Construction of mitochondrial quality regulation genes‐related prognostic model based on bulk‐RNA‐seq analysis in multiple myeloma

Abstract Mitochondrial quality regulation plays an important role in affecting the treatment sensitivity of multiple myeloma (MM). We aimed to develop a mitochondrial quality regulation genes (MQRGs)‐related prognostic model for MM patients. The Genomic Data Commons‐MM of bulk RNA‐seq, mutation, and single‐cell RNA‐seq (scRNA‐seq) dataset were downloaded, and the MQRGs gene set was collected previous study. “maftools” and CIBERSORT were used for mutation and immune‐infiltration analysis. Subsequently, the “ConsensusClusterPlus” was used to perform the unsupervised clustering analysis, “survminer” and “ssGSEA” R package was used for the Kaplan–Meier survival and enrichment analysis, “limma” R, univariate and Least Absolute Shrinkage and Selection Operator Cox were used for RiskScore model. The “timeROC” R package was used for Receiver Operating Characteristic Curve analysis. Finally, the “Seurat” R package was used for scRNA‐seq analysis. These MQRGs are mainly located on chromosome‐1,2,3,7, and 22 and had significant expression differences among age, gender, and stage groups, in which PPARGC1A and PPARG are the high mutation genes. Most MQRGs expression are closely associated with the plasma cells infiltration and can divide the patients into 2 different prognostic clusters (C1, C2). Then, 8 risk models were screened from 60 DEGs for RiskScore, which is an independent prognostic factor and effectively divided the patients into high and low risk groups with significant difference of immune checkpoint expression. Nomogram containing RiskScore can accurately predict patient prognosis, and a series of specific transcription factor PRDM1 and IRF1 were identified. We described the based molecular features and developed a high effective MQRGs‐related prognostic model in MM.