Spatial Transcriptomics of IPMN Reveals Divergent Indolent and Malignant Progenitor Phenotypes

Purpose: Intraductal papillary mucinous neoplasms (IPMN) occur in 5-10% of the population, but only a small minority progress to pancreatic ductal adenocarcinoma (PDAC). The lack of accurate predictors of high-risk disease leads both to unnecessary operations for indolent neoplasms as well as missed diagnoses of PDAC. Digital spatial RNA profiling (DSP-RNA) provides an opportunity to define and associate transcriptomic states with cancer risk. Results: Our analysis uncovered three distinct epithelial transcriptomic states - "normal-like" (cNL), "low-risk" (cLR), and "high-risk" (cHR) - which were significantly associated with pathologic grade. Furthermore, the three states were significantly correlated with the exocrine, classical, and basal-like molecular subtypes described in PDAC. Specifically, exocrine function diminished in cHR, classical activation distinguished neoplasia (cLR and cHR) from cNL, and basal-like genes were specifically upregulated in cHR. Intriguingly, markers of cHR were detected in NL and LGD regions from specimens with PDAC but not low-grade IPMN. Conclusions: DSP-RNA of IPMN revealed low-risk (indolent) and high-risk (malignant) expression programs that correlated with the activity of exocrine and basal-like PDAC signatures, respectively, and distinguished pathologically low-grade from malignant specimens. These findings contextualize IPMN pathogenesis and have the potential to improve risk stratification. Whole-transcriptome DSP-RNA profiling of 10 patients with IPMN was conducted using NanoString GeoMx. Epithelial (PanCK+) areas of interest (AOIs) were annotated as normal duct (NL), low-grade dysplasia (LGD), high-grade dysplasia (HGD), or invasive carcinoma (INV). Unique molecular identifier (UMI) encoded gene expression count data was generated by Illumina sequencing. The processed count data was then analyzed using R/Bioconductor.