A multi-omics prognostic model of cuproptosis affects the prognosis of stomach adenocarcinoma
Abstract Background Cuproptosis, a form of cell death associated with copper ions, has been linked to the pathogenesis of various cancers, including gastric cancer. Investigating the role of cuproptosis-related genes through multi-omics analysis can enhance our understanding of disease mechanisms an...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-06-01
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| Series: | Clinical Epigenetics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13148-025-01894-0 |
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| Summary: | Abstract Background Cuproptosis, a form of cell death associated with copper ions, has been linked to the pathogenesis of various cancers, including gastric cancer. Investigating the role of cuproptosis-related genes through multi-omics analysis can enhance our understanding of disease mechanisms and improve prognosis prediction. Objective This study aims to elucidate the role of cuproptosis-related genes in gastric cancer from a multi-omics perspective. Materials and Methods We utilized multi-omics sequencing data from TCGA and GEO databases to explore the relationships between cuproptosis genes and gastric carcinogenesis, clinical phenotypes, and prognosis. This analysis encompassed mutation, copy number variation, methylation, mRNA expression, alternative splicing, and APA alterations. Additionally, we examined the regulatory roles of cuproptosis genes in gastric cancer through ceRNA interactions, gene mutations, and DNA methylation. A multi-omics prognostic model for gastric cancer was subsequently constructed. Results Our findings revealed that CDKN2A was the most frequently mutated gene in gastric cancer. Overall mutations in cuproptosis genes and copy number alterations of PDHB significantly impacted gastric cancer prognosis. Methylation, alternative splicing, and APA alterations of CDKN2A also influenced patient outcomes. Notably, MTF1, a key gene in cuproptosis, was found to affect apoptosis and invasion in gastric cancer cell lines. Conclusion We successfully developed a multi-omics prognostic model for gastric cancer that offers significant predictive value for patient outcomes. |
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| ISSN: | 1868-7083 |