Journal Article

Single-cell transcriptome analysis of tumor and stromal compartments of pancreatic ductal adenocarcinoma primary tumors and metastatic lesions

Fraser, Cory, Fong, Yuman, Woo, Yanghee, Han, In Woong, Amini, Albert, Han, Haiyong, Park, Joon Oh, Lin, Wei, Borazanci, Erkut H., Heo, Jin Seok, Von Hoff, Daniel D., Noel, Pawan, Jameson, Gayle S., Lee, Jeeyun, Steinbach, Margaux, Cridebring, Derek

2020

Overview

Background Solid tumors such as pancreatic ductal adenocarcinoma (PDAC) comprise not just tumor cells but also a microenvironment with which the tumor cells constantly interact. Detailed characterization of the cellular composition of the tumor microenvironment is critical to the understanding of the disease and treatment of the patient. Single-cell transcriptomics has been used to study the cellular composition of different solid tumor types including PDAC. However, almost all of those studies used primary tumor tissues. Methods In this study, we employed a single-cell RNA sequencing technology to profile the transcriptomes of individual cells from dissociated primary tumors or metastatic biopsies obtained from patients with PDAC. Unsupervised clustering analysis as well as a new supervised classification algorithm, SuperCT, was used to identify the different cell types within the tumor tissues. The expression signatures of the different cell types were then compared between primary tumors and metastatic biopsies. The expressions of the cell type-specific signature genes were also correlated with patient survival using public datasets. Results Our single-cell RNA sequencing analysis revealed distinct cell types in primary and metastatic PDAC tissues including tumor cells, endothelial cells, cancer-associated fibroblasts (CAFs), and immune cells. The cancer cells showed high inter-patient heterogeneity, whereas the stromal cells were more homogenous across patients. Immune infiltration varies significantly from patient to patient with majority of the immune cells being macrophages and exhausted lymphocytes. We found that the tumor cellular composition was an important factor in defining the PDAC subtypes. Furthermore, the expression levels of cell type-specific markers for EMT + cancer cells, activated CAFs, and endothelial cells significantly associated with patient survival. Conclusions Taken together, our work identifies significant heterogeneity in cellular compositions of PDAC tumors and between primary tumors and metastatic lesions. Furthermore, the cellular composition was an important factor in defining PDAC subtypes and significantly correlated with patient outcome. These findings provide valuable insights on the PDAC microenvironment and could potentially inform the management of PDAC patients.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Adenocarcinoma / Algorithms / Analysis / Bioinformatics / Biomedical and Life Sciences / Biomedicine / Cancer / Cancer metastasis / Cancer Research / Carcinoma, Pancreatic Ductal - genetics / Carcinoma, Pancreatic Ductal - mortality / Carcinoma, Pancreatic Ductal - pathology / Care and treatment / Cell Line, Tumor / Cellular heterogeneity / Computational Biology / Drug resistance / Endothelial cells / Fibroblasts / Gene expression / Gene Expression Profiling - methods / Gene Expression Regulation, Neoplastic / Genetic Heterogeneity / Genomics / High-Throughput Nucleotide Sequencing / Human Genetics / Humans / Kaplan-Meier Estimate / Lesions / Lymphocytes / Macrophages / Medical research / Medicine/Public Health / Metabolomics / Metastases / Metastasis / Ontology / Pancreas / Pancreatic cancer / Pancreatic cancer subtypes / Pancreatic Neoplasms / Pancreatic Neoplasms - genetics / Pancreatic Neoplasms - mortality / Pancreatic Neoplasms - pathology / Patients / Prognosis / Quality control / Ribonucleic acid / RNA / RNA sequencing / Sequence analysis / Single-Cell Analysis - methods / Single-cell RNA sequencing / Solid tumors / Stromal cells / Stromal Cells - metabolism / Systems Biology / Transcriptome / Transcriptomics / Tumor cells / Tumor Microenvironment - genetics / Tumors / Visualization