PROJECT3: USINGNETWORKSTOSEEDHIERARCHICALWHOLECELL MODELSOFCANCER SUMMARY Knowledgeofcellbiologyisoftenmodeledintheformofmolecularnetworks(akainteractionmaps),consisting of sets of genegene or proteinprotein pairwise interactions. In reality, however, biological systems are not simply one large protein network, but consist of a deep and dynamic hierarchy of biological subsystems rangingacrossbiologicalscales.Here,wemovebeyondbasicinteractionmapsofcancertoinsteadusethe molecularinteractiondatatodirectlyinferhierarchicalstructure/functionmodelsofthecancercell.Theseplans are enabled by a computational framework called NetworkExtracted Ontologies (NeXO), which we have recently shown is able to capture and substantially extend the known hierarchy of cellular components and processesrecordedbypathwaydatabasessuchastheGeneOntology(GO).First(?Aim1?),wewillanalyzethe growing data on molecular networks to infer a Cancer Gene Ontology, representing a comprehensive, hierarchical description of the molecular complexes and pathways important for cancer. This hierarchical structurewillbedevelopedusingtheproteinproteininteractiondatageneratedin?Project1?,backstoppedby publicnetworkdata?itwillprovideanobjectivedefinitionofacancercellbysystematicallyidentifyingitsprotein modulesandtheirinterrelationships.Wewillnextusethisdescriptivehierarchytoseedpredictivewholecell modelsofcancer(?Aim2?).Usingthetoolsofdeepneuralnetworks,geneticlogicwillbeembeddedontoeach complex/pathway in the cell hierarchical structure to model how perturbations to this structure give rise to cancer phenotypes. The neural network structure will be set exactly to that of the Cancer Gene Ontology assembledin?Aim1??wewillthentrainthisneuralnetworktotranslateperturbationsbygenemutationsand drugs into predictions of cancer cell viability, as will be systematically measured in ?Project 2?. Finally, this hierarchical model will be validated and revised by applying it to predict therapeutic responses in patientderivedxenograftsofheadandneckandbreasttumorsaswellasinhumanbreasttumorsfromthe ISPY 2 trial (?Aim 3?). Through execution of these aims, we will endeavor to substantially advance our knowledgeofthestructuralandfunctionalhierarchyofmolecularpathwaysthatunderliecancer.Thishierarchy willbenotonlydescriptivebutalsopredictive,connectingbasicknowledgeofcancerpathwaystoaframework forusingthisknowledgeinprecisionmedicine.
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