Identification of cancer genes using a statistical framework for multiexperiment analysis of nondiscretized array CGH data

Nucleic Acids Research
Christiaan N KlijnLodewyk Wessels

Abstract

Tumor formation is in part driven by DNA copy number alterations (CNAs), which can be measured using microarray-based Comparative Genomic Hybridization (aCGH). Multiexperiment analysis of aCGH data from tumors allows discovery of recurrent CNAs that are potentially causal to cancer development. Until now, multiexperiment aCGH data analysis has been dependent on discretization of measurement data to a gain, loss or no-change state. Valuable biological information is lost when a heterogeneous system such as a solid tumor is reduced to these states. We have developed a new approach which inputs nondiscretized aCGH data to identify regions that are significantly aberrant across an entire tumor set. Our method is based on kernel regression and accounts for the strength of a probe's signal, its local genomic environment and the signal distribution across multiple tumors. In an analysis of 89 human breast tumors, our method showed enrichment for known cancer genes in the detected regions and identified aberrations that are strongly associated with breast cancer subtypes and clinical parameters. Furthermore, we identified 18 recurrent aberrant regions in a new dataset of 19 p53-deficient mouse mammary tumors. These regions, combined wi...Continue Reading

References

Mar 15, 1994·Proceedings of the National Academy of Sciences of the United States of America·A KallioniemiF M Waldman
Jan 23, 1999·Nature Genetics·L ShayestehJ W Gray
Sep 2, 1999·Nature Genetics·J R PollackP O Brown
Jan 27, 2000·Cell·D Hanahan, R A Weinberg
Aug 30, 2000·Nature·C M PerouD Botstein
May 23, 2002·Human Molecular Genetics·Katherine L NathansonBarbara L Weber
May 25, 2002·Hepatology : Official Journal of the American Association for the Study of Liver Diseases·Kohichiroh YasuiJohji Inazawa
Sep 26, 2002·Proceedings of the National Academy of Sciences of the United States of America·Jonathan R PollackPatrick O Brown
Jun 28, 2003·Proceedings of the National Academy of Sciences of the United States of America·Therese SorlieDavid Botstein
Mar 3, 2004·Nature Reviews. Cancer·P Andrew FutrealMichael R Stratton
Jun 3, 2004·Biochimica Et Biophysica Acta·Manuela Santarosa, Alan Ashworth
Aug 26, 2004·Clinical Cancer Research : an Official Journal of the American Association for Cancer Research·Torsten O NielsenCharles M Perou
Oct 12, 2004·Biostatistics·Adam B OlshenMichael Wigler
May 18, 2005·Clinical Cancer Research : an Official Journal of the American Association for Cancer Research·Justis P EhlersJ William Harbour
May 28, 2005·Nature Genetics·Daniel Pinkel, Donna G Albertson
Sep 15, 2005·Bioinformatics·Hanni Willenbrock, Jane Fridlyand
Nov 10, 2005·Biochimica Et Biophysica Acta·Olivier HagensVera Kalscheuer
Nov 18, 2005·Cancer Letters·Samuel Myllykangas, Sakari Knuutila
Dec 29, 2005·Molecular Cancer Research : MCR·Katharine S Richardson, Wayne Zundel
Jan 26, 2006·Bioinformatics·C RouveirolF Radvanyi
Jul 4, 2006·Cell·Daniel Peeper, Anton Berns
Jul 5, 2006·Breast Cancer Research : BCR·Erik H van Beers, Petra M Nederlof
Jul 19, 2006·Breast Cancer Research : BCR·Stefano CalzaYudi Pawitan
Nov 17, 2006·Nature Reviews. Cancer·Lauren M F MerloCarlo C Maley
Dec 13, 2006·PLoS Computational Biology·Jeroen de RidderLodewyk Wessels

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Citations

May 30, 2009·Bioinformatics·Sohrab P ShahKevin P Murphy
Dec 25, 2010·Bioinformatics·Vonn WalterFred A Wright
Aug 30, 2011·Bioinformatics·Sandro MorganellaMichele Ceccarelli
Feb 28, 2013·BMC Genomics·Gro NilsenOle Christian Lingjaerde
Sep 9, 2010·PLoS Computational Biology·Joseph E LucasJen-Tsan A Chi
Nov 2, 2016·Nucleic Acids Research·Joakim Karlsson, Erik Larsson
Sep 16, 2015·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Jianing Xi, Ao Li
Apr 15, 2014·Nature Methods·Theo A KnijnenburgIlya Shmulevich
Mar 22, 2018·Statistical Methods in Medical Research·Doulaye Dembélé
Oct 8, 2014·Cancer Informatics·Alberto CasseseMarina Vannucci
Oct 12, 2011·Genes, Chromosomes & Cancer·Eline BeertEric Legius
Sep 4, 2013·Genes, Chromosomes & Cancer·Szilárd NemesKhalil Helou
Feb 19, 2015·The Journal of Pathology·Jeffrey C FrancisAlan Ashworth
Dec 25, 2009·Circulation. Cardiovascular Genetics·Tianyuan Wang, Terrence S Furey
Nov 21, 2008·Veterinary Research·Sophie BlaniéChristelle Camus-Bouclainville
Aug 13, 2009·Genes, Chromosomes & Cancer·James F ReidMarco A Pierotti
Dec 22, 2012·Expert Review of Molecular Diagnostics·Geert Vandeweyer, R Frank Kooy
Aug 22, 2012·International Journal of Cancer. Journal International Du Cancer·Benjamin OttoGenrich V Tolstonog
Jul 28, 2016·The Journal of Clinical Investigation·Rinske DrostJos Jonkers
Nov 16, 2012·Cancer Research·Chris W DoornebalKarin E de Visser
Jan 8, 2009·Plant Physiology·Kevin L Childs
Dec 5, 2008·Microbiology and Molecular Biology Reviews : MMBR·Victor KuninPhilip Hugenholtz
Oct 26, 2010·Journal of Bacteriology·Silvia KnabIlka Haferkamp
Nov 22, 2008·Toxicology Letters·Marcel Ferrer-AlcónAntonio Martinez
Mar 17, 2009·Biochimica Et Biophysica Acta·Jenny MattisonDavid J Adams

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Datasets Mentioned

BETA
E-TABM-158
GSE7794

Software Mentioned

MATLAB
Biomart
HMM
CMAR
DAVID
Ensembl
KC
SMART
DAVID Bioinformatics Resources
STAC

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