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Through formalization of in silico systems approaches to understanding of the complex interplay of pathways and processes, my group develops and performs data-driven systems approaches to disease causal discovery. We use what we learn to prioritize drug/targets combinations.
Working on Alzheimer's, cancers and infectious diseases, we develop systems-based approaches to coding and noncoding RNA drug and target development, discovery, and enhancement of activity of pathways that appear to confer resilience against disease. Our current focus is on mapping the interplay between dysregulation of canonical pathways, disease and resilience signatures, and definition of specific drug combinations against target pathways.
My group developed the first systems-level synthesis of pathway and network activity that can be applied universally to gene expression profiles across species and platforms. Using [Pathprint], we discovered 4 common self-renewal pathways in acute myeloid leukemia in mouse and man. Defining pathways by correlated activity, I discovered large scale interaction between pathways and known Alzheimer’s Disease genes. Expanding pathway correlation to drug responses and diseases we established a powerful new paradigm by using pathways in children resilient to sepsis to successfully discover drugs that drive resilience in a mouse model. This work has made it possible, for the first time, to systematically define and drug the pathways that control disease.
Altschuler GM, Hofmann O, Kalatskaya I, Payne R, Ho Sui SJ, Saxena U, Krivtsov AV, Armstrong SA, Cai T, Stein L, Hide WA. Pathprinting: An integrative approach to understand the functional basis of disease. Genome Med. 2013;5(7):68. PubMed PMID: 23890051; PubMed Central PMCID: PMC3971351.
Joachim RB, Altschuler GM, Hutchinson JN, Wong HR, Hide WA, Kobzik L. The relative resistance of children to sepsis mortality: from pathways to drug candidates. Mol Syst Biol. 2018 May 17;14(5):e7998. PubMed PMID: 29773677.
Pita-Juárez Y, Altschuler G, Kariotis S, Wei W, Koler K, Green C, Tanzi RE, Hide W. The Pathway Coexpression Network: Revealing pathway relationships. PLoS Comput Biol. 2018 Mar;14(3):e1006042. PubMed PMID: 29554099; PubMed Central PMCID: PMC5875878.
Lal A, Thomas MP, Altschuler G, Navarro F, O’Day E, Li XL, Concepcion C, Han YC, Thiery J, Rajani DK, Deutsch A, Hofmann O, Ventura A, Hide W, Lieberman J. Capture of microRNA-bound mRNAs identifies the tumor suppressor miR-34a as a regulator of growth factor signaling. PLoS Genet. 2011 Nov;7(11):e1002363. PubMed PMID: 22102825; PubMed Central PMCID: PMC3213160.
Lal A, Navarro F, Maher CA, Maliszewski LE, Yan N, O’Day E, Chowdhury D, Dykxhoorn DM, Tsai P, Hofmann O, Becker KG, Gorospe M, Hide W, Lieberman J. miR-24 Inhibits cell proliferation by targeting E2F2, MYC, and other cell-cycle genes via binding to “seedless” 3’UTR microRNA recognition elements. Mol Cell. 2009 Sep 11;35(5):610-25. PubMed PMID: 19748357; PubMed Central PMCID: PMC2757794.
Petrocca F, Altschuler G, Tan SM, Mendillo ML, Yan H, Jerry DJ, Kung AL, Hide W, Ince TA, Lieberman J. A genome-wide siRNA screen identifies proteasome addiction as a vulnerability of basal-like triple-negative breast cancer cells. Cancer Cell. 2013 Aug 12;24(2):182-96. PubMed PMID: 23948298; PubMed Central PMCID: PMC3773329.