Establishing a novel Fanconi anemia signaling pathway-associated prognostic model and tumor clustering for pediatric acute myeloid leukemia patients

Considering the connection between the Fanconi anemia (FA) signaling pathway and tumor development, we aim to investigate the links between the FA gene expression and the survival prognosis of acute myeloid leukemia (AML) patients. Our study begins by identifying two distinct clusters of pediatric AML patients. Following the batch matching of the TARGET-AML, TCGA-LAML GSE71014, GSE12417, and GSE37642 cohorts, the samples were divided into a training set and an internal validation set. A Lasso regression modeling analysis was performed to identify five signatures: BRIP1, FANCC, FANCL, MAD2L2, and RFWD3. The AML samples were stratified into high- and low-risk groups by evaluating the risk scores. The AML high-risk patients showed a poorer overall survival prognosis. To predict the survival rates, we developed an FA Nomogram incorporating risk score, gender, age, and French-American-British classification. We further utilized the BEAT-AML cohort for the external validation of FA-associated prognostic models and observed good clinical validity. Additionally, we found a correlation between DNA repair, cell cycle, and peroxide-related metabolic events and FA-related high/low risk or cluster 1/2. In summary, our novel FA-associated prognostic models promise to enhance the prediction of pediatric AML prognosis.

Automated summary

This study aims to explore the association between Fanconi anemia (FA) gene expression and survival prognosis in acute myeloid leukemia (AML) patients. By analyzing patient samples, the researchers identified five gene signatures associated with AML risk and stratified patients based on these signatures. They also developed an FA Nomogram, which incorporates risk score, gender, age, and classification, to predict patient survival rates. External validation of these prognostic models confirmed their clinical validity.