predict the prognosis of gastric cancer patients. This tool is expected to be further applied to clinics in the future, thus providing a novel target for immunotherapy in gastric cancer patients.
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