Single-cell dissection of the multicellular ecosystem and molecular features underlying microvascular invasion in hepatocellular carcinoma

Abstract

Background and aims: Microvascular invasion (MVI) is a crucial pathological hallmark of hepatocellular carcinoma (HCC), intricately associated with poor outcomes, early recurrence and intrahepatic metastasis following surgical resection and transplantation. However, the intricate tumor microenvironment (TME) and transcriptional programs underlying MVI in HCC remain poorly understood. Approach and results: We performed single-cell RNA sequencing of 46,789 individual cells from 10 samples of MVI+ (MVI present) and MVI- (MVI absent) HCC patients. We conducted comprehensive and comparative analyses to characterize cellular and molecular features associated with MVI, and validated key findings using external bulk, single-cell and spatial transcriptomic datasets, coupled with multiplex immunofluorescence assays. The comparison identified specific subtypes of immune and stromal cells critical to the formation of the immunosuppressive and pro-metastatic microenvironment in MVI+ tumors, including cycling T cells, LAMP3+ dendritic cells, TREM2+ macrophages, myofibroblasts, and arterial i endothelial cells. MVI+ malignant cells are characterized by high proliferation rates while MVI-malignant cells exhibit an inflammatory milieu. Additionally, we identified the MDK-dominated interaction between TREM2+ macrophages and malignant cells as a contributor to MVI formation and tumor progression. Notably, we unveiled a spatially co-located multicellular community exerting a dominant role in shaping the immunosuppressive microenvironment of MVI and correlating with unfavorable prognosis. Conclusions: This study provides a comprehensive single-cell atlas of MVI in HCC, shedding light on the complex multicellular ecosystem and molecular features associated with MVI. These findings deepen our understanding of the underlying mechanisms driving MVI and provide valuable insights for improving clinical diagnosis and developing more effective treatment strategies.