Defining a Characteristic Gene Expression Set Responsible for Cancer Stem Cell-Like Features in a Sub-Population of Ewing Sarcoma Cells CADO-ES1.

Hotfilder M, Mallela N, Seggewiß J, Dirksen U, Korsching E

Research article (journal) | Peer reviewed

Abstract

One of the still open questions in Ewing sarcoma, a rare bone tumor with weak therapeutic options, is to identify the tumor-driving cell (sub) population and to understand the specifics in the biological network of these cells. This basic scientific insight might foster the development of more specific therapeutic target patterns. The experimental approach is based on a side population (SP) of Ewing cells, based on the model cell line CADO-ES1. The SP is established by flow cytometry and defined by the idea that tumor stem-like cells can be identified by the time-course in clearing a given artificial dye. The SP was characterized by a higher colony forming activity, by a higher differentiation potential, by higher resistance to cytotoxic drugs, and by morphology. Several SP and non-SP cell fractions and bone marrow-derived mesenchymal stem cell reference were analyzed by short read sequencing of the full transcriptome. The double-differential analysis leads to an altered expression structure of SP cells centered around the AP-1 and APC/c complex. The SP cells share only a limited proportion of the full mesenchymal stem cell stemness set of genes. This is in line with the expectation that tumor stem-like cells share only a limited subset of stemness features which are relevant for tumor survival.

Details about the publication

JournalInternational Journal of Molecular Sciences (IJMS) ( Int J Mol Sci)
Volume19
StatusPublished
Release year2018
Language in which the publication is writtenEnglish
DOI10.3390/ijms19123908
KeywordsAP-1; APC/c; Ewing sarcoma; cancer stem cells; gene expression; mesenchymal stem cells; side population; tumor driver cells

Authors from the University of Münster

Hotfilder, Marc
University Children's Hospital - Department of Paediatric Haematology and Oncology (UKM PHO)
Korsching, Eberhard
Institute of Bioinformatics
Mallela, Nikhil Vinod
Institute of Bioinformatics
Seggewiß, Jochen
Institute of Human Genetics