Ellson Ivan, Martorell-Marugán Jordi, Carmona-Sáez Pedro, Ramos-Mejia Verónica
GENYO, Centre for Genomics and Oncological Research Pfizer, University of Granada, Andalusian Regional Government, PTS, 18016, Granada, Spain.
Fundación para la Investigación Biosanitaria de Andalucía Oriental-Alejandro Otero (FIBAO), 18012, Granada, Spain.
NPJ Genom Med. 2024 Aug 6;9(1):40. doi: 10.1038/s41525-024-00424-w.
Accurately predicting patient outcomes is essential for optimizing treatment and improving outcomes in pediatric acute myeloid leukemia (AML). In recent years, microRNAs have emerged as a promising prognostic marker, with a growing body of evidence supporting their potential predictive value. We systematically reviewed all previous studies that have analyzed the expression of microRNAs as predictors of survival in pediatric AML and found 16 microRNAs and 4 microRNA signatures previously proposed as predictors of survival. We then used a public access cohort of 1414 pediatric AML patients from the TARGET project to develop a new predictive model using penalized lasso Cox regression based on microRNA expression. Here we propose a new score based on a 37-microRNA signature that is associated with AML and is able to predict survival more accurately than previous microRNA-based methods.
准确预测患者预后对于优化小儿急性髓系白血病（AML）的治疗和改善预后至关重要。近年来，微小RNA已成为一种有前景的预后标志物，越来越多的证据支持其潜在的预测价值。我们系统回顾了所有先前分析微小RNA表达作为小儿AML生存预测指标的研究，发现了先前提出的16种微小RNA和4种微小RNA特征作为生存预测指标。然后，我们使用来自TARGET项目的1414例小儿AML患者的公共队列，基于微小RNA表达，通过惩罚性套索Cox回归开发了一种新的预测模型。在此，我们提出了一种基于37种微小RNA特征的新评分，该评分与AML相关，并且能够比以前基于微小RNA的方法更准确地预测生存。
