Integrating single-cell and bulk RNA sequencing data to characterize the heterogeneity of glycan-lipid metabolism polarization in hepatocellular carcinoma.

Abstract

Background: Hepatocellular carcinoma (HCC) is high heterogeneity and remains an unmet medical challenge, but their metabolic heterogeneity has not been fully uncovered and required clinical applicable translational strategies.

Methods: By analyzing the RNA sequencing data in the in-house cohort and public HCC cohorts, we identified a metabolic subtype of HCC associated with multi-omics features and prognosis. Multi-omics alterations and clinicopathological information between different subtypes were analyzed. Gene signature, radiomics, contrast-enhanced ultrasound (CEUS), serum biomarkers were tested as potential surrogate methods for high throughput technology-based subtyping. Single-cell RNA sequencing analyses were employed to evaluate the immune characteristics changes between subtypes.

Results: By utilizing metabolic-related pathways, we identified two heterogeneous metabolic HCC subtypes, glycan-HCC and lipid-HCC, with distinct multi-omics features and prognosis. Kaplan-Meier and restricted mean survival time analyses revealed worse overall survival in glycan-HCCs. And glycan-HCCs were characterized with high genomic instability, proliferation-related pathways activation and exhausted immune microenvironment. Furthermore, we developed gene signatures, radiomics, CEUS and serum biomarkers for subtypes determination, which showed substantial agreement with high-throughput-based classification. Single-cell RNA-seq showed glycan-HCCs were associated with multifaceted immune distortion, including exhaustion of T cells and enriched SPP1 + macrophages.

Conclusion: Collectively, our analysis demonstrated the metabolic heterogeneity of HCCs and enabled the development of clinical translation strategies, thus promoting understanding and clinical applications about HCC metabolism heterogeneity.