Assessment tool based on fatty acid metabolic signatures for predicting the prognosis and treatment response in bladder cancer.

ABSTRACT:

Background

Fatty acid metabolism (FAM) is closely connected with tumorigenesis as well as disease progression and affects the efficacy of platinum-based drugs. Exploring biomarkers related to FAM in bladder cancer (BLCA) is essential to improve cancer prognosis.

Methods

High-throughput sequencing data from The Cancer Genome Atlas (TCGA) were bioinformatically resolved to identify molecular subtypes of fatty acid metabolic profiles in BLCA using coherent clustering analysis. Based on fatty acid metabolic profile, a prognostic model was created using COX and LASSO COX models. CIBERSORT, Estimation of STromal and Immune cells in MAlignant Tumours using Expression (ESTIMATE), MCP-Count, and single sample gene set enrichment analysis (ssGSEA) were used to assess the differences i

SUBMITTER: Chen X 

PROVIDER: S-EPMC10703629 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature