Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review

A variety of genome-wide profiling techniques are available to probe complementary aspects of genome structure and function. Integrative analysis of heterogeneous data sources can reveal higher-level interactions that cannot be detected based on individual observations. A standard integration task in cancer studies is to identify altered genomic regions that induce changes in the expression of the associated genes based on joint analysis of genome-wide gene expression and copy number profiling measurements. In this review, we provide a comparison among various modeling procedures for integrating genome-wide profiling data of gene copy number and transcriptional alterations and highlight common approaches to genomic data integration. A transparent benchmarking procedure is introduced to quantitatively compare the cancer gene prioritization performance of the alternative methods. The benchmarking algorithms and data sets are available at http://intcomp.r-forge.r-project.orgComment: PDF file including supplementary material. 9 pages. Preprin

A teratocarcinoma-like human embryonic stem cell (hESC) line and four hESC lines reveal potentially oncogenic genomic changes

The first Swiss human embryonic stem cell (hESC) line, CH-ES1, has shown features of a malignant cell line. It originated from the only single blastomere that survived cryopreservation of an embryo, and it more closely resembles teratocarcinoma lines than other hESC lines with respect to its abnormal karyotype and its formation of invasive tumors when injected into SCID mice. The aim of this study was to characterize the molecular basis of the oncogenicity of CH-ES1 cells, we looked for abnormal chromosomal copy number (by array Comparative Genomic Hybridization, aCGH) and single nucleotide polymorphisms (SNPs). To see how unique these changes were, we compared these results to data collected from the 2102Ep teratocarcinoma line and four hESC lines (H1, HS293, HS401 and SIVF-02) which displayed normal G-banding result. We identified genomic gains and losses in CH-ES1, including gains in areas containing several oncogenes. These features are similar to those observed in teratocarcinomas, and this explains the high malignancy. The CH-ES1 line was trisomic for chromosomes 1, 9, 12, 17, 19, 20 and X. Also the karyotypically (based on G-banding) normal hESC lines were also found to have several genomic changes that involved genes with known roles in cancer. The largest changes were found in the H1 line at passage number 56, when large 5 Mb duplications in chromosomes 1q32.2 and 22q12.2 were detected, but the losses and gains were seen already at passage 22. These changes found in the other lines highlight the importance of assessing the acquisition of genetic changes by hESCs before their use in regenerative medicine applications. They also point to the possibility that the acquisition of genetic changes by ESCs in culture may be used to explore certain aspects of the mechanisms regulating oncogenesis

A teratocarcinoma-like human embryonic stem cell (hESC) line and four hESC lines reveal potentially oncogenic genomic changes

The first Swiss human embryonic stem cell (hESC) line, CH-ES1, has shown features of a malignant cell line. It originated from the only single blastomere that survived cryopreservation of an embryo, and it more closely resembles teratocarcinoma lines than other hESC lines with respect to its abnormal karyotype and its formation of invasive tumors when injected into SCID mice. The aim of this study was to characterize the molecular basis of the oncogenicity of CH-ES1 cells, we looked for abnormal chromosomal copy number (by array Comparative Genomic Hybridization, aCGH) and single nucleotide polymorphisms (SNPs). To see how unique these changes were, we compared these results to data collected from the 2102Ep teratocarcinoma line and four hESC lines (H1, HS293, HS401 and SIVF-02) which displayed normal G-banding result. We identified genomic gains and losses in CH-ES1, including gains in areas containing several oncogenes. These features are similar to those observed in teratocarcinomas, and this explains the high malignancy. The CH-ES1 line was trisomic for chromosomes 1, 9, 12, 17, 19, 20 and X. Also the karyotypically (based on G-banding) normal hESC lines were also found to have several genomic changes that involved genes with known roles in cancer. The largest changes were found in the H1 line at passage number 56, when large 5 Mb duplications in chromosomes 1q32.2 and 22q12.2 were detected, but the losses and gains were seen already at passage 22. These changes found in the other lines highlight the importance of assessing the acquisition of genetic changes by hESCs before their use in regenerative medicine applications. They also point to the possibility that the acquisition of genetic changes by ESCs in culture may be used to explore certain aspects of the mechanisms regulating oncogenesis

A single-array preprocessing method for estimating full-resolution raw copy numbers from all Affymetrix genotyping arrays including GenomeWideSNP 5 & 6

Motivation: High-resolution copy-number (CN) analysis has in recent years gained much attention, not only for the purpose of identifying CN aberrations associated with a certain phenotype, but also for identifying CN polymorphisms. In order for such studies to be successful and cost effective, the statistical methods have to be optimized. We propose a single-array preprocessing method for estimating full-resolution total CNs. It is applicable to all Affymetrix genotyping arrays, including the recent ones that also contain non-polymorphic probes. A reference signal is only needed at the last step when calculating relative CNs

Software comparison for evaluating genomic copy number variation for Affymetrix 6.0 SNP array platform

<p>Abstract</p> <p>Background</p> <p>Copy number data are routinely being extracted from genome-wide association study chips using a variety of software. We empirically evaluated and compared four freely-available software packages designed for Affymetrix SNP chips to estimate copy number: Affymetrix Power Tools (APT), Aroma.Affymetrix, PennCNV and CRLMM. Our evaluation used 1,418 GENOA samples that were genotyped on the Affymetrix Genome-Wide Human SNP Array 6.0. We compared bias and variance in the locus-level copy number data, the concordance amongst regions of copy number gains/deletions and the false-positive rate amongst deleted segments.</p> <p>Results</p> <p>APT had median locus-level copy numbers closest to a value of two, whereas PennCNV and Aroma.Affymetrix had the smallest variability associated with the median copy number. Of those evaluated, only PennCNV provides copy number specific quality-control metrics and identified 136 poor CNV samples. Regions of copy number variation (CNV) were detected using the hidden Markov models provided within PennCNV and CRLMM/VanillaIce. PennCNV detected more CNVs than CRLMM/VanillaIce; the median number of CNVs detected per sample was 39 and 30, respectively. PennCNV detected most of the regions that CRLMM/VanillaIce did as well as additional CNV regions. The median concordance between PennCNV and CRLMM/VanillaIce was 47.9% for duplications and 51.5% for deletions. The estimated false-positive rate associated with deletions was similar for PennCNV and CRLMM/VanillaIce.</p> <p>Conclusions</p> <p>If the objective is to perform statistical tests on the locus-level copy number data, our empirical results suggest that PennCNV or Aroma.Affymetrix is optimal. If the objective is to perform statistical tests on the summarized segmented data then PennCNV would be preferred over CRLMM/VanillaIce. Specifically, PennCNV allows the analyst to estimate locus-level copy number, perform segmentation and evaluate CNV-specific quality-control metrics within a single software package. PennCNV has relatively small bias, small variability and detects more regions while maintaining a similar estimated false-positive rate as CRLMM/VanillaIce. More generally, we advocate that software developers need to provide guidance with respect to evaluating and choosing optimal settings in order to obtain optimal results for an individual dataset. Until such guidance exists, we recommend trying multiple algorithms, evaluating concordance/discordance and subsequently consider the union of regions for downstream association tests.</p

Using the R Package crlmm for Genotyping and Copy Number Estimation

Genotyping platforms such as Affymetrix can be used to assess genotype-phenotype as well as copy number-phenotype associations at millions of markers. While genotyping algorithms are largely concordant when assessed on HapMap samples, tools to assess copy number changes are more variable and often discordant. One explanation for the discordance is that copy number estimates are susceptible to systematic differences between groups of samples that were processed at different times or by different labs. Analysis algorithms that do not adjust for batch effects are prone to spurious measures of association. The R package crlmm implements a multilevel model that adjusts for batch effects and provides allele-specific estimates of copy number. This paper illustrates a workflow for the estimation of allele-specific copy number and integration of the marker-level estimates with complimentary Bioconductor software for inferring regions of copy number gain or loss. All analyses are performed in the statistical environment R.

A single-sample method for normalizing and combining full-resolution copy numbers from multiple platforms, labs and analysis methods

Motivation: The rapid expansion of whole-genome copy number (CN) studies brings a demand for increased precision and resolution of CN estimates. Recent studies have obtained CN estimates from more than one platform for the same set of samples, and it is natural to want to combine the different estimates in order to meet this demand. Estimates from different platforms show different degrees of attenuation of the true CN changes. Similar differences can be observed in CNs from the same platform run in different labs, or in the same lab, with different analytical methods. This is the reason why it is not straightforward to combine CN estimates from different sources (platforms, labs and analysis methods)

Copy Number Variation in Patients with Disorders of Sex Development Due to 46,XY Gonadal Dysgenesis

Disorders of sex development (DSD), ranging in severity from mild genital abnormalities to complete sex reversal, represent a major concern for patients and their families. DSD are often due to disruption of the genetic programs that regulate gonad development. Although some genes have been identified in these developmental pathways, the causative mutations have not been identified in more than 50% 46,XY DSD cases. We used the Affymetrix Genome-Wide Human SNP Array 6.0 to analyse copy number variation in 23 individuals with unexplained 46,XY DSD due to gonadal dysgenesis (GD). Here we describe three discrete changes in copy number that are the likely cause of the GD. Firstly, we identified a large duplication on the X chromosome that included DAX1 (NR0B1). Secondly, we identified a rearrangement that appears to affect a novel gonad-specific regulatory region in a known testis gene, SOX9. Surprisingly this patient lacked any signs of campomelic dysplasia, suggesting that the deletion affected expression of SOX9 only in the gonad. Functional analysis of potential SRY binding sites within this deleted region identified five putative enhancers, suggesting that sequences additional to the known SRY-binding TES enhancer influence human testis-specific SOX9 expression. Thirdly, we identified a small deletion immediately downstream of GATA4, supporting a role for GATA4 in gonad development in humans. These CNV analyses give new insights into the pathways involved in human gonad development and dysfunction, and suggest that rearrangements of non-coding sequences disturbing gene regulation may account for significant proportion of DSD cases

Preclinical activity of LBH589 alone or in combination with chemotherapy in a xenogeneic mouse model of human acute lymphoblastic leukemia.

Histone deacetylases (HDACs) have been identified as therapeutic targets due to their regulatory function in chromatin structure and organization. Here, we analyzed the therapeutic effect of LBH589, a class I-II HDAC inhibitor, in acute lymphoblastic leukemia (ALL). In vitro, LBH589 induced dose-dependent antiproliferative and apoptotic effects, which were associated with increased H3 and H4 histone acetylation. Intravenous administration of LBH589 in immunodeficient BALB/c-RAG2(-/-)γc(-/-) mice in which human-derived T and B-ALL cell lines were injected induced a significant reduction in tumor growth. Using primary ALL cells, a xenograft model of human leukemia in BALB/c-RAG2(-/-)γc(-/-) mice was established, allowing continuous passages of transplanted cells to several mouse generations. Treatment of mice engrafted with T or B-ALL cells with LBH589 induced an in vivo increase in the acetylation of H3 and H4, which was accompanied with prolonged survival of LBH589-treated mice in comparison with those receiving vincristine and dexamethasone. Notably, the therapeutic efficacy of LBH589 was significantly enhanced in combination with vincristine and dexamethasone. Our results show the therapeutic activity of LBH589 in combination with standard chemotherapy in pre-clinical models of ALL and suggest that this combination may be of clinical value in the treatment of patients with ALL