Search PubMedSearch

PubMed · 41098562

A First-in-Class Chemical-Induced Proximity System Achieves Dose-Dependent Control of Tumor Protein P53 Gene Activation in Preclinical Models of Gastric Cancer.

Abstract

The tumor protein P53 (TP53) gene has long been studied in cancer research with genomic and epigenetic aberrations playing a driving role in cancer pathology, yet even after decades of work, only a few methods have been developed to specifically target TP53 therapeutically. Some cancers are driven by loss-of-function TP53 mutations, while others have wild-type TP53 in a transcriptionally repressed state; the latter is exploitable by advances in epigenome editing. In our previous work, we demonstrated that deactivated CRISPR/Cas9 systems (dCas9), combined with an FK-506-binding protein (FKBP) recruitment protein tag and chemical epigenetic modifier (CEM) small molecules, can elicit gene-specific changes in expression in a dose-dependent manner. Here, we describe the development, application, and characterization of the dCas9-FKBP-CEM technology to increase TP53 expression. We demonstrate that catalyzing increased TP53 expression via dCas9-FKBP-CEM87 induced apoptosis, cell cycle arrest, and tumor growth inhibition in a dose-dependent manner in preclinical models of gastric cancer.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Travis J Nelson, Ryan M Kemper, Anna M Chiarella, Stephany Gonzalez Tineo, Michell Carroll, Surya Tripathi, Brandon J Clarke, Xufen Yu, Xiaoping Hu, Aidan J Cooke, Bhavika C Chirumamilla, Alicia Chandler, Evan McGilvary, Samantha G Pattenden, Jian Jin, Daniel J Crona, Nathaniel A Hathaway. 2025-09-08. A First-in-Class Chemical-Induced Proximity System Achieves Dose-Dependent Control of Tumor Protein P53 Gene Activation in Preclinical Models of Gastric Cancer.. https://doi.org/10.1021/acsptsci.5c00402

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Pathway-driven target prioritisation in drug discovery.

Genome-scale association studies and functional screens routinely implicate hundreds of candidate genes per disease, yet only a few will be clinically validated as drug targets. Choosing which to pursue is a central drug-discovery decision that depends on interpreting each candidate in its biological context. Curated pathway databases provide this context, while enrichment analysis applies it at scale, turning gene-level signals from genome-wide association, transcriptomic, proteomic and CRISPR studies into mechanistic hypotheses for prioritisation. This review examines how pathway-based methods inform target prioritisation, the databases and tools available for this purpose, and why pathway co-membership should be viewed as a starting point for validation rather than as evidence of causal involvement.

CRISPR

Screening for dual sgRNAs with comparable indel efficiencies enhances CRISPR-mediated large-fragment deletion.

CRISPR-mediated large-fragment deletion provides a powerful approach for gene clusters, noncoding regions and structural variants, but its broader application is limited by low and variable deletion efficiency. Here, we systematically designed and evaluated 78 sgRNAs targeting nine representative gene clusters (ttn.1-ttn.2 cluster, 7 hox clusters and nppb-nppa cluster), containing 31 large fragments (5 kb-340 kb) to investigate the determinants of deletion efficiency. We found two key rules for achieving high deletion efficiency: (i) using dual sgRNAs with similar indel efficiencies, and (ii) applying a single sgRNA pair rather than multiple sgRNAs. Based on those rules, a 340 kb deletion is detected in the progenies of 95% of founders. Whereas the deletion size showed no significant linear correlation with deletion efficiency within the tested range. Implementing these rules resulted in an average of 70% of founders transmitting deletions across all tested sgRNA pairs. Therefore, screening sgRNAs can effectively enhance CRISPR utility in deletions, thereby facilitating the application of genomic manipulation in vertebrates and other species.

CRISPR

Precision Engineering of Evolution-Resilient Rice against Bacterial Blight.

The persistent conflict between rice and Xanthomonas oryzae pv. oryzae (Xoo), the causal agent of bacterial blight, exemplifies a dynamic genetic arms race in agriculture. The cyclical deployment and erosion of major resistance (R) genes highlight the high adaptive potential of Xoo and the need for strategies that are durable rather than absolute. This review synthesizes a paradigm shift from reactive, single R-gene deployment toward proactive engineering of evolution-resilient resistance. We explore the molecular-genetic basis of Xoo adaptability, including TAL effector diversification, non-TAL virulence functions, genome variation, and immune suppression mechanisms. In response, we propose a framework for durable disease management with three connected components: precision disarmament through editing of susceptibility-gene effector-binding elements and executor/decoy designs; smart induction through targeted delivery and immune priming; and ecological fortification through protective microbiomes. We also discuss the limits, trade-offs, and field-validation requirements of these approaches. Integrating frontier technologies with evolutionary genetics, predictive genomics, and pathogen population dynamics can help develop rice varieties and deployment systems that are more difficult for Xoo populations to overcome.

CRISPR