Methionyl-tRNA synthetase 1 participates in hepatocellular carcinoma and its regulated gene profile possesses potent prognostic ability

Figure 1 MARS1 is a key gene associated with hepatocellular carcinoma. A: Flow chart illustrating the study design and workflow; B: Visualization of differentially expressed genes (DEGs) in hepatocellular carcinoma (HCC) compared to adjacent normal tissue; C: Mutation analysis and Kaplan-Meier survival curves based on DEGs identified in panel (B); D: Differential expression of MARS1 in HCC and normal tissue; E and F: Western blot (E) and Immunohistochemistry (F) showing MARS1 expression in HCC and normal liver tissues. Student’s t-test was used to compare differences between two groups. ^aP < 0.05; ^bP < 0.01; ^cP < 0.001. TCGA: The Cancer Genome Atlas; HCC: Hepatocellular carcinoma; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes.

Figure 2 MARS1 promotes the proliferation, migration, invasion, and tumor formation of hepatocellular carcinoma cells. A: Protein expression levels of MARS1 in LM3 and Huh7 cells transiently transfected with siRNA-NC and siRNA-MARS1; B: Cell viability of LM3 and Huh7 cells measured by CCK-8 assay; C: Cell proliferation of LM3 and Huh7 cells examined by EdU assay; D: Cell cycle distribution of LM3 and Huh7 cells examined by cell cycle assays; E and F: Cell migration and invasion of LM3 and Huh7 cells assessed by Transwell migration and Matrigel invasion assays; G: Impact of MARS1 suppression in LM3 and Huh7 cells on subcutaneous tumor growth. The weight of tumors was measured following euthanasia of the mice (n = 5); H: Tumor volumes were recorded every 3 days (n = 5). Student’s t-test was used to compare differences between two groups, while one-way analysis of variance was applied for comparisons among more than two groups. ^aP < 0.05; ^bP < 0.01; and ^cP < 0.001.

Figure 3 Visualization of differential MARS1-related genes. A: Volcano plot showing differential expression of MARS1-related genes between MARS1-mutated and wild-type patients with hepatocarcinoma. Genes with significant differential expression are represented by dots; B: Heatmap illustrating the expression patterns of differential MARS1-related genes; C and D: LASSO regression analysis identifies the optimal lambda value associated with the 10 prognostic genes significantly linked to overall survival; E: Forest plot of multivariate Cox regression analysis for 10 genes, depicting hazard ratios and their 95% confidence intervals.

Figure 4 Evaluation and verification of MRPS in The Cancer Genome Atlas and GSE14520. A and B: Kaplan–Meier curves illustrating the overall survival (OS) of patients classified into high and low MRPS groups in The Cancer Genome Atlas (TCGA)-hepatocellular carcinoma (HCC) (A) and GSE14520 (B); C and D: Receiver operating characteristic (ROC) curves showing the predictive performance of MRPS for 1-, 3-, and 5-year OS in the TCGA-HCC (C) and GSE14520 (D); E and F: Scatter plot of the risk score, OS, and corresponding heatmap based on MRPS in the TCGA (E) and GSE14520 (F). TCGA: The Cancer Genome Atlas; ROC: Receiver operating characteristic.

Figure 5  Kaplan-Meier curves illustrating overall survival differences between high-MRPS and low-MRPS groups across various clinical subgroups.

Figure 6 MRPS is an independent prognostic factor of hepatocellular carcinoma. A: Univariate Cox analysis revealed associations between clinical factors and risk scores. Significant associations were observed for the pathological stage, T stage, and MRPS; B: Multivariate Cox analysis confirmed MRPS as an independent prognostic factor, indicating its importance in predicting hepatocellular carcinoma prognosis; C: Receiver operating characteristic curves were utilized to assess the predictive accuracy of MRPS, compared to age, sex, grade, stage, T, N, M. AUC: Area under the curve.

Figure 7 Construction and evaluation of a prognostic nomogram. A: Prognostic nomogram integrating clinical factors and MRPS values for individualized prognostic assessment; B: Calibration plots predicting recurrence at 1, 3, and 5 years. Gray dashed lines represent the ideal predictions. OS: Overall survival.

Figure 8 Identification of different MRPS groups differentially expressed genes and functional enrichment analysis. A: Volcano plots showing 808 differentially expressed genes (DEGs) between different MRPS groups; B: Heatmap illustrating the expression patterns of the 808 DEGs between high and low MRPS patients; C: Gene Ontology enrichment analysis displaying the biological processes, cell components, and molecular functions associated with MARS1-related genes; D: Kyoto Encyclopedia of Genes and Genomes pathways analysis highlighting the pathways enriched in MARS1-related genes, including complement and coagulation cascades, cell cycle, xenobiotic metabolism by cytochrome P450, and bile secretion.

Figure 9 Comparison of immune microenvironment between different MRPS subgroups. A: Panel illustrates the comparison of immune cell infiltration between different MRPS groups, showing differential levels of various immune cell types; B: Panel depicts the immune checkpoint analysis in high and low MRPS groups; C: Panel displays the differential expression of PD-L1 in high and low MRPS groups; D: Panel illustrates the differential microsatellite instability levels in high and low MRPS groups. ^aP < 0.05, ^bP < 0.01, and ^cP < 0.001.

Figure 10  Association of MRPS groups with multiple chemotherapy drug sensitivities. ^aP < 0.001.