Development and validation of a microenvironment-related prognostic model for hepatocellular carcinoma patients based on histone deacetylase family

BACKGROUND: Histone deacetylase (HDAC) family can remove acetyl groups from histone lysine residues, and their high expression is closely related to the poor prognosis of hepatocellular carcinoma (HCC) patients. Recently, it has been reported to play an immunosuppressive role in the microenvironment, but little is known about the mechanism. METHODS: Through machine learning, we trained and verified the prognostic model composed of HDACs. CIBERSORT was used to calculate the percentage of immune cells in the microenvironment. Based on co-expression network, potential targets of HDACs were screened. After that, qRT-PCR was employed to evaluate the expression of downstream genes of HDACs, while HPLC-CAD analysis was applied to detect the concentration of arachidonic acid (AA). Finally, Flow cytometry, WB and IHC experiments were used to detect CD86 expression in RAW246.7. RESULTS: We constructed a great prognostic model composed of HDAC1 and HDAC11 that was significantly associated with overall survival. These HDACs were related to the abundance of macrophages, which might be attributed to their regulation of fatty-acid-metabolism related genes. In vitro experiments, the mRNA expression of ACSM2A, ADH1B, CYP2C8, CYP4F2 and SLC27A5 in HCC-LM3 was significantly down-regulated, and specific inhibitors of HDAC1 and HDAC11 significantly promoted the expression of these genes. HDAC inhibitors can promote the metabolism of AA, which may relieve the effect of AA on the polarization of M1 macrophages. CONCLUSIONS: Our study revealed the blocking effect of HDAC1 and HDAC11 on the polarization of macrophages M1 in the microenvironment by inhibiting fatty acid metabolism.