Integrated single-cell and bulk transcriptome analysis of R-loop score-based signature with regard to immune microenvironment, lipid metabolism and prognosis in HCC.

Abstract

Background: Hepatocellular carcinoma (HCC) is one of the most prevalent causes of cancer-related morbidity and mortality worldwide. Late-stage detection and the complex molecular mechanisms driving tumor progression contribute significantly to its poor prognosis. Dysregulated R-loops, three-stranded nucleic acid structures associated with genome instability, play a key role in the malignant characteristics of various tumors. However, the detailed role and mechanism of R-loops in HCC progression remain elusive and require further exploration. This study aimed to construct an R-loop scoring signature centered on prognosis and lipid metabolism, thereby enhancing our understanding of HCC progression and identifying potential therapeutic targets.

Methods: In this study, we utilized the single-cell RNA-sequencing (scRNA-seq) data from HCC patients (GSE149614 and CRA002308) to construct an R-loop scoring model based on the identified R-loop regulator genes (RLRGs) related to HBV infection through WGCNA analysis. We also explored the tumor microenvironment and intercellular communication related to R-loop score. Additionally, a prognostic risk model based on the fatty acid metabolism-associated RLRGs was constructed using data from the TCGA database, and its association with immune infiltration, mutations, and drug sensitivity was analyzed. In vitro and in vivo experiments were performed to investigate the role of RLRG CLTC in lipid metabolism and HCC progression.

Results: Using scRNA-seq data from HCC, we established an R-loop scoring model based on identified RLRGs related to HBV infection. Moreover, the more suppressive tumor immune microenvironment and stronger intercellular communication were displayed in malignant cells with high R-loop scores. The cell trajectory and cellular metabolism analysis exhibited a significant association between lipid metabolism and RLRGs. Additionally, we constructed a prognostic risk model consisting of 8 RLRGs related to fatty acid metabolism, which effectively evaluated the prognostic value, status of tumor immune microenvironment, gene mutations, and chemotherapeutic drug sensitivity for HCC patients. Notably, validation experiments suggested that CLTC could regulate lipid metabolism through R-loop formation and facilitate tumor progression in HCC.

Conclusion: Collectively, our study proposes an R-loop scoring model associated with tumor immune microenvironment, lipid metabolism and prognostic value. CLTC, an R-loop regulator, emerges as a promising prognostic biomarker and therapeutic target, offering new insights into potential treatment strategies for HCC patients.