Identification and validation of a prognostic risk-scoring model based on the level of TIM-3 expression in acute myeloid leukemia

Author:

Huang Wanxue,Zheng Shasha,Wang Qi,Zhao Na,Long Zhiguo

Abstract

AbstractAcute myeloid leukemia (AML) is characterized by an unfavorable prognosis due to the presence of self-renewing leukemic stem cells (LSCs). The presence of T-cell immunoglobulin mucin-3 (TIM-3) on the surface of LSCs has been observed in various types of human AML, exerting an impact on the prognostic outcome. Exploring the hub genes associated with varying levels of TIM-3 expression offers a valuable approach to enhance our understanding of the underlying mechanisms involving TIM-3 and to identify potential prognostic indicators in AML. Nevertheless, to date, no research studies have reported a prognostic model that relies on the level of TIM-3 expression. In our study, we screen the hub-genes based on different expression level of TIM-3 through WGCNA. The prognostic risk-scoring model was constructed based on hub-genes. The results show the risk prognostic model has extraordinary ability to predict prognosis in both the training and validation sets. The high-risk group present poor prognosis with mutation of NPM1, TP53 (Multiple Hit) and FLT3(multiple hit), while IDH2 (Missense Mutation), MUC16 (Multiple Hit/Missense Mutation) occur mutation in low-risk group presenting favorite prognosis than high-risk group. Leukocyte cell–cell adhesion, regulation of T cell activation and I-κB kinase/NF-κB signaling enriched in high-risk group, involving in HSCs or LSCs anchoring to BM, which implicated in LSCs survival and chemotherapy resistance. B7-H3 (CD276) and CD276 would be the potential immune targets in high-risk group. The risk score model may help in distinguishing immune and molecular characteristics, predicting patient outcomes.

Funder

China National Natural Science Foundation

Project of Key Medical Specialty and Treatment Center of Pudong Hospital of Fudan University.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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