Ferroptosis-based molecular prognostic model for adrenocortical carcinoma based on least absolute shrinkage and selection operator regression.

ABSTRACT:

Background

This study aimed to find ferroptosis-related genes linked to clinical outcomes of adrenocortical carcinoma (ACC) and assess the prognostic value of the model.

Methods

We downloaded the mRNA sequencing data and patient clinical data of 78 ACC patients from the TCGA data portal. Candidate ferroptosis-related genes were screened by univariate regression analysis, machine-learning least absolute shrinkage, and selection operator (LASSO). A ferroptosis-related gene-based prognostic model was constructed. The effectiveness of the prediction model was accessed by KM and ROC analysis. External validation was done using the GSE19750 cohort. A nomogram was generated. The prognostic accuracy was measured and compared with conventional staging systems (TNM stage). Functional

SUBMITTER: Lin C 

PROVIDER: S-EPMC9169198 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature