Fig 1.
Analysis process.
Fig 2.
Analysis Results of Mitophagy Genes Based on Multi-Omics.
A: The x-axis represents log2FoldChange, and the y-axis represents -log10 (P-value). Red nodes represent up-regulated differentially expressed genes, green nodes represent down-regulated differentially expressed genes, and gray nodes represent genes that are not significantly differentially expressed. B: Chromosomal Location of Mitophagy-Related Genes. C: Comparison of Differential Expression of Mitophagy-Related Genes between the Tumor Group and the Control Group. D: Waterfall Plot Illustrating Mutation Frequency of Mitophagy-Related Genes. E: Comprehensive Overview of Mutations Observed in TCGA-STAD Patients.
Fig 3.
Protein-Protein Interaction (PPI) and ceRNA Regulatory Network Analysis.
A. PPI Regulatory Network: This network provides detailed information about the nodes (proteins) within the network. The core gene set identified by MCODE is highlighted with a green box. B. Hub Gene Regulatory Network: This network was generated based on CytoHubba analysis. The intensity of red coloration reflects the CytoHubba score, with darker red nodes indicating higher hub roles within the network. C. ceRNA Regulatory Network: This network represents the competitive endogenous RNA (ceRNA) regulatory relationships. In this network, yellow nodes represent long non-coding RNAs (lncRNAs), blue nodes represent microRNAs (miRNAs), and green nodes represent messenger RNAs (mRNAs). Each color corresponds to a different type of RNA molecule. These networks collectively depict the protein interactions, hub gene roles, and ceRNA regulatory interactions, providing a comprehensive view of the molecular mechanisms underlying mitophagy-related gene regulation.
Fig 4.
LASSO-Cox Regression Analysis to Screen Prognosis-Related Genes.
A. In LASSO-Cox regression analysis, the chart illustrates the correlation (R) for each gene’s contribution to the regression synergy effect. Positive correlations are indicated by R > 0, while negative correlations are represented by R < 0. B. The y-axis shows the evaluation index corresponding to each λ value, with the optimal λ value highlighted. C. Correlation Analysis: Pearson correlation analysis was conducted among the expression values of the 8 mitophagy-related prognostic genes. This analysis reveals the degree of correlation between these genes. Notably, strong positive correlations are observed between RCAN1 and DUSP1 (R = 0. 49), while DUSP1 exhibits a negative correlation with TRIM25 (R = −0. 23), and CDC37 demonstrates a negative correlation with SEC23A (R = −0. 27). (p < 0. 05). These results provide valuable insights into the relationship between the selected genes and their potential influence on prognosis in the context of stomach adenocarcinoma.
Fig 5.
Prognostic Analysis of the Screened Mitophagy-Related Genes.
A: Based on the median expression of SEC23A, patients were divided into high and low expression groups, and survival curve analysis was performed. B: Similarly, based on the median expression of VPS35, survival curve analysis was conducted. C: For STX10, patients were categorized into high and low expression groups, followed by survival curve analysis. D: CDC37 expression levels were used to segregate patients into high and low expression groups for survival analysis. E: TRIM25’s median expression guided the classification of patients into high and low expression groups, followed by survival curve analysis. F: Similarly, for GLT8D1, patients were divided into high and low expression groups, and survival curve analysis was performed. G: Boxplot comparing the expression of DUSP1 between two risk groups in TCGA-STAD. H: Expression comparison of GLT8D1 between two risk groups in TCGA-STAD. I: Expression levels of RCAN1 in two risk groups of TCGA-STAD are depicted. J: Boxplot illustrating the expression of SEC23A in two risk groups of TCGA-STAD. K: Expression comparison of TRIM25 between two risk groups in TCGA-STAD. L: Expression levels of VPS35 in two risk groups of TCGA-STAD are shown. M: Boxplot depicting the expression of CDC37 in two risk groups of TCGA-STAD. N: Expression comparison of STX10 between two risk groups in TCGA-STAD. Note: In the Figs, “ns” indicates no significant difference (P > 0. 05), while asterisks represent statistical significance (*P < 0. 05, **P < 0. 01, ***P < 0. 001, ****P < 0. 0001). These analyses provide insights into the prognostic significance and expression patterns of the screened mitophagy-related genes in stomach adenocarcinoma (TCGA-STAD).
Fig 6.
Identification of the role of dusp1 in gastric cancer.
(A,C) The expression and distribution of major cell types;(B) cell-cell communication analysis; (D) The distribution of key mitophagy-related genes in many cell types.
Table 1.
Baseline data table.
Fig 7.
GO/KEGG Enrichment Analysis of Differentially Expressed Genes in High and Low-Risk Groups.
A. The Volcano Plot of Differentially Expressed Genes: The x-axis represents log2 fold change, while the y-axis represents -log10 (adjusted P-value). Up-regulated genes are depicted in red, and down-regulated genes are shown in blue. B. Bar Graph of GO and KEGG Enrichment Analysis: The y-axis represents -log10 (P-value), and the x-axis displays enriched GO terms and pathways. C. Heatmap of Differential Gene Expression: The x-axis lists gene names, while the y-axis represents sample groupings. Coloration indicates gene expression levels, with darker red indicating higher expression in the high-risk group and darker blue indicating lower expression. D. Chord Diagram for KEGG Enrichment Analysis: The left portion displays gene color blocks, with different colors representing corresponding logFC values. The right half showcases entry color blocks, with the size of each block indicating the corresponding counts (i. e. , the number of molecules included in this entry in the enrichment analysis). The connecting strings represent molecules contained within the entry. E. Circular Diagram for GO Enrichment Pathways: This diagram is divided into two parts, the inner circle, and the outer circle. Each column in the inner circle corresponds to an entry, with the column height indicating the relative size of p. adj. Higher values represent smaller p. adjust values for the ID. The filled color of each column represents the z-score value associated with the entry. These visualizations provide a comprehensive overview of the GO and KEGG enrichment analysis results, highlighting the significant pathways and gene expression patterns associated with high and low-risk groups in the context of gastric cancer. Additional information on GO enrichment analysis and KEGG enrichment analysis is provided in Table 2 and Table 3.
Table 2.
GO analysis.
Table 3.
KEGG analysis.
Fig 8.
GSEA Analysis of Differentially Expressed Genes in High and Low-Risk Groups.
A–E. Hill Plots of GSEA Analysis Results for TCGA-STAD High and Low-Risk Groups. In each plot, the x-axis represents the rank of the gene within the list of differentially expressed genes, with values greater than zero indicating up-regulation and values less than zero indicating down-regulation. The upper y-axis represents the enrichment score, while the lower y-axis shows the log-fold change (logFC) value. Each color corresponds to a specific pathway. Highlighted Pathways: C. MAPK Signaling Pathway (Fig 8C) E. PI3K- AKT Signaling Pathway (Fig 8E).
Table 4.
GSEA analysis.
Fig 9.
GSVA analysis of differentially expressed genes in high and low risk groups.
A-B. The complex numerical heat map (A) of the GSVA enrichment analysis results of DEGs between high and low risk groups in the TCGA-STAD dataset, and the group comparison map display (B). (ns: P > 0. 05, *P < 0. 05, **P < 0. 01, ***P < 0. 001, ****P < 0. 0001). TCGA: The cancer genome atlas; STAD-Stomach cancer; DEGs: differentially expressed genes; GSVA: Gene Set Variation Analysis.
Fig 10.
Differences in Immune Signatures Between High and Low-Risk Groups.
A. Stacked Diagram of Immune Cell Content in the Tumor Group: Different colors represent distinct immune cell types, and the horizontal axis corresponds to patient IDs. B,D. Box Plots of Immune Cells and Immune Checkpoint Genes in High- and Low-Risk Groups: Yellow represents high-risk group samples, while cyan represents low-risk group samples. C, E. Comparison Graphs of TMB and MSI Values Between High and Low-Risk Groups: TMB (tumor mutational burden) and MSI (microsatellite instability) values are displayed. In all panels, statistical significance is indicated as follows: ns (not significant, p > 0. 05), *p < 0. 05, **p < 0. 01, ***p < 0. 001, ****p < 0. 0001. These Figs illustrate the differences in immune cell infiltration, immune checkpoint gene expression, TMB, and MSI values between high and low-risk groups, providing valuable insights into the immune signatures associated with gastric cancer patients in distinct risk categories.
Fig 11.
Effect of Mitophagy Score on Immunotherapy for Different Datasets.
A, B. Heat maps depicting correlation analysis results between Risk score and immune infiltrating cells, scored using the ssGSEA algorithm and Cibersort algorithm, respectively. The horizontal axis represents various immune infiltrating cells, while the vertical axis represents different datasets. The intensity of the red grid color indicates the strength of the correlation between genes and immune cells, with ‘*’ indicating statistical significance. In both panels, statistical significance is denoted as follows: ns (not significant, p > 0. 05), *p < 0. 05, **p < 0. 01, ***p < 0. 001, ****p < 0. 0001. These heat maps illustrate the correlation between Risk score and immune infiltrating cells, providing insights into the potential impact of Mitophagy Score on immunotherapy across different datasets.
Fig 12.
Prognostic Correlation Analysis of Different Risk Factors in GC.
A. Forest plots displaying risk score, age, and gender in TCGA-STAD, demonstrating proportional hazards (HR) and P-value (C). B-E. Survival curves depicting high-risk and low-risk groups (B), age (C), stage TN (D-E) in TCGA-STAD.
Fig 13.
Nomogram and DCA Analysis of Prognostic Assessment.
A. Prediction of gastric cancer survival status based on the combination of various factors in the risk score. B-D. Decision curve analysis (DCA) predicting 1-, 3-, and 5-year survival rates for the TCGA-STAD dataset. The x-axis represents the probability threshold or threshold probability (Threshold Probability), while the y-axis represents net benefit. DCA: Decision Curve Analysis. This Fig presents the nomogram for predicting gastric cancer survival and the results of decision curve analysis (DCA) for assessing the clinical utility of the prognostic model at 1, 3, and 5 years in the TCGA-STAD dataset.
Fig 14.
DUSP1 expression and effect on proliferation and migration in GC.
A. Immunohistochemistry detection of the DUSP1 in the GC and normal adjacent tissue. B-C. Knockdown of DUSP1 in GC cells and validated the efficiency of si-DUSP1 and si-Control (NC) transfection in GC cells proliferation by qPCR. D-E. Knockdown of DUSP1 in GC cells and validated the efficiency of si-DUSP1 and si-Control (NC) transfection in GC cells proliferation by CCK-8. F. Wound healing assays of cell migration in GC cells. The images of wound closure are presented at the indicated number of hours after scratching (0, 24 h). G. Transwell assays were performed to examine the potential migration of si-DUSP1 cells or negative control cells. H. Colony formation assay were performed to examine proliferation of si-DUSP1 cells and si-NC of GC. Additional information is in S1 File.