<HashMap><database>biostudies-literature</database><scores><citationCount>0</citationCount><reanalysisCount>0</reanalysisCount><viewCount>56</viewCount><searchCount>0</searchCount></scores><additional><submitter>Roy DM</submitter><funding>Louis Gerstner Foundation</funding><funding>Sontag Foundation</funding><funding>NIH MSTP</funding><funding>MSKCC Brain Tumor Center</funding><funding>The Geoffrey Beene Foundation</funding><funding>NCI NIH HHS</funding><funding>National Institutes of Health</funding><funding>HHMI Medical Research Fellows Program</funding><funding>Canadian Institutes of Health Research</funding><funding>NIGMS NIH HHS</funding><pagination>737-750</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC4864611</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>29(5)</volume><pubmed_abstract>The identification of driver loci underlying arm-level somatic copy number alterations (SCNAs) in cancer has remained challenging and incomplete. Here, we assess the relative impact and present a detailed landscape of arm-level SCNAs in 10,985 patient samples across 33 cancer types from The Cancer Genome Atlas (TCGA). Furthermore, using chromosome 9p loss in lower grade glioma (LGG) as a model, we employ a unique multi-tiered genomic dissection strategy using 540 patients from three independent LGG datasets to identify genetic loci that govern tumor aggressiveness and poor survival. This comprehensive approach uncovered several 9p loss-specific prognostic markers, validated existing ones, and redefined the impact of CDKN2A loss in LGG.</pubmed_abstract><journal>Cancer cell</journal><pubmed_title>Integrated Genomics for Pinpointing Survival Loci within Arm-Level Somatic Copy Number Alterations.</pubmed_title><pmcid>PMC4864611</pmcid><funding_grant_id>T32 GM007739</funding_grant_id><funding_grant_id>P30 CA008748</funding_grant_id><funding_grant_id>RO1-CA154767A1</funding_grant_id><funding_grant_id>R01 CA154767</funding_grant_id><funding_grant_id>T32GM007739</funding_grant_id><funding_grant_id>RO1 CA177828</funding_grant_id><funding_grant_id>R01 CA177828</funding_grant_id><pubmed_authors>Huse JT</pubmed_authors><pubmed_authors>Gao J</pubmed_authors><pubmed_authors>Chan TA</pubmed_authors><pubmed_authors>Roy DM</pubmed_authors><pubmed_authors>Walsh LA</pubmed_authors><pubmed_authors>Desrichard A</pubmed_authors><pubmed_authors>Wu W</pubmed_authors><pubmed_authors>Lee W</pubmed_authors><pubmed_authors>Bose P</pubmed_authors><view_count>56</view_count></additional><is_claimable>false</is_claimable><name>Integrated Genomics for Pinpointing Survival Loci within Arm-Level Somatic Copy Number Alterations.</name><description>The identification of driver loci underlying arm-level somatic copy number alterations (SCNAs) in cancer has remained challenging and incomplete. Here, we assess the relative impact and present a detailed landscape of arm-level SCNAs in 10,985 patient samples across 33 cancer types from The Cancer Genome Atlas (TCGA). Furthermore, using chromosome 9p loss in lower grade glioma (LGG) as a model, we employ a unique multi-tiered genomic dissection strategy using 540 patients from three independent LGG datasets to identify genetic loci that govern tumor aggressiveness and poor survival. This comprehensive approach uncovered several 9p loss-specific prognostic markers, validated existing ones, and redefined the impact of CDKN2A loss in LGG.</description><dates><release>2016-01-01T00:00:00Z</release><publication>2016 May</publication><modification>2024-10-18T20:04:09.272Z</modification><creation>2019-03-27T02:13:32Z</creation></dates><accession>S-EPMC4864611</accession><cross_references><pubmed>27165745</pubmed><doi>10.1016/j.ccell.2016.03.025</doi></cross_references></HashMap>