A Novel Fatty Acid Metabolism-Associated Risk Model for Prognosis Prediction in Acute Myeloid Leukaemia

Nana Wang; Xiaoran Bai; Xinlu Wang; Dongmei Wang; Guangxin Ma; Fan Zhang; Jingjing Ye; Fei Lu; Chunyan Ji

doi:10.3390/curroncol30020193

A Novel Fatty Acid Metabolism-Associated Risk Model for Prognosis Prediction in Acute Myeloid Leukaemia

Curr Oncol. 2023 Feb 20;30(2):2524-2542. doi: 10.3390/curroncol30020193.

Authors

Nana Wang¹, Xiaoran Bai¹, Xinlu Wang¹, Dongmei Wang¹, Guangxin Ma², Fan Zhang³, Jingjing Ye¹, Fei Lu¹, Chunyan Ji¹

Affiliations

¹ Department of Hematology, Qilu Hospital of Shandong University, Jinan 250012, China.
² Hematology and Oncology Unit, Department of Geriatrics, Qilu Hospital of Shandong University, Jinan 250012, China.
³ Department of Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.

Abstract

Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults, with an unfavourable outcome and a high rate of recurrence due to its heterogeneity. Dysregulation of fatty acid metabolism plays a crucial role in the development of several tumours. However, the value of fatty acid metabolism (FAM) in the progression of AML remains unclear. In this study, we obtained RNA sequencing and corresponding clinicopathological information from the TCGA and GEO databases. Univariate Cox regression analysis and subsequent LASSO Cox regression analysis were utilized to identify prognostic FAM-related genes and develop a potential prognostic risk model. Kaplan-Meier analysis was used for prognostic significances. We also performed ROC curve to illustrate that the risk model in prognostic prediction has good performance. Moreover, significant differences in immune infiltration landscape were found between high-risk and low-risk groups using ESTIMATE and CIBERSOT algorithms. In the end, differential expressed genes (DEGs) were analyzed by gene set enrichment analysis (GSEA) to preliminarily explore the possible signaling pathways related to the prognosis of FAM and AML. The results of our study may provide potential prognostic biomarkers and therapeutic targets for AML patients, which is conducive to individualized precision therapy.

Keywords: acute myeloid leukaemia; fatty acid metabolism; prognosis signature.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Algorithms
Databases, Factual
Fatty Acids
Humans
Leukemia, Myeloid, Acute*
Prognosis

Substances

Fatty Acids

Grants and funding

This work was supported by grants from the Distinguished Taishan Scholars in Climbing Plan (tspd20210321), the National Natural Science Foundation of China (82070160, 82000165, 82170182), the Major Research Plan of the National Natural Science Foundation of China (91942306), the 68th China postdoctoral Science Foundation (2020M682171), the Key Program of Natural Science Foundation of Shandong Province (ZR2020KH016, ZR2021MH302), the Fundamental Research Funds for the Central Universities (2022JC012), the Independently Cultivate Innovative Teams of Jinan, Shandong Province (2021GXRC050) and the Clinical Practical New Technology and Development Fund of Qilu Hospital, Shandong University (2019-5).