Reverse Engineering of Ewing Sarcoma Regulatory Network Uncovers PAX7 and RUNX3 as Master Regulators Associated with Good Prognosis.

Abstract

Simple SummaryEwing Sarcoma is a rare cancer that, when localized, has an overall five-year survival rate of 70%. Patients with metastasis have a five-year survival rate of 15 to 30%. Early analysis of patient prognosis can be crucial to provide adequate treatment and increase chances of survival. Besides, it is a disease with several gaps in our understanding, including regulation of genes and which transcription factors are master regulators. This work addresses these two topics by inferring gene regulatory networks that allow us to identify putative master regulators to predict patient prognosis. We were able to identify two sets of master regulators that can predict good and bad patient outcomes.Ewing Sarcoma (ES) is a rare malignant tumor occurring most frequently in adolescents and young adults. The ES hallmark is a chromosomal translocation between the chromosomes 11 and 22 that results in an aberrant transcription factor (TF) through the fusion of genes from the FET and ETS families, commonly EWSR1 and FLI1. The regulatory mechanisms behind the ES transcriptional alterations remain poorly understood. Here, we reconstruct the ES regulatory network using public available transcriptional data. Seven TFs were identified as potential MRs and clustered into two groups: one composed by PAX7 and RUNX3, and another composed by ARNT2, CREB3L1, GLI3, MEF2C, and PBX3. The MRs within each cluster act as reciprocal agonists regarding the regulation of shared genes, regulon activity, and implications in clinical outcome, while the clusters counteract each other. The regulons of all the seven MRs were differentially methylated. PAX7 and RUNX3 regulon activity were associated with good prognosis while ARNT2, CREB3L1, GLI3, and PBX3 were associated with bad prognosis. PAX7 and RUNX3 appear as highly expressed in ES biopsies and ES cell lines. This work contributes to the understanding of the ES regulome, identifying candidate MRs, analyzing their methilome and pointing to potential prognostic factors.