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10.1038/celldisc.2016.25 http://scihub22266oqcxt.onion/10.1038/celldisc.2016.25 C5004232!5004232 !27625789     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=27625789 &cmd=llinks): Failed to open stream: HTTP request failed! 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Integrative analysis of mutational and transcriptional profiles reveals driver mutations of metastatic breast cancers |pdf=|usr=}}{{27625789 }} gab.com Text Integrative analysis of mutational and transcriptional profiles reveals driver mutations of metastatic breast cancers JO: Cell Discov http://www.kidney.de/pget.php?&tw=1&pmid=27625789 #FOAvip Despite the explosion in the numbers of cancer genomic studies, metastasis is still the major cause of cancer mortality. In breast cancer, approximately one-fifth of metastatic patients survive 5 years. Therefore, detecting the patients at a high risk of developing distant metastasis at first diagnosis is critical for effective treatment strategy. We hereby present a novel systems biology approach to identify driver mutations escalating the risk of metastasis based on both exome and RNA sequencing of our collected 78 normal-paired breast cancers. Unlike driver mutations occurring commonly in cancers as reported in the literature, the mutations detected here are relatively rare mutations occurring in less than half metastatic samples. By supposing that the driver mutations should affect the metastasis gene signatures, we develop a novel computational pipeline to identify the driver mutations that affect transcription factors regulating metastasis gene signatures. We identify driver mutations in ADPGK, NUP93, PCGF6, PKP2 and SLC22A5, which are verified to enhance cancer cell migration and prompt metastasis with in vitro experiments. The discovered somatic mutations may be helpful for identifying patients who are likely to develop distant metastasis. Twit Text FOAVip Integrative analysis of mutational and transcriptional profiles reveals driver mutations of metastatic breast cancers ????Cell Discov http://www.kidney.de/pget.php?&tw=1&pmid=27625789 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27625789 #FOAvip English Wikipedia <ref>{{Cite pmid|27625789 }}</ref> Integrative analysis of mutational and transcriptional profiles reveals driver mutations of metastatic breast cancers #MMPMID27625789 Lee JH ; Zhao XM ; Yoon I ; Lee JY ; Kwon NH ; Wang YY ; Lee KM ; Lee MJ ; Kim J ; Moon HG ; In Y ; Hao JK ; Park KM ; Noh DY ; Han W ; Kim S Cell Discov 2016[]; 2 (ä): 16025 PMID27625789 show ga Despite the explosion in the numbers of cancer genomic studies, metastasis is still the major cause of cancer mortality. In breast cancer, approximately one-fifth of metastatic patients survive 5 years. Therefore, detecting the patients at a high risk of developing distant metastasis at first diagnosis is critical for effective treatment strategy. We hereby present a novel systems biology approach to identify driver mutations escalating the risk of metastasis based on both exome and RNA sequencing of our collected 78 normal-paired breast cancers. Unlike driver mutations occurring commonly in cancers as reported in the literature, the mutations detected here are relatively rare mutations occurring in less than half metastatic samples. By supposing that the driver mutations should affect the metastasis gene signatures, we develop a novel computational pipeline to identify the driver mutations that affect transcription factors regulating metastasis gene signatures. We identify driver mutations in ADPGK, NUP93, PCGF6, PKP2 and SLC22A5, which are verified to enhance cancer cell migration and prompt metastasis with in vitro experiments. The discovered somatic mutations may be helpful for identifying patients who are likely to develop distant metastasis. äIntegrative analysis of mutational and transcriptional profiles reveal(epmc).pdf DeepDyve Pubget Overpricing