Identification of memory B cell-associated miRNA signature to establish a prognostic model in gastric adenocarcinoma

Abstract

Abstract Background Memory B cells and microRNA (miRNA) play important roles in the progression of gastric adenocarcinoma (STAD). However, there are few studies on utility of memory B cell-associated miRNAs for prognosis of STAD. Methods We identified the marker genes of memory B cells by single-cell RNA sequencing (scRNA-seq) and identified the miRNAs associated with memory B cells by constructing an mRNA-miRNA co-expression network. Then, univariate Cox, random survival forest (RSF), and stepwise multiple Cox regression (StepCox) algorithms were used to identify memory B cell-associated miRNAs that were significantly related to overall survival (OS). A prognostic risk model was constructed and validated using these miRNAs, and patients were divided into a low-risk group and a high-risk group. In addition, the differences in clinicopathological features, tumour microenvironment, immune blocking therapy, and sensitivity of anticancer drugs in the two high versus low risk groups were analyzed. Results Four memory B cell-associated miRNAs (hsa-mir-145, hsa-mir-125b-2, hsa-mir-100, hsa-mir-221) with significantly correlation to OS were identified and used to construct a prognostic model. Time-dependent receiver operating characteristic (ROC) curve analysis confirmed the feasibility of the model. Kaplan-Meier (K-M) survival curve analysis showed that the prognosis was poor in the high-risk group. The comprehensive analysis showed that the patients in the high-risk group have higher immune scores, matrix scores, immune cell infiltration, and poor effect of immune response. In addition, in terms of drug screening, we predicted eight drugs with higher sensitivity in the high-risk group, of which CGP-60474 was the most sensitive. Conclusions In summary, we identified memory B cell-associated miRNAs prognostic features and constructed a novel risk model for STAD based on scRNA-seq data and bulk RNA-seq data. Patients in the high-risk group showed the highest sensitivity to GCP-60474. This study provides prognostic insights for individualized and accurate treatment of STAD patients.