Dataset Information

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

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.

SUBMITTER: Wang N

PROVIDER: S-EPMC9955245 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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

Wang Nana N Bai Xiaoran X Wang Xinlu X Wang Dongmei D Ma Guangxin G Zhang Fan F Ye Jingjing J Lu Fei F Ji Chunyan C

Current oncology (Toronto, Ont.) 20230220 2

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 regress ...[more]

PMID: 36826154

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Project description:Acute myeloid leukaemia (AML) is a heterogeneous disease associated with poor outcomes. To identify AML-specific genes with prognostic value, we analysed transcriptome and clinical information from The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) datasets, and Genotype-Tissue Expression (GTEx) project. The metabolism-related gene, SLC25A21 was found to be significantly downregulated in AML, and was associated with high white blood cell (WBC) counts, high pretrial blood (PB) and bone marrow (BM) blast abundance, FLT3 mutation, NPM1 mutation, and death events (all p value <0.05). We validated the expression of SLC25A21 in our clinical cohort, and found that SLC25A21 was downregulated in AML. Moreover, we identified low expression of SLC25A21 as an independent prognostic factor by univariate Cox regression (hazard ratio [HR]: 0.550; 95% Confidence interval [CI]: 0.358-0.845; p value = 0.006) and multivariate Cox regression analysis (HR: 0.341; 95% CI: 0.209-0.557; p value <0.05). A survival prediction nomogram was established with a C-index of 0.735, which indicated reliable prognostic prediction. Subsequently, based on the median SLC25A21 expression level, patients in the TCGA-LAML cohort were divided into low- and high-expression groups. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs highlighted growth factor binding, extracellular structure organization, cytokine‒cytokine receptor interaction, etc. The results of gene set enrichment analysis (GSEA) indicated that the epithelial-mesenchymal transition, KRAS signalling, oxidative phosphorylation, and reactive oxygen species pathways were enriched. Through gene coexpression and protein‒protein interaction (PPI) network analysis, we identified two hub genes, EGFR and COL1A2, which were linked to worse clinical outcomes. Furthermore, we found that lower SLC25A21 expression was closely associated with a significant reduction in the levels of infiltrating immune cells, which might be associated with immune escape of AML cells. A similar trend was observed for the expression of checkpoint genes (CTLA4, LAG3, TIGIT, and HAVCR2). Finally, drug sensitivity testing suggested that the low-expression SLC25A21 group is sensitive to doxorubicin, mitomycin C, linifanib but resistant to JQ1, belinostat, and dasatinib. Hence, our study demonstrated that a low expression level of SLC25A21 predicts an unfavourable prognosis in patients with AML.

Dataset Information

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

Publications

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

Similar Datasets

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