Prediction of prognosis and immunotherapy response of tryptophan metabolism genes in acute myeloid leukemia

急性髓系白血病中色氨酸代谢基因对预后和免疫治疗反应的预测

阅读:1

Abstract

BACKGROUND: Acute myeloid leukemia (AML) is an aggressive and heterogeneous disease, associated with significant morbidity and mortality rates. Tryptophan metabolism has been implicated in the development of several tumors. The immune landscape within the tumor microenvironment plays a pivotal role in both leukemogenesis and the determination of patient prognosis. Nonetheless, the influence of tryptophan metabolic patterns and corresponding immune signatures in AML remains largely unclear. METHODS: Transcriptomic, genomic, and clinical data from TCGA were analyzed, and GSE71014 was used for external validation. Molecular subtypes were identified via consensus clustering of tryptophan metabolism-related genes (TRPRGs). Immune infiltration was quantified using ESTIMATE. A tryptophan-related prognostic risk score (TRPRS) was constructed using LASSO-Cox regression and evaluated for prognostic performance. RESULTS: We characterized alterations in 39 TRPRGs across AML cohorts and delineated the clinical and tumor microenvironmental features of two molecular subtypes. First, a TRPRG-based scoring system was established, identifying seven candidate genes significantly associated with patient outcomes. After LASSO-Cox regression selection, six genes were incorporated into the final prognostic model, stratify overall survival risk. The TRPRS effectively stratified overall survival in both the TCGA and GEO cohorts and remained an independent prognostic factor after multivariate adjustment. High-TRPRS patients exhibited distinct immune characteristics and differential drug sensitivity patterns. Functional experiments demonstrated that HADH and ECHS1 promote AML cell proliferation and survival. DISCUSSION: Our integrative analysis identified key tryptophan-metabolism-related genes in AML and developed a six-gene TRPRS capable of accurately distinguishing survival risk. This model not only provides mechanistic insights into AML progression but also offers a framework for individualized risk stratification and therapeutic guidance.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。