A telomere-related gene risk model for predicting prognosis and treatment response in acute myeloid leukemia.

ABSTRACT: Acute myeloid leukemia (AML) is a prevalent hematological malignancy among adults. Recent studies suggest that the length of telomeres could significantly affect both the risk of developing AML and the overall survival (OS). Despite the limited focus on the prognostic value of telomere-related genes (TRGs) in AML, our study aims at addressing this gap by compiling a list of TRGs from TelNet, as well as collecting clinical information and TRGs expression data through the Gene Expression Omnibus (GEO) database. The GSE37642 dataset, sourced from GEO and based on the GPL96 platform, was divided into training and validation sets at a 6:4 ratio. Additionally, the GSE71014 dataset (based on the GPL10558 platform), GSE12417 dataset (based on the GPL96 and GPL570 platforms), and another portion of

SUBMITTER: Shi HZ 

PROVIDER: S-EPMC11153201 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature