Introduction Pancreatic Ductal Adenomcarcinoma (PDAC) is one of the most lethal forms of cancer with a five-year survival rate of 8%. Genetic alterations such as activating mutations in KRAS and inactivating mutations in CDKN2A and TP53, accompanied with changes in surrounding stroma, are involved in progression of pancreatic cancer. However, since these alterations are not well understood at the single cell level, we have been performing single-cell RNA-sequencing (scRNA-seq) analysis of PDAC.
Material and methods We performed scRNA-seq and histological analysis of a resected human PDAC tumour specimen using the 10X platform and single cell cDNA library construction kit followed by sequencing on a HiSeq4000 (3,640 cells; over 10^5 reads per cell). Bioinformatic analysis included both standard pipelines and custom analysis of TCGA PDAC signatures as first described in (Raphael BJ, 2017; Cancer Cell 32, 2185).
Results and discussions Nine distinct cell types were identified by K-means clustering and differential expression analysis. In agreement with histological evidence, slightly less than 10% of the cells were actual ductal carcinoma cells, and the rest were either normal epithelial cells or stromal cells. The TCGA signature identified these ductal carcinoma cells as belonging to the basal subtype of PDAC. Individual clusters included normal pancreatic islet cells, B-lymphocytes, macrophages, mast cells, cells that resemble schwann cells, cancer-associated fibroblasts (CAFs), and normal fibroblasts. Bioinformatic analysis suggested two subtypes of CAFs with different functions: extracellular matrix production, and immunomodulatory, in agreement with a prior report (Ohlund D, Journal of Experimental Medicine, 2017;214(3):579). Histological analysis confirmed presence of the major cell types. Additionally, an epithelial-like cell cluster was observed and further histological analysis is underway to confirm the identity of the same.
Conclusion sc-RNAseq of a resected tumour specimen from a PDAC patient revealed the presence of diverse cell types in addition to tumour cells such as different immune cells, different types of fibroblasts, and a previously undescribed pancreatic cell type. Further application of this technology should yield additional insights and lead to the discovery of novel biomarkers for analysis of pancreatic cancer.
This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Statistics from Altmetric.com
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.