Allele-specific disparity in breast cancer

Background

Molecular alterations critical to development of cancer include mutations, copy number alterations (amplifications and deletions) as well as genomic rearrangements resulting in gene fusions. Massively parallel next generation sequencing, which enables the discovery of such changes, uses considerable quantities of genomic DNA (> 5 ug), a serious limitation in ever smaller clinical samples. However, a commonly available microarray platforms such as array comparative genomic hybridization (array CGH) allows the characterization of gene copy number at a single gene resolution using much smaller amounts of genomic DNA. In this study we evaluate the sensitivity of ultra-dense array CGH platforms developed by Agilent, especially that of the 1 million probe array (1 M array), and their application when whole genome amplification is required because of limited sample quantities.

Methods

We performed array CGH on whole genome amplified and not amplified genomic DNA from MCF-7 breast cancer cells, using 244 K and 1 M Agilent arrays. The ADM-2 algorithm was used to identify micro-copy number alterations that measured less than 1 Mb in genomic length.

Results

DNA from MCF-7 breast cancer cells was analyzed for micro-copy number alterations, defined as measuring less than 1 Mb in genomic length. The 4-fold extra resolution of the 1 M array platform relative to the less dense 244 K array platform, led to the improved detection of copy number variations (CNVs) and micro-CNAs. The identification of intra-genic breakpoints in areas of DNA copy number gain signaled the possible presence of gene fusion events. However, the ultra-dense platforms, especially the densest 1 M array, detect artifacts inherent to whole genome amplification and should be used only with non-amplified DNA samples.

Conclusions

This is a first report using 1 M array CGH for the discovery of cancer genes and biomarkers. We show the remarkable capacity of this technology to discover CNVs, micro-copy number alterations and even gene fusions. However, these platforms require excellent genomic DNA quality and do not tolerate relatively small imperfections related to the whole genome amplification.     

High frequency of common DNA copy number abnormalities detected by bacterial artificial chromosome array comparative genomic hybridization in 24 breast cancer cell lines

Breast cancer is a widespread disease in Japan and across the world. Breast cancer cells, as well as most other types of cancer cells, have diverse chromosomal aberrations. Clarifying the character of these chromosomal aberrations should contribute to the development of more suitable therapies, along with the predictions of metastasis and prognosis. Twenty-four breast cancer cell lines were analyzed by bacterial artificial chromosome (BAC) array comparative genomic hybridization (CGH). The array slide contained duplicate spots of 4030 BAC clone DNAs covering the entire human genome with 1 Mbp resolution. In all 24 breast cancer cell lines, frequent and significant amplifications as well as deletions were detected by BAC array CGH. Common DNA copy number gains, detected in 60% (above 15 cell lines) of the 24 breast cancer cell lines were found in 76 BAC clones, located at 1q, 5p, 8q, 9p, 16p, 17q, and 20q. Moreover, common DNA copy number loss was detected in 136 BAC clones, located at 1q, 2q, 3p, 4p, 6q, 8p, 9p, 11p, 13q, 17p, 18q, 19p, Xp, and Xq. The DNA copy number abnormalities found included abnormality of the well-known oncogene cMYC (8q24.21); however, most of them were not reported to relate to breast cancer. BAC array CGH has great potential to detect DNA copy number abnormalities, and has revealed that breast cancer cell lines have substantial heterogeneity.     

Digital karyotyping: an update of its applications in cancer

DNA copy number alterations, including entire chromosomal changes and small interstitial DNA amplifications and deletions, characterize the development of cancer. These changes usually affect the expression of target genes and subsequently the function of the target proteins. Since the completion of the human genome project, the capacity to comprehensively analyze the human cancer genome has expanded significantly. Techniques such as digital karyotyping have been developed to allow for the detection of DNA copy number alterations in cancer at the whole-genome scale. When compared with conventional methods such as spectral karyotyping, representational difference analysis, comparative genomic hybridization (CGH), or the more recent array CGH; digital karyotyping provides an evaluation of copy number of genetic material at higher resolution. Digital karyotyping has therefore promised to enhance our understanding of the cancer genome. This article provides an overview of digital karyotyping including the principle of the technology and its applications in identifying potential oncogenes and tumor suppressor genes.     

Analysis of mitochondrial DNA copy number variation in blood and tissue samples of metastatic breast cancer patients (A pilot study)

Changes in mitochondrial DNA (mt-DNA) copy number in blood/tissue have been linked to increased risk of several cancers; however, studies on their association in breast cancer is still lacking. In this pilot study, we investigated mt-DNA copy number variation in peripheral blood and tissue samples from metastatic breast cancer patients and compared their differences. For the study, peripheral blood samples from non-cancer individuals (control) and breast cancer patients, along with resected tissues from adjacent and tumor sites from same breast cancer patients were collected. Total genomic DNA was isolated and changes in mt-DNA copy number were measured by relative quantification using SYBR green based quantitative real time PCR method. Our results indicated a significant reduction in mt-DNA copy number in blood samples of breast cancer patients compared to control. However, a significantly higher mt-DNA copy number was observed in tumor tissue when compared with paired non tumor tissue. There was no significant difference in mt-DNA copy number between blood and adjacent tumor tissue samples of the breast cancer patients. Overall, our study reports for the first time a comparison of mt-DNA copy number in blood and paired tissue together and suggested that mt-DNA copy number is differentially regulated in blood and tumor tissues in breast cancer.     

Accurate detection of aneuploidies in array CGH and gene expression microarray data

MOTIVATION: Chromosomal copy number changes (aneuploidies) are common in cell populations that undergo multiple cell divisions including yeast strains, cell lines and tumor cells. Identification of aneuploidies is critical in evolutionary studies, where changes in copy number serve an adaptive purpose, as well as in cancer studies, where amplifications and deletions of chromosomal regions have been identified as a major pathogenetic mechanism. Aneuploidies can be studied on whole-genome level using array CGH (a microarray-based method that measures the DNA content), but their presence also affects gene expression. In gene expression microarray analysis, identification of copy number changes is especially important in preventing aberrant biological conclusions based on spurious gene expression correlation or masked phenotypes that arise due to aneuploidies. Previously suggested approaches for aneuploidy detection from microarray data mostly focus on array CGH, address only whole-chromosome or whole-arm copy number changes, and rely on thresholds or other heuristics, making them unsuitable for fully automated general application to gene expression datasets. There is a need for a general and robust method for identification of aneuploidies of any size from both array CGH and gene expression microarray data. RESULTS: We present ChARM (Chromosomal Aberration Region Miner), a robust and accurate expectation-maximization based method for identification of segmental aneuploidies (partial chromosome changes) from gene expression and array CGH microarray data. Systematic evaluation of the algorithm on synthetic and biological data shows that the method is robust to noise, aneuploidal segment size and P-value cutoff. Using our approach, we identify known chromosomal changes and predict novel potential segmental aneuploidies in commonly used yeast deletion strains and in breast cancer. ChARM can be routinely used to identify aneuploidies in array CGH datasets and to screen gene expression data for aneuploidies or array biases. Our methodology is sensitive enough to detect statistically significant and biologically relevant aneuploidies even when expression or DNA content changes are subtle as in mixed populations of cells. AVAILABILITY: Code available by request from the authors and on Web supplement at http://function.cs.princeton.edu/ChARM/     

Micro-Scale Genomic DNA Copy Number Aberrations as Another Means of Mutagenesis in Breast Cancer

Introduction

In breast cancer, the basal-like subtype has high levels of genomic instability relative to other breast cancer subtypes with many basal-like-specific regions of aberration. There is evidence that this genomic instability extends to smaller scale genomic aberrations, as shown by a previously described micro-deletion event in the PTEN gene in the Basal-like SUM149 breast cancer cell line.

Methods

We sought to identify if small regions of genomic DNA copy number changes exist by using a high density, gene-centric Comparative Genomic Hybridizations (CGH) array on cell lines and primary tumors. A custom tiling array for CGH (244,000 probes, 200 bp tiling resolution) was created to identify small regions of genomic change, which was focused on previously identified basal-like-specific, and general cancer genes. Tumor genomic DNA from 94 patients and 2 breast cancer cell lines was labeled and hybridized to these arrays. Aberrations were called using SWITCHdna and the smallest 25% of SWITCHdna-defined genomic segments were called micro-aberrations (<64 contiguous probes, ∼ 15 kb).

Results

Our data showed that primary tumor breast cancer genomes frequently contained many small-scale copy number gains and losses, termed micro-aberrations, most of which are undetectable using typical-density genome-wide aCGH arrays. The basal-like subtype exhibited the highest incidence of these events. These micro-aberrations sometimes altered expression of the involved gene. We confirmed the presence of the PTEN micro-amplification in SUM149 and by mRNA-seq showed that this resulted in loss of expression of all exons downstream of this event. Micro-aberrations disproportionately affected the 5′ regions of the affected genes, including the promoter region, and high frequency of micro-aberrations was associated with poor survival.

Conclusion

Using a high-probe-density, gene-centric aCGH microarray, we present evidence of small-scale genomic aberrations that can contribute to gene inactivation. These events may contribute to tumor formation through mechanisms not detected using conventional DNA copy number analyses.     

Allele-specific amplification in cancer revealed by SNP array analysis

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.     

A luminal breast cancer genome atlas: progress and barriers

The challenge of developing an atlas that catalogs all the functionally important genomic changes associated with the development of luminal-type breast cancer is discussed in this article. The development of genome-wide techniques such as expression profiling, array-based comparative genomic hybridization and unbiased sequencing have put a cancer genome atlas within reach. However these techniques have revealed that the somatic DNA alterations associated with the development of a common solid tumor such as breast cancer are extremely complex. For example, large scale tumor DNA resequencing projects, focused on a small number of cell lines and the analysis of many genes, suggest that as many as 100 somatic mutations may have accumulated by the time a diagnosis is made. Similarly, array comparative hybridization experiments have uncovered multiple gene amplification and deletion events. Dealing with this complexity requires access to tumor and matched normal DNA from a large number of cases, with sufficient material to complete a spectrum of analytical techniques. Second, an acceptable approach to patient consent or sample de-identification must be in place if DNA sequencing traces are to be entered into public databases. Third, samples must be linked to detailed information on disease outcomes in order to identify lesions associated with aggressive clinical behavior. We conclude that samples from neoadjuvant endocrine therapy clinical protocols offer the best sample sets to initiate a luminal breast cancer genome atlas because these studies are amongst the few in which investigators have obtained high quality frozen tumor samples associated with both short term information on the estrogen dependence of individual ER+ tumors, as well as conventional data on long-term cancer survival.     

Detection of differential gene copy number using denaturing high performance liquid chromatography

Genomic rearrangements leading to deletion or duplication of gene(s) resulting in alterations in gene copy number underlie the molecular lesion in several genetic disorders. Methods currently used to determine gene copy number including real time PCR, southern hybridization, fluorescence in situ hybridization, densitometric scanning of PCR product etc. have certain disadvantages and are also expensive and time consuming. Herein, we describe a simple and rapid method to assess gene copy number using denaturing high performance liquid chromatography (dHPLC). We used X chromosome genes as model to compare the gene copy numbers present on this chromosome in males and females. DNA from these samples were amplified by biplex PCR using primer pairs specific for X chromosome genes only (target gene) and for genes present on both X and Y chromosomes (internal control). Amplified products were analyzed using HPLC under non-denaturing conditions. The ratio of peak areas (target gene/internal control) of the amplified products was approximately twice in female samples than male samples (p < 0.001) demonstrating that the differential gene copy number can be easily detected using this method. This method can potentially be used for diagnostic purpose where the need is to distinguish samples based on the differential gene copy numbers.     

GeneCount: genome-wide calculation of absolute tumor DNA copy numbers from array comparative genomic hybridization data

Absolute tumor DNA copy numbers can currently be achieved only on a single gene basis by using fluorescence in situ hybridization (FISH). We present GeneCount, a method for genome-wide calculation of absolute copy numbers from clinical array comparative genomic hybridization data. The tumor cell fraction is reliably estimated in the model. Data consistent with FISH results are achieved. We demonstrate significant improvements over existing methods for exploring gene dosages and intratumor copy number heterogeneity in cancers.     

Coupled analysis of gene expression and chromosomal location

Microarray technology can be used to assess simultaneously global changes in expression of mRNA or genomic DNA copy number among thousands of genes in different biological states. In many cases, it is desirable to determine if altered patterns of gene expression correlate with chromosomal abnormalities or assess expression of genes that are contiguous in the genome. We describe a method, differential gene locus mapping (DIGMAP), which aligns the known chromosomal location of a gene to its expression value deduced by microarray analysis. The method partitions microarray data into subsets by chromosomal location for each gene interrogated by an array. Microarray data in an individual subset can then be clustered by physical location of genes at a subchromosomal level based upon ordered alignment in genome sequence. A graphical display is generated by representing each genomic locus with a colored cell that quantitatively reflects its differential expression value. The clustered patterns can be viewed and compared based on their expression signatures as defined by differential values between control and experimental samples. In this study, DIGMAP was tested using previously published studies of breast cancer analyzed by comparative genomic hybridization (CGH) and prostate cancer gene expression profiles assessed by cDNA microarray experiments. Analysis of the breast cancer CGH data demonstrated the ability of DIGMAP to deduce gene amplifications and deletions. Application of the DIGMAP method to the prostate data revealed several carcinoma-related loci, including one at 16q13 with marked differential expression encompassing 19 known genes including 9 encoding metallothionein proteins. We conclude that DIGMAP is a powerful computational tool enabling the coupled analysis of microarray data with genome location.     

Mitochondrial DNA Copy Number Is Associated with Breast Cancer Risk

Mitochondrial DNA (mtDNA) copy number in peripheral blood is associated with increased risk of several cancers. However, data from prospective studies on mtDNA copy number and breast cancer risk are lacking. We evaluated the association between mtDNA copy number in peripheral blood and breast cancer risk in a nested case-control study of 183 breast cancer cases with pre-diagnostic blood samples and 529 individually matched controls among participants of the Singapore Chinese Health Study. The mtDNA copy number was measured using real time PCR. Conditional logistic regression analyses showed that there was an overall positive association between mtDNA copy number and breast cancer risk (P_trend = 0.01). The elevated risk for higher mtDNA copy numbers was primarily seen for women with <3 years between blood draw and cancer diagnosis; ORs (95% CIs) for 2^nd, 3^rd, 4^th, and 5^th quintile of mtDNA copy number were 1.52 (0.61, 3.82), 2.52 (1.03, 6.12), 3.12 (1.31, 7.43), and 3.06 (1.25, 7.47), respectively, compared with the 1^st quintile (P_trend = 0.004). There was no association between mtDNA copy number and breast cancer risk among women who donated a blood sample ≥3 years before breast cancer diagnosis (P_trend = 0.41). This study supports a prospective association between increased mtDNA copy number and breast cancer risk that is dependent on the time interval between blood collection and breast cancer diagnosis. Future studies are warranted to confirm these findings and to elucidate the biological role of mtDNA copy number in breast cancer risk.     

Integration of DNA copy number alterations and transcriptional expression analysis in human gastric cancer

Background

Genomic instability with frequent DNA copy number alterations is one of the key hallmarks of carcinogenesis. The chromosomal regions with frequent DNA copy number gain and loss in human gastric cancer are still poorly defined. It remains unknown how the DNA copy number variations contributes to the changes of gene expression profiles, especially on the global level.

Principal Findings

We analyzed DNA copy number alterations in 64 human gastric cancer samples and 8 gastric cancer cell lines using bacterial artificial chromosome (BAC) arrays based comparative genomic hybridization (aCGH). Statistical analysis was applied to correlate previously published gene expression data obtained from cDNA microarrays with corresponding DNA copy number variation data to identify candidate oncogenes and tumor suppressor genes. We found that gastric cancer samples showed recurrent DNA copy number variations, including gains at 5p, 8q, 20p, 20q, and losses at 4q, 9p, 18q, 21q. The most frequent regions of amplification were 20q12 (7/72), 20q12–20q13.1 (12/72), 20q13.1–20q13.2 (11/72) and 20q13.2–20q13.3 (6/72). The most frequent deleted region was 9p21 (8/72). Correlating gene expression array data with aCGH identified 321 candidate oncogenes, which were overexpressed and showed frequent DNA copy number gains; and 12 candidate tumor suppressor genes which were down-regulated and showed frequent DNA copy number losses in human gastric cancers. Three networks of significantly expressed genes in gastric cancer samples were identified by ingenuity pathway analysis.

Conclusions

This study provides insight into DNA copy number variations and their contribution to altered gene expression profiles during human gastric cancer development. It provides novel candidate driver oncogenes or tumor suppressor genes for human gastric cancer, useful pathway maps for the future understanding of the molecular pathogenesis of this malignancy, and the construction of new therapeutic targets.     

Molecular quantification of environmental DNA using microfluidics and digital PCR

Real-time PCR has been widely used to evaluate gene abundance in natural microbial habitats. However, PCR-inhibitory substances often reduce the efficiency of PCR, leading to the underestimation of target gene copy numbers. Digital PCR using microfluidics is a new approach that allows absolute quantification of DNA molecules. In this study, digital PCR was applied to environmental samples, and the effect of PCR inhibitors on DNA quantification was tested. In the control experiment using λ DNA and humic acids, underestimation of λ DNA at 1/4400 of the theoretical value was observed with 6.58ngμL(-1) humic acids. In contrast, digital PCR provided accurate quantification data with a concentration of humic acids up to 9.34ngμL(-1). The inhibitory effect of paddy field soil extract on quantification of the archaeal 16S rRNA gene was also tested. By diluting the DNA extract, quantified copy numbers from real-time PCR and digital PCR became similar, indicating that dilution was a useful way to remedy PCR inhibition. The dilution strategy was, however, not applicable to all natural environmental samples. For example, when marine subsurface sediment samples were tested the copy number of archaeal 16S rRNA genes was 1.04×10(3)copies/g-sediment by digital PCR, whereas real-time PCR only resulted in 4.64×10(2)copies/g-sediment, which was most likely due to an inhibitory effect. The data from this study demonstrated that inhibitory substances had little effect on DNA quantification using microfluidics and digital PCR, and showed the great advantages of digital PCR in accurate quantifications of DNA extracted from various microbial habitats.     

A quantitative assay to detect α-thalassemia deletions and triplications using multiplex nested real-time quantitative polymerase chain reaction

Increasing evidence indicates that copy number variants (CNVs) have great relevance to common human diseases. In α-thalassemia, clinical phenotypes are related to genotypes, specifically copy number changes in the human α-globin gene cluster. Assays are available for high-throughput screening of unknown CNVs genome-wide and also for targeted CNV genotyping at loci associated with genetic disorders. Here we describe a universal quantitative approach based on nested real-time quantitative polymerase chain reaction for accurate determination of copy numbers at multiple particular gene loci. We used the α-globin gene as a model system, obtaining the reproducibility and sensitivity to analyze different gene copies and testing 95 DNA samples with 16 different known genotypes. Our results showed that this approach has high sensitivity and low standard deviations for correctly genotyping DNA samples containing different copy numbers of the α1 and α2 globin genes. Our method is rapid, simple, and reliable, and it could be used to simultaneously screen for α-thalassemia deletions or triplications. Moreover, it has potential as a versatile technology for the rapid genotyping of known CNVs in a targeted region.     

CNAmet: an R package for integrating copy number, methylation and expression data

SUMMARY: Gene copy number and DNA methylation alterations are key regulators of gene expression in cancer. Accordingly, genes that show simultaneous methylation, copy number and expression alterations are likely to have a key role in tumor progression. We have implemented a novel software package (CNAmet) for integrative analysis of high-throughput copy number, DNA methylation and gene expression data. To demonstrate the utility of CNAmet, we use copy number, DNA methylation and gene expression data from 50 glioblastoma multiforme and 188 ovarian cancer primary tumor samples. Our results reveal a synergistic effect of DNA methylation and copy number alterations on gene expression for several known oncogenes as well as novel candidate oncogenes. AVAILABILITY: CNAmet R-package and user guide are freely available under GNU General Public License at http://csbi.ltdk.helsinki.fi/CNAmet.     

Integrated analysis of gene expression and copy number data on gene shaving using independent component analysis

DNA microarray gene expression and microarray-based comparative genomic hybridization (aCGH) have been widely used for biomedical discovery. Because of the large number of genes and the complex nature of biological networks, various analysis methods have been proposed. One such method is "gene shaving," a procedure which identifies subsets of the genes with coherent expression patterns and large variation across samples. Since combining genomic information from multiple sources can improve classification and prediction of diseases, in this paper we proposed a new method, "ICA gene shaving" (ICA, independent component analysis), for jointly analyzing gene expression and copy number data. First we used ICA to analyze joint measurements, gene expression and copy number, of a biological system and project the data onto statistically independent biological processes. Next, we used these results to identify patterns of variation in the data and then applied an iterative shaving method. We investigated the properties of our proposed method by analyzing both simulated and real data. We demonstrated that the robustness of our method to noise using simulated data. Using breast cancer data, we showed that our method is superior to the Generalized Singular Value Decomposition (GSVD) gene shaving method for identifying genes associated with breast cancer.     

Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatic analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We separately examined CNV and DNA methylation for 42 primary serous ovarian cancer samples using MOMA-ROMA assays and 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with altered copy number and correlated changes in expression. Among these genes CCNE1, POP4, UQCRB, PHF20L1 and C19orf2 were identified within both data sets. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We therefore identify changes in DNA methylation and expression for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic features for these modalities and perform a correlation analysis with expression. We predicted 611 potential oncogenes and tumor suppressors candidates by integrating these data types. Genes with a strong correlation for methylation dependent expression changes exhibited at varying copy number aberrations include CDCA8, ATAD2, CDKN2A, RAB25, AURKA, BOP1 and EIF2C3. We provide copy number variation and DNA methylation analysis for over 11,500 individual genes covering the genetic landscape of ovarian cancer tumors. We show the extent of genomic and epigenetic alterations for known tumor suppressors and oncogenes and also use these defined features to identify potential ovarian cancer gene candidates.