Defining the role of stromal cells in determining HCC patient response to immunotherapies at single-cell resolution

ongoing

Hepatocellular carcinoma (HCC), remains a critical global health challenge, with limited treatment efficacy, particularly in advanced stages. The rising incidence of HCC is intricately linked to metabolic dysfunctions, such as metabolic-associated fatty liver disease (MAFLD) and its severe form, metabolic-associated steatohepatitis (MASH), highlighting an urgent need for enhanced precision oncology approaches. Despite recent advances, the lack of effective biomarkers and precision therapies for HCC underscores the complexity and heterogeneity of the disease. This proposal aims to address these gaps by integrating cutting-edge bioinformatics tools and genomic data to uncover novel mechanisms of HCC progression and treatment resistance. We will focus on three primary objectives: (1) Characterizing the immunosuppressive tumor microenvironment (TME) in HCC, emphasizing cell-type-specific regulatory programs and enhancer-promoter interactions that influence tumor progression and immune evasion. (2) Identifying specific cancer-associated fibroblast (CAF) subtypes and their role in patient response to immune-based combination therapies, particularly atezolizumab and bevacizumab. (3) Leveraging whole-genome sequencing (WGS) to pinpoint targetable mutations in regulatory regions, which can guide personalized treatment strategies and improve patient outcomes. By analyzing single-cell data and integrating it with whole-genome and RNA sequencing, this project aims to develop a comprehensive understanding of HCC's molecular underpinnings and its interaction with the TME. The expected outcomes include identifying new biomarkers for patient stratification, elucidating the role of CAFs in therapy response, and proposing actionable genomic targets for precision treatment. This research promises to revolutionize HCC management by providing innovative strategies for better-targeted therapies and improving clinical outcomes through enhanced precision oncology methodologies.