NCACC maps cross-sample spatial niches and reveals cIgG+ epithelial rare cells driving liver cancer invasion.
TL;DR
This study establishes NCACC as a generalisable framework for high-confidence rare malignant cell identification across heterogeneous spatial transcriptomic cohorts, highlighting the cIgG-JAK-STAT as a therapeutically actionable driver of liver cancer invasion.
Abstract
Background
Liver cancer exhibits profound spatial and cellular heterogeneity, contributing to tumour progression, invasion and therapeutic resistance. Emerging evidence suggests that rare low-abundance malignant cell populations residing within discrete tissue niches influence these processes. However, their reliable detection and identification remain challenging due to the limitations of conventional spatial and single-cell transcriptomic analyses, which often rely on single-sample convergence and a lack of cross-cohort reproducibility.
Objective
To develop a robust framework for identifying rare malignant cell populations across heterogeneous spatial transcriptomic datasets and to characterise their functional role in liver cancer progression.
Design
We developed the Niche Cluster Atlas with Cellular Co-localisation (NCACC), a dual-layer framework integrating spatial organisation with cellular composition to enable cross-sample niche discovery. NCACC was applied to a comprehensive liver cancer transcriptomic atlas to identify rare niche-associated malignant cell populations.
Results
NCACC stratified liver cancer tumour architecture into reproducible multicellular niche modules and enabled a tumour-invasive front-enriched rare cancer-derived IgG (cIgG)+ epithelial cell population. These cells enhanced proliferative and invasive characteristics and were associated with disease progression. Mechanistic analyses identified a STAT1-dependent cIgG-JAK-STAT signalling axis sustaining the invasive-front phenotype and promoting cIgG+ epithelial cell aggressive behaviours. We then combined structure-guided virtual screening with patient-derived organoid validation to identify nordihydroguaiaretic acid and gallic aldehyde as candidate modulators.
Conclusion
Our study establishes NCACC as a generalisable framework for high-confidence rare malignant cell identification across heterogeneous spatial transcriptomic cohorts, highlighting the cIgG-JAK-STAT as a therapeutically actionable driver of liver cancer invasion.