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SUMMARY:Integrative transcriptome-based drug repurposing in tuberculosis
DESCRIPTION:Statistical Bioinformatics SeminarSpeaker: Kewalin Samart\, University of Colorado \n\n\n\nThis is an online event held via Zoom: https://uni-sydney.zoom.us/j/85114748391 \n\n\n\n\n\n\n\n\n\nTuberculosis (TB) remains the leading cause of death from infectious disease\, with rising antibiotic resistance highlighting the need for host-directed therapeutics (HDTs). Transcriptome-based connectivity mapping offers a promising strategy by identifying drugs that reverse disease gene expression signatures\, but current approaches are limited by reliance on single datasets\, platforms\, or scoring methods. \n\n\n\nHere\, we present a unified computational framework that systematically integrates heterogeneous transcriptomic data and multiple connectivity methods for robust drug prioritization. Our approach combines 28 TB gene expression signatures spanning microarray and RNAseq platforms\, diverse cell types\, and infection conditions\, and applies multi-method connectivity scoring to identify consistent disease-drug reversal signals. By aggregating signals across datasets and methods\, the framework captures dominant TB signatures while mitigating platform and biological variability. Using this integrative strategy\, we prioritized 64 FDA-approved drugs as candidate HDTs\, including previously reported host-directed therapeutic candidates such as statins and tamoxifen. Downstream pathway and network analyses further revealed enrichment in TB-relevant mechanisms and identified key bridging genes (e.g.\, IL-8\, CXCR2) as potential therapeutic targets. \n\n\n\nThis work establishes transcriptome-based connectivity mapping as a viable approach for systematic HDT discovery in bacterial infections and provides a robust computational framework applicable to other infectious diseases. Our findings offer immediate opportunities for experimental validation of prioritized drug candidates and mechanistic investigation of identified druggable targets in TB pathogenesis. \n\n\n\n\n\n\nSubscribe to our seminar mailing list\n\n\n\n\n→\n\n\n\n\n\n\n\nFind out more about the Statistical Bioinformatics seminar series\n\n\n\n\n\n→\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nKewalin Samart\n\n\n\nKewalin Samart is a PhD candidate in Computational Bioscience at the University of Colorado Anschutz Medical Campus. She earned her B.Sc. in Computational Mathematics from Michigan State University. Her research focuses on developing and applying computational methods to uncover host response mechanisms and identify novel host-directed therapeutic strategies for infectious diseases.Find out more on X and LinkedIn:https://x.com/KewalinSamarthttps://www.linkedin.com/in/kewalinsamart
URL:https://spds.sydney.edu.au/event/integrative-transcriptome-based-drug-repurposing-in-tuberculosis/
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