Discovering Tumor Suppressor Genes Through Genome-Wide Copy Number Analysis

S Michael Rothenberg,Jeff Settleman

doi:10.2174/138920210791616734

S Michael Rothenberg, Jeff Settleman

Open Access

https://doi.org/10.2174/138920210791616734

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Abstract

Classical tumor suppressor gene discovery has largely involved linkage analysis and loss-of-heterozygosity (LOH) screens, followed by detailed mapping of relatively large chromosomal regions. Subsequent efforts made use of genome-wide PCR-based methods to detect rare homozygous deletions. More recently, high-resolution genomic arrays have been applied to cancer gene discovery. However, accurate characterization of regions of genomic loss is particularly challenging due to sample heterogeneity, the small size of deleted regions and the high frequency of germline copy number polymorphisms. Here, we review the application of genome-wide copy number analysis to the specific problem of identifying tumor suppressor genes.

Highlights

Ever since the seminal demonstration by Bishop and Varmus more than 30 years ago that transforming oncogenes arise from normal cellular genes, the discovery of additional cancer-specific mutations has fueled the hope of diagnosing and treating cancer with tumor-specific modalities [1]
Genetic approaches for discovering tumor suppressor genes (TSGs) have required validating several candidate genes contained within a large chromosomal region implicated by linkage analysis in families afflicted with cancer predisposition syndromes or targeted by tumorspecific allelic loss
In no other field of biology or medicine has the potential value of genome-wide approaches been as thoroughly exploited as human cancer genetics

Summary

INTRODUCTION

Ever since the seminal demonstration by Bishop and Varmus more than 30 years ago that transforming oncogenes arise from normal cellular genes, the discovery of additional cancer-specific mutations has fueled the hope of diagnosing and treating cancer with tumor-specific modalities [1]. To facilitate the analysis of the very large datasets generated by such methodologies, several automated approaches have been developed to systematically refine the number of candidate cancer genes for further genetic and functional characterization. Genetic approaches for discovering tumor suppressor genes (TSGs) have required validating several candidate genes contained within a large chromosomal region implicated by linkage analysis in families afflicted with cancer predisposition syndromes or targeted by tumorspecific allelic loss (so called loss-of-heterozygosity/LOH). In the “pre-genomic” era, the chromosomal regions implicated in cancer by linkage analysis or LOH screens were usually very large (on the order of many megabases), and would normally require many iterative steps of genotyping with many more genetic markers, and eventually, the sequencing of many candidate genes to detect inactivating mutations indicative of the targeted TSG.

Methodology

Very Small Deletions can Inactivate Genes

Findings

CONCLUSIONS