Given the prevalence of crosstalk among oncogenic pathways and disease heterogeneity, it has become increasingly apparent that combination therapies are required to achieve long-term cure and to minimize development of resistance mutations and escape pathways. The majority of existing combination therapies are developed in an ad hoc fashion, namely one agent at a time, without systematic consideration of potential complex interactions among the gene targets by leveraging disease-specific omics data. Moreover, the existing combination therapies are based on targets of existing drugs, which only represent a small portion of the human proteome. To this end, we hypothesize that systematic identification of synergistic key regulators represents a promising approach for nominating targets of combination therapy. Towards this goal, we will forward engineer a platform for identifying synergistic regulatory nodes in a cancer gene regulatory network as the targets for combination therapy. We will generate disease-specific multi-omics data to construct an integrative gene regulatory network, a pre-requisite for understanding the deregulated gene network in the cancer cells and for developing effective and lasting therapy. We will focus our study on Philadelphia-like acute lymphoblastic leukemia as a proof-of-principle. Our team proposes a novel approach to this problem by leveraging the unique strengths of the investigators in systems biology, genomics, proteomics, and translational research, as well as the large cohort of patient samples available at our institutions. If successful, the proposed framework would be a tremendous advance and paradigm shift to understand genetic interactions among oncogenic pathways for eventual therapeutic intervention.
Combination therapy, by targeting more than one oncoogenic pathways, is an effective strategy to combat drug resistance. This project will develop a critically needed approach for systematic discovery of combination therapeutic targets.
