Machine learning models predict the mTOR signal pathway-related signature in the gastric cancer involving 2063 samples of 7 centers.

ABSTRACT: Gastric cancer, as a tumor with poor prognosis, has been widely studied. Distinguishing the types of gastric cancer is helpful. Using the transcriptome data of gastric cancer in our study, relevant proteins of mTOR signaling pathway were screened to identify key genes by four machine learning models, and the models were validated in external datasets. Through correlation analysis, we explored the relationship between five key genes and immune cells and immunotherapy. By inducing cellular senescence in gastric cancer cells with bleomycin, we investigated changes in the expression levels of HRAS through western blot. By PCA clustering analysis, we used the five key genes for gastric cancer typing and explored differences in drug sensitivity and enrichment pathways between different clusterin

SUBMITTER: Zhang H 

PROVIDER: S-EPMC10373976 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature