Abstract 4403: Predicting therapeutic sensitivities from molecular interaction network rewiring of RUNX1-RUNX1T1 fusion

Abstract

Abstract Cancer driver events are thought to converge on a subset of molecular systems that regulate the hallmark behaviors of cancer cells. However, the complexity of biological systems makes it difficult to evaluate the impact of individual mutations at the level of such cellular processes and behaviors. In order to overcome this, we propose to study the effects of cancer mutations by modeling them as perturbations to molecular network architectures, allowing network-based prediction of drug sensitivities. We first built the infrastructure to study protein-protein interaction network rewiring by variants by mapping different classes of variants onto edges of the PPI network using protein structure information. Mutations that cause a larger disruption to the underlying network architecture can create more vulnerabilities that can be used as drug targets. Therefore, in this project we decided to focus on fusion events which can interfere with many interactions of their parent proteins. In order to assess the disruption that can be caused by fusion events, we collected 2,699 cancer fusion proteins and demonstrated the centrality of their parents within a high confidence human PPI network of 12,047 proteins. This indicates that the parent proteins of fusion genes tend to interact with more protein partners and are more likely to display network topological properties suggesting a role in information transduction in molecular interaction networks. As leukemias are often impacted by chromosomal aberrations that can result in fusion and tend to harbor fewer somatic mutations than solid tumors, they provide a good setting to develop a network-based model to study fusion events in the context of drug responses. Therefore, we chose to study the RUNX1-RUNX1T1 translocation, t(8;21)(q22;q22), in AML which is thought to be a pre-leukemic event that can result in tumors after receiving additional mutations. This translocation replaces the transactivation domain of RUNX1 with most of the RUNX1T1 protein which changes its function as an essential transcriptional activator of hematopoiesis. In order to study the transcriptional effects of RUNX1-RUNX1T1 fusion on the underlying interactome network architecture, U937T cells induced with RUNX1-RUNX1T1 fusion were grown in triplicate and RNA was harvested prior to induction and at certain times post-induction. Wild type U937T cells with no perturbation serve as negative control. RNA sequencing was performed, followed by alignment of the reads to the reference genome. A differential gene expression analysis showed that 1,582 genes are differentially expressed in fusion induced cells versus wild type at FDR<0.05, among which 47 of them encode proteins in RUNX1-RUNX1T1 subnetwork. Gene set enrichment analysis using these genes revealed that 30 gene sets are significantly enriched at nominal p-value<0.01. Citation Format: Kivilcim Ozturk, Hannah Carter. Predicting therapeutic sensitivities from molecular interaction network rewiring of RUNX1-RUNX1T1 fusion [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4403.