Our Science:

Targeting dysregulated transcription factors in cancer

Addressing the complexity of oncogenic TRNs requires a sophisticated and holistic approach to targeting cancer biology. TRNs encompass hundreds of proteins that function in a coordinated fashion to orchestrate specific gene expression programs that control development and function of healthy cells. Dysregulated TRNs resulting from aberrant transcription factor expression or activity are frequently responsible for reprogramming healthy cells into cancerous tumor cells. We apply computational biology to map the TRNs and identify the critical nodes and gene expression signatures that drive cancer. We believe that these critical nodes present attractive targets for therapeutic intervention using a biomarker-driven precision medicine strategy.

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MAP: Targeting oncogenic TRNs

We begin with selection of an oncogenic transcription factor with a well-defined and central role in driving a particular type of cancer, and for which precision medicine strategies are available to select patients for therapy based on relevant biomarkers. We leverage our computational biology expertise to map the structure of oncogenic TRNs defined by specific transcription factors and identify the gene expression signature of selective transcription factor modulation that can be carried forward into clinical translation.

Hit prioritization based on gene expression signature

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SCREEN: SMM Platform

We apply our SMM product engine to conduct high throughput binding assays against traditionally undruggable target proteins in tumor cell lysate. By conducting screens in cell lysate, we maintain endogenous protein structures and complexes and can probe the entire target protein interactome (often dozens or hundreds of protein-protein interactions) in a single assay.

Hits identified in SMM lysate screens may be binders of the target proteins or its immediate co-factors, and may regulate the target protein through a variety of direct or indirect mechanisms including inhibition, stabilization or destabilization of target proteins or complexes. This unbiased approach may produce hits that directly engage either historically tractable targets or those considered more challenging such as transcription factors. We prioritize hits that selectively replicate the gene expression signature of transcription factor modulation.

Small molecule microarray (SMM) discovery platform

  • 240,000 compound library covalently printed on slides
  • Allows screening of cell lysates/nuclear extracts
    • Target protein in native conformation and context
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OPTIMIZE:

From hit to product candidate

We focus on understanding the connection between molecular characteristics and target engagement to refine pharmacological properties of hits from our SMM platform to match the desired clinical product profile.

VALIDATE:

Rapid clinical proof-of-concept

We leverage our translational expertise to design and execute hypothesis-driven clinical trials in biomarker-selected patient populations to rapidly achieve clinical proof of concept and inform a more efficient product approval strategy.

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Publications

Richters, A, et al. Targeting oncogenic transcription in prostate cancer with a novel, oral bioavailable, and ultra-selective CDK9 inhibitor AACR poster, 2020

Struntz N, et al. Stabilization of the Max Homodimer with a Small Molecule Attenuates Myc-Driven Transcription. Cell Chem. Biol. 2019, 26, 1-13

Walker A et al. Results of a Phase 1b/2 Study of Entospletinib Monotherapy and In Combination With Induction Chemotherapy In Newly Diagnosed Patients With Acute Myeloid Leukemia. EHA abstract S118, 2018

Tyner, J et al. Functional genomic landscape of acute myeloid leukemia. Nature. 2018, 562, 526-552

Mohr, S et al. Hoxa9 and Meis1 Cooperatively Induce Addition to Syk Signaling by Suppressing miR-146a in Acute Myeloid Leukemia. Cancer Cell. 2017, 31, 549-562

Pop, M et al. Probing Small-Molecule Microarrays. Curr. Protoc. Chem. Biol. 2014, 6, 209-220

Bradner, J et al. A method for the covalent capture and screening of diverse small molecules. Nature Protocols. 2006, 1(5), 2344-2352