Dataset Information

Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

ABSTRACT: A variety of models have been proposed to explain regions of recurrent somatic copy number alteration (SCNA) in human cancer. Our study employs Whole Genome DNA Sequence (WGS) data from tumor samples (n = 103) to comprehensively assess the role of the Knudson two hit genetic model in SCNA generation in prostate cancer. 64 recurrent regions of loss and gain were detected, of which 28 were novel, including regions of loss with more than 15% frequency at Chr4p15.2-p15.1 (15.53%), Chr6q27 (16.50%) and Chr18q12.3 (17.48%). Comprehensive mutation screens of genes, lincRNA encoding sequences, control regions and conserved domains within SCNAs demonstrated that a two-hit genetic model was supported in only a minor proportion of recurrent SCNA losses examined (15/40). We found that recurrent breakpoints and regions of inversion often occur within Knudson model SCNAs, leading to the identification of ZNF292 as a target gene for the deletion at 6q14.3-q15 and NKX3.1 as a two-hit target at 8p21.3-p21.2. The importance of alterations of lincRNA sequences was illustrated by the identification of a novel mutational hotspot at the KCCAT42, FENDRR, CAT1886 and STCAT2 loci at the 16q23.1-q24.3 loss. Our data confirm that the burden of SCNAs is predictive of biochemical recurrence, define nine individual regions that are associated with relapse, and highlight the possible importance of ion channel and G-protein coupled-receptor (GPCR) pathways in cancer development. We concluded that a two-hit genetic model accounts for about one third of SCNA indicating that mechanisms, such haploinsufficiency and epigenetic inactivation, account for the remaining SCNA losses.

SUBMITTER: Camacho N

PROVIDER: S-EPMC5628936 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

Camacho Niedzica N Van Loo Peter P Edwards Sandra S Kay Jonathan D JD Matthews Lucy L Haase Kerstin K Clark Jeremy J Dennis Nening N Thomas Sarah S Kremeyer Barbara B Zamora Jorge J Butler Adam P AP Gundem Gunes G Merson Sue S Luxton Hayley H Hawkins Steve S Ghori Mohammed M Marsden Luke L Lambert Adam A Karaszi Katalin K Pelvender Gill G Massie Charlie E CE Kote-Jarai Zsofia Z Raine Keiran K Jones David D Howat William J WJ Hazell Steven S Livni Naomi N Fisher Cyril C Ogden Christopher C Kumar Pardeep P Thompson Alan A Nicol David D Mayer Erik E Dudderidge Tim T Yu Yongwei Y Zhang Hongwei H Shah Nimish C NC Gnanapragasam Vincent J VJ Isaacs William W Visakorpi Tapio T Hamdy Freddie F Berney Dan D Verrill Clare C Warren Anne Y AY Wedge David C DC Lynch Andrew G AG Foster Christopher S CS Lu Yong Jie YJ Bova G Steven GS Whitaker Hayley C HC McDermott Ultan U Neal David E DE Eeles Rosalind R Eeles Rosalind R Cooper Colin S CS Brewer Daniel S DS

PLoS genetics 20170925 9

A variety of models have been proposed to explain regions of recurrent somatic copy number alteration (SCNA) in human cancer. Our study employs Whole Genome DNA Sequence (WGS) data from tumor samples (n = 103) to comprehensively assess the role of the Knudson two hit genetic model in SCNA generation in prostate cancer. 64 recurrent regions of loss and gain were detected, of which 28 were novel, including regions of loss with more than 15% frequency at Chr4p15.2-p15.1 (15.53%), Chr6q27 (16.50%) a ...[more]

PMID: 28945760

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Project description:DUF1220 protein domains found primarily in Neuroblastoma BreakPoint Family (NBPF) genes show the greatest human lineage-specific increase in copy number of any coding region in the genome. There are 302 haploid copies of DUF1220 in hg38 (~160 of which are human-specific) and the majority of these can be divided into 6 different subtypes (referred to as clades). Copy number changes of specific DUF1220 clades have been associated in a dose-dependent manner with brain size variation (both evolutionarily and within the human population), cognitive aptitude, autism severity, and schizophrenia severity. However, no published methods can directly measure copies of DUF1220 with high accuracy and no method can distinguish between domains within a clade.Here we describe a novel method for measuring copies of DUF1220 domains and the NBPF genes in which they are found from whole genome sequence data. We have characterized the effect that various sequencing and alignment parameters and strategies have on the accuracy and precision of the method and defined the parameters that lead to optimal DUF1220 copy number measurement and resolution. We show that copy number estimates obtained using our read depth approach are highly correlated with those generated by ddPCR for three representative DUF1220 clades. By simulation, we demonstrate that our method provides sufficient resolution to analyze DUF1220 copy number variation at three levels: (1) DUF1220 clade copy number within individual genes and groups of genes (gene-specific clade groups) (2) genome wide DUF1220 clade copies and (3) gene copy number for DUF1220-encoding genes.To our knowledge, this is the first method to accurately measure copies of all six DUF1220 clades and the first method to provide gene specific resolution of these clades. This allows one to discriminate among the ~300 haploid human DUF1220 copies to an extent not possible with any other method. The result is a greatly enhanced capability to analyze the role that these sequences play in human variation and disease.

Project description:Changes in DNA copy number are one of the hallmarks of the genetic instability common to most human cancers. Previous microarray-based methods have been used to identify chromosomal gains and losses; however, they are unable to genotype alleles at the level of single nucleotide polymorphisms (SNPs). Here we describe a novel algorithm that uses a recently developed high-density oligonucleotide array-based SNP genotyping method, whole genome sampling analysis (WGSA), to identify genome-wide chromosomal gains and losses at high resolution. WGSA simultaneously genotypes over 10,000 SNPs by allele-specific hybridisation to perfect match (PM) and mismatch (MM) probes synthesised on a single array. The copy number algorithm jointly uses PM intensity and discrimination ratios between paired PM and MM intensity values to identify and estimate genetic copy number changes. Values from an experimental sample are compared with SNP-specific distributions derived from a reference set containing over 100 normal individuals to gain statistical power. Genomic regions with statistically significant copy number changes can be identified using both single point analysis and contiguous point analysis of SNP intensities. We identified multiple regions of amplification and deletion using a panel of human breast cancer cell lines. We verified these results using an independent method based on quantitative polymerase chain reaction and found that our approach is both sensitive and specific and can tolerate samples which contain a mixture of both tumour and normal DNA. In addition, by using known allele frequencies from the reference set, statistically significant genomic intervals can be identified containing contiguous stretches of homozygous markers, potentially allowing the detection of regions undergoing loss of heterozygosity (LOH) without the need for a matched normal control sample. The coupling of LOH analysis, via SNP genotyping, with copy number estimations using a single array provides additional insight into the structure of genomic alterations. With mean and median inter-SNP euchromatin distances of 244 kilobases (kb) and 119 kb, respectively, this method affords a resolution that is not easily achievable with non-oligonucleotide-based experimental approaches.

Dataset Information

Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

Publications

Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

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