ArticlePloS one2025
Utilizing Multi-omics analysis to elucidate the role of mitochondrial gene defects in Gastric cancer progression.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Review
- Multi-omics investigation of benzo[a]pyrene in gastric cancer: comprehensive network toxicology, machine learning and molecular docking approaches.Molecular diversity · 2026Article
- The vesicle transport gene SEC23A is a novel prognostic indicator and therapeutic target in gastric cancer.Frontiers in oncology · 2026Article
- Exploring the regulatory mechanisms of paraptosis-related prognostic genes in gastric cancer using single-cell sequencing and transcriptome analysis.Scientific reports · 2025Article
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7 authors.
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Abstract
backgroundGastric cancer is a leading cause of cancer-related mortality worldwide, with poor survival outcomes despite advances in diagnostic and therapeutic methods. Mitochondrial autophagy, or mitophagy, is crucial for maintaining cellular homeostasis and has significant implications in tumor biology. DUSP1, a bispecific phosphatase regulating MAP kinase activity, has been associated with various cancers, but its role in GC remains unclear. MATERIALS AND
methodsIn order to gain a deeper understanding of gastric cancer cells, this study utilized bulk RNA-seq data from TCGA and GEO, combined with the MSigDB database, to screen for mitophagy-related genes. Univariate Cox regression and LASSO analysis were employed to further identify key mitophagy-related genes. Single-cell RNA sequencing data from the database was analyzed using Seurat software to investigate the mitochondrial autophagy genes in each candidate gastric tissue. To clarify the functional pathways involved, enrichment analysis and differential gene expression analysis were conducted. The characteristics of the immune microenvironment were assessed using the CIBERSORT R package. Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.
resultsWe identified eight prognostic genes-STX10, CDC37, VPS35, RCAN1, TRIM25, DUSP1, SEC23A, and GLT8D1-using LASSO-Cox regression analysis. RCAN1 and DUSP1 are strongly positively correlated, while DUSP1 is strongly negatively correlated with TRIM25, and CDC37 is strongly negatively correlated with SEC23A. By incorporating mitochondrial autophagy scores and clinical characteristics, we established a prognostic model that accurately predicts the 3-year survival status of gastric cancer (GC) patients. Additionally, our single-cell analysis identified DUSP1 as a key mitophagy-related gene. Functional studies demonstrated that DUSP1 knockdown significantly inhibits GC cell proliferation and migration.
conclusionIn this study, we developed a risk score based on eight mitochondrial autophagy-related genes and analyzed their expression across different cell types using single-cell analysis. DUSP1 stood out as a key player in gastric cancer progression, with higher expression in tumor tissues and a significant role in cell proliferation, apoptosis, and drug resistance. Our research also linked this risk score to tumor microenvironment immune cell infiltration and tumor mutational burden, revealing distinct high and low-risk groups in gastric cancer patients. This risk score holds potential for improving patient survival assessment and guiding personalized treatment, including enhancing immunotherapy efficacy.
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