Geyer, F. H.; Ritter, A.; Kinn-Gurzo, S.; Faehling, T.; Li, J.; Jarosch, A.; Ngo, C.; Vinca, E.; Aljakouch, K.; Orynbek, A.; Ohmura, S.; Kirchner, T.; Imle, R.; Romero-Perez, L.; Bertram, S.; de Alava, E.; Postel-Vilnay, S.; Banito, A.; Sill, M.; Versleijen-Jonkers, Y. M. H.; Mayer, B. F. B.; Ebinger, M.; Sparber-Sauer, M.; Stegmaier, S.; Baumhoer, D.; Hartmann, W.; Krijgsveld, J.; Horst, D.; Delattre, O.; Grohar, P. J.; Gruenewald, T. G. P.; Cidre-Aranaz, F.

Desmoplastic small round cell tumor (DSRCT) is a highly aggressive cancer predominantly occurring in male adolescents and young adults. The lack of a comprehensive understanding on the biology of the disease is paralleled by its dismal survival rates (5-20%). To overcome this challenge, we first identified and prioritized urgently needed resources for clinicians and researchers. Thus, we established genome-wide single-cell RNA-sequencing and bulk proteomic data of in vitro and in vivo-generated knockdown models of the pathognomonic DSRCT fusion oncoprotein (EWSR1::WT1) and combined them with an original systems-biology-based pipeline including patient data and the largest histology collection of DSRCTs and morphological mimics available to date. These novel tools were enriched with curated public datasets including patient- and cell line-derived ChIP-seq, bulk and single-cell RNA-seq studies resulting in a multi-model and multi-omic toolbox for discovery analyses. As a proof of concept, our approach revealed the alpha-2/delta subunit of the voltage-dependent calcium channel complex, CACNA2D2, as a highly overexpressed, super-enhancer driven, direct target of EWSR1::WT1. Single-cell and bulk-level analyses of patient samples and xenografted cell lines highlighted CACNA2D2 as a critical component of our newly established EWSR1::WT1 oncogenic signature, that can be employed to robustly identify DSRCT in reference sets. Finally, we show that CACNA2D2 is a highly sensitive and specific single biomarker for fast, simple, and cost-efficient diagnosis of DSRCT. Collectively, we establish a large-scale multi-omics dataset for this devastating disease and provide a blueprint of how such toolbox can be used to identify new and clinically relevant diagnostic markers, which may significantly reduce misdiagnoses, and thus improve patient care.