Literature DB >> 16140926

Distinct genomic profiles in hereditary breast tumors identified by array-based comparative genomic hybridization.

Göran Jönsson1, Tara L Naylor, Johan Vallon-Christersson, Johan Staaf, Jia Huang, M Renee Ward, Joel D Greshock, Lena Luts, Håkan Olsson, Nazneen Rahman, Michael Stratton, Markus Ringnér, Ake Borg, Barbara L Weber.   

Abstract

Mutations in BRCA1 and BRCA2 account for a significant proportion of hereditary breast cancers. Earlier studies have shown that inherited and sporadic tumors progress along different somatic genetic pathways and that global gene expression profiles distinguish between these groups. To determine whether genomic profiles similarly discriminate among BRCA1, BRCA2, and sporadic tumors, we established DNA copy number profiles using comparative genomic hybridization to BAC-clone microarrays providing <1 Mb resolution. Tumor DNA was obtained from BRCA1 (n = 14) and BRCA2 (n = 12) mutation carriers, as well as sporadic cases (n = 26). Overall, BRCA1 tumors had a higher frequency of copy number alterations than sporadic breast cancers (P = 0.00078). In particular, frequent losses on 4p, 4q, and 5q in BRCA1 tumors and frequent gains on 7p and 17q24 in BRCA2 tumors distinguish these from sporadic tumors. Distinct amplicons at 3q27.1-q27.3 were identified in BRCA1 tumors and at 17q23.3-q24.2 in BRCA2 tumors. A homozygous deletion on 5q12.1 was found in a BRCA1 tumor. Using a set of 169 BAC clones that detect significantly (P < 0.001) different frequencies of copy number changes in inherited and sporadic tumors, these could be discriminated into separate groups using hierarchical clustering. By comparing DNA copy number and RNA expression for genes in these regions, several candidate genes affected by up- or down-regulation were identified. Moreover, using support vector machines, we correctly classified BRCA1 and BRCA2 tumors (P < 0.0000004 and 0.00005, respectively). Further validation may prove this tumor classifier to be useful for selecting familial breast cancer cases for further mutation screening, particularly, as these data can be obtained using archival tissue.

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Year:  2005        PMID: 16140926     DOI: 10.1158/0008-5472.CAN-05-0570

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  61 in total

1.  Tumor characteristics as an analytic tool for classifying genetic variants of uncertain clinical significance.

Authors:  Robert M W Hofstra; Amanda B Spurdle; Diana Eccles; William D Foulkes; Niels de Wind; Nicoline Hoogerbrugge; Frans B L Hogervorst
Journal:  Hum Mutat       Date:  2008-11       Impact factor: 4.878

2.  Comprehensive characterization of the DNA amplification at 13q34 in human breast cancer reveals TFDP1 and CUL4A as likely candidate target genes.

Authors:  Lorenzo Melchor; Laura Paula Saucedo-Cuevas; Iván Muñoz-Repeto; Socorro María Rodríguez-Pinilla; Emiliano Honrado; Alfredo Campoverde; Jose Palacios; Katherine L Nathanson; María José García; Javier Benítez
Journal:  Breast Cancer Res       Date:  2009-12-08       Impact factor: 6.466

3.  Distinct high resolution genome profiles of early onset and late onset colorectal cancer integrated with gene expression data identify candidate susceptibility loci.

Authors:  Marianne Berg; Trude H Agesen; Espen Thiis-Evensen; Marianne A Merok; Manuel R Teixeira; Morten H Vatn; Arild Nesbakken; Rolf I Skotheim; Ragnhild A Lothe
Journal:  Mol Cancer       Date:  2010-05-06       Impact factor: 27.401

4.  The influence of genetic variation in 30 selected genes on the clinical characteristics of early onset breast cancer.

Authors:  William Tapper; Victoria Hammond; Sue Gerty; Sarah Ennis; Peter Simmonds; Andrew Collins; Diana Eccles
Journal:  Breast Cancer Res       Date:  2008-12-18       Impact factor: 6.466

5.  Normalized, segmented or called aCGH data?

Authors:  Wessel N van Wieringen; Mark A van de Wiel; Bauke Ylstra
Journal:  Cancer Inform       Date:  2007-09-17

6.  Genome-wide copy number profiling on high-density bacterial artificial chromosomes, single-nucleotide polymorphisms, and oligonucleotide microarrays: a platform comparison based on statistical power analysis.

Authors:  Jayne Y Hehir-Kwa; Michael Egmont-Petersen; Irene M Janssen; Dominique Smeets; Ad Geurts van Kessel; Joris A Veltman
Journal:  DNA Res       Date:  2007-03-15       Impact factor: 4.458

7.  Genomic profiling of breast tumours in relation to BRCA abnormalities and phenotypes.

Authors:  Olafur Andri Stefansson; Jon Gunnlaugur Jonasson; Oskar Thor Johannsson; Kristrun Olafsdottir; Margret Steinarsdottir; Sigridur Valgeirsdottir; Jorunn Erla Eyfjord
Journal:  Breast Cancer Res       Date:  2009-07-09       Impact factor: 6.466

8.  Identification of proteins involved in neural progenitor cell targeting of gliomas.

Authors:  Karin Staflin; Thole Zuchner; Gabriella Honeth; Anna Darabi; Cecilia Lundberg
Journal:  BMC Cancer       Date:  2009-06-26       Impact factor: 4.430

9.  Integrative molecular profiling of triple negative breast cancers identifies amplicon drivers and potential therapeutic targets.

Authors:  N Turner; M B Lambros; H M Horlings; A Pearson; R Sharpe; R Natrajan; F C Geyer; M van Kouwenhove; B Kreike; A Mackay; A Ashworth; M J van de Vijver; J S Reis-Filho
Journal:  Oncogene       Date:  2010-01-18       Impact factor: 9.867

10.  BRCA1 tumours correlate with a HIF-1alpha phenotype and have a poor prognosis through modulation of hydroxylase enzyme profile expression.

Authors:  M Yan; M Rayoo; E A Takano; H Thorne; S B Fox
Journal:  Br J Cancer       Date:  2009-09-01       Impact factor: 7.640

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