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Abstract
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.
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1 PTS, GENYO, Centre for Genomics and Oncological Research Pfizer, University of Granada, Andalusian Regional Government, Granada, Spain (GRID:grid.418805.0) (ISNI:0000 0004 0500 8423)
2 PTS, GENYO, Centre for Genomics and Oncological Research Pfizer, University of Granada, Andalusian Regional Government, Granada, Spain (GRID:grid.418805.0) (ISNI:0000 0004 0500 8423); Fundación para la Investigación Biosanitaria de Andalucía Oriental-Alejandro Otero (FIBAO), Granada, Spain (GRID:grid.418805.0)
3 PTS, GENYO, Centre for Genomics and Oncological Research Pfizer, University of Granada, Andalusian Regional Government, Granada, Spain (GRID:grid.418805.0) (ISNI:0000 0004 0500 8423); University of Granada, Department of Statistics, Granada, Spain (GRID:grid.4489.1) (ISNI:0000 0001 2167 8994)
4 PTS, GENYO, Centre for Genomics and Oncological Research Pfizer, University of Granada, Andalusian Regional Government, Granada, Spain (GRID:grid.418805.0) (ISNI:0000 0004 0500 8423); University of Granada, Department of Cell Biology, Faculty of Sciences, Granada, Spain (GRID:grid.4489.1) (ISNI:0000 0001 2167 8994)