Macrophage-related Genomic Signatures Predict HCC Prognosis and Therapy Response

Area of Science:

• Oncology
• Genomics
• Immunology

Background:

• Hepatocellular carcinoma (HCC) presents significant challenges due to heterogeneity, drug resistance, and recurrence.
• Tumor-associated macrophages (TAMs) play a key role in the HCC tumor microenvironment, but their full prognostic and therapeutic impact is not yet understood.

Purpose of the Study:

• Identify macrophage-related genomic signatures in HCC.
• Delineate distinct molecular subtypes of HCC.
• Develop a prognostic model to predict patient survival and response to therapy.

Main Methods:

• Integrated single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data.
• Identified macrophage-related genes using differential expression analysis.
• Employed consensus clustering for HCC subtype delineation and Principal Component Analysis (PCA) for prognostic model construction.
• Analyzed immune infiltration and drug sensitivity using ssGSEA, IPS, and pRRophetic.

Main Results:

• Discovered four distinct HCC molecular subtypes, with Cluster C exhibiting the most favorable survival outcomes.
• The PCA-derived prognostic score significantly correlated with overall survival (OS) and immunotherapy response.
• Higher scores indicated enhanced sensitivity to immunotherapy, increased effector T cell infiltration, and reduced T cell exhaustion.
• Observed varied responses to immunotherapy and conventional treatments across different HCC subgroups.

Conclusions:

• Macrophage-related genomic signatures are vital for determining HCC prognosis and therapeutic outcomes.
• The developed PCA-based model shows potential as a biomarker for personalized HCC treatment strategies.
• Further validation in larger cohorts and mechanistic studies are warranted.