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Unbiased discovery of cancer pathways and therapeutics using Pathway Ensemble Tool and Benchmark

Author

Listed:
  • Luopin Wang

    (Purdue University
    Purdue University)

  • Aryamav Pattnaik

    (Purdue University
    Purdue University)

  • Subhransu Sekhar Sahoo

    (Purdue University
    Purdue University)

  • Ella G. Stone

    (Purdue University
    Purdue University)

  • Yuxin Zhuang

    (Purdue University
    Purdue University)

  • Annaleigh Benton

    (Purdue University
    Purdue University)

  • Md Tajmul

    (Purdue University
    National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH)

  • Srishti Chakravorty

    (Purdue University
    Purdue University)

  • Deepika Dhawan

    (Purdue University)

  • My An Nguyen

    (Purdue University
    Purdue University)

  • Isabella Sirit

    (Purdue University
    Purdue University)

  • Kyle Mundy

    (Purdue University)

  • Christopher J. Ricketts

    (National Cancer Institute (NCI), NIH)

  • Marco Hadisurya

    (Purdue University
    Purdue University)

  • Garima Baral

    (Purdue University
    Purdue University)

  • Samantha L. Tinsley

    (Purdue University
    Purdue University)

  • Nicole L. Anderson

    (Purdue University
    Purdue University)

  • Smriti Hoda

    (Purdue University)

  • Scott D. Briggs

    (Purdue University
    Purdue University)

  • Hristos Z. Kaimakliotis

    (Indiana University)

  • Brittany L. Allen-Petersen

    (Purdue University
    Purdue University)

  • W. Andy Tao

    (Purdue University
    Purdue University
    Purdue University)

  • W. Marston Linehan

    (National Cancer Institute (NCI), NIH)

  • Deborah W. Knapp

    (Purdue University
    Purdue University)

  • Jason A. Hanna

    (Purdue University
    Purdue University)

  • Matthew R. Olson

    (Purdue University
    Purdue University)

  • Behdad Afzali

    (National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH)

  • Majid Kazemian

    (Purdue University
    Purdue University
    Purdue University)

Abstract

Correctly identifying perturbed biological pathways is a critical step in uncovering basic disease mechanisms and developing much-needed therapeutic strategies. However, whether current tools are optimal for unbiased discovery of relevant pathways remains unclear. Here, we create “Benchmark” to critically evaluate existing tools and find that most function sub-optimally. We thus develop the “Pathway Ensemble Tool” (PET), which outperforms existing methods. Deploying PET, we identify prognostic pathways across 12 cancer types. PET-identified prognostic pathways offer additional insights, with genes within these pathways serving as reliable biomarkers for clinical outcomes. Additionally, normalizing these pathways using drug repurposing strategies represents therapeutic opportunities. For example, the top predicted repurposed drug for bladder cancer, a CDK2/9 inhibitor, represses cell growth in vitro and in vivo. We anticipate that using Benchmark and PET for unbiased pathway discovery will offer additional insights into disease mechanisms across a spectrum of diseases, enabling biomarker discovery and therapeutic strategies.

Suggested Citation

  • Luopin Wang & Aryamav Pattnaik & Subhransu Sekhar Sahoo & Ella G. Stone & Yuxin Zhuang & Annaleigh Benton & Md Tajmul & Srishti Chakravorty & Deepika Dhawan & My An Nguyen & Isabella Sirit & Kyle Mund, 2024. "Unbiased discovery of cancer pathways and therapeutics using Pathway Ensemble Tool and Benchmark," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51859-9
    DOI: 10.1038/s41467-024-51859-9
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    References listed on IDEAS

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    1. Marta Paczkowska & Jonathan Barenboim & Nardnisa Sintupisut & Natalie S. Fox & Helen Zhu & Diala Abd-Rabbo & Miles W. Mee & Paul C. Boutros & Jüri Reimand, 2020. "Integrative pathway enrichment analysis of multivariate omics data," Nature Communications, Nature, vol. 11(1), pages 1-16, December.
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    3. Scooter Willis & Victor M Villalobos & Olivier Gevaert & Mark Abramovitz & Casey Williams & Branimir I Sikic & Brian Leyland-Jones, 2016. "Single Gene Prognostic Biomarkers in Ovarian Cancer: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-6, February.
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