The role of the mitochondrial ribosomal protein family in detecting hepatocellular carcinoma and predicting prognosis, immune features, and drug sensitivity

Background Hepatocellular carcinoma (HCC) is one of the most common types of malignant tumors, with a slow onset, rapid progression, and frequent recurrence. Previous research has implicated mitochondrial ribosomal genes in the development, metastasis, and prognosis of various cancers. However, further research is necessary to establish a link between mitochondrial ribosomal protein (MRP) family expression and HCC diagnosis, prognosis, ferroptosis-related gene (FRG) expression, m6A modification-related gene expression, tumor immunity, and drug sensitivity. Methods Bioinformatics resources were used to analyze data from patients with HCC retrieved from the TCGA, ICGC, and GTEx databases (GEPIA, UALCAN, Xiantao tool, cBioPortal, STRING, Cytoscape, TISIDB, and GSCALite). Results Among the 82 MRP family members, 14 MRP genes (MRPS21, MRPS23, MRPL9, DAP3, MRPL13, MRPL17, MRPL24, MRPL55, MRPL16, MRPL14, MRPS17, MRPL47, MRPL21, and MRPL15) were significantly upregulated differentially expressed genes (DEGs) in HCC tumor samples in comparison to normal samples. Receiver-operating characteristic curve analysis indicated that all 14 DEGs show good diagnostic performance. Furthermore, TCGA analysis revealed that the mRNA expression of 39 MRPs was associated with overall survival (OS) in HCC. HCC was divided into two molecular subtypes (C1 and C2) with distinct prognoses using clustering analysis. The clusters showed different FRG expression and m6A methylation profiles and immune features, and prognostic models showed that the model integrating 5 MRP genes (MRPS15, MRPL3, MRPL9, MRPL36, and MRPL37) and 2 FRGs (SLC1A5 and SLC5A11) attained a greater clinical net benefit than three other prognostic models. Finally, analysis of the CTRP and GDSC databases revealed several potential drugs that could target prognostic MRP genes (AU)

The role of the mitochondrial ribosomal protein family in detecting hepatocellular carcinoma and predicting prognosis, immune features, and drug sensitivity.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common types of malignant tumors, with a slow onset, rapid progression, and frequent recurrence. Previous research has implicated mitochondrial ribosomal genes in the development, metastasis, and prognosis of various cancers. However, further research is necessary to establish a link between mitochondrial ribosomal protein (MRP) family expression and HCC diagnosis, prognosis, ferroptosis-related gene (FRG) expression, m6A modification-related gene expression, tumor immunity, and drug sensitivity. METHODS: Bioinformatics resources were used to analyze data from patients with HCC retrieved from the TCGA, ICGC, and GTEx databases (GEPIA, UALCAN, Xiantao tool, cBioPortal, STRING, Cytoscape, TISIDB, and GSCALite). RESULTS: Among the 82 MRP family members, 14 MRP genes (MRPS21, MRPS23, MRPL9, DAP3, MRPL13, MRPL17, MRPL24, MRPL55, MRPL16, MRPL14, MRPS17, MRPL47, MRPL21, and MRPL15) were significantly upregulated differentially expressed genes (DEGs) in HCC tumor samples in comparison to normal samples. Receiver-operating characteristic curve analysis indicated that all 14 DEGs show good diagnostic performance. Furthermore, TCGA analysis revealed that the mRNA expression of 39 MRPs was associated with overall survival (OS) in HCC. HCC was divided into two molecular subtypes (C1 and C2) with distinct prognoses using clustering analysis. The clusters showed different FRG expression and m6A methylation profiles and immune features, and prognostic models showed that the model integrating 5 MRP genes (MRPS15, MRPL3, MRPL9, MRPL36, and MRPL37) and 2 FRGs (SLC1A5 and SLC5A11) attained a greater clinical net benefit than three other prognostic models. Finally, analysis of the CTRP and GDSC databases revealed several potential drugs that could target prognostic MRP genes. CONCLUSION: We identified 14 MRP genes as HCC diagnostic markers. We investigated FRG and m6A modification-related gene expression profiles and immune features in patients with HCC, and developed and validated a model incorporating MRP and FRG expression that accurately and reliably predicts HCC prognosis and may predict disease progression and treatment response.