Integrative single-cell transcriptome analysis of human pancreatic cancer reveals transitional cell status associated with poor prognosis

Background: Recent studies using single cell transcriptomic analysis have reported several distinct clusters of neoplastic epithelial cells and cancer-associated fibroblasts in the pancreatic cancer tumor microenvironment. However, their molecular characteristics and biological significance have not been clearly elucidated due to intra- and inter-tumoral heterogeneity.

Methods: We performed single cell RNA sequencing using enriched non-immune cell populations from 17 pancreatic cancer tumor tissues and demonstrated a high-resolution landscape of epithelial cells and fibroblasts in the tumor microenvironment.

Results: We identified seven distinct epithelial cell clusters and six distinct fibroblast clusters and delineated their molecular characteristics and biological significance by analyzing transcription factor activities and cell-to-cell interactions. The novel epithelial cell cluster Ep_VGLL1 exhibited transitional cell characteristics linking classical and basal-like subtypes and was associated with poor patient prognosis. Consistent with the gene expression pattern, the Ep_VGLL1 signature transiently emerged after chemotherapy in pancreatic cancer cells, supporting their transitional nature.

Conclusion: This integrative analysis provides a novel model of the dynamic states of pancreatic cancer cells and unveils potential therapeutic targets.