ArticleFrontiers in genetics2022
A Novel Risk Model Identified Based on Pyroptosis-Related lncRNA Predicts Overall Survival and Associates With the Immune Landscape of GC Patients.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Long Non-Coding RNAs in Drug Resistance of Gastric Cancer: Complex Mechanisms and Potential Clinical Applications.Biomolecules · 2024Review
- Cell death affecting the progression of gastric cancer.Cell death discovery · 2022Review
- Risk Model and Immune Signature of m7G-Related lncRNA Based on Lung Adenocarcinoma.Frontiers in genetics · 2022Article
- Noncoding RNA-mediated regulation of pyroptotic cell death in cancer.Frontiers in oncology · 2022Review
- Targeted Pyroptosis Is a Potential Therapeutic Strategy for Cancer.Journal of oncology · 2022Review
- Identification of pyroptosis-related lncRNA signature and AC005253.1 as a pyroptosis-related oncogene in prostate cancer.Frontiers in oncology · 2022Article
- A prognostic signature of pyroptosis-related lncRNAs verified in gastric cancer samples to predict the immunotherapy and chemotherapy drug sensitivity.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastric cancer (GC) is one of the most common malignant gastrointestinal tumors worldwide. Pyroptosis was widely reported to exert a crucial function in tumor development. In addition, pyroptosis was also proved to be associated with the immune landscape. However, whether pyroptosis-related lncRNAs are associated with the prognosis and the immune landscape of GC remains unclear. In the present study, we first constructed a novel risk model by using pyroptosis-related lncRNAs. We identified 11 pyroptosis-related lncRNAs for the establishment of the risk model. The risk model could be used to predict the survival outcome and immune landscape of GC patients. The results of survival analysis and AUC value of a time-related ROC curve proved that our risk model has an elevated efficiency and accuracy in predicting the survival outcome of patients. We also found that the risk model was also associated with the immune landscape, drug sensitivity, and tumor mutation burden of GC patients. In conclusion, our risk model plays a crucial role in the tumor immune microenvironment and could be used to predict survival outcomes of GC patients.
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