JISTIC: Identification of Significant Targets in Cancer
TLDR
JISTIC is an easy-to-install platform independent implementation of GISTIC that outperforms the original algorithm detecting more relevant candidate genes and regions and is an improvement over the widely used GISTic algorithm.Abstract:
Background
Cancer is caused through a multistep process, in which a succession of genetic changes, each conferring a competitive advantage for growth and proliferation, leads to the progressive conversion of normal human cells into malignant cancer cells. Interrogation of cancer genomes holds the promise of understanding this process, thus revolutionizing cancer research and treatment. As datasets measuring copy number aberrations in tumors accumulate, a major challenge has become to distinguish between those mutations that drive the cancer versus those passenger mutations that have no effect.read more
Citations
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Journal ArticleDOI
GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers.
Craig H. Mermel,Steven E. Schumacher,Barbara Hill,Matthew Meyerson,Rameen Beroukhim,Gad Getz +5 more
TL;DR: By separating SCNA profiles into underlying arm-level and focal alterations, the estimation of background rates for each category is improved, and a probabilistic method for defining the boundaries of selected-for SCNA regions with user-defined confidence is described.
Journal ArticleDOI
Trans-ancestry mutational landscape of hepatocellular carcinoma genomes
Yasushi Totoki,Kenji Tatsuno,Kyle R. Covington,Hiroki R. Ueda,Chad J. Creighton,Mamoru Kato,Shingo Tsuji,Lawrence A. Donehower,Betty L. Slagle,Hiromi Nakamura,Shogo Yamamoto,Eve Shinbrot,Natsuko Hama,Megan Lehmkuhl,Fumie Hosoda,Yasuhito Arai,Kim Walker,Mahmoud Dahdouli,Kengo Gotoh,Genta Nagae,Marie-Claude Gingras,Donna M. Muzny,Hidenori Ojima,Kazuaki Shimada,Yutaka Midorikawa,John A. Goss,Ronald T. Cotton,Akimasa Hayashi,Junji Shibahara,Shumpei Ishikawa,Jacfranz J. Guiteau,Mariko Tanaka,Tomoko Urushidate,Shoko Ohashi,Naoko Okada,Harsha Doddapaneni,Min Wang,Yiming Zhu,Huyen Dinh,Takuji Okusaka,Norihiro Kokudo,Tomoo Kosuge,Tadatoshi Takayama,Masashi Fukayama,Richard A. Gibbs,David A. Wheeler,Hiroyuki Aburatani,Tatsuhiro Shibata +47 more
TL;DR: A combination of hotspot TERT promoter mutation, TERT focal amplification and viral genome integration occurs in more than 68% of cases, implicating TERT as a central and ancestry-independent node of hepatocarcinogenesis.
Journal ArticleDOI
An integrated approach to uncover drivers of cancer.
Uri David Akavia,Oren Litvin,Jessica J. Kim,Jessica J. Kim,Felix Sanchez-Garcia,Dylan Kotliar,Helen C. Causton,Panisa Pochanard,Panisa Pochanard,Eyal Mozes,Levi A. Garraway,Levi A. Garraway,Dana Pe'er +12 more
TL;DR: A computational framework is developed that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression and correctly identified known drivers of melanoma and predicted multiple tumor dependencies.
Journal ArticleDOI
Identifying driver mutations in sequenced cancer genomes: computational approaches to enable precision medicine
TL;DR: Approaches to detect somatic mutations from high-throughput DNA sequencing data, particularly for tumor samples that comprise heterogeneous populations of cells, and techniques to identify recurrent combinations of somatics mutations are described.
Journal ArticleDOI
Multilevel Whole-Genome Analysis Reveals Candidate Biomarkers in Clear Cell Renal Cell Carcinoma
Andrew H. Girgis,Vladimir Iakovlev,Ben Beheshti,Jane Bayani,Jeremy A. Squire,Anna Bui,Marina Mankaruos,Youssef M. Youssef,Bishoy Khalil,Heba Wz Khella,Maria D. Pasic,George M. Yousef +11 more
TL;DR: These findings provide a significant advance in the delineation of the ccRCC genome by better defining the impact of CNAs in conjunction with methylation changes on the expression of cancer-related genes, miRNAs, and proteins and their influence on patient survival.
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TL;DR: Evidence is provided that widespread DNA copy number alteration can lead directly to global deregulation of gene expression, which may contribute to the development or progression of cancer.
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