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Sökning: WFRF:(Gatto Francesco 1987) > (2015) > Flux balance analys...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00003129naa a2200361 4500
001oai:research.chalmers.se:5a657c7e-e3e8-482d-b59b-43351449dbab
003SwePub
008171007s2015 | |||||||||||000 ||eng|
024a https://research.chalmers.se/publication/2187372 URI
024a https://doi.org/10.1038/srep107382 DOI
040 a (SwePub)cth
041 a engb eng
042 9 SwePub
072 7a art2 swepub-publicationtype
072 7a ref2 swepub-contenttype
100a Gatto, Francesco,d 1987u Chalmers tekniska högskola,Chalmers University of Technology4 aut0 (Swepub:cth)gatto
2451 0a Flux balance analysis predicts essential genes in clear cell renal cell carcinoma metabolism
264 c 2015-06-04
264 1b Springer Science and Business Media LLC,c 2015
338 a electronic2 rdacarrier
520 a Flux balance analysis is the only modelling approach that is capable of producing genome-wide predictions of gene essentiality that may aid to unveil metabolic liabilities in cancer. Nevertheless, a systemic validation of gene essentiality predictions by flux balance analysis is currently missing. Here, we critically evaluated the accuracy of flux balance analysis in two cancer types, clear cell renal cell carcinoma (ccRCC) and prostate adenocarcinoma, by comparison with large-scale experiments of gene essentiality in vitro. We found that in ccRCC, but not in prostate adenocarcinoma, flux balance analysis could predict essential metabolic genes beyond random expectation. Five of the identified metabolic genes, AGPAT6, GALT, GCLC, GSS, and RRM2B, were predicted to be dispensable in normal cell metabolism. Hence, targeting these genes may selectively prevent ccRCC growth. Based on our analysis, we discuss the benefits and limitations of flux balance analysis for gene essentiality predictions in cancer metabolism, and its use for exposing metabolic liabilities in ccRCC, whose emergent metabolic network enforces outstanding anabolic requirements for cellular proliferation.
650 7a NATURVETENSKAPx Biologix Bioinformatik och systembiologi0 (SwePub)106102 hsv//swe
650 7a NATURAL SCIENCESx Biological Sciencesx Bioinformatics and Systems Biology0 (SwePub)106102 hsv//eng
700a Miess, H.u Cancer Research UK4 aut
700a Schulze, A.u Julius-Maximilians Universität Würzburg,University of Würzburg,Cancer Research UK,Comprehensive Cancer Center Mainfranken4 aut
700a Nielsen, Jens B,d 1962u Chalmers tekniska högskola,Chalmers University of Technology4 aut0 (Swepub:cth)nielsenj
710a Chalmers tekniska högskolab Cancer Research UK4 org
773t Scientific Reportsd : Springer Science and Business Media LLCg 5, s. Art. no. 10738-q 5<Art. no. 10738-x 2045-2322x 2045-2322
856u http://dx.doi.org/10.1038/srep10738y FULLTEXT
856u https://research.chalmers.se/publication/218737/file/218737_Fulltext.pdfx primaryx freey FULLTEXT
856u https://doi.org/10.1038/srep10738
8564 8u https://research.chalmers.se/publication/218737
8564 8u https://doi.org/10.1038/srep10738

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