Dissecting and understanding the cancer ecosystem, especially that around the tumor margins, which have strong implications for tumor cell infiltration and invasion, are essential for exploring the mechanisms of tumor metastasis and developing effective new treatments. Using a novel tumor border scanning and digitization model enabled by nanoscale resolution-SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq), we identified a 500 µm-wide zone centered around the tumor border in patients with liver cancer, referred to as “the invasive zone”. We detected strong immunosuppression, metabolic reprogramming, and severely damaged hepatocytes in this zone. We also identified a subpopulation of damaged hepatocytes with increased expression of serum amyloid A1 and A2 (referred to collectively as SAAs) located close to the border on the paratumor side. Overexpression of CXCL6 in adjacent malignant cells could induce activation of the JAK-STAT3 pathway in nearby hepatocytes, which subsequently caused SAAs’ overexpression in these hepatocytes. Furthermore, overexpression and secretion of SAAs by hepatocytes in the invasive zone could lead to the recruitment of macrophages and M2 polarization, further promoting local immunosuppression, potentially resulting in tumor progression. Clinical association analysis in additional five independent cohorts of patients with primary and secondary liver cancer (n = 423) showed that patients with overexpression of SAAs in the invasive zone had a worse prognosis. Further in vivo experiments using mouse liver tumor models in situ confirmed that the knockdown of genes encoding SAAs in hepatocytes decreased macrophage accumulation around the tumor border and delayed tumor growth. The identification and characterization of a novel invasive zone in human cancer patients not only add an important layer of understanding regarding the mechanisms of tumor invasion and metastasis, but may also pave the way for developing novel therapeutic strategies for advanced liver cancer and other solid tumors.

Solid tumors are complex ecosystems, and heterogeneity is the major challenge for overcoming tumor relapse and metastasis. Uncovering the spatial heterogeneity of cell types and functional states in tumors is essential for developing effective treatment, especially in invasive fronts of tumor, the most active region for tumor cells infiltration and invasion. We firstly used SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq) with a nanoscale resolution to characterize the tumor microenvironment of intrahepatic cholangiocarcinoma (ICC). Enrichment of distinctive immune cells, suppressive immune microenvironment and metabolic reprogramming of tumor cells were identified in the 500µm-wide zone centered bilaterally on the tumor boundary, namely invasive fronts of tumor. Furthermore, we found the damaged states of hepatocytes with overexpression of Serum Amyloid A (SAA) in invasive fronts, recruiting macrophages for facilitating further tumor invasion, and thus resulting in a worse prognosis. We also confirmed these findings in hepatocellular carcinoma and other liver metastatic cancers. Our work highlights the remarkable potential of high-resolution-spatially resolved transcriptomic approaches to provide meaningful biological insights for comprehensively dissecting the tumor ecosystem and guiding the development of novel therapeutic strategies for solid tumors.

Single-cell RNA-sequencing (scRNA-seq) enables systematic mapping of cellular differentiation trajectories. However, inferring the cell-fate transitions under diseases or perturbations is still challenging due to the high cellular plasticity. Here, we demonstrate that monotonically expressed genes (MEGs) along cell divisions record the directions of state transitions regardless of the cellular processes. We developed a computational framework (PhyloVelo) to identify MEGs and reconstruct a novel transcriptomic velocity field by leveraging both scRNA-seq and phylogenetic information. PhyloVelo accurately recovered linear, bifurcated and convergent differentiations in simulations and C. elegans. It outperformed current approaches for delineating cellular trajectories in embryo development and tumor evolution through analysis of five CRISPR/Cas9-based lineage tracing datasets. Together, our study unveils an internal cellular clock and provides a powerful method for cell-fate analysis in diverse biological contexts.