Background: Hepatocellular carcinoma (HCC) is one of the most lethal malignancies. We aimed to identify a robust lipid metabolism-related signature associated with the HCC microenvironment to improve the prognostic prediction of HCC patients.

Methods: We analyzed the gene expression profiles of lipid metabolism from Molecular Signatures Database and information of patients from The Cancer Genome Atlas. Gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and principal component analysis (PCA) were employed for functional annotation. Quantitative real-time polymerase chain reaction (qRT-PCR) was employed to verify the expression of model genes in HCC and adjacent tissues.

Results: As a result, a lipid metabolism-related signature consisting of acyl-CoA synthetase long-chain family member 6 (ACSL6), lysophosphatidylcholine acyltransferase 1, phospholipase A2 group 1B, lecithin-cholesterol acyltransferase (LCAT), and sphingomyelin phosphodiesterase 4 (SMPD4) was identified among HCC patients. Lysophosphatidylcholine acyltransferase 1, PLA2G1B, and SMPD4 were proved significantly high expression while ACSL6 and LCAT were remarkably low expression in our 15 pairs of matched HCC and normal tissues by qRT-PCR. Under different conditions, the overall survival (OS) of patients in low-risk group was prolonged than that in high-risk group. Moreover, the as-constructed signature was an independent factor, which was remarkably associated with gender, histologic grade, and platelet level of HCC patients. In addition, the receiver operating characteristic (ROC) curve analysis confirmed the good potency of the model. Functional enrichment analysis further revealed that lower fatty acid (FA) oxidation and higher infiltration of immunocytes were detected in patients from the high-risk group compared with those in the low-risk group.

Conclusions: Our findings indicate that the lipid metabolism-related signature shows prognostic significance for HCC.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571839PMC
http://dx.doi.org/10.1002/cam4.3353DOI Listing

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