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A new precision medicine initiative at the dawn of exascale computing

  1. Author:
    Nussinov,Ruth
    Jang,Hyunbum
    Nir, Guy
    Tsai,Chung-Jung
    Cheng, Feixiong

  2. Author Address

    NCI, Computat Struct Biol Sect, Frederick Natl Lab Canc Res, Lab Canc Immunometab, Frederick, MD 21702 USA.Tel Aviv Univ, Sackler Sch Med, Dept Human Mol Genet & Biochem, IL-69978 Tel Aviv, Israel.Harvard Med Sch, Dept Genet, Boston, MA 02115 USA.Harvard Univ, Wyss Inst Biol Inspired Engn, Boston, MA 02115 USA.Cleveland Clin, Lerner Res Inst, Gen Med Inst, Cleveland, OH 44106 USA.Case Western Reserve Univ, Cleveland Clin, Dept Mol Med, Lerner Coll Med, Cleveland, OH 44195 USA.Univ Texas Med Branch, Sealy Ctr Struct Biol & Mol Biophys, Dept Biochem & Mol Biol, Dept Neurosci Cell Biol & Anat, Galveston, TX 77555 USA.
    1. Year: 2021
    2. Date: Jan 6
    3. Epub Date: 2021 01 06
  2. Journal: Signal transduction and targeted therapy
  3. SPRINGERNATURE,
    1. 6
    2. 1
  5. Type of Article: Review
  6. Article Number: 3
  7. ISSN: 2095-9907
  1. Abstract:

    Which signaling pathway and protein to select to mitigate the patient's expected drug resistance? The number of possibilities facing the physician is massive, and the drug combination should fit the patient status. Here, we briefly review current approaches and data and map an innovative patient-specific strategy to forecast drug resistance targets that centers on parallel (or redundant) proliferation pathways in specialized cells. It considers the availability of each protein in each pathway in the specific cell, its activating mutations, and the chromatin accessibility of its encoding gene. The construction of the resulting Proliferation Pathway Network Atlas will harness the emerging exascale computing and advanced artificial intelligence (AI) methods for therapeutic development. Merging the resulting set of targets, pathways, and proteins, with current strategies will augment the choice for the attending physicians to thwart resistance.

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External Sources

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  2. DOI: 10.1038/s41392-020-00420-3
  3. PMID: 33402669
  4. PMCID: PMC7785737
  5. View record in Web of Science®
  6. WOS: 000605204000001

Library Notes

  1. Fiscal Year: FY2020-2021
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