ArticleJournal of immunology research2021
Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer.
Article in Journal of immunology research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The role of microRNAs in gastritis, intestinal metaplasia, and gastric cancer: a narrative review.Translational cancer research · 2025Review
- Ubiquilin-4 induces immune escape in gastric cancer by activating the notch signaling pathway.Cellular oncology (Dordrecht, Netherlands) · 2024Article
- Prognostic value of nicotinamide adenine dinucleotide (NADJournal of gastrointestinal oncology · 2022Article
- Overview of MicroRNAs as Diagnostic and Prognostic Biomarkers for High-Incidence Cancers in 2021.International journal of molecular sciences · 2022Review
- PLK4 initiates crosstalk between cell cycle, cell proliferation and macrophages infiltration in gliomas.Frontiers in oncology · 2022Article
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Authors and funding
6 authors.
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Abstract
backgroundIncreasing evidence suggests that microRNAs (miRNAs) are involved in genome instability (GI) and drive the occurrence of tumors. However, the role of GI-related miRNAs in gastric cancer (GC) remains largely unknown. Herein, we developed a novel GI-related miRNA signature (GIMiSig) and further investigated its role in prognosis, the immune landscape, and immunotherapy responses in GC patients.
methodsAn analysis of somatic mutation data on 434 gastric cancer cases from The Cancer Genome Atlas (TCGA) database was performed, thereby generating genome stability (GS) and GI groups. By detecting differentially expressed miRNAs between the GS and GI groups that were associated with overall survival, 8 miRNAs were identified and used to construct the GIMiSig.
resultsThe GIMiSig showed high accuracy in detecting GC patients. Using GIMiSig to stratify the patients into the high- and low-risk subgroups to predict survival outperformed the use of regular clinical features such as age, gender, or disease stage. Patients with low risk had a more favorable survival time than those with high risk. More importantly, the high-risk patients were associated with decreased UBQLN4 expression, higher accumulation of immune cells, lower Titin (TTN) mutation frequency, worse immunotherapy efficacy, and cancer-associated pathways. Conversely, the low-risk patients were characterized by UBQLN4 overexpression, lower fraction of immune cells, higher TTN mutation frequency, better response to immunotherapy, and GI-related pathways.
conclusionIn summary, we constructed a novel GIMiSig that could stratify GC patients into distinct risk groups that have different survival outcomes and immunotherapy efficacy. The results may provide new clues for improving GC outcomes.
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