Development and Validation of a 10-Gene Prognostic Signature in Acute Myeloid Leukemia

Abstract

Background: Acute myeloid leukemia (AML) is the most common type of adult acute leukemia and has a poor prognosis. Thus, optimal risk stratification is of greatest importance for reasonable choice of treatment and prognostic evaluation. The purpose of our investigation was to construct a prognostic signature for risk stratification. Methods: A total of 1707 samples of AML patients from 3 public database were divided into meta training, meta testing and validation sets. The meta training set was used to build risk prediction model, and the other four sets were employed for validation. The log-rank test and univariate COX regression analysis as well as LASSO-COX were used to screen survival-related gene in the meta training set, which were subsequently calculated to construct AML risk score (AMLRS). A nomogram was established based on prognostic signature and clinical parameters for clinical application. Results: AML patients were divided into high-risk and low-risk groups based on AMLRS which was constituted by 10 survival-related genes. In meta training, meta testing and validation sets, the patient in low-risk group all had a significantly longer OS (overall survival) than those in high-risk group (P < 0.001), and the area under ROC curve (AUC) by time-dependent ROC were 0.5854-0.7905 for 1 year, 0.6652-0.8066 for 3 years, and 0.6622-0.8034 for 5 years. Multivariate COX regression analysis indicated that AMLRS was an independent prognostic factor in 5 datasets. Nomogram combining the AMLRS and 2 clinical parameters performed well in predicting 5-year OS. Conclusion: 10-gene prognostic signature was identified as a promising risk stratification model. Funding Statement: Not needed. Declaration of Interests: The authors state: There are no conflicts of interest. Ethics Approval Statement: Not needed.