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Updated: Aug 28, 2025

Mass Cytometry Analysis of Systemic and Local Immune Responses in Hepatocellular Carcinoma
Published on: April 25, 2025
Metabolomics-based classification reveals subtypes of hepatocellular carcinoma
Guojun Hou1, Dongyang Ding1, Tao Tian1
1The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China.
Abstract:
Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death, and the prognosis varies due to its high heterogeneity, systematic evaluation of HCC is mainly based on genomic and transcriptomic features, metabolomics-based classification has yet to be reported. Here we performed RNA-seq on 50 paired samples and metabolomics analysis on 72 paired samples of both normal and tumor tissues from HCC patients. Through unsupervised hierarchical cluster analysis with train and test data sets, metabolic and gene expression signatures were identified. We found that most fluxes related to glutamate are attenuated, except for the glutamate-proline pathway. Three subgroups were identified with distinct survival, clinical observations, and metabolic/gene signatures. S1 is characterized by a relatively poor prognosis, a low concentration of the degradation products of phosphatidylcholine and phosphatidylethanolamine, an enrichment of specific genes related to focal adhesion, and an upregulation of genes on chromosome 6q27. Beyond commonly downregulated metabolites, S2 tumors are largely characterized by few alterations in metabolites and genes, as well as low incidence of mutations/loss of heterozygosity, the metabolite signature of this group consists of hexoses and their phosphates, and the prognosis is the best, with a 5-year survival rate of greater than 80%. S3 is characterized by the worst survival (an approximately 20% 5-year survival rate), unsaturated fatty acid metabolites, an upregulation of specific genes involved in metastasis, and an upregulation of genes on chromosome 1q21. The metabolite-based classifications are more stable and reproducible, with each subgroup characterized by a distinct molecular signature and disease prognosis.
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