title: Phenotype-based cell-specific metabolic modeling reveals metabolic liabilities of cancer.
abstract: Utilizing molecular data to derive functional physiological models tailored for specific cancer cells can facilitate the use of individually tailored therapies. To this end we present an approach termed PRIME for generating cell-specific genome-scale metabolic models (GSMMs) based on molecular and phenotypic data. We build >280 models of normal and cancer cell-lines that successfully predict metabolic phenotypes in an individual manner. We utilize this set of cell-specific models to predict drug targets that selectively inhibit cancerous but not normal cell proliferation. The top predicted target, MLYCD, is experimentally validated and the metabolic effects of MLYCD depletion investigated. Furthermore, we tested cell-specific predicted responses to the inhibition of metabolic enzymes, and successfully inferred the prognosis of cancer patients based on their PRIME-derived individual GSMMs. These results lay a computational basis and a counterpart experimental proof of concept for future personalized metabolic modeling applications, enhancing the search for novel selective anticancer therapies.
authors.affiliation: Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel.
authors.forename: Keren
authors.initials: K
authors.lastname: Yizhak
authors.affiliation: MRC Cancer Unit, University of Cambridge, Cambridge, United Kingdom.
authors.forename: Edoardo
authors.initials: E
authors.lastname: Gaude
authors.affiliation: Division of Toxicology, Leiden Academic Center for Drug Research, Leiden University, Leiden, Netherlands.
authors.forename: Sylvia
authors.initials: S
authors.lastname: Le Dévédec
authors.affiliation: Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel.
authors.forename: Yedael Y
authors.initials: YY
authors.lastname: Waldman
authors.affiliation: Department of Internal Medicine 'B', Beilinson Hospital, Rabin Medical Center, Petah-Tikva, Israel.
authors.forename: Gideon Y
authors.initials: GY
authors.lastname: Stein
authors.affiliation: Division of Toxicology, Leiden Academic Center for Drug Research, Leiden University, Leiden, Netherlands.
authors.forename: Bob
authors.initials: B
authors.lastname: van de Water
authors.affiliation: MRC Cancer Unit, University of Cambridge, Cambridge, United Kingdom.
authors.forename: Christian
authors.initials: C
authors.lastname: Frezza
authors.affiliation: Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel.
authors.forename: Eytan
authors.initials: E
authors.lastname: Ruppin
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000494:pharmacology / Q000627:therapeutic use; D014408:Biomarkers, Tumor / Q000378:metabolism; D002262:Carboxy-Lyases / Q000378:metabolism; D045744:Cell Line, Tumor; D049109:Cell Proliferation / Q000187:drug effects; D002952:Citric Acid Cycle / Q000187:drug effects; D005227:Fatty Acids / Q000096:biosynthesis; D055785:Gene Knockdown Techniques; D015894:Genome, Human; D006801:Humans; D008214:Lymphocytes / Q000187:drug effects / Q000378:metabolism; D008954:Models, Biological; D009369:Neoplasms / Q000188:drug therapy / Q000378:metabolism* / Q000473:pathology*; D010084:Oxidation-Reduction / Q000187:drug effects; D010641:Phenotype; D057285:Precision Medicine
chemical_list: D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor; D005227:Fatty Acids; D002262:Carboxy-Lyases; C021532:malonyl-CoA decarboxylase
keywords: cancer; cell biology; genome-scale metabolic modeling; human; human biology; medicine; personalized medicine; selective drug targets