An anoikis-related gene signature predicts prognosis in patients with acute myeloid leukemia and immunotherapy.

ABSTRACT: Acute myeloid leukemia (AML) is a malignant blood disorder and the most common type of acute leukemia in adults. Notwithstanding the plethora of therapeutic modalities, a significant cohort of patients fail to respond to treatment and experience relapse. Anoikis, a distinct modality of programmed cell death, has been linked to cancer progression. However, the prognostic significance of anoikis in AML remains unclear. In this study, a non-negative matrix factorization algorithm was utilized to efficiently reduce the dimensions of merged datasets. We used differential analysis, weighted gene co-expression network analysis (WGCNA), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression to identify genes associated with prognosis and develop a risk sc

SUBMITTER: Xu R 

PROVIDER: S-EPMC11626272 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature