Cell type-specific transcriptomics of esophageal adenocarcinoma as a scalable alternative for single cell transcriptomics
| Autor: | Jana Wittig, Hakan Alakus, Axel M. Hillmer, Seung-Hun Chon, Sören Büsker, Heike Löser, Kat Folz-Donahue, Wolfgang Schröder, Alexander Quaas, Hans A. Schlößer, Christiane J. Bruns, Reinhard Büttner, Marek Franitza, Isabel Garcia-Marquez, Patrick Sven Plum, Oscar Velazquez Camacho, Christina B. Wölwer, Martin Thelen, Max Krämer, Janine Altmüller |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Male
0301 basic medicine Cancer Research Cell type esophageal adenocarcinoma Esophageal Neoplasms Cell Adenocarcinoma lcsh:RC254-282 CD19 Transcriptome transcriptomics 03 medical and health sciences 0302 clinical medicine Biomarkers Tumor Genetics medicine tumor microenvironment Humans CD90 Research Articles Aged Aged 80 and over Principal Component Analysis Tumor microenvironment cancer‐associated fibroblasts Mucous Membrane biology Gene Expression Profiling General Medicine Middle Aged Cell sorting lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens Gene Expression Regulation Neoplastic Gene Ontology 030104 developmental biology medicine.anatomical_structure Oncology 030220 oncology & carcinogenesis Cancer research biology.protein Molecular Medicine Cancer-Associated Fibroblasts Female Technology Platforms Single-Cell Analysis cell types Research Article |
| Zdroj: | Mol Oncol Molecular Oncology Molecular Oncology, Vol 14, Iss 6, Pp 1170-1184 (2020) |
| Popis: | Single‐cell transcriptomics have revolutionized our understanding of the cell composition of tumors and allowed us to identify new subtypes of cells. Despite rapid technological advancements, single‐cell analysis remains resource‐intense hampering the scalability that is required to profile a sufficient number of samples for clinical associations. Therefore, more scalable approaches are needed to understand the contribution of individual cell types to the development and treatment response of solid tumors such as esophageal adenocarcinoma where comprehensive genomic studies have only led to a small number of targeted therapies. Due to the limited treatment options and late diagnosis, esophageal adenocarcinoma has a poor prognosis. Understanding the interaction between and dysfunction of individual cell populations provides an opportunity for the development of new interventions. In an attempt to address the technological and clinical needs, we developed a protocol for the separation of esophageal carcinoma tissue into leukocytes (CD45+), epithelial cells (EpCAM+), and fibroblasts (two out of PDGFRα, CD90, anti‐fibroblast) by fluorescence‐activated cell sorting and subsequent RNA sequencing. We confirm successful separation of the three cell populations by mapping their transcriptomic profiles to reference cell lineage expression data. Gene‐level analysis further supports the isolation of individual cell populations with high expression of CD3, CD4, CD8, CD19, and CD20 for leukocytes, CDH1 and MUC1 for epithelial cells, and FAP, SMA, COL1A1, and COL3A1 for fibroblasts. As a proof of concept, we profiled tumor samples of nine patients and explored expression differences in the three cell populations between tumor and normal tissue. Interestingly, we found that angiogenesis‐related genes were upregulated in fibroblasts isolated from tumors compared with normal tissue. Overall, we suggest our protocol as a complementary and more scalable approach compared with single‐cell RNA sequencing to investigate associations between clinical parameters and transcriptomic alterations of specific cell populations in esophageal adenocarcinoma. Little is known about the interactions between the different intratumoral cell types, that is, epithelial tumor cells, cancer‐associated fibroblasts, and immune cells. We developed a scalable and cost‐effective workflow to separate these cell types from esophageal adenocarcinoma (EAC) biopsies using fluorescence‐activated cell sorting and subsequent RNA sequencing. Using this approach, we characterize these cell types in EAC and normal tissue. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|