Metastatic castration-resistant prostate cancer (mCRPC) remains driven by persistent androgen receptor (AR) signaling, including ligand-independent activity mediated by AR splice variants such as AR-V7. These variants are not addressed by current therapies, highlighting the need for novel approaches to suppress AR signaling.Here, we describe a first-in-class strategy targeting the RNA-binding protein NONO using TF-Scan, a mass spectrometry–based functional proteomics platform that quantifies chromatin-associated protein networks in live cells. NONO is involved in the alternative splicing of a subset of mRNAs, including AR, enabling a unique opportunity to target all AR isoforms, including mutants and splice variants.Using TF-Scan, we identified a covalent small-molecule series that selectively engages NONO at C145 in prostate cancer cells. Mechanistically, these compounds act as RNA molecular glues, modulating the association of NONO to AR pre-mRNA and altering its processing. This results in reduced accumulation of AR mRNA isoforms and decreased levels of both full-length AR and AR-V7 proteins.TF-Scan profiling demonstrates a concomitant reduction in chromatin-bound AR and HOXB13, confirming pathway suppression at the functional level. Through iterative medicinal chemistry guided by proteome-wide selectivity and functional readouts, we optimized compounds with sub-micromolar potency and robust anti-proliferative activity in AR-dependent models. Importantly, using an inactive enantiomer and RNA-seq, we demonstrate that our compounds are highly selective, perturbing a restricted subset of genes, including AR.Together, these findings establish NONO as a tractable target in mCRPC and introduce RNA molecular gluing as a novel modality to suppress AR signaling. More broadly, this work highlights the power of mass spectrometry–based functional proteomics to enable drug discovery against transcriptional regulators and RNA-processing proteins.
Brian McEllin, Daniele Canzani, Lindsay Pino, David Moebius, Gaelle Mercenne, Alexander Federation. Targeting NONO as a therapeutic strategy for metastatic castration-resistant prostate cancer (mCRPC) [abstract]. In: Proceedings of AACR Drug Discovery and Development (AACR D3) Conference; 2026 Jul 21-24; Boston, MA. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(14_Suppl):Abstract nr B096.
Brian McEllin, D. Canzani, Lindsay K. Pino et al.· Clinical Cancer Research· 0 citations
A common outcome of quantitative mass spectrometry-based proteomic and phosphoproteomic experiments is a list of proteins that are differentially abundant between conditions. However, biological interpretation requires evaluation in the context of prior knowledge of biological mechanisms and protein function. One approach to facilitate mechanistic biological interpretation is to integrate such lists with biological network databases, built from manually curated resources and text mining systems. This manuscript automates this process with MSstatsBioNet, a Bioconductor package that integrates MSstats, a family of open-source packages for detecting differentially abundant proteins, and INDRA, a system that extracts biomolecular networks from biomedical literature using text mining and merges those networks with the content of curated knowledge bases. Taking as input a list of differentially abundant proteins from MSstats, MSstatsBioNet retrieves a protein subnetwork from INDRA and overlays experimental fold changes onto the underlying subnetwork. Users can then interact with the network and overlaid data, interrogating primary literature evidence to construct granular mechanistic narratives for iterative hypothesis generation. We demonstrate the utility of this approach with three case studies, two measuring changes in protein abundance and one measuring changes in phosphorylation.
Anthony Wu, Devon Kohler, Pruthvi Prakash Navada et al.· bioRxiv· 0 citations
Ptarmigan-1 is presented, a contrastive model that co-embeds the residues of a protein with candidate small molecules in a shared latent space, from sequence and two-dimensional chemistry alone, and without ever constructing a pose.
W. Fondrie, D. Canzani, L. Tatka et al.· bioRxiv· 1 citation
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