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Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality. Human phenylalanine tRNA synthetase (PheRS) comprises two α catalytic subunits encoded by the FARSA gene and two β regulatory subunits encoded by the FARSB gene. FARSB is a potential oncogene, but no experimental data show the relationship between FARSB and HCC progression. We found that the high expression of FARSB in liver cancer is closely related to patients' low survival and poor prognosis. In liver cancer cells, the mRNA and protein expression levels of FARSB are increased and promote cell proliferation and migration. Mechanistically, FARSB activates the mTOR complex 1 (mTORC1) signaling pathway by binding to the component Raptor of the mTORC1 complex to play a role in promoting cancer. In addition, we found that FARSB can inhibit erastin-induced ferroptosis by regulating the mTOR signaling pathway, which may be another mechanism by which FARSB promotes HCC progression. In summary, FARSB promotes HCC progression and is associated with the poor prognosis of patients. FARSB is expected to be a biomarker for early screening and treatment of HCC.

Background: Nuclear respiratory factor 1 (NRF1) is a transcription factor that participates in several kinds of tumor, but its role in hepatocellular carcinoma (HCC) remains elusive. This study aims to explore the role of NRF1 in HCC progression and investigate the underlying mechanisms., Results: NRF1 was overexpressed and hyperactive in HCC tissue and cell lines and high expression of NRF1 indicated unfavorable prognosis of HCC patients. NRF1 promoted proliferation, migration and invasion of HCC cells both in vitro and in vivo. Mechanistically, NRF1 activated ERK1/2-CREB signaling pathway by transactivating lysophosphatidylcholine acyltransferase 1 (LPCAT1), thus promoting cell cycle progression and epithelial mesenchymal transition (EMT) of HCC cells. Meanwhile, LPCAT1 upregulated the expression of NRF1 by activating ERK1/2-CREB signaling pathway, forming a positive feedback loop., Conclusions: NRF1 is overexpressed in HCC and promotes HCC progression by activating LPCAT1-ERK1/2-CREB axis. NRF1 is a promising therapeutic target for HCC patients., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Liver cancer is one of the most common malignancies worldwide. HCC (hepatocellular carcinoma) is the predominant pathological type of liver cancer, accounting for approximately 75-85 % of all liver cancers. Lipid metabolic reprogramming has emerged as an important feature of HCC. However, the influence of lipid metabolism-related gene expression in HCC patient prognosis remains unknown. In this study, we performed a comprehensive analysis of HCC gene expression data from TCGA (The Cancer Genome Atlas) to acquire further insight into the role of lipid metabolism-related genes in HCC patient prognosis., Methods: We analyzed the mRNA expression profiles of 424 HCC patients from the TCGA database. GSEA(Gene Set Enrichment Analysis) was performed to identify lipid metabolism-related gene sets associated with HCC. We performed univariate Cox regression and LASSO(least absolute shrinkage and selection operator) regression analyses to identify genes with prognostic value and develop a prognostic model, which was tested in a validation cohort. We performed Kaplan-Meier survival and ROC (receiver operating characteristic) analyses to evaluate the performance of the model., Results: We identified three lipid metabolism-related genes (ME1, MED10, MED22) with prognostic value in HCC and used them to calculate a risk score for each HCC patient. High-risk HCC patients exhibited a significantly lower survival rate than low-risk patients. Multivariate Cox regression analysis revealed that the 3-gene signature was an independent prognostic factor in HCC. Furthermore, the signature provided a highly accurate prediction of HCC patient prognosis., Conclusions: We identified three lipid-metabolism-related genes that are upregulated in HCC tissues and established a 3-gene signature-based risk model that can accurately predict HCC patient prognosis. Our findings support the strong links between lipid metabolism and HCC and may facilitate the development of new metabolism-targeted treatment approaches for HCC.