Identification of fatty acid metabolism-related lncRNAs in the prognosis and immune microenvironment of colon adenocarcinoma

Author:

Wu Shuang,Gong Yuzhu,Chen Jianfang,Zhao Xiang,Qing Huimin,Dong Yan,Li Sisi,Li Jianjun,Wang Zhe

Abstract

Abstract Background Cancer metabolism is largely altered compared to normal cells. This study aims to explore critical metabolism pathways in colon adenocarcinoma (COAD), and reveal the possible mechanism of their role in cancer progression. Methods Expression data and sequencing data of COAD samples were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The expression profiles between tumor and normal samples were compared to identify differential metabolism pathways through single sample gene set enrichment analysis. Results Fatty acid synthesis was identified as a key metabolism pathway in COAD. Based on fatty acid-related lncRNAs, two molecular subtypes (C1 and C2) were defined. C2 subtype with worse prognosis had higher immune infiltration and higher expression of immune checkpoints. Five transcription factors (TFs) including FOS, JUN, HIF1A, STAT3 and STAT2 were highly expressed in C2 subtype. Five fatty acid-related lncRNAs were identified to be biomarkers for predicting COAD prognosis. Finally, further experients showed that knockdown of lncRNA PAXIP1-AS1 decreased the triglyceride content and the fatty acid synthase and acetyl-CoA carboxylase 1 expressions, which suggested that lncRNA PAXIP1-AS1 plays an important role in fatty acid metabolism of COAD. Conclusions This study demonstrated that fatty acid synthesis was greatly altered in COAD. Fatty acid-related lncRNAs were speculated to be involved in cancer progression through associating with TFs. The five screened TFs may serve as new drug targets for treating COAD.

Funder

National Natural Science Foundation of China

Medical Science and Technology Innovation Found of The First Hospital Affiliated to Army Medical University

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Immunology

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