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10.3389/fonc.2020.01710 http://scihub22266oqcxt.onion/10.3389/fonc.2020.01710 33014847!7509113!33014847     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Front+Oncol 2020 ; 10 (ä): 1710 Nephropedia Template TP {{tp|p=33014847|t=2020. Prognostic Implications of Metabolism Related Gene Signature in Cutaneous Melanoma |pdf=|usr=}}{{33014847}} gab.com Text Prognostic Implications of Metabolism Related Gene Signature in Cutaneous Melanoma JO: Front Oncol http://www.kidney.de/pget.php?&tw=1&pmid=33014847 #FOAvip Metabolic reprogramming is closely related to melanoma. However, the prognostic role of metabolism-related genes (MRGs) remains to be elucidated. We aimed to establish a nomogram by combining MRGs signature and clinicopathological factors to predict melanoma prognosis. Eighteen prognostic MRGs between melanoma and normal samples were identified using The Cancer Genome Atlas (TCGA) and GSE15605. WARS (HR = 0.881, 95% CI = 0.788-0.984, P = 0.025) and MGST1 (HR = 1.124, 95% CI = 1.007-1.255, P = 0.037) were ultimately identified as independent prognostic MRGs with LASSO regression and multivariate Cox regression. The MRGs signature was established according to these two genes and externally validated in the Gene Expression Omnibus (GEO) dataset. Kaplan-Meier survival analysis indicated that patients in the high-risk group had significantly poorer overall survival (OS) than those in the low-risk group. Furthermore, the MRGs signature was identified as an independent prognostic factor for melanoma survival. An MRGs nomogram based on the MRGs signature and clinicopathological factors was developed in TCGA cohort and validated in the GEO dataset. Calibration plots showed good consistency between the prediction of nomogram and actual observation. The receiver operating characteristic curve and decision curve analysis indicated that MRGs nomogram had better OS prediction and clinical net benefit than the stage system. To our knowledge, we are the first to develop a prognostic nomogram based on MRGs signature with better predictive power than the current staging system, which could assist individualized prognosis prediction and improve treatment. Twit Text FOAVip Prognostic Implications of Metabolism Related Gene Signature in Cutaneous Melanoma ????Front Oncol http://www.kidney.de/pget.php?&tw=1&pmid=33014847 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33014847 #FOAvip English Wikipedia <ref>{{Cite pmid|33014847}}</ref> Prognostic Implications of Metabolism Related Gene Signature in Cutaneous Melanoma #MMPMID33014847 Zeng F; Su J; Peng C; Liao M; Zhao S; Guo Y; Chen X; Deng G Front Oncol 2020[]; 10 (ä): 1710 PMID33014847show ga Metabolic reprogramming is closely related to melanoma. However, the prognostic role of metabolism-related genes (MRGs) remains to be elucidated. We aimed to establish a nomogram by combining MRGs signature and clinicopathological factors to predict melanoma prognosis. Eighteen prognostic MRGs between melanoma and normal samples were identified using The Cancer Genome Atlas (TCGA) and GSE15605. WARS (HR = 0.881, 95% CI = 0.788-0.984, P = 0.025) and MGST1 (HR = 1.124, 95% CI = 1.007-1.255, P = 0.037) were ultimately identified as independent prognostic MRGs with LASSO regression and multivariate Cox regression. The MRGs signature was established according to these two genes and externally validated in the Gene Expression Omnibus (GEO) dataset. Kaplan-Meier survival analysis indicated that patients in the high-risk group had significantly poorer overall survival (OS) than those in the low-risk group. Furthermore, the MRGs signature was identified as an independent prognostic factor for melanoma survival. An MRGs nomogram based on the MRGs signature and clinicopathological factors was developed in TCGA cohort and validated in the GEO dataset. Calibration plots showed good consistency between the prediction of nomogram and actual observation. The receiver operating characteristic curve and decision curve analysis indicated that MRGs nomogram had better OS prediction and clinical net benefit than the stage system. To our knowledge, we are the first to develop a prognostic nomogram based on MRGs signature with better predictive power than the current staging system, which could assist individualized prognosis prediction and improve treatment. äPrognostic Implications of Metabolism Related Gene Signature in Cutane(epmc).pdf DeepDyve Pubget Overpricing