ß-Catenin Activation Reprograms Ammonia Metabolism to Promote Senescence Resistance in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a typical tumor that undergoes metabolic reprogramming, differing from normal liver tissue in glucose, lipid, nucleic acid, and amino acid metabolism. Although ammonia is a toxic metabolic by-product, it has also been recently recognized as a signaling molecule to activate lipid metabolism, and it can be a nitrogen source for biosynthesis to support tumorigenesis. In this study, we revealed that ß-catenin activation increases ammonia production in HCC mainly by stimulating glutaminolysis. ß-Catenin/LEF1 activated the transcription of the glutamate dehydrogenase GLUD1, which then promoted ammonia utilization to enhance the production of glutamate, aspartate, and proline as evidenced by 15NH4Cl metabolic flux. ß-Catenin/TCF4 induced the transcription of SLC4A11, an ammonia transporter, to excrete excess ammonia. SLC4A11 was upregulated in HCC tumor tissues, and high SLC4A11 expression was associated with poor prognosis and advanced disease stages. Loss of SLC4A11 induced HCC cell senescence in vitro by blocking ammonia excretion and reduced ß-catenin-driven tumor growth in vivo. Furthermore, elevated levels of plasma ammonia promoted the progression of ß-catenin mutant HCC, which was impeded by SLC4A11 deficiency. Downregulation of SLC4A11 led to ammonia accumulation in tumor interstitial fluid and decreased plasma ammonia levels in HCC with activated ß-catenin. Altogether, this study indicates that ß-catenin activation reprograms ammonia metabolism and that blocking ammonia excretion by targeting SLC4A11 could be a promising approach to induce senescence in ß-catenin mutant HCC. SIGNIFICANCE: Ammonia metabolism reprogramming mediated by aberrant activation of ß-catenin induces resistance to senescence in HCC and can be targeted by inhibiting SLC4A11 as a potential therapy for ß-catenin mutant liver cancer.

Liver Regeneration-Related Genes of Nontumor Liver Tissues Predict the Prognosis of Patients with Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is one of the most serious malignant tumors threatening human life with a high mortality rate. The liver regenerative capacity after hepatectomy in early-stage HCC patients is influenced by various factors, including surgical methods and energy metabolism. This study aims to provide a prognostic model based on genes related to liver regeneration that can predict the prognosis of non-tumor tissues in HCC patients. Patients and Methods: A total of 584 non-tumor tissues from HCC patients were collected from three independent databases. Kaplan-Meier survival curves were used to identify prognostic liver-regeneration genes. Subsequently, a prognostic indicator, designated as the Liver Regeneration score (LR score), was determined using single-sample gene set enrichment analysis (ssGSEA). Independent cohorts were used to verify the relationship between LR score and prognosis in non-tumor tissues of HCC patients. Furthermore, a liver regeneration-related model was established to validate key genes identified through LASSO Cox regression analysis. Results: We constructed a gene set comprising 24 liver regeneration-related genes, and the LR score was utilized to predict the prognosis of HCC patients based on its levels in non-tumor tissues. In non-tumor tissues of HCC patients, higher LR scores were associated with improved prognosis. Higher LR scores in non-tumor tissues indicate improved liver metabolism in HCC patients, revealed by Enrichment analysis. LASSO Cox regression analysis identified two key genes, DHTKD1 (dehydrogenase E1 and transketolase domain containing 1) and PHYH (phytanoyl-CoA 2-hydroxylase), and higher expression levels of these genes in non-tumor tissues were correlated with better prognosis. The expression levels of these two genes also changed corresponding to the progression of liver regeneration. Conclusion: In summary, our study has introduced a novel LR gene signature for HCC patients, providing a predictive model for estimating clinical prognosis from non-tumor tissues. The LR score demonstrates promise as a reliable indicator for predicting overall survival in HCC.