A Novel Cuproptosis-Related Gene Signature can Predict Prognosis in Acute Myeloid Leukemia: Bioinformatics Analysis and Experimental Validation

Abstract

Background: Acute myeloid leukemia (AML) is the most common type of leukemia that has a poor prognosis. Biomarkers and effective treatments for AML are still under research. Cuproptosis is a type of copper-dependent programmed cell death that has been linked to cancer progression. However, the clinical impacts of cuproptosis-related genes (CRGs) remain unclear. Purpose: This study aimed to evaluate the potential role of CRGs to prognose AML. Methods: It was examined the expression of 14 CRGs, and a 3-gene risk model using RNA-sequencing data from The Cancer Genome Atlas (TCGA) cohort was constructed. The least absolute shrinkage and selection operator (LASSO)-penalized Cox regression analyses were used to generate a risk score and discriminate the cohort into low- and high-risk AML groups. Then they were analyzed for chemotherapeutic and immune responses. Findings were further validated with AML clinical samples. Results: Thirteen CRGs were differentially expressed between AML patients and healthy controls. Patients with high-risk exhibited shorter overall survival (p = 0.003 in TCGA, p = 0.0216 in GSE37642), worse therapeutic response and increased inflammation. Thus, risk-score generated from the 3-gene risk model (risk score = (–0.01161) × GCSH expression + (–0.40387) × LIPT1 expression + (0.248985) × PDHA1 expression) could act as an independent prognostic factor. At last, GCSH expression decreased was validated with the clinical samples (p = 0.0312). Conclusions: Cuproptosis has a strong relationship with AML. The 3 CRG-related risk model could well predict AML prognosis.