Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1158/1535-7163.MCT-13-0750 http://scihub22266oqcxt.onion/10.1158/1535-7163.MCT-13-0750 C4090263!4090263!24785412     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Mol+Cancer+Ther 2014 ; 13 (7): 1929-41 Nephropedia Template TP {{tp|p=24785412|t=2014. Computational repositioning and preclinical validation of pentamidine for renal cell cancer |pdf=|usr=}}{{24785412}} gab.com Text Computational repositioning and preclinical validation of pentamidine for renal cell cancer JO: Mol Cancer Ther http://www.kidney.de/pget.php?&tw=1&pmid=24785412 #FOAvip While early stages of clear cell renal cell carcinoma (ccRCC) are curable, survival outcome for metastatic ccRCC remains poor. We previously established a highly accurate signature of differentially expressed genes that distinguish ccRCC from normal kidney. The purpose of the current study was to apply a new individualized bioinformatics analysis (IBA) strategy to these transcriptome data in conjunction with Gene Set Enrichment Analysis of the Connectivity Map (C-MAP) database to identify and reposition FDA-approved drugs for anti-cancer therapy. Here we demonstrate that one of the drugs predicted to revert the RCC gene signature towards normal kidney, pentamidine, is effective against RCC cells in culture and in a RCC xenograft model. ccRCC-specific gene expression signatures of individual patients were used to query the C-MAP software. Eight drugs with negative correlation and p-value <0.05 were analyzed for efficacy against RCC in vitro and in vivo. Our data demonstrate consistency across most ccRCC patients for the set of high scoring drugs. Most of the selected high scoring drugs potently induce apoptosis in RCC cells. Several drugs also demonstrate selectivity for VHL negative RCC cells. Most importantly, at least one of these drugs, pentamidine, slows tumor growth in the 786-O human ccRCC xenograft mouse model. Our findings suggest that pentamidine might be a new therapeutic agent to be combined with current standard-of-care regimens for metastatic ccRCC patients and support our notion that IBA combined with C-MAP analysis enables repurposing of FDA-approved drugs for potential anti-RCC therapy. Twit Text FOAVip Computational repositioning and preclinical validation of pentamidine for renal cell cancer ????Mol Cancer Ther http://www.kidney.de/pget.php?&tw=1&pmid=24785412 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24785412 #FOAvip English Wikipedia <ref>{{Cite pmid|24785412}}</ref> Computational repositioning and preclinical validation of pentamidine for renal cell cancer #MMPMID24785412 Zerbini LF; Bhasin MK; de Vasconcellos JF; Paccez JD; Gu X; Kung AL; Libermann TA Mol Cancer Ther 2014[Jul]; 13 (7): 1929-41 PMID24785412show ga While early stages of clear cell renal cell carcinoma (ccRCC) are curable, survival outcome for metastatic ccRCC remains poor. We previously established a highly accurate signature of differentially expressed genes that distinguish ccRCC from normal kidney. The purpose of the current study was to apply a new individualized bioinformatics analysis (IBA) strategy to these transcriptome data in conjunction with Gene Set Enrichment Analysis of the Connectivity Map (C-MAP) database to identify and reposition FDA-approved drugs for anti-cancer therapy. Here we demonstrate that one of the drugs predicted to revert the RCC gene signature towards normal kidney, pentamidine, is effective against RCC cells in culture and in a RCC xenograft model. ccRCC-specific gene expression signatures of individual patients were used to query the C-MAP software. Eight drugs with negative correlation and p-value <0.05 were analyzed for efficacy against RCC in vitro and in vivo. Our data demonstrate consistency across most ccRCC patients for the set of high scoring drugs. Most of the selected high scoring drugs potently induce apoptosis in RCC cells. Several drugs also demonstrate selectivity for VHL negative RCC cells. Most importantly, at least one of these drugs, pentamidine, slows tumor growth in the 786-O human ccRCC xenograft mouse model. Our findings suggest that pentamidine might be a new therapeutic agent to be combined with current standard-of-care regimens for metastatic ccRCC patients and support our notion that IBA combined with C-MAP analysis enables repurposing of FDA-approved drugs for potential anti-RCC therapy. äComputational repositioning and preclinical validation of pentamidine (epmc).pdf DeepDyve Pubget Overpricing