Abstract
Intraductal papillary mucinous neoplasms (IPMN) occur in 5% to 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 to both unnecessary operations for indolent neoplasms and missed diagnoses of PDAC. Digital spatial RNA profiling (DSP-RNA) provides an opportunity to define and associate transcriptomic states with cancer risk.
We performed whole-transcriptome DSP-RNA profiling on 10 IPMN specimens encompassing the spectrum of dysplastic changes from normal duct to cancer. Epithelial regions within each tissue were annotated as normal duct, low-grade dysplasia, high-grade dysplasia, or invasive carcinoma. The resulting digital gene expression data were analyzed with R/Bioconductor.
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 normal duct and low-grade dysplasia regions from specimens with PDAC but not from specimens containing only low-grade IPMN.
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 specimens from malignant specimens. These findings contextualize IPMN pathogenesis and have the potential to improve risk stratification.
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