Related Experiment Video
Updated: Aug 10, 2025

Isolation and Characterization of Patient-derived Pancreatic Ductal Adenocarcinoma Organoid Models
Published on: January 14, 2020
Open-source curation of a pancreatic ductal adenocarcinoma gene expression analysis platform (pdacR) supports a
Luke A Torre-Healy1, Ryan R Kawalerski1,2, Ki Oh1
1Department of Biomedical Informatics, Stony Brook Medicine, Stony Brook, NY, USA.
Abstract:
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease for which potent therapies have limited efficacy. Several studies have described the transcriptomic landscape of PDAC tumors to provide insight into potentially actionable gene expression signatures to improve patient outcomes. Despite centralization efforts from multiple organizations and increased transparency requirements from funding agencies and publishers, analysis of public PDAC data remains difficult. Bioinformatic pitfalls litter public transcriptomic data, such as subtle inclusion of low-purity and non-adenocarcinoma cases. These pitfalls can introduce non-specificity to gene signatures without appropriate data curation, which can negatively impact findings. To reduce barriers to analysis, we have created pdacR ( http://pdacR.bmi.stonybrook.edu , github.com/rmoffitt/pdacR), an open-source software package and web-tool with annotated datasets from landmark studies and an interface for user-friendly analysis in clustering, differential expression, survival, and dimensionality reduction. Using this tool, we present a multi-dataset analysis of PDAC transcriptomics that confirms the basal-like/classical model over alternatives.

