ArticleBMC genomic data2022
Identification of metabolism-related genes for predicting peritoneal metastasis in patients with gastric cancer.
Article in BMC genomic data, 2022. 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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Who cites it
4 citing papers in PubMed.
- Elucidation of population stratifying markers and selective sweeps in crossbred Landlly pig population using genome-wide SNP data.Mammalian genome : official journal of the International Mammalian Genome Society · 2024Article
- Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients.Molecular biotechnology · 2023Article
- Gastric cancer peritoneal metastasis related signature predicts prognosis and sensitivity to immunotherapy in gastric cancer.Journal of cellular and molecular medicine · 2023Article
- Discovery of CDK signature and CDK5 as potential biomarkers for predicting prognosis and immunotherapeutic response in gastric cancer peritoneal metastases.American journal of cancer research · 2023Article
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Authors and funding
9 authors.
Funding
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Abstract
objectiveThe reprogramming of metabolism is an important factor in the metastatic process of cancer. In our study, we intended to investigate the predictive value of metabolism-related genes (MRGs) in recurrent gastric cancer (GC) patients with peritoneal metastasis.
methodsThe sequencing data of mRNA of GC patients were obtained from Asian Cancer Research Group (ACRG) and the GEO databases (GSE53276). The differentially expressed MRGs (DE-MRGs) between a cell line without peritoneal metastasis (HSC60) and one with peritoneal metastasis (60As6) were analyzed with the Limma package. According to the LASSO regression, eight MRGs were identified as crucially related to peritoneal seeding recurrence in patients. Then, disease free survival related genes were screened using Cox regression, and a promising prognostic model was constructed based on 8 MRGs. We trained and verified it in two independent cohort.
resultsWe confirmed 713 DE-MRGs and the enriched pathways. Pathway analysis found that the MRG-related pathways were related to tumor metabolism development. With the help of Kaplan-Meier analysis, we found that the group with higher risk scores had worse rates of peritoneal seeding recurrence than the group with lower scores in the cohorts.
conclusionsThis study developed an eight-gene signature correlated with metabolism that could predict peritoneal seeding recurrence for GC patients. This signature could be a promising prognostic model, providing better strategy in treatment.
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