Copy-number variation of cancer-gene orthologs is sufficient to induce cancer-like symptoms in Saccharomyces cerevisiae

Michaela De Clare,Stephen G Oliver

doi:10.1186/1741-7007-11-24

Abstract

BackgroundCopy-number variation (CNV), rather than complete loss of gene function, is increasingly implicated in human disease. Moreover, gene dosage is recognised as important in tumourigenesis, and there is an increasing realisation that CNVs may not be just symptomatic of the cancerous state but may, in fact, be causative. However, the identification of CNV-related phenotypes for mammalian genes is a slow process, due to the technical difficulty of constructing deletion mutants. Using the genome-wide deletion library for the model eukaryote, Saccharomyces cerevisiae, we have identified genes (termed haploproficient, HP) which, when one copy is deleted from a diploid cell, result in an increased rate of proliferation. Since haploproficiency under nutrient-sufficient conditions is a novel phenotype, we sought here to characterise a subset of the yeast haploproficient genes which seem particularly relevant to human cancers.ResultsWe show that, for a subset of HP genes, heterozygous deletion is sufficient to cause aberrant cell cycling and altered rates of apoptosis, phenotypes associated with cancer in mammalian cells. A majority of these yeast genes are the orthologs of mammalian cancer genes, and hence our studies suggest that CNV of these oncogenic orthologs may be sufficient to lead to tumourigenesis in human cells. Moreover, where not already implicated, this cluster of cancer-like phenotypes in this model eukaryote may be predictive of the involvement in cancer of the mammalian orthologs of these yeast HP genes. Using the yeast set as a model, we show that the response to a range of anti-cancer drugs is strongly dependent on gene dosage, such that intermediate concentrations of the drugs can actually increase a mutant’s growth rate.ConclusionsThe exploitation of data on the phenotypic impact of heterozygosis in Saccharomyces cerevisiae has permitted the prediction of CNVs affecting tumourigenesis in humans. Our yeast data also suggest that the identification of CNVs in tumour cells may assist both the selection of anti-cancer drugs and the dosages at which they should be administered if they are to be a beneficial, rather than a deleterious, therapy.

Highlights

Copy-number variation (CNV), rather than complete loss of gene function, is increasingly implicated in human disease
Yeast haploproficient genes are involved in the maintenance of genome integrity and are orthologs of human cancer genes The existence of haploproficient genes, and the inference that the yeast genome has not been optimised for maximal growth rate, does not appear to be an accident, nor unique to S. cerevisiae
A Gene Ontology term-enrichment revealed that the HP set is enriched for genes involved in the mitotic cell cycle (p = 0.003), and, in particular, the response to and repair of DNA damage (p = 0.006) (Figure 1; Additional file 2: Table S2). Given their integral role in maintaining genome stability, it is unsurprising that yeast HP genes are very much more likely to be orthologous to cancer genes than the S. cerevisaie genome average (p < 10-10)

Summary

Introduction

Copy-number variation (CNV), rather than complete loss of gene function, is increasingly implicated in human disease. A screen of > 5,800 deletion mutants, each heterozygous for a different protein-encoding gene in the S. cerevisiae genome, revealed that over 18% of these heterozygotes displayed a significantly reduced growth rate [7] This haploinsufficient phenotype was displayed even under conditions where there are no external constraints (such as nutrient limitations) on cell growth [8]. 600 genes, listed in Additional file 1: Table S1) of ‘haploproficient’ genes, heterozygous deletion of the gene elicits significantly faster growth than the wild type Using these yeast phenotypes, we have previously made correct predictions of a genedosage-related phenotype for their orthologous human genes [9], and verified these predictions by controlled RNAi knockdown in human cell lines [10]

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