Network perturbation of lactate metabolism identifies an aggressive hepatocellular carcinoma subtype with distinct immune and microbial features.
- 1Key Laboratory of Molecular Animal Nutrition, Ministry of Education, College of Animal Sciences, Zhejiang University, Hangzhou, China.
- 2Zhejiang Key Laboratory of Precise Diagnosis and Treatment of Abdominal Infection, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Abstract
Hepatocellular carcinoma (HCC) exhibits significant heterogeneity, and the reprogramming of lactate metabolism (LM) plays a crucial role in tumor progression and immune evasion. Classification based on perturbations in the gene interaction network related to LM may reveal new molecular subtypes. This study aimed to construct an LM interaction perturbation-based classification of HCC and to characterize the clinical, immune, and intratumoral microbial features of the identified subtypes. We constructed a gene interaction perturbation matrix using 262 lactate metabolism-related genes (LMRGs), performed spectral clustering on The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort (374 cases), and independently replicated it in the GSE76427 cohort (115 tumor cases). Subsequently, we systematically evaluated the differences in clinical characteristics, pathway activity, immune microenvironment, drug sensitivity, and intratumoral bacterial communities between the two subtypes, and constructed an exploratory prognostic model. Two subtypes were identified (Cluster 1 with 200 cases, Cluster 2 with 174 cases). Cluster 2 had a poorer prognosis, with activated proliferation pathways, increased immune infiltration and immune checkpoint expression, and an elevated tumor immune dysfunction and exclusion (TIDE)/exclusion score, presenting an immune excluded-like phenotype; the independent cohort could replicate the structure of the two subtypes. The analysis of intratumoral bacterial communities showed that the composition of Cluster 2 changed, and ANCOM-BC2 identified differences in enrichment of Streptomyces and Alistipes, whose abundance was related to immune evasion indicators and LM scores. The 13-gene prognostic model constructed based on subtype-specific genes could independently predict overall survival (OS). This study established a classification method for HCC based on the perturbation of LM network, identifying an aggressive Cluster 2 subtype with immune excluded-like characteristics and specific bacterial microbiota associations. This provides a new perspective for the study of HCC heterogeneity, but the microbiota-immune associations require independent validation.
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BibTeX
@article{guo2026network,
title = {{Network perturbation of lactate metabolism identifies an aggressive hepatocellular carcinoma subtype with distinct immune and microbial features.}},
author = {Tao Guo and Huahua Du},
journal = {Translational cancer research},
year = {2026},
month = sep,
doi = {10.21037/tcr-2026-1983},
url = {https://europepmc.org/article/MED/42997728},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Network perturbation of lactate metabolism identifies an aggressive hepatocellular carcinoma subtype with distinct immune and microbial features.
AU - Tao Guo
AU - Huahua Du
PY - 2026
DA - 2026/09/28
JO - Translational cancer research
DO - 10.21037/tcr-2026-1983
UR - https://europepmc.org/article/MED/42997728
AB - Hepatocellular carcinoma (HCC) exhibits significant heterogeneity, and the reprogramming of lactate metabolism (LM) plays a crucial role in tumor progression and immune evasion. Classification based on perturbations in the gene interaction network related to LM may reveal new molecular subtypes. This study aimed to construct an LM interaction perturbation-based classification of HCC and to characterize the clinical, immune, and intratumoral microbial features of the identified subtypes. We constructed a gene interaction perturbation matrix using 262 lactate metabolism-related genes (LMRGs), performed spectral clustering on The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort (374 cases), and independently replicated it in the GSE76427 cohort (115 tumor cases). Subsequently, we systematically evaluated the differences in clinical characteristics, pathway activity, immune microenvironment, drug sensitivity, and intratumoral bacterial communities between the two subtypes, and constructed an exploratory prognostic model. Two subtypes were identified (Cluster 1 with 200 cases, Cluster 2 with 174 cases). Cluster 2 had a poorer prognosis, with activated proliferation pathways, increased immune infiltration and immune checkpoint expression, and an elevated tumor immune dysfunction and exclusion (TIDE)/exclusion score, presenting an immune excluded-like phenotype; the independent cohort could replicate the structure of the two subtypes. The analysis of intratumoral bacterial communities showed that the composition of Cluster 2 changed, and ANCOM-BC2 identified differences in enrichment of Streptomyces and Alistipes, whose abundance was related to immune evasion indicators and LM scores. The 13-gene prognostic model constructed based on subtype-specific genes could independently predict overall survival (OS). This study established a classification method for HCC based on the perturbation of LM network, identifying an aggressive Cluster 2 subtype with immune excluded-like characteristics and specific bacterial microbiota associations. This provides a new perspective for the study of HCC heterogeneity, but the microbiota-immune associations require independent validation.
SN - 2218-676X
SN - 2219-6803
ER -