Integrated gene-metabolite association network analysis reveals key metabolic pathways in gastric adenocarcinoma
Gastric adenocarcinoma is one of the most death cause cancers worldwide. Metabolomics is an effective approach for investigating the occurrence and progression of cancer and detecting prognostic biomarkers by studying the profiles of small bioactive molecules. To fully decipher the functional roles of the disrupted metabolites that modulate the cellular mechanism of gastric cancer, integrated gene-metabolite association network methods are critical to map the associations between metabolites and genes. In this study, we constructed a knowledge-based gene-metabolite association network of gastric cancer using the dysregulated metabolites and genes between gastric cancer patients and control group. The topological pathway analysis and gene-protein-metabolite-disease association analysis revealed four key gene-metabolite pathways which include eleven metabolites associated with modulated genes. The integrated gene-metabolite association network enables mechanistic investigation and provides a comprehensive overview regarding the investigation of molecular mechanisms of gastric cancer, which facilitates the in-depth understanding of metabolic biomarker roles in gastric cancer.
Authors
- Jie Chai (ORCID: https://orcid.org/0000-0002-7705-2402)
- Botao Xu
- Yuying Shi (ORCID: https://orcid.org/0000-0002-3048-7871)
- Qitao Chen (ORCID: https://orcid.org/0000-0001-9259-179X)
- Chuang Yuan
- Zhe Wang (ORCID: https://orcid.org/0000-0002-9092-6143)
- Cheng Wang (ORCID: https://orcid.org/0000-0001-8135-4473)
Institutions
- Shandong University (CN)
- Peking University (CN)
- Shandong Tumor Hospital (CN)
- National Science Library (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Heliyon
- Published
- 2024-08-30
- DOI
- https://doi.org/10.1016/j.heliyon.2024.e37156
- Citations
- 2
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.47
Funders
- Shandong University