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PMID: 16322765 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Allele-specific amplification in cancer revealed by SNP array analysis.

PLoS computational biology ·Vol. 1 ·No. 6 ·2005-11-00 ·Pages e65

LaFramboise T, Weir BA, Zhao X, Beroukhim R, Li C, Harrington D, Sellers WR, Meyerson M

Abstract

Amplification, deletion, and loss of heterozygosity of genomic DNA are hallmarks of cancer. In recent years a variety of studies have emerged measuring total chromosomal copy number at increasingly high resolution. Similarly, loss-of-heterozygosity events have been finely mapped using high-throughput genotyping technologies. We have developed a probe-level allele-specific quantitation procedure that extracts both copy number and allelotype information from single nucleotide polymorphism (SNP) array data to arrive at allele-specific copy number across the genome. Our approach applies an expectation-maximization algorithm to a model derived from a novel classification of SNP array probes. This method is the first to our knowledge that is able to (a) determine the generalized genotype of aberrant samples at each SNP site (e.g., CCCCT at an amplified site), and (b) infer the copy number of each parental chromosome across the genome. With this method, we are able to determine not just where amplifications and deletions occur, but also the haplotype of the region being amplified or deleted. The merit of our model and general approach is demonstrated by very precise genotyping of normal samples, and our allele-specific copy number inferences are validated using PCR experiments. Applying our method to a collection of lung cancer samples, we are able to conclude that amplification is essentially monoallelic, as would be expected under the mechanisms currently believed responsible for gene amplification. This suggests that a specific parental chromosome may be targeted for amplification, whether because of germ line or somatic variation. An R software package containing the methods described in this paper is freely available at http://genome.dfci.harvard.edu/~tlaframb/PLASQ.

MeSH Terms
Alleles Cell Line, Tumor Chromosomes, Human/genetics DNA, Neoplasm/genetics ErbB Receptors/genetics Gene Amplification/genetics Gene Dosage/genetics Gene Expression Regulation, Neoplastic/genetics Haplotypes Humans Models, Genetic Neoplasms/genetics Oligonucleotide Array Sequence Analysis Polymorphism, Single Nucleotide/genetics
Chemicals
DNA, Neoplasm ErbB Receptors
Authors & Affiliations
8 authors, click to expand affiliations / ORCID
LaFramboise Thomas
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.
Weir Barbara A
Zhao Xiaojun
Beroukhim Rameen
Li Cheng
Harrington David
Sellers William R
Meyerson Matthew
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Article Info
Journal
PLoS computational biology
Abbr.
PLoS Comput Biol
ISSN
1553-7358
Published
2005-11-00
Epub
2005-00-25
Pages
e65
Language
English
Region
United States
NLM ID
101238922
PMCID
PMC1289392
Subset
IM
Grants
NCI NIH HHS · R01CA109038 · United States
NCI NIH HHS · T32 CA009172 · United States
NCI NIH HHS · R01 CA109038 · United States
NIAID NIH HHS · R01 AI052817 · United States
NIAID NIH HHS · 2R01 AI052817 · United States
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