Abstract 2067: QUANTROseq, a transcriptomic based drug discovery platform using time-resolved gene expression profiling: Identification of inhibitors and degraders of transcription factors and cell signaling regulators
Authors: Sabò Arianna , Griesmayr Nina Fasching , Neumann Tobias , Manzenreither Raphael , Ivankovic Maja , Costa Rodrigo Pacheco Valamatos , Rieser Sarah , Scinicariello Sara , Triska Petr , Stingeder Anna , Gruss Astrid , Cubero Ryan , Frank Olga , Sowemimo Ivica , Kirchgatterer Paul , Cantoran Adriana , Ameres Stefan , Zuber Johannes , Bauer Michael 
Published: March 2024

Abstract
Integrative analyses of CRISPR/Cas9 screening datasets from different sources revealed - besides known oncogenes - a series of transcriptional master regulators as most prominent context-specific dependencies in cancer that remained largely inaccessible to conventional drug discovery approaches. New chemical entities (NCEs) that specifically interfere with a transcription factor (TF) at any level should induce and be detectable based on selective effects on their primary biochemical activity - i.e., the transcriptional activation of specific target genes. However, the definition of direct targets of a TF and, more generally, the unbiased detection of direct transcriptional effects has remained challenging due to the limited time resolution of conventional techniques for gene perturbation and transcriptional profiling. To overcome this limitation, QUANTRO Therapeutics relies on SLAMseq technology that, by metabolic labeling de novo-synthesized RNA immediately after intervention and conserving the information for later readout, provides unprecedent time-resolution in transcriptomic analysis.
Aiming to target previously undruggable targets, we set out to first build definitive knowledge around their direct effect on transcription, inducing their quick protein degradation through the auxin-inducible degron (AID) technology followed by immediate transcriptional readout though SLAMseq -before any secondary, confounding effect could appear in the cell.
The targets´ mRNA fingerprints produced are then used as a reference and cross-compared with existing and new chemical entities to:
(i) benchmark the real mode of action of existing drugs; (ii) identify new drug candidates that specifically interfere with disease-causing transcriptional programs in cancer; (iii) interrogate the efficiency, selectivity, and potency of drug candidates during Hit-validation and Hit-to-Lead activities.
Proof of concept data demonstrated that time-resolved transcriptional profiling can reveal drugs´ mode of action with unprecedent precision and sensitivity, when drugs act on Targets that have a direct effect on transcriptional regulation - such as TFs and signaling pathways. Building on this knowledge, QUANTRO Therapeutics unleashed the unique potential of mRNA fingerprinting technology for HTS-compatible drug discovery by (1) establishing scalable and automated workflows for metabolic RNA labeling, treatment of cells, and RNA extraction; (2) developing algorithms for combinatorial mRNA fingerprint-readout that allow for the simultaneous assessment of TF signatures by multiplexed targeted RNA sequencing (QUANTROseq), thus transforming the precision and scope of cell-based compound screens.
Citation Format: Arianna Sabò, Nina Fasching Griesmayr, Tobias Neumann, Raphael Manzenreither, Maja Ivankovic, Rodrigo Pacheco Valamatos Costa, Sarah Rieser, Sara Scinicariello, Petr Triska, Anna Stingeder, Astrid Gruss, Ryan Cubero, Olga Frank, Ivica Sowemimo, Paul Kirchgatterer, Adriana Cantoran, Stefan Ameres, Johannes Zuber, Michael Bauer. QUANTROseq, a transcriptomic based drug discovery platform using time-resolved gene expression profiling: Identification of inhibitors and degraders of transcription factors and cell signaling regulators [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2067.