Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer

Abstract

Background. Increasing 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. Methods. An 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. Results. The 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. Conclusion. In 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.

Prognostic value of nicotinamide adenine dinucleotide (NAD+) metabolic genes in patients with stomach adenocarcinoma based on bioinformatics analysis

“…Mutations in TTN , the gene encoding giant myofilament titin, cause familial dilated cardiomyopathy ( 45 ). Study has shown that patients with a high frequency of TTN mutations have a better prognosis, which is similar to our results ( 46 ). Yang et al found that TTN mutations were effective in predicting GC prognosis, tumor mutation burden (TMB), and immunotherapy response ( 47 ).…”

PLK4 initiates crosstalk between cell cycle, cell proliferation and macrophages infiltration in gliomas

“…We used the "Gene" module of SangerBox (6), a web-based program (http://www.sangerbox.com), to examine the mRNA expression levels of PLK4 in different tumor and normal tissues as reported by TCGA and performed an integrated analysis of the TCGA (7) and GTEx (8) databases. Furthermore, several TCGA tumors were analyzed using the "Pathological Stage Plot" module of GEPIA2.…”

Overview of MicroRNAs as Diagnostic and Prognostic Biomarkers for High-Incidence Cancers in 2021

“…Similarly, Liu et al also constructed the GI-related miRNAs signature (GIMiSig) for predicting the survival rate of GC patients based on eight miRNAs, and compared it with the current clinically commonly used cancer staging methods. As a result, GIMiSig achieved a better prediction effect on the survival rate of GC patients [ 86 ]. In addition, Qi et al built a risk scoring formula based on three miRNAs including miRNA-126-3p, miRNA-143-5p, and miRNA-1275, which was verified and might be used to predict the prognosis of GC patients [ 87 ].…”