Identifying novel druggable targets in dedifferentiated liposarcoma using biological networks

Abstract

Dedifferentiated liposarcoma (DDLPS) is a rare and aggressive adult soft tissue malignancy with limited treatment options and high relapse rates following surgical resection and radiotherapeutic interventions. DDLPS are characterised by amplifications of the MDM2 and CDK4 genes. Consequently, these have been targeted with small molecule inhibitors which have shown mixed results in clinical trials; DDLPS is in dire need of more targeted therapy options. This study applies a systems biology approach using gene co-expression network (GCN) analysis to identify novel therapeutic targets in DDLPS.
A GCN was constructed from DDLPS RNA-seq data (TCGA) and was sorted into modules using weighted gene co-expression network analysis (WGCNA) with optimised parameters. Modules of co-expressed genes were ranked by gene significance (GS) that describe disease characteristics, and sub-networks were inspected using a random walk with restart algorithm to identify hub genes. Integration with protein-protein interaction networks (PPIN) (STRING.db) and drug-targe databases (Therapeutic Target Database and Chemical Probes Portal) enabled drug identification.
UBE2C was identified as hub gene in the top-ranked module, with UBA1, acting upstream of UBE2C was found to be targeted by TAK-243 which is a small molecule inhibitor in phase 1 clinical trials. Beyond the identification of drug targets, it was identified that interferon signalling may contribute to a fibrotic tumour microenvironment (TME) and stromal heterogeneity through epigenetic mechanisms. Furthermore, vascular cells show gene expression patterns that indicate vascular mimicry and endothelial to mesenchymal transition. Lastly, enrichments for lipid metabolism, notably cholesterol efflux correlated to stem-cell like tumour features.
The integrative approach used here effectively identified genes associated with DDLPS biology. The ubiquitin-mediated proteasome was implicated through UBA1 targeting by TAK-243. Future work is needed to validate TAK-243 as a drug candidate in DDLPS.

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Identifiers

ORCID for William Tapper: orcid.org/0000-0002-5896-1889

ORCID for Zoë Walters: orcid.org/0000-0002-1835-5868

ORCID for Matthew Rose-Zerilli: orcid.org/0000-0002-1064-5350

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