Detecting gene copy number fluctuations in tumor cells by microarray analysis of genomic representations

Statistical Contributions to Bioinformatics: Design, Modeling, Structure Learning, and Integration

The advent of high-throughput multi-platform genomics technologies providing whole-genome molecular summaries of biological samples has revolutionalized biomedical research. These technologiees yield highly structured big data, whose analysis poses significant quantitative challenges. The field of Bioinformatics has emerged to deal with these challenges, and is comprised of many quantitative and biological scientists working together to effectively process these data and extract the treasure trove of information they contain. Statisticians, with their deep understanding of variability and uncertainty quantification, play a key role in these efforts. In this article, we attempt to summarize some of the key contributions of statisticians to bioinformatics, focusing on four areas: (1) experimental design and reproducibility, (2) preprocessing and feature extraction, (3) unified modeling, and (4) structure learning and integration. In each of these areas, we highlight some key contributions and try to elucidate the key statistical principles underlying these methods and approaches. Our goals are to demonstrate major ways in which statisticians have contributed to bioinformatics, encourage statisticians to get involved early in methods development as new technologies emerge, and to stimulate future methodological work based on the statistical principles elucidated in this article and utilizing all availble information to uncover new biological insights.

Selection of suitable endogenous reference genes for relative copy number detection in sugarcane

Transgene copy number has a great impact on the expression level and stability of exogenous gene in transgenic plants. Proper selection of endogenous reference genes is necessary for detection of genetic components in genetically modification (GM) crops by quantitative real-time PCR (qPCR) or by qualitative PCR approach, especially in sugarcane with polyploid and aneuploid genomic structure. qPCR technique has been widely accepted as an accurate, time-saving method on determination of copy numbers in transgenic plants and on detection of genetically modified plants to meet the regulatory and legislative requirement. In this study, to find a suitable endogenous reference gene and its real-time PCR assay for sugarcane (Saccharum spp. hybrids) DNA content quantification, we evaluated a set of potential "single copy" genes including P4H, APRT, ENOL, CYC, TST and PRR, through qualitative PCR and absolute quantitative PCR. Based on copy number comparisons among different sugarcane genotypes, including five S. officinarum, one S. spontaneum and two S. spp. hybrids, these endogenous genes fell into three groups: ENOL-3--high copy number group, TST-1 and PRR-1--medium copy number group, P4H-1, APRT-2 and CYC-2--low copy number group. Among these tested genes, P4H, APRT and CYC were the most stable, while ENOL and TST were the least stable across different sugarcane genotypes. Therefore, three primer pairs of P4H-3, APRT-2 and CYC-2 were then selected as the suitable reference gene primer pairs for sugarcane. The test of multi-target reference genes revealed that the APRT gene was a specific amplicon, suggesting this gene is the most suitable to be used as an endogenous reference target for sugarcane DNA content quantification. These results should be helpful for establishing accurate and reliable qualitative and quantitative PCR analysis of GM sugarcane.

Determination of transgene copy number in stably transfected mammalian cells by PCR-capillary electrophoresis assay

The quantitative determination of transgene copy number in stably transfected mammalian cells has been traditionally estimated by Southern blot analysis. Recently, other methods have become available for appraisal of gene copy number, such as real-time PCR. Herein we describe a new method based on a fluorescently labeled PCR, followed by capillary electrophoresis. We amplified our target gene (prothrombin) and the internal control originating from genomic DNA (18S rRNA) in the same PCR tube and calculated the mean peak height ratio of the target:control gene for every cell clone sample. With this approach we identified stably transfected cell clones bearing the same transgene copy number. The results of our assay were confirmed by real-time PCR. Our method proves to be fast, low-cost, and reproducible compared with traditionally used methods. This assay can be used as a rapid screening tool for the determination of gene copy number in gene expression experiments.

RNA-dependent genome processing during nuclear differentiation: the model systems of stichotrichous ciliates

We introduce ciliated protozoa, and more specifically the stichotrichous ciliates Oxytricha and Stylonychia, as biological model systems for the analysis of programmed DNA-reorganization processes during nuclear differentiation. These include DNA excision, DNA elimination, reordering of gene segments and specific gene amplification. We show that small nuclear RNAs specify DNA sequences to be excised or retained, but also discuss the need for a RNA template molecule derived from the parental nucleus for these processes. This RNA template guides reordering of gene segments to become functional genes and determines gene copy number in the differentiated nucleus. Since the template is derived from the parental macronucleus, gene reordering and DNA amplification are inherited in a non-Mendelian epigenetic manner.

Evaluation of designer crops for biosafety--a scientist's perspective

With the advent of transgenic technology, it has become possible to mobilize and express foreign genes into plants and to design crop varieties with better agronomic attributes and adaptability to challenging environmental conditions. Recent advances in transgenic technology have led to concerns about safety of transgenic crops to human and animal health and environment. Biosafety focuses on preventing, minimizing and eliminating risks associated with the research, production, and use of transgenic crops. Food biosafety involves studies of substantial equivalence related to compositional analysis, toxicity and allergenicity. Environmental biosafety involves glasshouse and field trials and study of unintended effects on non-target organisms. Transgenics are characterized at phenotypic and molecular levels for understanding the location of transgene insertion site, ploidy level, copy number, integrated vector sequences, protein expression and stability of the transgene. Various techniques employed for transgene characterization include flow cytometry, southern, northern and western analyses, real-time (qRT) PCR, competitive PCR, FISH, fiber-FISH, DNA micro-arrays, mRNA profiling, 2DE-MS, iTRAQ, FT-MS, NMR, GC-MS, CE-MS and biosensor-based approaches. Evaluation of transgene expression involves the application of integrated phenomics, transcriptomics, proteomics and metabolomics approaches. However, the relevance and application of these approaches may vary in different cases. The elaborate analysis of transgenic crops will facilitate the safety assessment and commercialization of transgenics and lead to global food security for the future.

COPS: a sensitive and accurate tool for detecting somatic Copy Number Alterations using short-read sequence data from paired samples

Copy Number Alterations (CNAs) such as deletions and duplications; compose a larger percentage of genetic variations than single nucleotide polymorphisms or other structural variations in cancer genomes that undergo major chromosomal re-arrangements. It is, therefore, imperative to identify cancer-specific somatic copy number alterations (SCNAs), with respect to matched normal tissue, in order to understand their association with the disease. We have devised an accurate, sensitive, and easy-to-use tool, COPS, COpy number using Paired Samples, for detecting SCNAs. We rigorously tested the performance of COPS using short sequence simulated reads at various sizes and coverage of SCNAs, read depths, read lengths and also with real tumor:normal paired samples. We found COPS to perform better in comparison to other known SCNA detection tools for all evaluated parameters, namely, sensitivity (detection of true positives), specificity (detection of false positives) and size accuracy. COPS performed well for sequencing reads of all lengths when used with most upstream read alignment tools. Additionally, by incorporating a downstream boundary segmentation detection tool, the accuracy of SCNA boundaries was further improved. Here, we report an accurate, sensitive and easy to use tool in detecting cancer-specific SCNAs using short-read sequence data. In addition to cancer, COPS can be used for any disease as long as sequence reads from both disease and normal samples from the same individual are available. An added boundary segmentation detection module makes COPS detected SCNA boundaries more specific for the samples studied. COPS is available at ftp://115.119.160.213 with username “cops” and password “cops”.

Bayesian Random Segmentation Models to Identify Shared Copy Number Aberrations for Array CGH Data

Array-based comparative genomic hybridization (aCGH) is a high-resolution high-throughput technique for studying the genetic basis of cancer. The resulting data consists of log fluorescence ratios as a function of the genomic DNA location and provides a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimation of the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most current methods proceed by modeling a single sample/array at a time, and thus fail to borrow strength across multiple samples to infer shared regions of copy number aberrations. We propose a hierarchical Bayesian random segmentation approach for modeling aCGH data that utilizes information across arrays from a common population to yield segments of shared copy number changes. These changes characterize the underlying population and allow us to compare different population aCGH profiles to assess which regions of the genome have differential alterations. Our method, referred to as BDSAcgh (Bayesian Detection of Shared Aberrations in aCGH), is based on a unified Bayesian hierarchical model that allows us to obtain probabilities of alteration states as well as probabilities of differential alteration that correspond to local false discovery rates. We evaluate the operating characteristics of our method via simulations and an application using a lung cancer aCGH data set.

RNA-Mediated Epigenetic Programming of Genome Rearrangements

RNA, normally thought of as a conduit in gene expression, has a novel mode of action in ciliated protozoa. Maternal RNA templates provide both an organizing guide for DNA rearrangements and a template that can transport somatic mutations to the next generation. This opportunity for RNA-mediated genome rearrangement and DNA repair is profound in the ciliate Oxytricha, which deletes 95% of its germline genome during development in a process that severely fragments its chromosomes and then sorts and reorders the hundreds of thousands of pieces remaining. Oxytricha's somatic nuclear genome is therefore an epigenome formed through RNA templates and signals arising from the previous generation. Furthermore, this mechanism of RNA-mediated epigenetic inheritance can function across multiple generations, and the discovery of maternal template RNA molecules has revealed new biological roles for RNA and has hinted at the power of RNA molecules to sculpt genomic information in cells.

Strategies for genotyping

The identification of genomic loci linked to or associated with human disease has been greatly facilitated by the evolution of genotyping strategies and techniques. The success of these strategies continues to be based upon clear clinical assessment, accurate sample handling, and careful data management, but also increasingly upon experimental design. Technological advances in the field of genotyping have permitted increasingly complex and large population studies to be performed. An understanding of publicly available genetic variation databases, including an awareness of the limitations of these data, and an appreciation of the strategic approaches that should be used to exploit this information will provide tremendous insight for researchers are aiming to utilize this accessible technology. As genome-wide association studies (GWAS) and Next Generation (NextGen) sequencing become the mainstays of genetic analyses, it is important that their technical strengths and limitations, as well as their impact on study design, be understood before use in a linkage or genetic association study.

RNA-mediated epigenetic regulation of DNA copy number

Increasing evidence suggests that parentally supplied RNA plays crucial roles during eukaryotic development. This epigenetic contribution may regulate gene expression from the earliest stages. Although present in a variety of eukaryotes, maternally inherited characters are especially prominent in ciliated protozoa, in which parental noncoding RNA molecules instruct whole-genome reorganization. This includes removal of nearly all noncoding DNA and sorting the remaining fragments, producing extremely gene-rich somatic genomes. Chromosome fragmentation and extensive replication produce variable DNA copy numbers in the somatic genome. Understanding the forces that drive and regulate copy number change is fundamental. We show that RNA molecules present in parental cells during sexual reproduction can regulate chromosome copy number in the developing nucleus of the ciliate Oxytricha. Experimentally induced changes in RNA abundance can both increase and decrease the levels of corresponding DNA molecules in progeny, demonstrating epigenetic inheritance of chromosome copy number. These results suggest that maternal RNA, in addition to controlling gene expression or DNA processing, can also program DNA amplification levels.

DNA fingerprinting techniques for the analysis of genetic and epigenetic alterations in colorectal cancer

Genetic somatic alterations are fundamental hallmarks of cancer. In addition to point and other small mutations targeting cancer genes, solid tumors often exhibit aneuploidy as well as multiple chromosomal rearrangements of large fragments of the genome. Whether somatic chromosomal alterations and aneuploidy are a driving force or a mere consequence of tumorigenesis remains controversial. Recently it became apparent that not only genetic but also epigenetic alterations play a major role in carcinogenesis. Epigenetic regulation mechanisms underlie the maintenance of cell identity crucial for development and differentiation. These epigenetic regulatory mechanisms have been found substantially altered during cancer development and progression. In this review, we discuss approaches designed to analyze genetic and epigenetic alterations in colorectal cancer, especially DNA fingerprinting approaches to detect changes in DNA copy number and methylation. DNA fingerprinting techniques, despite their modest throughput, played a pivotal role in significant discoveries in the molecular basis of colorectal cancer. The aim of this review is to revisit the fingerprinting technologies employed and the oncogenic processes that they unveiled.

High-throughput identification of genetic markers using representational oligonucleotide microarray analysis

We describe a novel approach for high-throughput development of genetic markers using representational oligonucleotide microarray analysis. We test the performance of the method in sugar beet (Beta vulgaris L.) as a model for crop plants with little sequence information available. Genomic representations of both parents of a mapping population were hybridized on microarrays containing in total 146,554 custom made oligonucleotides based on sugar beet bacterial artificial chromosome (BAC) end sequences and expressed sequence tags (ESTs). Oligonucleotides showing a signal with one parental line only, were selected as potential marker candidates and placed onto an array, designed for genotyping of 184 F(2) individuals from the mapping population. Utilizing known co-dominant anchor markers we obtained 511 new dominant markers (392 derived from BAC end sequences, and 119 from ESTs) distributed over all nine sugar beet linkage groups and calculated genetic maps. Further improvements for large-scale application of the approach are discussed and its feasibility for the cost-effective and flexible generation of genetic markers is presented.

Genomic instability in breast cancer: pathogenesis and clinical implications

Breast cancer is a heterogeneous disease, appreciable by molecular markers, gene-expression profiles, and most recently, patterns of genomic alteration. In particular, genomic profiling has revealed three distinct patterns of DNA copy-number alteration: a "simple" type with few gains or losses of whole chromosome arms, an "amplifier" type with focal high-level DNA amplifications, and a "complex" type marked by numerous low-amplitude changes and copy-number transitions. The three patterns are associated with distinct gene-expression subtypes, and preferentially target different loci in the genome (implicating distinct cancer genes). Moreover, the different patterns of alteration imply distinct underlying mechanisms of genomic instability. The amplifier pattern may arise from transient telomere dysfunction, although new data suggest ongoing "amplifier" instability. The complex pattern shows similarity to breast cancers with germline BRCA1 mutation, which also exhibit "basal-like" expression profiles and complex-pattern genomes, implicating a possible defect in BRCA1-associated repair of DNA double-strand breaks. As such, targeting presumptive DNA repair defects represents a promising area of clinical investigation. Future studies should clarify the pathogenesis of breast cancers with amplifier and complex-pattern genomes, and will likely identify new therapeutic opportunities.

Multiplex Amplifiable Probe Hybridization (MAPH) methodology as an alternative to comparative genomic hybridization (CGH)

Genomic imbalances in locus copy-number are highly significant for the diagnosis and prognosis of cancer. Rapidly progressing DNA microarray technologies detect such pathogenic copy-number changes in the genome with high throughput, efficiency, and resolution. A variety of different microarray-based approaches have emerged, with array comparative genomic hybridization (array-CGH) being the method of choice in current clinical practice. Here we describe an alternative microarray-based technique called array-MAPH, derived from conventional Multiplex Amplifiable Probe Hybridization (MAPH).The main novelty of array-MAPH is the directed reduction of test DNA complexity prior to hybridization, yielding a mixture of specific probes, identical to target sequences on the microarray and thus increasing hybridization specificity. Unique amplifiable 400-600 bp fragments can be designed for any genomic region of interest, PCR-amplified, and spotted onto arrays as targets. The same sequences are combined into a probe mixture and hybridized to genomic DNA immobilized on a membrane. Bound probes are recovered by quantitative PCR and hybridized to the array. Array-MAPH can be used for the detection of small-scale copy-number changes, thereby providing new insights into the genetic basis of several diseases, including cancer.

A statistical change point model approach for the detection of DNA copy number variations in array CGH data

Array comparative genomic hybridization (aCGH) provides a high-resolution and high-throughput technique for screening of copy number variations (CNVs) within the entire genome. This technique, compared to the conventional CGH, significantly improves the identification of chromosomal abnormalities. However, due to the random noise inherited in the imaging and hybridization process, identifying statistically significant DNA copy number changes in aCGH data is challenging. We propose a novel approach that uses the mean and variance change point model (MVCM) to detect CNVs or breakpoints in aCGH data sets. We derive an approximate p-value for the test statistic and also give the estimate of the locus of the DNA copy number change. We carry out simulation studies to evaluate the accuracy of the estimate and the p-value formulation. These simulation results show that the approach is effective in identifying copy number changes. The approach is also tested on fibroblast cancer cell line data, breast tumor cell line data, and breast cancer cell line aCGH data sets that are publicly available. Changes that have not been identified by the circular binary segmentation (CBS) method but are biologically verified are detected by our approach on these cell lines with higher sensitivity and specificity than CBS.

Sensitive and accurate detection of copy number variants using read depth of coverage

Methods for the direct detection of copy number variation (CNV) genome-wide have become effective instruments for identifying genetic risk factors for disease. The application of next-generation sequencing platforms to genetic studies promises to improve sensitivity to detect CNVs as well as inversions, indels, and SNPs. New computational approaches are needed to systematically detect these variants from genome sequence data. Existing sequence-based approaches for CNV detection are primarily based on paired-end read mapping (PEM) as reported previously by Tuzun et al. and Korbel et al. Due to limitations of the PEM approach, some classes of CNVs are difficult to ascertain, including large insertions and variants located within complex genomic regions. To overcome these limitations, we developed a method for CNV detection using read depth of coverage. Event-wise testing (EWT) is a method based on significance testing. In contrast to standard segmentation algorithms that typically operate by performing likelihood evaluation for every point in the genome, EWT works on intervals of data points, rapidly searching for specific classes of events. Overall false-positive rate is controlled by testing the significance of each possible event and adjusting for multiple testing. Deletions and duplications detected in an individual genome by EWT are examined across multiple genomes to identify polymorphism between individuals. We estimated error rates using simulations based on real data, and we applied EWT to the analysis of chromosome 1 from paired-end shotgun sequence data (30x) on five individuals. Our results suggest that analysis of read depth is an effective approach for the detection of CNVs, and it captures structural variants that are refractory to established PEM-based methods.

Genomic events associated with progression of pleural malignant mesothelioma

Pleural malignant mesothelioma (MM) is an aggressive cancer with a very long latency and a very short median survival. Little is known about the genetic events that trigger MM and their relation to poor outcome. The goal of our study was to characterize major genomic gains and losses associated with MM origin and progression and assess their clinical significance. We performed Representative Oligonucleotide Microarray Analysis (ROMA) on DNA isolated from tumors of 22 patients who recurred at variable interval with the disease after surgery. The total number of copy number alterations (CNA) and frequent imbalances for patients with short time (<12 months from surgery) and long time to recurrence were recorded and mapped using the Analysis of Copy Errors algorithm. We report a profound increase in CNA in the short-time recurrence group with most chromosomes affected, which can be explained by chromosomal instability associated with MM. Deletions in chromosomes 22q12.2, 19q13.32 and 17p13.1 appeared to be the most frequent events (55-74%) shared between MM patients followed by deletions in 1p, 9p, 9q, 4p, 3p and gains in 5p, 18q, 8q and 17q (23-55%). Deletions in 9p21.3 encompassing CDKN2A/ARF and CDKN2B were characterized as specific for the short-term recurrence group. Analysis of the minimal common areas of frequent gains and losses identified candidate genes that may be involved in different stages of MM: OSM (22q12.2), FUS1 and PL6 (3p21.3), DNAJA1 (9p21.1) and CDH2 (18q11.2-q12.3). Imbalances seen by ROMA were confirmed by Affymetrix genome analysis in a subset of samples.

Copy number alterations in pancreatic cancer identify recurrent PAK4 amplification

Pancreatic cancer is one of the most lethal of all cancers. The median survival is six months and less than 5% of those diagnosed survive five years. Recurrent genetic deletions and amplifications in 72 pancreatic adenocarcinomas, the largest sample set analyzed to date for pancreatic cancer, were defined using comparative genomic hybridization The recurrent genetic alterations identified target a number of previously well-characterized genes, as well as regions that contain possible new oncogenes and tumor suppressor genes. We have focused on chromosome 19q13, a region frequently found amplified in pancreatic cancer and demonstrate how boundaries of common regions of mutation can be mapped and how a gene, in this case PAK4 amplified on chromosome19q13, can be functionally validated. We show that although the PAK4 gene is not activated by mutation in cell lines with gene amplification, an oncogenic form of the KRAS2 gene is present in these cells and oncogenic KRAS2 can activate PAK4. In fact in the three samples we identified with PAK4 gene amplification, the KRAS2 gene was activated and genomically amplified. The kinase activity of the PAK4 protein is significantly higher in cells with genomic amplification as compared to cells without amplification. Our study demonstrates the utility of analyzing copy number data in a large set of neoplasms to identify genes involved in cancer. We have generated a useful dataset which will be particularly useful for the pancreatic cancer community as efforts are undertaken to sequence the pancreatic cancer genome.

Novel genomic alterations and clonal evolution in chronic lymphocytic leukemia revealed by representational oligonucleotide microarray analysis (ROMA)

We examined copy number changes in the genomes of B cells from 58 patients with chronic lymphocytic leukemia (CLL) by using representational oligonucleotide microarray analysis (ROMA), a form of comparative genomic hybridization (CGH), at a resolution exceeding previously published studies. We observed at least 1 genomic lesion in each CLL sample and considerable variation in the number of abnormalities from case to case. Virtually all abnormalities previously reported also were observed here, most of which were indeed highly recurrent. We observed the boundaries of known events with greater clarity and identified previously undescribed lesions, some of which were recurrent. We profiled the genomes of CLL cells separated by the surface marker CD38 and found evidence of distinct subclones of CLL within the same patient. We discuss the potential applications of high-resolution CGH analysis in a clinical setting.

The BAC resource: tools for array CGH and FISH

Bacterial Artificial Chromosome (BAC) vector clones carrying human DNA were chosen as the intermediate templates for the sequencing of the human genome due to their inherent stability and fidelity to the genome sequence from which they were derived. In this unit, we describe a set of protocols for BAC-based array comparative genomic hybridization (aCGH) that comprise the generation of targets for printing solutions onto glass slides, the subsequent hybridization steps, and CGH analysis of a test sample compared to a reference normal sample. The BAC clones through their sequence allow the extent and gene content of numerical aberrations to be delineated by aCGH, and also provide cytogeneticists with tools for subsequent validation or fine mapping studies.

Structural variation of the human genome

There is growing appreciation that the human genome contains significant numbers of structural rearrangements, such as insertions, deletions, inversions, and large tandem repeats. Recent studies have defined approximately 5% of the human genome as structurally variant in the normal population, involving more than 800 independent genes. We present a detailed review of the various structural rearrangements identified to date in humans, with particular reference to their influence on human phenotypic variation. Our current knowledge of the extent of human structural variation shows that the human genome is a highly dynamic structure that shows significant large-scale variation from the currently published genome reference sequence.

Oligonucleotide arrays for high-resolution analysis of copy number alteration in mental retardation/multiple congenital anomalies

Genetic diseases arising from microdeletions and microduplications lead to copy number alterations of genomic regions containing one or more genes. Clinically, these rearrangements may be detected by routine cytogenetic testing, which may include karyotype analysis, subtelomeric analysis with fluorescence in situ hybridization, and/or fluorescence in situ hybridization directed at known chromosomal rearrangement-based disorders. The major limitations of these tests are low resolution and limited coverage of the genome. Array-based comparative genomic hybridization has recently become a widely used approach in the genome-wide analysis of copy number alterations in children with mental retardation and/or multiple congenital anomalies. Oligonucleotide-based arrays provide a genome-wide coverage at a much higher resolution than microarrays currently used in clinical diagnostics, greatly improving the rate of detection of submicroscopic copy number alterations in children with mental retardation and/or multiple congenital anomalies.

Molecular biomarkers for cancer detection in blood and bodily fluids

Cancer is a major and increasing public health problem worldwide. Traditionally, the diagnosis and staging of cancer, as well as the evaluation of response to therapy have been primarily based on morphology, with relatively few cancer biomarkers currently in use. Conventional biomarker studies have been focused on single genes or discrete pathways, but this approach has had limited success because of the complex and heterogeneous nature of many cancers. The completion of the human genome project and the development of new technologies have greatly facilitated the identification of biomarkers for assessment of cancer risk, early detection of primary cancers, monitoring cancer treatment, and detection of recurrence. This article reviews the various approaches used for development of such markers and describes markers of potential clinical interest in major types of cancer. Finally, we discuss the reasons why so few cancer biomarkers are currently available for clinical use.

Digital karyotyping technology: exploring the cancer genome

Identifying gene-specific alterations in cancer genomes has revealed molecules that are causal effectors of carcinogenesis and specific targets for cancer molecular diagnosis and molecular-based cancer therapies. Whole-genome analyses of many cancer genomes at the resolution of single genes is thus a desirable yet incompletely realized goal that could expedite progress in cancer diagnosis and treatment. Although methods for routine whole-genome sequencing or high-resolution epigenetic measurements are currently under development, high-resolution measurements of gene copy number, or 'gene dosage', are now underway in several laboratories. Digital karyotyping, array comparative genomic hybridization, and single nucleotide polymorphism arrays are techniques that have the potential to detect gene amplification, homozygous deletion and loss of heterozygosity at or below the average length of single genes. Recently, digital karyotyping of a small number (<20) of colon and brain cancer genomes has revealed tumor cases with significant genetic dosage alterations affecting few and, in some cases, only one complete gene. These experiments suggest that gene-specific gene dosage alterations may be sufficiently frequent to enable the identification of promising tumor gene candidates in small-scale experiments. The purpose of this review is to describe our understanding of cancer as a genetic disease, review the basic principles, methodologies and interpretational issues of traditional and high-resolution whole-genome screens, and describe the potential of our first detailed look at whole cancer genomes for progress in the understanding and treatment of cancer.

Detection of small genomic imbalances using microarray-based multiplex amplifiable probe hybridization

Array-based genome-wide screening methods were recently introduced to clinical practice in order to detect small genomic imbalances that may cause severe genetic disorders. The continuous advancement of such methods plays an extremely important role in diagnostic genetics and medical genomics. We have modified and adapted the original multiplex amplifiable probe hybridization (MAPH) to a novel microarray format providing an important new diagnostic tool for detection of small size copy-number changes in any locus of human genome. Here, we describe the new array-MAPH diagnostic method and show proof of concept through fabrication, interrogation and validation of a human chromosome X-specific array. We have developed new bioinformatic tools and methodology for designing and producing amplifiable hybridization probes (200-600 bp) for array-MAPH. We designed 558 chromosome X-specific probes with median spacing 238 kb and 107 autosomal probes, which were spotted onto microarrays. DNA samples from normal individuals and patients with known and unknown chromosome X aberrations were analyzed for validation. Array-MAPH detected exactly the same deletions and duplications in blind studies, as well as other unknown small size deletions showing its accuracy and sensitivity. All results were confirmed by fluorescence in situ hybridization and probe-specific PCR. Array-MAPH is a new microarray-based diagnostic tool for the detection of small-scale copy-number changes in complex genomes, which may be useful for genotype-phenotype correlations, identification of new genes, studying genetic variation and provision of genetic services.

Molecular profiling techniques and bioinformatics in cancer research

AIMS

Our aim was to describe the commonly used molecular profiling techniques in cancer research, to examine their limitations and to discuss the challenges of bioinformatics.

METHODS

A literature search was performed using the PubMed database to identify publications relevant to this review. Citations from these articles were also examined to yield further relevant publications.

RESULTS

We describe the use of DNA microarrays, comparative genomic hybridisation, tissue microarrays and digital differential display. The limitations of these technologies, their contribution to cancer research and the challenges of bioinformatics are also discussed.

CONCLUSIONS

Although these high throughput technologies each have their own limitations they are rapidly developing and contributing significantly to our understanding of cancer genetics. They have also led to the emergence of bioinformatics as a rapidly developing and vital field.

Technology Insight: querying the genome with microarrays--progress and hope for neurological disease

The ability to perform large-scale analysis of the genome at the level of gene sequence, gene copy number and messenger RNA transcript expression characterizes the post-genomic era. In the past decade, the microarray-based approach has emerged as one of the major tools in this area of genome biology, contributing to advances in the understanding of Mendelian and complex neurological disorders. Despite technical issues regarding design, data analysis and validation that have to be addressed in the planning and interpretation of a microarray study, microarray-based approaches for studying transcript expression, single-nucleotide-polymorphism genotyping and gene resequencing are becoming more widely adopted. Genomic microarrays are providing an unprecedented opportunity to dissect the genetic risk for complex neurological disorders. Numerous clinical and preclinical applications are likely to dominate the ambitious microarray agenda within the next decade.

The impact of genomic alterations on the transcriptome: a prostate cancer cell line case study

Genetic instability may lead to the loss/gain of transcriptional control. Here we investigated the effect of genomic instability, that is loss/gain of chromosomal regions on the global transcriptome of prostate cancer cell line DU145. The genomic loss/gain map obtained through BAC array-based CGH was superimposed on the dynamic transcriptome of DU145 cells treated with serum for 0 h (serum starved), 2 h and 12 h. The genomic analysis suggested that in DU145 cells: (1) chromosomal gains are prominent than losses and (2) copy number changes are associated with chromosome-specific and dynamic gene expression regulatory mechanisms. A significant proportion of the genes in the stable regions of the chromosome were up-regulated whereas a higher proportion of genes were down-regulated at 2 and 12 h in the deleted regions of the chromosomes following serum treatment. No change in expression was observed for the genes in the gained regions over a period of time. This analysis led us to propose that loss of heterozygosity leads to an overall transcriptional down-regulation that may further lead to a decrease in the expression of putative tumor suppressors. The genomic profile of DU145 is similar to pathological specimens of prostate cancer, hence the genomic/transcriptomic signature of DU145 can be used to understand the pathology of prostate cancer. It is expected that this analysis will allow a better understanding of transcriptional regulatory mechanisms in the context of genomic loss and gain and may lead to the discovery of novel oncogenes and tumor suppressors and the underlying regulatory pathways.

Combined microarray analysis of small cell lung cancer reveals altered apoptotic balance and distinct expression signatures of MYC family gene amplification

DNA amplifications and deletions frequently contribute to the development and progression of lung cancer. To identify such novel alterations in small cell lung cancer (SCLC), we performed comparative genomic hybridization on a set of 24 SCLC cell lines, using cDNA microarrays representing approximately 22,000 human genes (providing an average mapping resolution of <70 kb). We identified localized DNA amplifications corresponding to oncogenes known to be amplified in SCLC, including MYC (8q24), MYCN (2p24) and MYCL1 (1p34). Additional highly localized DNA amplifications suggested candidate oncogenes not previously identified as amplified in SCLC, including the antiapoptotic genes TNFRSF4 (1p36), DAD1 (14q11), BCL2L1 (20q11) and BCL2L2 (14q11). Likewise, newly discovered PCR-validated homozygous deletions suggested candidate tumor-suppressor genes, including the proapoptotic genes MAPK10 (4q21) and TNFRSF6 (10q23). To characterize the effect of DNA amplification on gene expression patterns, we performed expression profiling using the same microarray platform. Among our findings, we identified sets of genes whose expression correlated with MYC, MYCN or MYCL1 amplification, with surprisingly little overlap among gene sets. While both MYC and MYCN amplification were associated with increased and decreased expression of known MYC upregulated and downregulated targets, respectively, MYCL1 amplification was associated only with the latter. Our findings support a role of altered apoptotic balance in the pathogenesis of SCLC, and suggest that MYC family genes might affect oncogenesis through distinct sets of targets, in particular implicating the importance of transcriptional repression.

Validation of S. Pombe Sequence Assembly by Microarray Hybridization

We describe a method to make physical maps of genomes using correlative hybridization patterns of probes to random pools of BACs. We derive thereby an estimated distance between probes, and then use this estimated distance to order probes. To test the method, we used BAC libraries from Schizzosaccharomyces pombe. We compared our data to the known sequence assembly, in order to assess accuracy. We demonstrate a small number of significant discrepancies between our method and the map derived by sequence assembly. Some of these discrepancies may arise because genome order within a population is not stable; imposing a linear order on a population may not be biologically meaningful.

Comparative genomic hybridization

Altering DNA copy number is one of the many ways that gene expression and function may be modified. Some variations are found among normal individuals ( 14, 35, 103 ), others occur in the course of normal processes in some species ( 33 ), and still others participate in causing various disease states. For example, many defects in human development are due to gains and losses of chromosomes and chromosomal segments that occur prior to or shortly after fertilization, whereas DNA dosage alterations that occur in somatic cells are frequent contributors to cancer. Detecting these aberrations, and interpreting them within the context of broader knowledge, facilitates identification of critical genes and pathways involved in biological processes and diseases, and provides clinically relevant information. Over the past several years array comparative genomic hybridization (array CGH) has demonstrated its value for analyzing DNA copy number variations. In this review we discuss the state of the art of array CGH and its applications in medical genetics and cancer, emphasizing general concepts rather than specific results.

Design considerations for array CGH to oligonucleotide arrays

BACKGROUND

Representational oligonucleotide microarray analysis has been developed for detection of single nucleotide polymorphisms and/or for genome copy number changes. In this process, the intensity of hybridization to oligonucleotides arrays is increased by hybridizing a polymerase chain reaction (PCR)-amplified representation of reduced genomic complexity. However, hybridization to some oligonucleotides is not sufficiently high to allow precise analysis of that portion of the genome.

METHODS

In an effort to identify aspects of oligonucleotide hybridization affecting signal intensity, we explored the importance of the PCR product strand to which each oligonucleotide is homologous and the sequence of the array oligonucleotides. We accomplished this by hybridizing multiple PCR-amplified products to oligonucleotide arrays carrying two sense and two antisense 50-mer oligonucleotides for each PCR amplicon.

RESULTS

In some cases, hybridization intensity depended more strongly on the PCR amplicon strand (i.e., sense vs. antisense) than on the detection oligonucleotide sequence. In other cases, the oligonucleotide sequence seemed to dominate.

CONCLUSION

Oligonucleotide arrays for analysis of DNA copy number or for single nucleotide polymorphism content should be designed to carry probes to sense and antisense strands of each PCR amplicon to ensure sufficient hybridization and signal intensity.

Transforming science: cancer gene identification

Methods for cancer gene discovery include identification of viral oncogenes, identification of genes associated with recurrent chromosomal aberrations, and screens for genes capable of the transformation of cells in culture. In recent years, the completed genome sequence of human and model organisms has markedly enhanced cancer gene identification. Whole genome, high-throughput screens have been facilitated by the advent of new technologies such as murine leukemia virus-based mutagenesis, Sleeping Beauty-based mutagenesis, RNA interference, exon re-sequencing, and high-resolution methods for detecting chromosomal amplifications and deletions; these, in turn, have led to the identification of novel tumor suppressors and oncogenes. The identification of genes that are altered by mutation or expression and which are directly involved in tumor initiation and maintenance will be instrumental for understanding cancer phenotypic variation and for identifying crucial therapeutic targets.

Array-based comparative genomic hybridization identifies localized DNA amplifications and homozygous deletions in pancreatic cancer

Pancreatic cancer, the fourth leading cause of cancer death in the United States, is frequently associated with the amplification and deletion of specific oncogenes and tumor-suppressor genes (TSGs), respectively. To identify such novel alterations and to discover the underlying genes, we performed comparative genomic hybridization on a set of 22 human pancreatic cancer cell lines, using cDNA microarrays measuring approximately 26,000 human genes (thereby providing an average mapping resolution of <60 kb). To define the subset of amplified and deleted genes with correspondingly altered expression, we also profiled mRNA levels in parallel using the same cDNA microarray platform. In total, we identified 14 high-level amplifications (38-4934 kb in size) and 15 homozygous deletions (46-725 kb). We discovered novel localized amplicons, suggesting previously unrecognized candidate oncogenes at 6p21, 7q21 (SMURF1, TRRAP), 11q22 (BIRC2, BIRC3), 12p12, 14q24 (TGFB3), 17q12, and 19q13. Likewise, we identified novel polymerase chain reaction-validated homozygous deletions indicating new candidate TSGs at 6q25, 8p23, 8p22 (TUSC3), 9q33 (TNC, TNFSF15), 10q22, 10q24 (CHUK), 11p15 (DKK3), 16q23, 18q23, 21q22 (PRDM15, ANKRD3), and Xp11. Our findings suggest candidate genes and pathways, which may contribute to the development or progression of pancreatic cancer.

Complex phenotypes and complex genetics: an introduction to genetic studies of complex traits

There is currently intense interest in the genetic factors contributing to many diseases with cardiovascular complications. Diseases like atherosclerosis, diabetes, and hypertension are referred to as complex traits because multiple genes contribute to the phenotype either individually or through interactions with each other or the environment. Enabled and energized by the striking successes over the past 20 years in identifying genes that are responsible for single gene traits, many geneticists have turned to the investigation of methods that will allow for the dissection of complex traits. There have already been some successes, so there is no reason to consider the problem as inherently intractable. However, it is important to reflect on what conditions are necessary for the identification of genes that operate in complex traits. A recurring theme in this research area has been difficulty in repeating and validating research findings, and this most often can be attributed to limitations in study design. It is also important to consider that any particular research strategy can only hope to describe a portion of factors that contribute to variation in the population; therefore, the genetic approach cannot be a panacea. New efficient technologies for genotyping and public databases describing the fine structure of genetic correlations in the genome should aid many aspects of the gene discovery process.

Array-based comparative genomic hybridization from formalin-fixed, paraffin-embedded breast tumors

Identification of prognostic and predictive genomic markers requires long-term clinical follow-up of patients. Extraction of high-quality DNA from archived formalin-fixed, paraffin-embedded material is essential for such studies. Of particular importance is a robust reproducible method of whole genome amplification for small tissue samples. This is especially true for high-resolution analytical approaches because different genomic regions and sequences may amplify differentially. We have tested a number of protocols for DNA amplification for array-based comparative genomic hybridization (CGH), in which relative copy number of the entire genome is measured at 1 to 2 mb resolution. Both random-primed amplification and degenerate oligonucleotide-primed amplification approaches were tested using varying amounts of fresh and paraffin-extracted normal and breast tumor input DNAs. We found that random-primed amplification was clearly superior to degenerate oligonucleotide-primed amplification for array-based CGH. The best quality and reproducibility strongly depended on accurate determination of the amount of input DNA using a quantitative polymerase chain reaction-based method. Reproducible and high-quality results were attained using 50 ng of input DNA, and some samples yielded quality results with as little as 5 ng input DNA. We conclude that random-primed amplification of DNA isolated from paraffin sections is a robust and reproducible approach for array-based CGH analysis of archival tumor samples.

Array comparative genomic hybridization and its applications in cancer

Alteration in DNA copy number is one of the many ways in which gene expression and function may be modified. Some variations are found among normal individuals, others occur in the course of normal processes in some species and still others participate in causing various disease states. For example, many defects in human development are due to gains and losses of chromosomes and chromosomal segments that occur before or shortly after fertilization, and DNA dosage-alteration changes occurring in somatic cells are frequent contributors to cancer. Detecting these aberrations and interpreting them in the context of broader knowledge facilitates the identification of crucial genes and pathways involved in biological processes and disease. Over the past several years, array comparative genomic hybridization has proven its value for analyzing DNA copy-number variations. Here, we discuss the state of the art of array comparative genomic hybridization and its applications in cancer, emphasizing general concepts rather than specific results.

Exon array CGH: detection of copy-number changes at the resolution of individual exons in the human genome

The development of high-throughput screening methods such as array-based comparative genome hybridization (array CGH) allows screening of the human genome for copy-number changes. Current array CGH strategies have limits of resolution that make detection of small (less than a few tens of kilobases) gains or losses of genomic DNA difficult to identify. We report here a significant improvement in the resolution of array CGH, with the development of an array platform that utilizes single-stranded DNA array elements to accurately measure copy-number changes of individual exons in the human genome. Using this technology, we screened 31 patient samples across an array containing a total of 162 exons for five disease genes and detected copy-number changes, ranging from whole-gene deletions and duplications to single-exon deletions and duplications, in 100% of the cases. Our data demonstrate that it is possible to screen the human genome for copy-number changes with array CGH at a resolution that is 2 orders of magnitude higher than that previously reported.

Quantifying the mechanisms for segmental duplications in mammalian genomes by statistical analysis and modeling

A large number of the segmental duplications in mammalian genomes have been cataloged by genome-wide sequence analyses. The molecular mechanisms involved in these duplications mostly remain a matter of speculation. To uncover, test, and further quantify the hypotheses on the mechanisms for the recent duplications in the mammalian genomes, we have performed a series of statistical analyses on the sequences flanking the duplicated segments and proposed a dynamic model for the duplication process. The model, when applied to the human duplication data, indicates that approximately 30% of the recent human segmental duplications were caused by a recombination-like mechanism, among which 12% were mediated by the most recently active repeat, Alu. But a significant proportion of the duplications are caused by some mechanism independent of the repeat distribution. A less sure but similar picture is found in the rodent genomes. A further analysis on the physical features of the flanking sequences suggests that one of the uncharacterized duplication mechanisms shared by the mammalian genomes is surprisingly well correlated with the physical instability in the DNA sequences.

Estimating the copy number of transgenes in transformed rice by real-time quantitative PCR

In transgenic plants, transgene copy number can greatly influence the expression level and genetic stability of the target gene, making estimation of transgene copy number an important area of genetically modified (GM) crop research. Transgene copy numbers are currently estimated by Southern analysis, which is laborious and time-consuming, requires relatively large amounts of plant materials and may involve hazardous radioisotopes. We report here the development of a sensitive, high-throughput real-time (RT)-PCR technique for estimating transgene copy number in GM rice. This system uses TaqMan quantitative RT-PCR and comparison to a novel rice endogenous reference gene coding for sucrose phosphate synthase (SPS) to determine the copy numbers of the exogenous beta-glucuronidase (GUS) and hygromycin phosphotransferase (HPT) genes in transgenic rice. The copy numbers of the GUS and HPT in primary rice transformants (T0) were calculated by comparing quantitative PCR results of the GUS and HPT genes with those of the internal standard, SPS. With optimized PCR conditions, we achieved significantly accurate estimates of one, two, three and four transgene copies in the T0 transformants. Furthermore, our copy number estimations of both the GUS reporter gene and the HPT selective marker gene showed that rearrangements of the T-DNA occurred more frequently than is generally believed in transgenic rice.

A versatile statistical analysis algorithm to detect genome copy number variation

We have developed a versatile statistical analysis algorithm for the detection of genomic aberrations in human cancer cell lines. The algorithm analyzes genomic data obtained from a variety of array technologies, such as oligonucleotide array, bacterial artificial chromosome array, or array-based comparative genomic hybridization, that operate by hybridizing with genomic material obtained from cancer and normal cells and allow detection of regions of the genome with altered copy number. The number of probes (i.e., resolution), the amount of uncharacterized noise per probe, and the severity of chromosomal aberrations per chromosomal region may vary with the underlying technology, biological sample, and sample preparation. Constrained by these uncertainties, our algorithm aims at robustness by using a priorless maximum a posteriori estimator and at efficiency by a dynamic programming implementation. We illustrate these characteristics of our algorithm by applying it to data obtained from representational oligonucleotide microarray analysis and array-based comparative genomic hybridization technology as well as to synthetic data obtained from an artificial model whose properties can be varied computationally. The algorithm can combine data from multiple sources and thus facilitate the discovery of genes and markers important in cancer, as well as the discovery of loci important in inherited genetic disease.

An integrated view of copy number and allelic alterations in the cancer genome using single nucleotide polymorphism arrays

Changes in DNA copy number contribute to cancer pathogenesis. We now show that high-density single nucleotide polymorphism (SNP) arrays can detect copy number alterations. By hybridizing genomic representations of breast and lung carcinoma cell line and lung tumor DNA to SNP arrays, and measuring locus-specific hybridization intensity, we detected both known and novel genomic amplifications and homozygous deletions in these cancer samples. Moreover, by combining genotyping with SNP quantitation, we could distinguish loss of heterozygosity events caused by hemizygous deletion from those that occur by copy-neutral events. The simultaneous measurement of DNA copy number changes and loss of heterozygosity events by SNP arrays should strengthen our ability to discover cancer-causing genes and to refine cancer diagnosis.