The Genomic Landscapes of Human Breast and Colorectal Cancers

Author:

Wood Laura D.12345,Parsons D. Williams12345,Jones Siân12345,Lin Jimmy12345,Sjöblom Tobias12345,Leary Rebecca J.12345,Shen Dong12345,Boca Simina M.12345,Barber Thomas12345,Ptak Janine12345,Silliman Natalie12345,Szabo Steve12345,Dezso Zoltan12345,Ustyanksky Vadim12345,Nikolskaya Tatiana12345,Nikolsky Yuri12345,Karchin Rachel12345,Wilson Paul A.12345,Kaminker Joshua S.12345,Zhang Zemin12345,Croshaw Randal12345,Willis Joseph12345,Dawson Dawn12345,Shipitsin Michail12345,Willson James K. V.12345,Sukumar Saraswati12345,Polyak Kornelia12345,Park Ben Ho12345,Pethiyagoda Charit L.12345,Pant P. V. Krishna12345,Ballinger Dennis G.12345,Sparks Andrew B.12345,Hartigan James12345,Smith Douglas R.12345,Suh Erick12345,Papadopoulos Nickolas12345,Buckhaults Phillip12345,Markowitz Sanford D.12345,Parmigiani Giovanni12345,Kinzler Kenneth W.12345,Velculescu Victor E.12345,Vogelstein Bert12345

Affiliation:

1. The Ludwig Center for Cancer Genetics and Therapeutics and The Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer Center, Baltimore, MD 21231, USA.

2. Department of Biostatistics, Johns Hopkins Medical Institutions, Baltimore, MD 21231, USA.

3. GeneGo, St. Joseph, MI 49085, USA.

4. Vavilov Institute of General Genetics, Moscow, Russia.

5. Department of Biomedical Engineering, Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.

Abstract

Human cancer is caused by the accumulation of mutations in oncogenes and tumor suppressor genes. To catalog the genetic changes that occur during tumorigenesis, we isolated DNA from 11 breast and 11 colorectal tumors and determined the sequences of the genes in the Reference Sequence database in these samples. Based on analysis of exons representing 20,857 transcripts from 18,191 genes, we conclude that the genomic landscapes of breast and colorectal cancers are composed of a handful of commonly mutated gene “mountains” and a much larger number of gene “hills” that are mutated at low frequency. We describe statistical and bioinformatic tools that may help identify mutations with a role in tumorigenesis. These results have implications for understanding the nature and heterogeneity of human cancers and for using personal genomics for tumor diagnosis and therapy.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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