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Safra Bioinformatics center at Tel\u2010Aviv University"},{"DOI":"10.13039\/501100005155","name":"Azrieli Foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100005155","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Netherlands Consortium for Systems Biology"},{"name":"EU FP7 Systems Microscopy NoE project","award":["258068"],"award-info":[{"award-number":["258068"]}]},{"DOI":"10.13039\/501100024871","name":"Netherlands Genomics Initiative","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100024871","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100003977","name":"Israeli Science Foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003977","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Israeli Cancer Research Fund"},{"name":"I\u2010CORE Program of the Planning and Budgeting Committee","award":["41\/11"],"award-info":[{"award-number":["41\/11"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mol Syst Biol"],"published-print":{"date-parts":[[2014,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Over the last decade, the field of cancer metabolism has mainly focused on studying the role of tumorigenic metabolic rewiring in supporting cancer proliferation. Here, we perform the first genome\u2010scale computational study of the metabolic underpinnings of cancer migration. We build genome\u2010scale metabolic models of the NCI\u201060 cell lines that capture the Warburg effect (aerobic glycolysis) typically occurring in cancer cells. The extent of the Warburg effect in each of these cell line models is quantified by the ratio of glycolytic to oxidative ATP flux (AFR), which is found to be highly positively associated with cancer cell migration. We hence predicted that targeting genes that mitigate the Warburg effect by reducing the AFR may specifically inhibit cancer migration. By testing the anti\u2010migratory effects of silencing such 17 top predicted genes in four breast and lung cancer cell lines, we find that up to 13 of these novel predictions significantly attenuate cell migration either in all or one cell line only, while having almost no effect on cell proliferation. Furthermore, in accordance with the predictions, a significant reduction is observed in the ratio between experimentally measured ECAR and OCR levels following these perturbations. Inhibiting anti\u2010migratory targets is a promising future avenue in treating cancer since it may decrease cytotoxic\u2010related side effects that plague current anti\u2010proliferative treatments. Furthermore, it may reduce cytotoxic\u2010related clonal selection of more aggressive cancer cells and the likelihood of emerging resistance.<\/jats:p>","DOI":"10.15252\/msb.20134993","type":"journal-article","created":{"date-parts":[[2014,8,2]],"date-time":"2014-08-02T03:44:25Z","timestamp":1406951065000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":67,"title":["A computational study of the Warburg effect identifies metabolic targets inhibiting cancer migration"],"prefix":"10.1038","volume":"10","author":[{"given":"Keren","family":"Yizhak","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sylvia E","family":"Le D\u00e9v\u00e9dec","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vasiliki Maria","family":"Rogkoti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Franziska","family":"Baenke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincent C","family":"de Boer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Frezza","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Almut","family":"Schulze","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bob","family":"van de Water","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eytan","family":"Ruppin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2014,8,1]]},"reference":[{"key":"BFMSB134993_CR1","doi-asserted-by":"crossref","first-page":"e1002518","DOI":"10.1371\/journal.pcbi.1002518","volume":"8","author":"R Agren","year":"2012","unstructured":"Agren R, Bordel S, Mardinoglu A, Pornputtapong N, Nookaew I, Nielsen J (2012) Reconstruction of genome\u2010scale active metabolic networks for 69 human cell types and 16 cancer types using INIT. 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