{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["12"],"submitter":["Yang J"],"pubmed_abstract":["<h4>Background</h4>Stomach adenocarcinoma (STAD) arises from the mutations of stomach cells and has poor overall survival. Chemotherapy is commonly indicated for patients with stomach cancer following surgical resection. The most prevalent alteration that affects cancer growth is N6-methyladenosine methylation (m6A), although the possible function of m6A in STAD prognosis is not recognized.<h4>Method</h4>The research measured predictive FRGs in BLCA samples from the TCGA and GEO datasets. Data on the stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and corresponding clinical characteristics were obtained from TCGA and GEO. STAD from TCGA and GEO at 24 m6A was investigated. Lasso regression was used to construct the prediction model to as"],"journal":["Frontiers in oncology"],"pagination":["1050288"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9814967"],"repository":["biostudies-literature"],"pubmed_title":["Constructing and validating of m6a-related genes prognostic signature for stomach adenocarcinoma and immune infiltration: Potential biomarkers for predicting the overall survival."],"pmcid":["PMC9814967"],"pubmed_authors":["Wu Z","Xia X","Yang J","Zeng J","Chen S","Wu X"],"additional_accession":[]},"is_claimable":false,"name":"Constructing and validating of m6a-related genes prognostic signature for stomach adenocarcinoma and immune infiltration: Potential biomarkers for predicting the overall survival.","description":"<h4>Background</h4>Stomach adenocarcinoma (STAD) arises from the mutations of stomach cells and has poor overall survival. Chemotherapy is commonly indicated for patients with stomach cancer following surgical resection. The most prevalent alteration that affects cancer growth is N6-methyladenosine methylation (m6A), although the possible function of m6A in STAD prognosis is not recognized.<h4>Method</h4>The research measured predictive FRGs in BLCA samples from the TCGA and GEO datasets. Data on the stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and corresponding clinical characteristics were obtained from TCGA and GEO. STAD from TCGA and GEO at 24 m6A was investigated. Lasso regression was used to construct the prediction model to as","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2026-05-28T03:49:55.194Z","creation":"2025-04-06T14:10:54.996Z"},"accession":"S-EPMC9814967","cross_references":{"pubmed":["36620557"],"doi":["10.3389/fonc.2022.1050288"]}}