Development and Validation of a Novel Prognostic Model for Acute Myeloid Leukemia Based on Immune-Related Genes

Overview

Journal Front Immunol

Specialty Allergy & Immunology

Date 2021 May 24

PMID 34025649

Citations 7

Authors

Ran Li

Zuoyou Ding

Peng Jin

Shishuang Wu

Ge Jiang

Rufang Xiang

Wenfang Wang

Zhen Jin

Xiaoyang Li

Kai Xue

Xiaolu Wu

Junmin Li

Affiliations

Soon will be listed here.

Abstract

The prognosis of acute myeloid leukemia (AML) is closely related to immune response changes. Further exploration of the pathobiology of AML focusing on immune-related genes would contribute to the development of more advanced evaluation and treatment strategies. In this study, we established a novel immune-17 signature based on transcriptome data from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) databases. We found that immune biology processes and transcriptional dysregulations are critical factors in the development of AML through enrichment analyses. We also formulated a prognostic model to predict the overall survival of AML patients by using LASSO (Least Absolute Shrinkage and Selection Operator) regression analysis. Furthermore, we incorporated the immune-17 signature to improve the prognostic accuracy of the ELN2017 risk stratification system. We concluded that the immune-17 signature represents a novel useful model for evaluating AML survival outcomes and may be implemented to optimize treatment selection in the next future.

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