Dysregulated heparan sulfate proteoglycan metabolism promotes Ewing sarcoma tumor growth
Abstract
The Ewing sarcoma family of tumors is a group of malignant small round blue cell tumors (SRBCTs) that affects children, adolescents, and young adults. The tumors are characterized by reciprocal chromosomal translocations that generate chimeric fusion oncogenes, the most common of which is EWSR1-FLI1. Survival is extremely poor for patients with metastatic or relapsed disease, and no molecularly-targeted therapy for this disease currently exists. The absence of a reliable genetic animal model of Ewing sarcoma has impaired investigation of tumor cell/microenvironmental interactions in vivo. We have developed a new genetic model of Ewing sarcoma based on Cre-inducible expression of human EWSR1-FLI1 in wild type zebrafish, which causes rapid onset of SRBCTs at high penetrance. The tumors express canonical EWSR1-FLI1 target genes and stain for known Ewing sarcoma markers including CD99. Growth of tumors is associated with activation of the MAPK/ERK pathway, which we link to dysregulated extracellular matrix metabolism in general and heparan sulfate catabolism in particular. Targeting heparan sulfate proteoglycans with the specific heparan sulfate antagonist Surfen reduces ERK1/2 signaling and decreases tumorigenicity of Ewing sarcoma cells in vitro and in vivo. These results highlight the important role of the extracellular matrix in Ewing sarcoma tumor growth and the potential of agents targeting proteoglycan metabolism as novel therapies for this disease.
Data availability
Proteomics data have been deposited in Dryad (doi:10.5061/dryad.x95x69pj8)
-
Proteomics analysis of normal and EWSR1-FLI1-expressing embryos/tissueDryad Digital Repository, doi:10.5061/dryad.x95x69pj8.
-
Proteomics analysis of normal and EWSR1-FLI1-expressing embryos/tissueDryad Digital Repository, doi:10.5061/dryad.x95x69pj8.
-
Inflammatory gene profiling of Ewing sarcoma family of tumors (set B)NCBI Gene Expression Omnibus, GSE17674.
-
Gene Expression in Human RhabdomyosarcomaNCBI Gene Expression Omnibus, GSE108022.
Article and author information
Author details
Funding
National Cancer Institute (U54CA231649-01)
- James F Amatruda
1 Million 4 Anna
- James F Amatruda
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols of the University of Southern California, protocol number 21150.
Copyright
© 2022, Vasileva et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,022
- views
-
- 271
- downloads
-
- 23
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Cancer Biology
- Evolutionary Biology
In asexual populations that don’t undergo recombination, such as cancer, deleterious mutations are expected to accrue readily due to genome-wide linkage between mutations. Despite this mutational load of often thousands of deleterious mutations, many tumors thrive. How tumors survive the damaging consequences of this mutational load is not well understood. Here, we investigate the functional consequences of mutational load in 10,295 human tumors by quantifying their phenotypic response through changes in gene expression. Using a generalized linear mixed model (GLMM), we find that high mutational load tumors up-regulate proteostasis machinery related to the mitigation and prevention of protein misfolding. We replicate these expression responses in cancer cell lines and show that the viability in high mutational load cancer cells is strongly dependent on complexes that degrade and refold proteins. This indicates that the upregulation of proteostasis machinery is causally important for high mutational burden tumors and uncovers new therapeutic vulnerabilities.
-
- Cancer Biology
- Cell Biology
Understanding the cell cycle at the single-cell level is crucial for cellular biology and cancer research. While current methods using fluorescent markers have improved the study of adherent cells, non-adherent cells remain challenging. In this study, we addressed this gap by combining a specialized surface to enhance cell attachment, the FUCCI(CA)2 sensor, an automated image analysis pipeline, and a custom machine learning algorithm. This approach enabled precise measurement of cell cycle phase durations in non-adherent cells. This method was validated in acute myeloid leukemia cell lines NB4 and Kasumi-1, which have unique cell cycle characteristics, and we tested the impact of cell cycle-modulating drugs on NB4 cells. Our cell cycle analysis system, which is also compatible with adherent cells, is fully automated and freely available, providing detailed insights from hundreds of cells under various conditions. This report presents a valuable tool for advancing cancer research and drug development by enabling comprehensive, automated cell cycle analysis in both adherent and non-adherent cells.