Abstract 1902: PADCAS: A friendly web page for exploratory analysis of pancreatic ductal adenocarcinoma datasets

Abstract

Abstract In recent years, rapidly decreasing sequencing costs have lead to an exponential growth in the availability of both bulk and single-cell transcriptomic data. Compilation of datasets generated from different research groups would allow for many additional or improved analyses, both due to increased computational power and accessibility. However, the process of accurately and effectively integrating datasets in an easily interpretable manner is challenging, and there is an unmet need for additional tools that incorporate multiple datasets in an effective and intuitive manner. Pancreatic ductal adenocarcinoma (PDA) is the third most common cause of cancer mortality, and there are several web portals, including cBioportal or TCGA, that integrate and analyze multi-omics data from multiple large-scale projects. However, these tools fail to integrate datasets generated by independent laboratories and thus leave a large portion of the available PDA data untapped. An tool that incorporates these data into a single easy-to-use source is not only useful but necessary to the PDA research community. Here we present PADCAS (PAncreatic Ductal Cancer AnalysiS), an intuitive tool that allows researchers and clinicians rapid access to multiple datasets related to PDA. Using a friendly visualization and easy-to-use exploratory panels, PADCAS allows the user to perform various statistical analyses investigating the expression of one or multiple genes of interest in normal tissue, primary tumor, or metastatic samples in both bulk and single-cell RNA sequencing data. The tool integrates four public single-cell data sets where users can analyze gene(s) of interest in different context, such as across cell types (fibroblasts vs. macrophages vs. epithelial cells, for example) or tissue conditions. Additionally, regulatory network analyses have been performed and incorporated into the tool for a subset of the datasets, allowing users to investigate and visualize the activity of key proteins in both the ductal and stroma compartments. A complementary novel dataset generated from 23 PDA cell lines is also included with similar analysis options at the gene expression or protein activity level. PADCAS also incorporates bulk RNAseq data generated using laser capture microdissection (LCM-RNA-Seq) at Columbia University. LCM-RNA-Seq dataset includes human PDA, and low grade samples PanIN-1 and IPMN-adenomas), with cross-condition analyses performed at the gene expression level including survival analysis. Finally, all plots generated by PADCAS can be easily downloaded in different formats and sizes. The tool has been designed to be easily maintained and extended as long as new datasets and functionalities are required. Thus, PADCAS represents the first public, free-of-programming resource compilating multiple omics datasets, including single cell RNAseq, for exploratory analysis in PDAC Citation Format: Alvaro Curiel-Garcia, Lorenzo Tomassoni, Lukas J. Vlahos, Carlo H. Maurer, Andrea Califano, Kenneth P. Olive. PADCAS: A friendly web page for exploratory analysis of pancreatic ductal adenocarcinoma datasets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1902.