ArticleCurrent medicinal chemistry2024
A Five-gene Signature based on MicroRNA for Predicting Prognosis and Immunotherapy in Stomach Adenocarcinoma.
Article in Current medicinal chemistry, 2024. 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.
- Exploring the Functional and Prognostic Significance of miR-217 in Uterine Corpus Endometrial Carcinoma.Current medicinal chemistry · 2026Article
- Vitamin D-regulated miRNA expression in tumoral and normal adjacent tissue of localized gastric cancer patients: the impact on survival and time to relapse.Translational cancer research · 2025Article
- Construction of a PANoptosis-related Prognostic Signature for Predicting Prognosis, Tumor Microenvironment, and Immune Response in Ovarian Cancer.Current medicinal chemistry · 2025Article
- Development of Novel PANoptosis-Related Gene Signatures to Predict the Prognosis of Patients With Stomach Adenocarcinoma.Human mutation · 2025Article
- A New Medical Evaluation for Gastric Cancer Patients to Increase the Success Rate of Immunotherapy: A 2024 Update.Pharmaceuticals (Basel, Switzerland) · 2024Review
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9 authors.
Funding
Abstract
aimsWe aimed to classify molecular subtypes and establish a prognostic gene signature based on miRNAs for the prognostic prediction and therapeutic response in Stomach adenocarcinoma (STAD).
backgroundSTAD is a common diagnosed gastrointestinal malignancy and its heterogeneity is a big challenge that influences prognosis and precision therapies. Present study was designed to classify molecular subtypes and construct a prognostic gene signature based on miRNAs for the prognostic prediction and therapeutic response in STAD.
objectiveThe objective of this study is to investigate the molecular subtypes and prognostic model for STAD.
methodsA STAD specific miRNA-messenger RNA (mRNA) competing endogenous RNA (ceRNA) network was generated using the RNA-Seq and miRNA expression profiles from The Cancer Genome Atlas (TCGA) database, in which miRNA-related mRNAs were screened. Molecular subtypes were then determined using miRNA-related genes. Through univariate Cox analysis and multivariate regression analysis, a prognostic model was established in GSE84437 Train dataset and validated in GSE84437 Test, TCGA, GSE84437 and GSE66229 datasets. Immunotherapy datasets were employed for assessing the performance of the risk model. Finally, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was applied to validate the expression of hub genes used for the risk score signature.
resultsWe constructed a ceRNA network containing 84 miRNAs and 907 mRNAs and determined two molecular subtypes based on 26 genes from the intersection of TCGASTAD and GSE84437 datasets. Subtype S2 had poor prognosis, lower tumor mutational burden, higher immune score and lower response to immunotherapy. Subtype S1 was more sensitive to Sorafenib, Pyrimethamine, Salubrinal, Gemcitabine, Vinorelbine and AKT inhibitor VIII. Next, a five-gene signature was generated and its robustness was validated in Test and external datasets. This risk model also had a good prediction performance in immunotherapy datasets.
conclusionThis study promotes the underlying mechanisms of miRNA-based genes in STAD and offers directions for classification. A five-gene signature accurately predicts the prognosis and helps therapeutic options.
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