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10.1158/0008-5472.CAN-16-2074 http://scihub22266oqcxt.onion/10.1158/0008-5472.CAN-16-2074 C5380541!5380541 !28202516     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28202516 &cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       Cancer+Res 2017 ; 77 (7 ): 1564-1574 Nephropedia Template TP {{tp|p=28202516 |t=2017. Modeling the Genetic Regulation of Cancer Metabolism: Interplay between Glycolysis and Oxidative Phosphorylation |pdf=|usr=}}{{28202516 }} gab.com Text Modeling the Genetic Regulation of Cancer Metabolism: Interplay between Glycolysis and Oxidative Phosphorylation JO: Cancer Res http://www.kidney.de/pget.php?&tw=1&pmid=28202516 #FOAvip Abnormal metabolism is a hallmark of cancer, yet its regulation remains poorly understood. Cancer cells were considered to utilize primarily glycolysis for ATP production, referred to as the Warburg effect. However, recent evidence suggests that oxidative phosphorylation (OXPHOS) plays a crucial role during cancer progression. Here we utilized a systems biology approach to decipher the regulatory principle of glycolysis and OXPHOS. Integrating information from literature, we constructed a regulatory network of genes and metabolites, from which we extracted a core circuit containing HIF-1, AMPK, and ROS. Our circuit analysis showed that while normal cells have an oxidative state and a glycolytic state, cancer cells can access a hybrid state with both metabolic modes coexisting. This was due to higher ROS production and/or oncogene activation, such as RAS, MYC, and c-SRC. Guided by the model, we developed two signatures consisting of AMPK and HIF-1 downstream genes, respectively, to quantify the activity of glycolysis and OXPHOS. By applying the AMPK and HIF-1 signatures to The Cancer Genome Atlas patient transcriptomics data of multiple cancer types and single-cell RNA-seq data of lung adenocarcinoma, we confirmed an anticorrelation between AMPK and HIF-1 activities and the association of metabolic states with oncogenes. We propose that the hybrid phenotype contributes to metabolic plasticity, allowing cancer cells to adapt to various microenvironments. Using model simulations, our theoretical framework of metabolism can serve as a platform to decode cancer metabolic plasticity and design cancer therapies targeting metabolism. Cancer Res; 77(7); 1564-74. ©2017 AACR. Twit Text FOAVip Modeling the Genetic Regulation of Cancer Metabolism: Interplay between Glycolysis and Oxidative Phosphorylation ????Cancer Res http://www.kidney.de/pget.php?&tw=1&pmid=28202516 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28202516 #FOAvip English Wikipedia <ref>{{Cite pmid|28202516 }}</ref> Modeling the Genetic Regulation of Cancer Metabolism: Interplay between Glycolysis and Oxidative Phosphorylation #MMPMID28202516 Yu L ; Lu M ; Jia D ; Ma J ; Ben-Jacob E ; Levine H ; Kaipparettu BA ; Onuchic JN Cancer Res 2017[Apr]; 77 (7 ): 1564-1574 PMID28202516 show ga Abnormal metabolism is a hallmark of cancer, yet its regulation remains poorly understood. Cancer cells were considered to utilize primarily glycolysis for ATP production, referred to as the Warburg effect. However, recent evidence suggests that oxidative phosphorylation (OXPHOS) plays a crucial role during cancer progression. Here we utilized a systems biology approach to decipher the regulatory principle of glycolysis and OXPHOS. Integrating information from literature, we constructed a regulatory network of genes and metabolites, from which we extracted a core circuit containing HIF-1, AMPK, and ROS. Our circuit analysis showed that while normal cells have an oxidative state and a glycolytic state, cancer cells can access a hybrid state with both metabolic modes coexisting. This was due to higher ROS production and/or oncogene activation, such as RAS, MYC, and c-SRC. Guided by the model, we developed two signatures consisting of AMPK and HIF-1 downstream genes, respectively, to quantify the activity of glycolysis and OXPHOS. By applying the AMPK and HIF-1 signatures to The Cancer Genome Atlas patient transcriptomics data of multiple cancer types and single-cell RNA-seq data of lung adenocarcinoma, we confirmed an anticorrelation between AMPK and HIF-1 activities and the association of metabolic states with oncogenes. We propose that the hybrid phenotype contributes to metabolic plasticity, allowing cancer cells to adapt to various microenvironments. Using model simulations, our theoretical framework of metabolism can serve as a platform to decode cancer metabolic plasticity and design cancer therapies targeting metabolism. Cancer Res; 77(7); 1564-74. ©2017 AACR. |*Glycolysis [MESH] |*Oxidative Phosphorylation [MESH] |AMP-Activated Protein Kinases/physiology [MESH] |Humans [MESH] |Hypoxia-Inducible Factor 1/physiology [MESH] |Models, Biological [MESH] |Neoplasms/genetics/*metabolism/therapy [MESH] |Proto-Oncogene Proteins c-myc/physiology [MESH] |Reactive Oxygen Species/metabolism [MESH]Modeling the Genetic Regulation of Cancer Metabolism: Interplay betwee(epmc).pdf DeepDyve Pubget Overpricing