Comprehensive Metabolic Profiling and Genome-wide Analysis Reveal Therapeutic Modalities for Hepatocellular Carcinoma

Abstract

Understanding the details of metabolic reprogramming in hepatocellular carcinoma (HCC) is critical to improve stratification for therapy. Both multiomics analysis and cross-cohort validation were performed to investigate the metabolic dysregulation of 562 HCC patients from 4 cohorts. On the basis of the identified dynamic network biomarkers, 227 substantial metabolic genes were identified and a total of 343 HCC patients were classified into 4 heterogeneous metabolic clusters with distinct metabolic characteristics: cluster 1, the pyruvate subtype, associated with upregulated pyruvate metabolism; cluster 2, the amino acid subtype, with dysregulated amino acid metabolism as the reference; cluster 3, the mixed subtype, in which lipid metabolism, amino acid metabolism, and glycan metabolism are dysregulated; and cluster 4, the glycolytic subtype, associated with the dysregulated carbohydrate metabolism. These 4 clusters showed distinct prognoses, clinical characteristics and immune cell infiltrations, which was further validated by genomic alterations, transcriptomics, metabolomics, and immune cell profiles in the other 3 independent cohorts. Besides, the sensitivity of different clusters to metabolic inhibitors varied depending on their metabolic features. Importantly, cluster 2 is rich in immune cells in tumor tissues, especially programmed cell death protein 1 (PD-1)-expressing cells, which may be due to the tryptophan metabolism disorders, and potentially benefiting more from PD-1 treatment. In conclusion, our results suggest the metabolic heterogeneity of HCC and make it possible to treat HCC patients precisely and effectively on specific metabolic characteristics.