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Ramamoorthy, G.

Publications and source records attributed to Ramamoorthy, G..

2 recordsLinked to original sources

Abbapolin inhibitors of the PLK1 PBD as Prostate Cancer Therapeutics, in vivo activity and synergy with androgen therapy

Polo-like kinase 1 (PLK1) is an established therapeutic target in cancer; however, ATP-competitive kinase inhibitors have shown limited clinical success because of toxicity, acquired resistance, and incomplete inhibition of non-catalytic PLK1 functions. Targeting the Polo-box domain (PBD), which regulates PLK1 localization and substrate recognition, represents an alternative therapeutic strategy but has been hindered by the lack of selective, cell-active small molecules. Here, the optimization and biological characterization of abbapolins, a series of non-peptidic PLK1 PBD inhibitors developed using the REPLACE strategy are described. Structure-guided optimization and screening across the NCI-60 cancer cell panel identified compounds with preferential activity against prostate cancer cells. Proteomic analyses demonstrated that cellular sensitivity correlated with PLK1 protein abundance, supporting an on-target mechanism of action. Abbapolins directly engaged PLK1 in cells, induced selective degradation of endogenous PLK1, and suppressed long-term clonogenic growth. Lead compounds demonstrated favorable pharmacokinetic properties and significantly inhibited prostate tumor growth in xenograft models without detectable systemic toxicity. PLK1 abundance was significantly reduced in treated tumors and correlated with tumor response, identifying PLK1 degradation as a potential pharmacodynamic biomarker. Abbapolins also synergized with enzalutamide in castration- resistant prostate cancer cells, supporting their potential as combination therapies for advanced disease. Collectively, these studies establish selective inhibition of the PLK1 Polo-box domain as a viable therapeutic strategy, provide in vivo proof-of-concept for the REPLACE approach, and identify abbapolins as promising leads for advanced prostate cancer.

cancer biology↗

GenomeMUSter mouse genetic variation service enables multi-trait, multi-population data integration and analyses

Hundreds of inbred laboratory mouse strains and intercross populations have been used to functionalize genetic variants that contribute to disease. Thousands of disease relevant traits have been characterized in mice and made publicly available. New strains and populations including the Collaborative Cross, expanded BXD and inbred wild-derived strains add to set of complex disease mouse models, genetic mapping resources and sensitized backgrounds against which to evaluate engineered mutations. The genome sequences of many inbred strains, along with dense genotypes from others could allow integrated analysis of trait - variant associations across populations, but these analyses are not feasible due to the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense data resource by harmonizing multiple variant datasets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extensible to other model organism species. The result is a web- and programmatically-accessible data service called GenomeMUSter (https://muster.jax.org), comprising allelic data covering 657 strains at 106.8M segregating sites. Interoperation with phenotype databases, analytic tools and other resources enable a wealth of applications including multi-trait, multi-population meta-analysis. We demonstrate this in a cross-species comparison of the meta-analysis of Type 2 Diabetes and of substance use disorders, resulting in the more specific characterization of the role of human variant effects in light of mouse phenotype data. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

genetics↗