Abstract 5353: Single cell RNA sequencing of pancreatic ductal adenocarcinoma reveals tumor heterogeneity
Authors: Pawan Noel, Wei Lin, Erkut Borazanci, Albert Amini, Ruben Muñoz, Emily Rodela, Serina Ng, Daniel Von Hoff, Haiyong Han
Journal: Cancer Research (2018)

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) accounts for ~95% of pancreatic cancer cases and is currently the 3rd leading cause of adult cancer deaths in the US. Due to the lack of methods for early detection and limited treatment options, PDAC has a dismal 5-year survival rate at just &amp;lt;9%. The desmoplastic PDAC tumor microenvironment (TME) is complex and heterogeneous. With recent advances in technology, the characterization of tumors to investigate cellular diversity and evolution in cancer is rapidly accelerating. Here we employed single cell RNA sequencing (scRNA-Seq) to profile transcriptomes of individual cells from dissociated pancreatic tumors isolated from either patients or transgenic mice developing spontaneous PDAC (KPC). This approach elucidated the cellular makeup of individual tumor to reveal distinct cell types like epithelial, endothelial and immune cells, cancer associated fibroblasts (CAFs) and cells undergoing epithelial-to-mesenchymal transition (EMT). Deregulated pathways specific to distinctly identified cell populations were also mapped. Methods: Freshly harvested human or mouse PDAC tumors were mechanically and enzymatically dissociated to single cells using a Miltenyi gentleMACS Tissue Dissociator. The 10X Genomics Chromium Single Cell 3′ Solution was employed for capture, amplification and labeling of mRNA from single cells and for library preparation. scRNA-Seq was performed on Illumina HiSeq 2500. Custom R packages were used for clustering and bioinformatics data analyses. Results: Viability of single cell suspensions used for library preps from all samples was &amp;gt;81%. By unsupervised clustering of the scRNA-Seq matrix and using known signature genes for various cell types we revealed the cellular heterogeneity in a human PDAC to identify distinct cell types. These included epithelial tumor cells (EPCAM+, KRT19+); CD133+ tumor stem cells; CAFs (COL5A1+, COL6A2+, SPARC+); endothelial cells CDH5+ VWF+; and CD45 (PTPRC)+ immune cells also positive for CD3D, CD2, FCGR2A; and cells undergone EMT (CDH2+, ITGA5+, SNAI2+). Using a similar strategy, mouse PDAC diversity was represented by epithelial and EMT tumor cells, CAFs, endothelial cells, macrophages and MDSCs. KRAS and glycolysis signaling pathways in epithelial tumor cells, while hypoxia in the EMT cluster were up regulated. KPC tumors differed in the extent of immune cell infiltration, with a low influx in the smaller versus large tumor, both perhaps representing distinct stages of tumor progression. Conclusions: Our data supports high throughput scRNA-Seq of solid tumors like PDAC as a powerful method to probe and elucidate the underlying tumor heterogeneity. Understanding diversity and complexity of the PDAC TME in individual tumors may help identify unique therapeutic targets and potentially inform treatment/maintenance strategies for patients with advanced disease. Citation Format: Pawan Noel, Wei Lin, Erkut Borazanci, Albert Amini, Ruben Muñoz, Emily Rodela, Serina Ng, Daniel Von Hoff, Haiyong Han. Single cell RNA sequencing of pancreatic ductal adenocarcinoma reveals tumor heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5353.