Table1_Cellular Senescence-Related Genes: Predicting Prognosis in Gastric Cancer.DOCX
Our study aimed to explore the effect of cellular senescence and to find potential therapeutic strategies for gastric cancer. Cellular senescence-related genes were acquired from the CellAge database, while gastric cancer data were obtained from GEO and TCGA databases. SMARCA4 had the highest mutation frequency (6%), and it was linked to higher overall survival (OS) and progression-free survival (PFS). The gastric cancer data in TCGA database served as a training set to construct a prognostic risk score signature, and GEO data were used as a testing set to validate the accuracy of the signature. Patients with the low-risk score group had a longer survival time, while the high-risk score group is the opposite. Patients with low-risk scores had higher immune infiltration and active immune-related pathways. The results of drug sensitivity analysis and the TIDE algorithm showed that the low-risk score group was more susceptible to chemotherapy and immunotherapy. Most patients with mutation genes had a lower risk score than the wild type. Therefore, the risk score signature with cellular senescence-related genes can predict gastric cancer prognosis and identify gastric cancer patients who are sensitive to chemotherapy and immunotherapy.
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Categories
- Gene and Molecular Therapy
- Gene Expression (incl. Microarray and other genome-wide approaches)
- Genetics
- Genetically Modified Animals
- Livestock Cloning
- Developmental Genetics (incl. Sex Determination)
- Epigenetics (incl. Genome Methylation and Epigenomics)
- Biomarkers
- Genomics
- Genome Structure and Regulation
- Genetic Engineering
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