Abstract 486: A systems biology approach to defining tumor heterogeneity, prognostic and targetable master regulator protein signatures from bulk and single cell RNA-seq in diffuse midline glioma (DMG)
Authors: Fernández Ester Calvo , Wang Junqiang , Griffin Aaron T. , Szalontay Luca , Zacharoulis Stergios , Pavisic Jovana , Califano Andrea 
Published: June 2022

Despite major advances in molecular profiling and numerous clinical trials, diffuse midline glioma (DMG) remains a fatal disease with median survival of only ~9 months and no identified effective drugs. To address this challenge, we leveraged network-based methodologies to dissect the heterogeneity of DMG tumors and to discover Master Regulator (MR) proteins representing pharmacologically accessible, mechanistic determinants of molecularly distinct DMG cell states. The study has produced the first DMG-specific regulatory network, reverse-engineered from 122 publicly available pediatric DMG RNA-seq profiles with ARACNe (Basso et al. Nat Genet 2005). Using this network, we measured protein activity for each sample via VIPER (Alvarez et al., Nat Genet 2016). Activity-based clustering identified 2 clusters, characterized by significant overall survival difference (&gt;1 year, p-val=0.02 by χ2 analysis). Protein activity signatures were not significantly associated with tumor location and Histone3 mutation status. The most aberrantly activated MR proteins across all DMG patients (i.e., TOP2A, CENPF, BUB1B, FOXM1, GTSE1, MKI67, and E2F8), relative to normal caudate tissue from GTEx, were highly enriched in cell cycle regulation members, with samples in the worst outcome cluster showing significantly higher activity. Pharmacologically accessible MRs found to be significantly activated in subsets of patients (p-val&lt;10E-5) include TOP2A, CHEK1, CDK2, and EZH2.

To dissect DMG intra-tumor heterogeneity, we measured protein activity from published single-cell RNA-seq profiles of 6 DMG patients, using single-cell based regulatory networks. Activity-based analysis of tumor cells identified 8 clusters representing distinct differentiation and proliferation stages—i.e. astrocyte-like, oligodendrocyte-like, and multiple oligodendrocyte precursor cell (OPC)-like subpopulations. Consistent with bulk-based findings, these included an OPC-like-cycling population presenting highly aberrant activity of proliferative MRs (i.e. TOP2A, CENPF, FOXM1, E2F8, ZWINT, and CCNA2), suggesting this as a key DMG regulatory module (Tumor Checkpoint). We are working to define targetable MRs in these subpopulations, and generating RNA-seq profiles of SU-DIPG-VI and SF8628, two DMG cell lines showing protein activity similarity to &gt;95% of patient samples by enrichment analysis (p-val &lt; 10E-5), following perturbation with ~400 oncology drugs. This will allow us to identify drugs capable of inducing tumor demise by inverting the activity of the MRs of each tumor subpopulation, using the NY Dept. of Health approved OncoTreat algorithm (Alvarez et al., Nat Genet 2018). We are currently finalizing and validating both MR and drug predictions to nominate novel, much-needed therapeutic strategies.

Citation Format: Ester Calvo Fernández, Junqiang Wang, Aaron T. Griffin, Luca Szalontay, Stergios Zacharoulis, Jovana Pavisic, Andrea Califano. A systems biology approach to defining tumor heterogeneity, prognostic and targetable master regulator protein signatures from bulk and single cell RNA-seq in diffuse midline glioma (DMG) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 486.