Single-nuclei RNA and ATAC Sequencing Uncovers Subtypes In Pancreatic Neuroendocrine Tumors

Authors

• CO Mbulu
• J Diss
• L Yang
• K Maki
• C Crayton
• J Barb
• M Schwandt
• K Herman
• S Sharon
• N Diazgranados
• V Ramchandani
• G Wallen

Abstract

Pancreatic neuroendocrine tumors (PNETs) are a rare form of cancer, thought to originate from the endocrine lineage of the pancreas—which generates hormone producing cells. PNETs have limited curative options with rising incidence, and are categorized into grades based on Ki67, a generic replication marker. To improve diagnosis and treatments, it's critical to move beyond current diagnostic approaches that rely on incomplete understanding of PNET markers and subtypes. In this study, we used single-cell multiome assays on cryopreserved primary PNETs of varying grade, stage, and metastasis to characterize their chromatin and transcriptome profiles at single-cell resolution. Additionally, we performed multiome analysis on normal endocrine and exocrine pancreas for comparison between healthy pancreas and PNETs at the single-cell level.
Our multimodal analysis revealed extensive inter-tumor heterogeneity with few shared genes across the PNET cohort. In contrast, we found minimal heterogeneity within each tumor, suggesting originating from a single founder cell. Using differential gene expression analysis, we identified distinct cell populations within PNETs, including tumor, endothelial, and immune cells. The tumors had distinct gene profiles: cell markers (PDX1/ARX), cancer metabolism (VHL and HIF1a/HIF2a), and chromatin regulation (DAXX/ATRX). We performed ligand-receptor analysis to find communication networks associated with PNETs, comparing findings to normal pancreas. For a subset of tumors, we identified interactions previously understudied in PNETs. We observed diverse molecular profiles of PNETs with little overlap between patients, explaining the difficulty finding successful treatments for most cases. Our results can help develop personalized medicine by elucidating molecular markers varying between PNETs, by further classification.

Scientific Focus Area: Cancer Biology

This page was last updated on Monday, September 25, 2023