{"id":598,"date":"2018-01-25T10:31:40","date_gmt":"2018-01-25T16:31:40","guid":{"rendered":"http:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/?p=598"},"modified":"2018-01-25T10:31:40","modified_gmt":"2018-01-25T16:31:40","slug":"netsig-network-based-discovery-from-cancer-genomes","status":"publish","type":"post","link":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/2018\/01\/25\/netsig-network-based-discovery-from-cancer-genomes\/","title":{"rendered":"NetSig: network-based discovery from cancer genomes"},"content":{"rendered":"<p>Our next meeting will be at 2pm on Jan 29th, in room 4160 of the Discovery building. Our Selected paper is <a href=\"https:\/\/www.nature.com\/articles\/nmeth.4514\">NetSig: network-based discovery from cancer genomes.<\/a><br \/>\nThe abstract is as follows.<\/p>\n<blockquote><p>Methods that integrate molecular network information and tumor genome data could complement gene-based statistical tests to identify likely new cancer genes; but such approaches are challenging to validate at scale, and their predictive value remains unclear. We developed a robust statistic (NetSig) that integrates protein interaction networks with data from 4,742 tumor exomes. NetSig can accurately classify known driver genes in 60% of tested tumor types and predicts 62 new driver candidates. Using a quantitative experimental framework to determine <i>in vivo<\/i> tumorigenic potential in mice, we found that NetSig candidates induce tumors at rates that are comparable to those of known oncogenes and are ten-fold higher than those of random genes. By reanalyzing nine tumor-inducing NetSig candidates in 242 patients with oncogene-negative lung adenocarcinomas, we find that two (<i>AKT2<\/i> and <i>TFDP2<\/i>) are significantly amplified. Our study presents a scalable integrated computational and experimental workflow to expand discovery from cancer genomes.<\/p><\/blockquote>\n<p>We welcome all who can join us for this discussion. Feel free to begin that discussion in the comments section below.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Our next meeting will be at 2pm on Jan 29th, in room 4160 of the Discovery building. Our Selected paper is NetSig: network-based discovery from cancer genomes. The abstract is as follows. Methods that integrate molecular network information and tumor genome data could complement gene-based statistical tests to identify likely new cancer genes; but such [&hellip;]<\/p>\n","protected":false},"author":197,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[104,111],"tags":[],"_links":{"self":[{"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/posts\/598"}],"collection":[{"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/users\/197"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/comments?post=598"}],"version-history":[{"count":1,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/posts\/598\/revisions"}],"predecessor-version":[{"id":599,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/posts\/598\/revisions\/599"}],"wp:attachment":[{"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/media?parent=598"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/categories?post=598"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/tags?post=598"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}