Copy number alterations in enzyme-coding and cancer-causing genes reprogram tumor metabolism

• Verfasst von: Sharma, Ashwini Kumar [VerfasserIn]
• Verfasst von: Eils, Roland [VerfasserIn]
• Verfasst von: König, Rainer [VerfasserIn]
• Titel: Copy number alterations in enzyme-coding and cancer-causing genes reprogram tumor metabolism
• Verf.angabe: Ashwini Kumar Sharma, Roland Eils, and Rainer König
• E-Jahr: 2016
• Jahr: May 23, 2016
• Umfang: 10 S.
• Fussnoten: Gesehen am 06.05.2020
• Titel Quelle: Enthalten in: Cancer research
• Ort Quelle: Philadelphia, Pa. : AACR, 1916
• Jahr Quelle: 2016
• Band/Heft Quelle: 76(2016), 14, Seite 4058-4067
• ISSN Quelle: 1538-7445
• DOI: doi:10.1158/0008-5472.CAN-15-2350
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1697275761

Abstract

Somatic copy number alterations frequently occur in the cancer genome affecting not only oncogenic or tumor suppressive genes, but also passenger and potential codriver genes. An intrinsic feature resulting from such genomic perturbations is the deregulation in the metabolism of tumor cells. In this study, we have shown that metabolic and cancer-causing genes are unexpectedly often proximally positioned in the chromosome and share loci with coaltered copy numbers across multiple cancers (19 cancer types from The Cancer Genome Atlas). We have developed an analysis pipeline, Identification of Metabolic Cancer Genes (iMetCG), to infer the functional impact on metabolic remodeling from such coamplifications and codeletions and delineate genes driving cancer metabolism from those that are neutral. Using our identified metabolic genes, we were able to classify tumors based on their tissue and developmental origins. These metabolic genes were similar to known cancer genes in terms of their network connectivity, isoform frequency, and evolutionary features. We further validated these identified metabolic genes by (i) using gene essentiality data from several tumor cell lines, (ii) showing that these identified metabolic genes are strong indicators for patient survival, and (iii) observing a significant overlap between our identified metabolic genes and known cancer-metabolic genes. Our analyses revealed a hitherto unknown generic mechanism for large-scale metabolic reprogramming in cancer cells based on linear gene proximities between cancer-causing and -metabolic genes. We have identified 119 new metabolic cancer genes likely to be involved in rewiring cancer cell metabolism. Cancer Res; 76(14); 4058-67. ©2016 AACR.