# Allele-Specific Amplification in Cancer Revealed by SNP Array Analysis

**Authors:** Thomas LaFramboise, Barbara A Weir, Xiaojun Zhao, Rameen Beroukhim, Cheng Li, David Harrington, William R Sellers, Matthew Meyerson

PMC · DOI: 10.1371/journal.pcbi.0010065 · PLoS Computational Biology · 2005-11-25

## TL;DR

This paper introduces a new method to analyze cancer DNA changes using SNP arrays, revealing that gene amplifications in lung cancer are mostly from one parent's chromosome.

## Contribution

The paper introduces the first method to infer allele-specific copy number and generalized genotype from SNP arrays using an expectation-maximization algorithm.

## Key findings

- Amplification in lung cancer samples is predominantly monoallelic, with only one parental chromosome contributing to copy number elevation.
- The method enables precise genotyping and haplotype identification in cancer genomes.
- The approach is validated using PCR experiments and applied to over 100 lung cancer samples.

## 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.

Human cancer is driven by the acquisition of genomic alterations. These alterations include amplifications and deletions of portions of one or both chromosomes in the cell. The localization of such copy number changes is an important pursuit in cancer genomics research because amplifications frequently harbor cancer-causing oncogenes, while deleted regions often contain tumor-suppressor genes. In this paper the authors present an expectation-maximization-based procedure that, when applied to data from single nucleotide polymorphism arrays, estimates not only total copy number at high resolution across the genome, but also the contribution of each parental chromosome to copy number. Applying this approach to data from over 100 lung cancer samples the authors find that, in essentially all cases, amplification is monoallelic. That is, only one of the two parental chromosomes contributes to the copy number elevation in each amplified region. This phenomenon makes possible the identification of haplotypes, or patterns of single nucleotide polymorphism alleles, that may serve as markers for the tumor-inducing genetic variants being targeted.

## Linked entities

- **Diseases:** lung cancer (MONDO:0005138)

## Full-text entities

- **Genes:** Egfr (epidermal growth factor receptor) [NCBI Gene 13649] {aka 9030024J15Rik, Erbb, Errb1, Errp, Wa5, wa-2}, Ccnd1 (cyclin D1) [NCBI Gene 12443] {aka CycD1, Cyl-1, PRAD1, bcl-1, cD1}, IGKV5-2 (immunoglobulin kappa variable 5-2) [NCBI Gene 28907] {aka B2, IGKV52}, Hras (Hras proto-oncogene, GTPase) [NCBI Gene 15461] {aka H-ras, Ha-ras, Harvey-ras, Hras-1, Hras1, Kras2}, EGFR (epidermal growth factor receptor) [NCBI Gene 1956] {aka ERBB, ERBB1, ERRP, HER1, NISBD2, NNCIS}
- **Diseases:** PSCNs (MESH:D063129), CL (MESH:D002971), Lung Cancer (MESH:D008175), skin tumors (MESH:D012878), ASCNs (MESH:D000080888), renal carcinoma tumors (MESH:D002292), tumorigenesis (MESH:D063646), Cancer (MESH:D009369), BS (MESH:D001816)
- **Species:** Mus musculus (house mouse, species) [taxon 10090], Homo sapiens (human, species) [taxon 9606]
- **Mutations:** E746 A750del, rs 1323113, S0177T, S0465T, rs 2284867, rs 2273762
- **Cell lines:** H2087 — Homo sapiens (Human), Lung adenocarcinoma, Cancer cell line (CVCL_1524), H2882 — Homo sapiens (Human), Lung squamous cell carcinoma, Cancer cell line (CVCL_5158), S0515T. — Homo sapiens (Human), Finite cell line (CVCL_9A52), HCC1359 — Homo sapiens (Human), Lung giant cell carcinoma, Cancer cell line (CVCL_5128), HCC827 — Homo sapiens (Human), Lung adenocarcinoma, Cancer cell line (CVCL_2063), H2122 — Homo sapiens (Human), Lung adenocarcinoma, Cancer cell line (CVCL_1531), H2126 — Homo sapiens (Human), Lung large cell carcinoma, Cancer cell line (CVCL_1532), H157 — Homo sapiens (Human), Buccal mucosa squamous cell carcinoma, Cancer cell line (CVCL_2458), HCC1171 — Homo sapiens (Human), Lung adenocarcinoma, Cancer cell line (CVCL_5126), HCC95 — Homo sapiens (Human), Lung squamous cell carcinoma, Cancer cell line (CVCL_5137)

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC1289392/full.md

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC1289392/full.md

## References

39 references — full list in the complete paper: https://tomesphere.com/paper/PMC1289392/full.md

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Source: https://tomesphere.com/paper/PMC1289392