A stepwise framework for the normalization of array CGH data

Identifying crossovers and shared genetic material in whole genome sequencing data from families

Large, whole-genome sequencing (WGS) data sets containing families provide an important opportunity to identify crossovers and shared genetic material in siblings. However, the high variant calling error rates of WGS in some areas of the genome can result in spurious crossover calls, and the special inheritance status of the X Chromosome presents challenges. We have developed a hidden Markov model that addresses these issues by modeling the inheritance of variants in families in the presence of error-prone regions and inherited deletions. We call our method PhasingFamilies. We validate PhasingFamilies using the platinum genome family NA1281 (precision: 0.81; recall: 0.97), as well as simulated genomes with known crossover positions (precision: 0.93; recall: 0.92). Using 1925 quads from the Simons Simplex Collection, we found that PhasingFamilies resolves crossovers to a median resolution of 3527.5 bp. These crossovers recapitulate existing recombination rate maps, including for the X Chromosome; produce sibling pair IBD that matches expected distributions; and are validated by the haplotype estimation tool SHAPEIT. We provide an efficient, open-source implementation of PhasingFamilies that can be used to identify crossovers from family sequencing data.

Differentially expressed microRNAs in lung adenocarcinoma invert effects of copy number aberrations of prognostic genes

In many cancers, significantly down- or upregulated genes are found within chromosomal regions with DNA copy number alteration opposite to the expression changes. Generally, this paradox has been overlooked as noise, but can potentially be a consequence of interference of epigenetic regulatory mechanisms, including microRNA-mediated control of mRNA levels.

To explore potential associations between microRNAs and paradoxes in non-small-cell lung cancer (NSCLC) we curated and analyzed lung adenocarcinoma (LUAD) data, comprising gene expressions, copy number aberrations (CNAs) and microRNA expressions. We integrated data from 1,062 tumor samples and 241 normal lung samples, including newly-generated array comparative genomic hybridization (aCGH) data from 63 LUAD samples.

We identified 85 “paradoxical” genes whose differential expression consistently contrasted with aberrations of their copy numbers. Paradoxical status of 70 out of 85 genes was validated on sample-wise basis using The Cancer Genome Atlas (TCGA) LUAD data. Of these, 41 genes are prognostic and form a clinically relevant signature, which we validated on three independent datasets. By meta-analysis of results from 9 LUAD microRNA expression studies we identified 24 consistently-deregulated microRNAs. Using TCGA-LUAD data we showed that deregulation of 19 of these microRNAs explains differential expression of the paradoxical genes.

Our results show that deregulation of paradoxical genes is crucial in LUAD and their expression pattern is maintained epigenetically, defying gene copy number status.

Computational Methods for the Analysis of Array Comparative Genomic Hybridization

Array comparative genomic hybridization (array CGH) is a technique for assaying the copy number status of cancer genomes. The widespread use of this technology has lead to a rapid accumulation of high throughput data, which in turn has prompted the development of computational strategies for the analysis of array CGH data. Here we explain the principles behind array image processing, data visualization and genomic profile analysis, review currently available software packages, and raise considerations for future software development.

Normalized, Segmented or Called aCGH Data?

Array comparative genomic hybridization (aCGH) is a high-throughput lab technique to measure genome-wide chromosomal copy numbers. Data from aCGH experiments require extensive pre-processing, which consists of three steps: normalization, segmentation and calling. Each of these pre-processing steps yields a different data set: normalized data, segmented data, and called data. Publications using aCGH base their findings on data from all stages of the pre-processing. Hence, there is no consensus on which should be used for further down-stream analysis. This consensus is however important for correct reporting of findings, and comparison of results from different studies. We discuss several issues that should be taken into account when deciding on which data are to be used. We express the believe that called data are best used, but would welcome opposing views.

Early dissemination seeds metastasis in breast cancer

Accumulating data suggest that metastatic dissemination often occurs early during tumour formation but the mechanisms of early metastatic spread have not yet been addressed. Here, we studied metastasis in a HER2-driven mouse breast cancer model and found that progesterone-induced signalling triggered migration of cancer cells from early lesions shortly after HER2 activation, but promoted proliferation in advanced primary tumour cells. The switch from migration to proliferation was regulated by elevated HER2 expression and increased tumour cell density involving miRNA-mediated progesterone receptor (PGR) down-regulation and was reversible. Cells from early, low-density lesions displayed more stemness features than cells from dense, advanced tumours, migrated more and founded more metastases. Strikingly, we found that at least 80% of metastases were derived from early disseminated cancer cells (DCC). Karyotypic and phenotypic analysis of human disseminated cancer cells and primary tumours corroborated the relevance of these findings for human metastatic dissemination.

NBN gain is predictive for adverse outcome following image-guided radiotherapy for localized prostate cancer

Despite the use of clinical prognostic factors (PSA, T-category and Gleason score), 20-60% of localized prostate cancers (PCa) fail primary local treatment. Herein, we determined the prognostic importance of main sensors of the DNA damage response (DDR): MRE11A, RAD50, NBN, ATM, ATR and PRKDC. We studied copy number alterations in DDR genes in localized PCa treated with image-guided radiotherapy (IGRT; n=139) versus radical prostatectomy (RadP; n=154). In both cohorts, NBN gains were the most frequent genomic alteration (14.4 and 11% of cases, respectively), and were associated with overall tumour genomic instability (p<0.0001). NBN gains were the only significant predictor of 5yrs biochemical relapse-free rate (bRFR) following IGRT (46% versus 77%; p=0.00067). On multivariate analysis, NBN gain remained a significant independent predictor of bRFR after adjusting for known clinical prognostic variables (HR=3.28, 95% CI 1.56–6.89, Wald p-value=0.0017). No DDR-sensing gene was prognostic in the RadP cohort. In vitro studies correlated NBN gene overexpression with PCa cells radioresistance. In conclusion, NBN gain predicts for decreased bRFR in IGRT, but not in RadP patients. If validated independently, Nibrin gains may be the first PCa predictive biomarker to facilitate local treatment decisions using precision medicine approaches with surgery or radiotherapy.

Molecular characterization of immortalized normal and dysplastic oral cell lines

BACKGROUND

Cell lines have been developed for modeling cancer and cancer progression. The molecular background of these cell lines is often unknown to those using them to model disease behaviors. As molecular alterations are the ultimate drivers of cell phenotypes, having an understanding of the molecular make-up of these systems is critical for understanding the disease biology modeled.

METHODS

Six immortalized normal, one immortalized dysplasia, one self-immortalized dysplasia, and two primary normal cell lines derived from oral tissues were analyzed for DNA copy number changes and changes in both mRNA and miRNA expression using SMRT-v.2 genome-wide tiling comparative genomic hybridization arrays, Agilent Whole Genome 4x44k expression arrays, and Exiqon V2.M-RT-PCR microRNA Human panels.

RESULTS

DNA copy number alterations were detected in both normal and dysplastic immortalized cell lines-as well as in the single non-immortalized dysplastic cell line. These lines were found to have changes in expression of genes related to cell cycle control as well as alterations in miRNAs that are deregulated in clinical oral squamous cell carcinoma tissues. Immortal lines-whether normal or dysplastic-had increased disruption in expression relative to primary lines. All data are available as a public resource.

CONCLUSIONS

Molecular profiling experiments have identified DNA, mRNA, and miRNA alterations for a panel of normal and dysplastic oral tissue cell lines. These data are a valuable resource to those modeling diseases of the oral mucosa, and give insight into the selection of model cell lines and the interpretation of data from those lines.

Recurring DNA copy number gain at chromosome 9p13 plays a role in the activation of multiple candidate oncogenes in progressing oral premalignant lesions

Genomic alteration at chromosome 9p has been previously reported as a frequent and critical event in oral premalignancy. While this alteration is typically reported as a loss driven by selection for CDKN2A deactivation (at 9p21.3), we detect a recurrent DNA copy number gain of ∼2.49 Mbp at chromosome 9p13 in oral premalignant lesions (OPLs) that later progressed to invasive lesions. This recurrent alteration event has been validated using fluorescence in situ hybridization in an independent set of OPLs. Analysis of publicly available gene expression datasets aided in identifying three oncogene candidates that may have driven selection for DNA copy number increases in this region (VCP, DCTN3, and STOML2). We performed in vitro silencing and activation experiments for each of these genes in oral cancer cell lines and found that each gene is independently capable of upregulating proliferation and anchorage-independent growth. We next analyzed the activity of each of these genes in biopsies of varying histological grades that were obtained from a diseased oral tissue field in a single patient, finding further molecular evidence of parallel activation of VCP, DCTN3, and STOML2 during progression from normal healthy tissue to invasive oral carcinoma. Our results support the conclusion that DNA gain at 9p13 is important to the earliest stages of oral tumorigenesis and that this alteration event likely contributes to the activation of multiple oncogene candidates capable of governing oral cancer phenotypes.

YEATS4 is a novel oncogene amplified in non-small cell lung cancer that regulates the p53 pathway

Genetic analyses of lung cancer have helped found new treatments in this disease. We conducted an integrative analysis of gene expression and copy number in 261 non-small cell lung cancers (NSCLC) relative to matched normal tissues to define novel candidate oncogenes, identifying 12q13-15 and more specifically the YEATS4 gene as amplified and overexpressed in ~20% of the NSCLC cases examined. Overexpression of YEATS4 abrogated senescence in human bronchial epithelial cells. Conversely, RNAi-mediated attenuation of YEATS4 in human lung cancer cells reduced their proliferation and tumor growth, impairing colony formation and inducing cellular senescence. These effects were associated with increased levels of p21WAF1 and p53 and cleavage of PARP, implicating YEATS4 as a negative regulator of the p21-p53 pathway. We also found that YEATS4 expression affected cellular responses to cisplastin, with increased levels associated with resistance and decreased levels with sensitivity. Taken together, our findings reveal YEATS4 as a candidate oncogene amplified in NSCLC, and a novel mechanism contributing to NSCLC pathogenesis.

Evaluation of calling algorithms for array-CGH

Copy number variation (CNV) detection has become an integral part many of genetic studies and new technologies promise to revolutionize our ability to detect and link them to disease. However, recent studies highlight discrepancies in the genome wide CNV profile when measured by different technologies and even by the same technology. Furthermore, the change point algorithms used to call CNVs can have substantial disagreement on the same data set. We focus this article on comparative genomic hybridization (CGH) arrays because this platform lends itself well to accurate statistical modeling. We describe some newer methodological developments in local statistics that are well suited for CNV detection and calling on CGH arrays. Then we use both simulation studies and public data to compare these new local methods with the global methods that currently dominate literature. These results offer suggestions for choosing a particular method and provide insight to the lack of reproducibility that has been seen in the field so far.

Elevated expression of BIRC6 protein in non-small-cell lung cancers is associated with cancer recurrence and chemoresistance

INTRODUCTION

Non-small-cell lung cancer (NSCLC) is an aggressive, highly chemoresistant disease. Reliable prognostic assays and more effective treatments are critically required. BIRC6 (baculoviral inhibitors of apoptosis proteins repeat-containing 6) protein is a member of the inhibitors of apoptosis protein family thought to play an important role in the progression or chemoresistance of many cancers. In this study, we investigated whether BIRC6 expression can be used as a prognostic marker or potential therapeutic target for NSCLC.

METHODS

In a retrospective analysis, BIRC6 protein expression was determined for 78 resected primary NSCLCs and nine benign lung tissues. Twenty-nine chemoresistant or chemosensitive subrenal capsule NSCLC tissue xenografts were assessed for BIRC6 expression, using immunohistochemistry, and 13 of them for BIRC6 gene copy number, using array comparative genomic hybridization analysis. The effect of small interfering RNA-induced BIRC6 knockdown on the growth of human NSCLC cell cultures and apoptosis (in combination with cisplatin) was investigated.

RESULTS

Elevated BIRC6 protein expression in NSCLC tissues was associated with poor 3-year relapse-free patient survival, lymph node involvement, and advanced pathological tumor, node, metastasis stage. In patient-derived lung squamous cell carcinoma xenografts, chemoresistance was associated with elevated BIRC6 expression and increased gene copy number. Small interfering RNA-induced BIRC6 down-regulation inhibited growth of the NSCLC cells and sensitized the cells to cisplatin.

CONCLUSIONS

BIRC6 may play an important role in the malignant progression and chemoresistance of NSCLC. Elevated BIRC6 protein expression may serve as a predictive marker for chemoresistance of NSCLCs and a poor prognostic factor for NSCLC patients. Down-regulation of the BIRC6 gene as a therapeutic approach may be effective, especially in combination with conventional chemotherapeutics.

SOX15 is a candidate tumor suppressor in pancreatic cancer with a potential role in Wnt/β-catenin signaling

Pancreatic cancer is among the top five deadliest cancers in developed countries. Better knowledge of the molecular mechanisms contributing to its tumorigenesis is imperative to improve patient prognosis. Identification of novel tumor suppressor genes (TSGs) in pancreatic cancer will reveal new mechanisms of pathway deregulation and will ultimately help improve our understanding of this aggressive disease. According to Knudson's two-hit model, TSGs are classically disrupted by two concerted genetic events. In this study, we combined DNA methylation profiling with copy number and mRNA expression profiling to identify novel TSGs in a set of 20 pancreatic cancer cell lines. These data sets were integrated for each of ∼12 000 genes in each cell line enabling the elucidation of those genes that undergo DNA hypermethylation, copy-number loss and mRNA downregulation simultaneously in multiple cell lines. Using this integrative genomics strategy, we identified SOX15 (sex determining region Y-box 15) as a candidate TSG in pancreatic cancer. Expression of SOX15 in pancreatic cancer cell lines with undetectable expression resulted in reduced viability of cancer cells both in vitro and in vivo demonstrating its tumor suppressive capability. We also found reduced expression, homozygous deletion and aberrant DNA methylation of SOX15 in clinical pancreatic tumor data sets. Furthermore, we deduced a novel role for SOX15 in suppressing the Wnt/β-catenin signaling pathway, which we hypothesize is a pathway through which SOX15 may exert its tumor suppressive effects in pancreatic cancer.

Array comparative genomic hybridization: an overview of protocols, applications, and technology trends

From the earliest observations of human chromosomes in the late 1800s to modern day next generation sequencing technologies, much has been learned about human cancers by the vigorous application of the techniques of the day. In general, resolution has improved tremendously, and correspondingly the size of the datasets generated has grown exponentially such that computational methods required to handle massive datasets have had to be devised. This chapter provides a brief synopsis of the evolution of such techniques as an introduction to the subsequent chapters that provide methods and applications, relevant to research, and clinical diagnostics.

Divergent genomic and epigenomic landscapes of lung cancer subtypes underscore the selection of different oncogenic pathways during tumor development

For therapeutic purposes, non-small cell lung cancer (NSCLC) has traditionally been regarded as a single disease. However, recent evidence suggest that the two major subtypes of NSCLC, adenocarcinoma (AC) and squamous cell carcinoma (SqCC) respond differently to both molecular targeted and new generation chemotherapies. Therefore, identifying the molecular differences between these tumor types may impact novel treatment strategy. We performed the first large-scale analysis of 261 primary NSCLC tumors (169 AC and 92 SqCC), integrating genome-wide DNA copy number, methylation and gene expression profiles to identify subtype-specific molecular alterations relevant to new agent design and choice of therapy. Comparison of AC and SqCC genomic and epigenomic landscapes revealed 778 altered genes with corresponding expression changes that are selected during tumor development in a subtype-specific manner. Analysis of >200 additional NSCLCs confirmed that these genes are responsible for driving the differential development and resulting phenotypes of AC and SqCC. Importantly, we identified key oncogenic pathways disrupted in each subtype that likely serve as the basis for their differential tumor biology and clinical outcomes. Downregulation of HNF4α target genes was the most common pathway specific to AC, while SqCC demonstrated disruption of numerous histone modifying enzymes as well as the transcription factor E2F1. In silico screening of candidate therapeutic compounds using subtype-specific pathway components identified HDAC and PI3K inhibitors as potential treatments tailored to lung SqCC. Together, our findings suggest that AC and SqCC develop through distinct pathogenetic pathways that have significant implication in our approach to the clinical management of NSCLC.

Copy number alterations of c-MYC and PTEN are prognostic factors for relapse after prostate cancer radiotherapy

Despite the use of PSA, Gleason score, and T-category as prognosticators in intermediate-risk prostate cancer, 20-40% of patients will fail local therapy. In order to optimize treatment approaches for intermediate-risk patients, additional genetic prognosticators are needed. Previous reports using array comparative genomic hybridization (aCGH) in radical prostatectomy cohorts suggested a combination of allelic loss of the PTEN gene on 10q and allelic gain of the c-MYC gene on 8q were associated with metastatic disease. We tested whether copy number alterations (CNAs) in PTEN (allelic loss) and c-MYC (allelic gain) were associated with biochemical relapse following modern-era, image-guided radiotherapy (mean dose 76.4 Gy). We used aCGH analyses validated by fluorescence in-situ hybridization (FISH) of DNA was derived from frozen, pre-treatment biopsies in 126 intermediate-risk prostate cancer patients. Patients whose tumors had CNAs in both PTEN and c-MYC had significantly increased genetic instability (percent genome alteration; PGA) compared to tumors with normal PTEN and c-MYC status (p < 0.0001). We demonstrate that c-MYC gain alone, or combined c-MYC gain and PTEN loss, were increasingly prognostic for relapse on multivariable analyses (hazard ratios (HR) of 2.58/p = 0.005 and 3.21/p = 0.0004; respectively). Triaging patients by the use of CNAs within pre-treatment biopsies may allow for better use of systemic therapies to target sub-clinical metastases or locally recurrent disease and improve clinical outcomes.

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.

Bayesian Hidden Markov Modeling of Array CGH Data

Genomic alterations have been linked to the development and progression of cancer. The technique of comparative genomic hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of statistics for learning about the genomic alterations from array CGH data. As increasing amounts of array CGH data become available, there is a growing need for automated algorithms for characterizing genomic profiles. Specifically, there is a need for algorithms that can identify gains and losses in the number of copies based on statistical considerations, rather than merely detect trends in the data.We adopt a Bayesian approach, relying on the hidden Markov model to account for the inherent dependence in the intensity ratios. Posterior inferences are made about gains and losses in copy number. Localized amplifications (associated with oncogene mutations) and deletions (associated with mutations of tumor suppressors) are identified using posterior probabilities. Global trends such as extended regions of altered copy number are detected. Because the posterior distribution is analytically intractable, we implement a Metropolis-within-Gibbs algorithm for efficient simulation-based inference. Publicly available data on pancreatic adenocarcinoma, glioblastoma multiforme, and breast cancer are analyzed, and comparisons are made with some widely used algorithms to illustrate the reliability and success of the technique.

Reducing system noise in copy number data using principal components of self-self hybridizations

Genomic copy number variation underlies genetic disorders such as autism, schizophrenia, and congenital heart disease. Copy number variations are commonly detected by array based comparative genomic hybridization of sample to reference DNAs, but probe and operational variables combine to create correlated system noise that degrades detection of genetic events. To correct for this we have explored hybridizations in which no genetic signal is expected, namely "self-self" hybridizations (SSH) comparing DNAs from the same genome. We show that SSH trap a variety of correlated system noise present also in sample-reference (test) data. Through singular value decomposition of SSH, we are able to determine the principal components (PCs) of this noise. The PCs themselves offer deep insights into the sources of noise, and facilitate detection of artifacts. We present evidence that linear and piecewise linear correction of test data with the PCs does not introduce detectable spurious signal, yet improves signal-to-noise metrics, reduces false positives, and facilitates copy number determination.

NKX3.1 haploinsufficiency is prognostic for prostate cancer relapse following surgery or image-guided radiotherapy

BACKGROUND

Despite the use of prostate specific antigen (PSA), Gleason-score, and T-category as prognostic factors, up to 40% of patients with intermediate-risk prostate cancer will fail radical prostatectomy or precision image-guided radiotherapy (IGRT). Additional genetic prognosticators are needed to triage these patients toward intensified combination therapy with novel targeted therapeutics. We tested the role of the NKX3.1 gene as a determinant of treatment outcome given its reported roles in tumor initiating cell (TIC) renewal, the DNA damage response, and cooperation with c-MYC during prostate cancer progression.

METHODS

Using high-resolution array comparative genomic hybridization (aCGH), we profiled the copy number alterations in TIC genes using tumor DNA from frozen needle biopsies derived from 126 intermediate-risk patients who underwent IGRT. These data were correlated to biochemical relapse-free rate (bRFR) by the Kaplan-Meier method and Cox proportional hazards models.

RESULTS

A screen of the aCGH-IGRT data for TIC genes showed frequent copy number alterations for NKX3.1, PSCA, and c-MYC. NKX3.1 haploinsufficiency was associated with increased genomic instability independent of PSA, T-category, and Gleason-score. After adjusting for clinical factors in a multivariate model, NKX3.1 haploinsufficiency was associated with bRFR when tested alone (HR = 3.05, 95% CI: 1.46-6.39, P = 0.0030) or when combined with c-MYC gain (HR = 3.88, 95% CI: 1.78-8.49, P = 0.00067). A similar association was observed for patients following radical prostatectomy with a public aCGH database. NKX3.1 status was associated with positive biopsies post-IGRT and increased clonogen radioresistance in vitro.

CONCLUSIONS

Our results support the use of genomic predictors, such as NKX3.1 status, in needle biopsies for personalized approaches to prostate cancer management.

Cyclin E1 is amplified and overexpressed in osteosarcoma

Osteosarcoma is a genetically complex malignancy, predominantly afflicting the adolescent population and associated still with relatively poor long-term outcomes. Although there has been some improvement in the understanding of osteosarcoma biology, this has not yet translated particularly well into therapeutic advances. By using a whole-genome tiling path array for comparative genomic hybridization analysis, we sought to evaluate DNA copy number changes in 22 osteosarcoma tumor samples. Regions of most frequent gains or losses generated by Genomic Identification of Significant Targets in Cancer analysis were evaluated for genes of interest. Correlation of the copy number data with preexisting expression data for these genes yielded not only targets known to be important in osteosarcoma but also novel targets, notably cyclin E1. Fluorescence in situ hybridization and immunohistochemical analysis confirmed the findings. Overexpression of cyclin E1 has potential prognostic and therapeutic implications that are discussed herein.

A new normalizing algorithm for BAC CGH arrays with quality control metrics

The main focus in pin-tip (or print-tip) microarray analysis is determining which probes, genes, or oligonucleotides are differentially expressed. Specifically in array comparative genomic hybridization (aCGH) experiments, researchers search for chromosomal imbalances in the genome. To model this data, scientists apply statistical methods to the structure of the experiment and assume that the data consist of the signal plus random noise. In this paper we propose "SmoothArray", a new method to preprocess comparative genomic hybridization (CGH) bacterial artificial chromosome (BAC) arrays and we show the effects on a cancer dataset. As part of our R software package "aCGHplus," this freely available algorithm removes the variation due to the intensity effects, pin/print-tip, the spatial location on the microarray chip, and the relative location from the well plate. removal of this variation improves the downstream analysis and subsequent inferences made on the data. Further, we present measures to evaluate the quality of the dataset according to the arrayer pins, 384-well plates, plate rows, and plate columns. We compare our method against competing methods using several metrics to measure the biological signal. With this novel normalization algorithm and quality control measures, the user can improve their inferences on datasets and pinpoint problems that may arise in their BAC aCGH technology.

Integrative molecular characterization of head and neck cancer cell model genomes

BACKGROUND

Cell lines are invaluable model systems for the investigation of cancer. Knowledge of the molecular alterations that exist within cell models is required to define the mechanisms governing cellular phenotypes.

METHODS

Five tongue squamous cell carcinomas cell lines and 1 submaxillary salivary gland epidermoid carcinoma cell line were analyzed for copy number and mRNA expression by tiling-path DNA microarrays and Agilent Whole Human Genome Oligoarrays, respectively.

RESULTS

Integrative analysis of genetic and expression alterations revealed the molecular landscape of each cell line. Molecular results for individual cell lines and across all samples have been summarized and made available for easy reference.

CONCLUSION

Our integrative genomic analyses have defined the DNA and RNA alterations for each individual line. These data will be useful to anyone modeling oral cancer behavior, providing a molecular context that will be useful for deciphering cell phenotypes.

VEGA: variational segmentation for copy number detection

MOTIVATION

Genomic copy number (CN) information is useful to study genetic traits of many diseases. Using array comparative genomic hybridization (aCGH), researchers are able to measure the copy number of thousands of DNA loci at the same time. Therefore, a current challenge in bioinformatics is the development of efficient algorithms to detect the map of aberrant chromosomal regions.

METHODS

We describe an approach for the segmentation of copy number aCGH data. Variational estimator for genomic aberrations (VEGA) adopt a variational model used in image segmentation. The optimal segmentation is modeled as the minimum of an energy functional encompassing both the quality of interpolation of the data and the complexity of the solution measured by the length of the boundaries between segmented regions. This solution is obtained by a region growing process where the stop condition is completely data driven.

RESULTS

VEGA is compared with three algorithms that represent the state of the art in CN segmentation. Performance assessment is made both on synthetic and real data. Synthetic data simulate different noise conditions. Results on these data show the robustness with respect to noise of variational models and the accuracy of VEGA in terms of recall and precision. Eight mantle cell lymphoma cell lines and two samples of glioblastoma multiforme are used to evaluate the behavior of VEGA on real biological data. Comparison between results and current biological knowledge shows the ability of the proposed method in detecting known chromosomal aberrations.

AVAILABILITY

VEGA has been implemented in R and is available at the address http://www.dsba.unisannio.it/Members/ceccarelli/vega in the section Download.

Arsenic-related DNA copy-number alterations in lung squamous cell carcinomas

Background:

Lung squamous cell carcinomas (SqCCs) occur at higher rates following arsenic exposure. Somatic DNA copy-number alterations (CNAs) are understood to be critical drivers in several tumour types. We have assembled a rare panel of lung tumours from a population with chronic arsenic exposure, including SqCC tumours from patients with no smoking history.

Methods:

Fifty-two lung SqCCs were analysed by whole-genome tiling-set array comparative genomic hybridisation. Twenty-two were derived from arsenic-exposed patients from Northern Chile (10 never smokers and 12 smokers). Thirty additional cases were obtained for comparison from North American smokers without arsenic exposure. Twenty-two blood samples from healthy individuals from Northern Chile were examined to identify germline DNA copy-number variations (CNVs) that could be excluded from analysis.

Results:

We identified multiple CNAs associated with arsenic exposure. These alterations were not attributable to either smoking status or CNVs. DNA losses at chromosomes 1q21.1, 7p22.3, 9q12, and 19q13.31 represented the most recurrent events. An arsenic-associated gain at 19q13.33 contains genes previously identified as oncogene candidates.

Conclusions:

Our results provide a comprehensive approach to molecular characteristics of the arsenic-exposed lung cancer genome and the non-smoking lung SqCC genome. The distinct and recurrent arsenic-related alterations suggest that this group of tumours may be considered as a separate disease subclass.

Identification of metastasis-associated breast cancer genes using a high-resolution whole genome profiling approach

PURPOSE

We employed a whole genome tumor profiling approach in an attempt to identify DNA copy number alterations (CNAs) and new candidate genes that are correlated with the metastatic potential of a primary breast carcinoma and with progression at the metastatic site.

METHODS

Fifty-four small (≤ 2 cm), high grade, ER-positive, formalin-fixed invasive ductal carcinomas were suitable for whole genome profiling analysis. Twenty-four of them did not form metastases within 5-10 years (unmatched primaries, UP). Thirty tumors had at least one synchronous axillary lymph node metastasis (matched primaries, MP; matched lymph node metastases, ML). Genomic DNA was hybridized to high density (19k) BAC arrays. Statistical analysis revealed differential distributions of CNAs between UP and MP and between MP and ML, respectively. We selected 27 candidate genes for validation experiments using quantitative (Q-)PCR of genomic DNA. For tetraspanin TSPAN1, we studied mRNA expression levels in a separate cohort of primary breast carcinomas and in breast cell lines.

RESULTS

Matched primary (MP) tumors had a threefold higher rate of DNA copy number losses compared to UP tumors. In the UP-MP comparison, 186 BACs were differentially amplified or deleted. Most of them were localized to chromosomes 7p, 16q and 18q. In the MP-ML comparison, 131 BACs showed differential CNAs. Most of them were localized to chromosomes 1q and 20. By Q-PCR, seven candidate genes could be confirmed to show differential distributions of CNAs. TSPAN1 was amplified in UP and deleted in MP tumors. The gene was markedly downregulated in ER-negative and high-grade breast cancers.

CONCLUSIONS

Metastasizing tumors had a higher rate of deletions, suggesting possible inactivation of metastasis suppressor genes. We provide preliminary evidence that TSPAN1 may be another important breast cancer suppressor gene belonging to the tetraspanin superfamily.

Integrative genomic analyses identify BRF2 as a novel lineage-specific oncogene in lung squamous cell carcinoma

BACKGROUND

Traditionally, non-small cell lung cancer is treated as a single disease entity in terms of systemic therapy. Emerging evidence suggests the major subtypes--adenocarcinoma (AC) and squamous cell carcinoma (SqCC)--respond differently to therapy. Identification of the molecular differences between these tumor types will have a significant impact in designing novel therapies that can improve the treatment outcome.

METHODS AND FINDINGS

We used an integrative genomics approach, combing high-resolution comparative genomic hybridization and gene expression microarray profiles, to compare AC and SqCC tumors in order to uncover alterations at the DNA level, with corresponding gene transcription changes, which are selected for during development of lung cancer subtypes. Through the analysis of multiple independent cohorts of clinical tumor samples (>330), normal lung tissues and bronchial epithelial cells obtained by bronchial brushing in smokers without lung cancer, we identified the overexpression of BRF2, a gene on Chromosome 8p12, which is specific for development of SqCC of lung. Genetic activation of BRF2, which encodes a RNA polymerase III (Pol III) transcription initiation factor, was found to be associated with increased expression of small nuclear RNAs (snRNAs) that are involved in processes essential for cell growth, such as RNA splicing. Ectopic expression of BRF2 in human bronchial epithelial cells induced a transformed phenotype and demonstrates downstream oncogenic effects, whereas RNA interference (RNAi)-mediated knockdown suppressed growth and colony formation of SqCC cells overexpressing BRF2, but not AC cells. Frequent activation of BRF2 in >35% preinvasive bronchial carcinoma in situ, as well as in dysplastic lesions, provides evidence that BRF2 expression is an early event in cancer development of this cell lineage.

CONCLUSIONS

This is the first study, to our knowledge, to show that the focal amplification of a gene in Chromosome 8p12, plays a key role in squamous cell lineage specificity of the disease. Our data suggest that genetic activation of BRF2 represents a unique mechanism of SqCC lung tumorigenesis through the increase of Pol III-mediated transcription. It can serve as a marker for lung SqCC and may provide a novel target for therapy. Please see later in the article for the Editors' Summary.

An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

Background

Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer.

Results

Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD) analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations.

Conclusions

Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.

A critical assessment of cross-species detection of gene duplicates using comparative genomic hybridization

Background

Comparison of genomic DNA among closely related strains or species is a powerful approach for identifying variation in evolutionary processes. One potent source of genomic variation is gene duplication, which is prevalent among individuals and species. Array comparative genomic hybridization (aCGH) has been successfully utilized to detect this variation among lineages. Here, beyond the demonstration that gene duplicates among species can be quantified with aCGH, we consider the effect of sequence divergence on the ability to detect gene duplicates.

Results

Using the X chromosome genomic content difference between male D. melanogaster and female D. yakuba and D. simulans, we describe a decrease in the ability to accurately measure genomic content (copy number) for orthologs that are only 90% identical. We demonstrate that genome characteristics (e.g. chromatin environment and non-orthologous sequence similarity) can also affect the ability to accurately measure genomic content. We describe a normalization strategy and statistical criteria to be used for the identification of gene duplicates among any species group for which an array platform is available from a closely related species.

Conclusions

Array CGH can be used to effectively identify gene duplication and genome content; however, certain biases are present due to sequence divergence and other genome characteristics resulting from the divergence between lineages. Highly conserved gene duplicates will be more readily recovered by aCGH. Duplicates that have been retained for a selective advantage due to directional selection acting on many loci in one or both gene copies are likely to be under-represented. The results of this study should inform the interpretation of both previously published and future work that employs this powerful technique.

Transcriptome profiles of carcinoma-in-situ and invasive non-small cell lung cancer as revealed by SAGE

Background

Non-small cell lung cancer (NSCLC) presents as a progressive disease spanning precancerous, preinvasive, locally invasive, and metastatic lesions. Identification of biological pathways reflective of these progressive stages, and aberrantly expressed genes associated with these pathways, would conceivably enhance therapeutic approaches to this devastating disease.

Methodology/Principal Findings

Through the construction and analysis of SAGE libraries, we have determined transcriptome profiles for preinvasive carcinoma-in-situ (CIS) and invasive squamous cell carcinoma (SCC) of the lung, and compared these with expression profiles generated from both bronchial epithelium, and precancerous metaplastic and dysplastic lesions using Ingenuity Pathway Analysis. Expression of genes associated with epidermal development, and loss of expression of genes associated with mucociliary biology, are predominant features of CIS, largely shared with precancerous lesions. Additionally, expression of genes associated with xenobiotic metabolism/detoxification is a notable feature of CIS, and is largely maintained in invasive cancer. Genes related to tissue fibrosis and acute phase immune response are characteristic of the invasive SCC phenotype. Moreover, the data presented here suggests that tissue remodeling/fibrosis is initiated at the early stages of CIS. Additionally, this study indicates that alteration in copy-number status represents a plausible mechanism for differential gene expression in CIS and invasive SCC.

Conclusions/Significance

This study is the first report of large-scale expression profiling of CIS of the lung. Unbiased expression profiling of these preinvasive and invasive lesions provides a platform for further investigations into the molecular genetic events relevant to early stages of squamous NSCLC development. Additionally, up-regulated genes detected at extreme differences between CIS and invasive cancer may have potential to serve as biomarkers for early detection.

Methylation analysis by DNA immunoprecipitation

DNA methylation regulates gene expression primarily through modification of chromatin structure. Global methylation studies have revealed biologically relevant patterns of DNA methylation in the human genome affecting sequences such as gene promoters, gene bodies, and repetitive elements. Disruption of normal methylation patterns and subsequent gene expression changes have been observed in several diseases especially in human cancers. Immunoprecipitation (IP)-based methods to evaluate methylation status of DNA have been instrumental in such genome-wide methylation studies. This review describes techniques commonly used to identify and quantify methylated DNA with emphasis on IP based platforms. In an effort to consolidate the wealth of information and highlight critical aspects of methylated DNA analysis, sample considerations, experimental and bioinformatic approaches for analyzing genome-wide methylation profiles, and the benefit of integrating DNA methylation data with complementary dimensions of genomic data are discussed.

A dynamic oral cancer field: unraveling the underlying biology and its clinical implication

Oral cancer is a complex disease that is characterized by histologic and genetic heterogeneity. The evolution and progression of this disease is thought to result from the accumulation of alterations in molecular pathways. Although the oral cavity is accessible for routine screening of suspicious lesions, gene alterations are known to accrue in histologically normal tissues. Therefore, some cancer forerunners may remain undetected clinically or histologically. Recently emerging optical and molecular technologies have provided a powerful means for redefining the extent of the field of alteration. Often this means expanding upon regions detectable with standard white light approaches. In this report, we used a newly developed optical technique, direct fluorescence visualization, to define a contiguous field that extended beyond the margins of a clinically visible oral squamous cell carcinoma. Multiple biopsies were taken within this contiguous optically altered field. Genome alterations detected for each specimen were compared to define whether each lesion arose independently or as a consequence of a shared progenitor cell. Our results indicate that the field effect of oral cancer is extremely dynamic, with different genetic alterations present in different biopsies within a field. This case study also demonstrated that 2 genetically unrelated squamous cell carcinoma could be developed within 10 mm at the right lateral tongue of this patient. These findings provide evidence for the importance to implement optical technologies in defining surgical margins and support the use of whole genome technologies in the diagnosis of clonal versus independent lesions of the oral cavity, which may have implications on treatment strategies.

Accurate confidence aware clustering of array CGH tumor profiles

MOTIVATION

Chromosomal aberrations tend to be characteristic for given (sub)types of cancer. Such aberrations can be detected with array comparative genomic hybridization (aCGH). Clustering aCGH tumor profiles aids in identifying chromosomal regions of interest and provides useful diagnostic information on the cancer type. An important issue here is to what extent individual aCGH tumor profiles can be reliably assigned to clusters associated with a given cancer type.

RESULTS

We introduce a novel evolutionary fuzzy clustering (EFC) algorithm, which is able to deal with overlapping clusterings. Our method assesses these overlaps by using cluster membership degrees, which we use here as a confidence measure for individual samples to be assigned to a given tumor type. We first demonstrate the usefulness of our method using a synthetic aCGH dataset and subsequently show that EFC outperforms existing methods on four real datasets of aCGH tumor profiles involving four different cancer types. We also show that in general best performance is obtained using 1- Pearson correlation coefficient as a distance measure and that extra preprocessing steps, such as segmentation and calling, lead to decreased clustering performance.

AVAILABILITY

The source code of the program is available from http://ibi.vu.nl/programs/efcwww

Multiple pathways in the FGF signaling network are frequently deregulated by gene amplification in oral dysplasias

Genetic alteration in oral premalignant lesions (OPLs), the precursors of oral squamous cell carcinomas (OSCCs), may represent key changes in disease initiation and development. We ask if DNA amplification occurs at this early stage of cancer development and which oncogenic pathways are disrupted in OPLs. Here, we evaluated 50 high-grade dysplasias and low-grade dysplasias that later progressed to cancer for gene dosage aberrations using tiling-path DNA microarrays. Early occurrences of DNA amplification and homozygous deletion were frequently detected, with 40% (20/50) of these early lesions exhibiting such features. Expression for 88 genes in 7 recurrent amplicons were evaluated in 5 independent head and neck cancer datasets, with 40 candidates found to be overexpressed relative to normal tissues. These genes were significantly enriched in the canonical ERK/MAPK, FGF, p53, PTEN and PI3K/AKT signaling pathways (p = 8.95 x 10(-3) to 3.18 x 10(-2)). These identified pathways share interactions in one signaling network, and amplification-mediated deregulation of this network was found in 30.0% of these preinvasive lesions. No such alterations were found in 14 low-grade dysplasias that did not progress, whereas 43.5% (10/23) of OSCCs were found to have altered genes within the pathways with DNA amplification. Multitarget FISH showed that amplification of EGFR and CCND1 can coexist in single cells of an oral dysplasia, suggesting the dependence on multiple oncogenes for OPL progression. Taken together, these findings identify a critical biological network that is frequently disrupted in high-risk OPLs, with different specific genes disrupted in different individuals.

CGHnormaliter: an iterative strategy to enhance normalization of array CGH data with imbalanced aberrations

BACKGROUND

Array comparative genomic hybridization (aCGH) is a popular technique for detection of genomic copy number imbalances. These play a critical role in the onset of various types of cancer. In the analysis of aCGH data, normalization is deemed a critical pre-processing step. In general, aCGH normalization approaches are similar to those used for gene expression data, albeit both data-types differ inherently. A particular problem with aCGH data is that imbalanced copy numbers lead to improper normalization using conventional methods.

RESULTS

In this study we present a novel method, called CGHnormaliter, which addresses this issue by means of an iterative normalization procedure. First, provisory balanced copy numbers are identified and subsequently used for normalization. These two steps are then iterated to refine the normalization. We tested our method on three well-studied tumor-related aCGH datasets with experimentally confirmed copy numbers. Results were compared to a conventional normalization approach and two more recent state-of-the-art aCGH normalization strategies. Our findings show that, compared to these three methods, CGHnormaliter yields a higher specificity and precision in terms of identifying the 'true' copy numbers.

CONCLUSION

We demonstrate that the normalization of aCGH data can be significantly enhanced using an iterative procedure that effectively eliminates the effect of imbalanced copy numbers. This also leads to a more reliable assessment of aberrations. An R-package containing the implementation of CGHnormaliter is available at http://www.ibi.vu.nl/programs/cghnormaliterwww.

Genomic imbalances in precancerous tissues signal oral cancer risk

Oral cancer develops through a series of histopathological stages: through mild (low grade), moderate, and severe (high grade) dysplasia to carcinoma in situ and then invasive disease. Early detection of those oral premalignant lesions (OPLs) that will develop into invasive tumors is necessary to improve the poor prognosis of oral cancer. Because no tools exist for delineating progression risk in low grade oral lesions, we cannot determine which of these cases require aggressive intervention. We undertook whole genome analysis by tiling-path array comparative genomic hybridization for a rare panel of early and late stage OPLs (n = 62), all of which had extensive longitudinal follow up (>10 years). Genome profiles for oral squamous cell carcinomas (n = 24) were generated for comparison. Parallel analysis of genome alterations and clinical parameters was performed to identify features associated with disease progression. Genome alterations in low grade dysplasias progressing to invasive disease more closely resembled those observed for later stage disease than they did those observed for non-progressing low grade dysplasias. This was despite the histopathological similarity between progressing and non-progressing cases. Strikingly, unbiased computational analysis of genomic alteration data correctly classified nearly all progressing low grade dysplasia cases. Our data demonstrate that high resolution genomic analysis can be used to evaluate progression risk in low grade OPLs, a marked improvement over present histopathological approaches which cannot delineate progression risk. Taken together, our data suggest that whole genome technologies could be used in management strategies for patients presenting with precancerous oral lesions.

Minimum altered regions in early prostate cancer progression identified by high resolution whole genome tiling path BAC array comparative hybridization

BACKGROUND

Carcinoma of the prostate (CaP) is a serious health problem. The altered molecular mechanisms that lead to this disease are poorly understood.

METHODS

Specimens from radical prostatectomies and blood were collected from 18 CaP surgery patients. For CGH studies, 20 CaP-related samples (16 Gleason grade 3, 3 higher grades, 1 BPH sample) and 18 samples of patient-matched normal epithelial cells were obtained by laser-assisted microdissection from frozen sections of the 18 prostatectomy specimens. High resolution SMRT aCGH was used to compare genomic profiles of prostatic samples to patient-matched blood and pooled female DNA. TMPRSS2-ERG fusion transcript analysis was performed by RT-PCR in relation to alterations detected at the TMPRSS2 locus.

RESULTS

Our comprehensive aCGH approach allowed us to define 35 regions of recurrent alterations while excluding germline copy number polymorphisms. Novel regions identified include 2q14.2, containing INHBB, and 17q21.31. The TMPRSS2 locus at 21q22.3 may be a hotspot for rearrangements with 75% of the alterations resulting in the expression of a TMPRSS2-ERG fusion transcript. Differences in fusion expression in different areas in an individual tumor focus and expression in adjacent normal epithelium supported intrafocal heterogeneity and field cancerization, respectively. Both features challenge our efforts to develop more objective markers for diagnosis and prediction of the severity of CaP.

CONCLUSION

The high-density array enabled precise mapping of genomic alterations and consequently definition of minimum altered regions smaller than previously reported thus facilitating identification of those genes that contribute to the cancer transformation process.

Defining genomic alteration boundaries for a combined small cell and non-small cell lung carcinoma

In the rare case of a male patient presenting with a combined small cell lung carcinoma (SCLC), large cell neuroendocrine carcinoma and adenocarcinoma, we used whole genome analysis by tiling-path array comparative genomic hybridization to evaluate the clonal relationship between nodules. In two areas of SCLC distinguishable by divergent neuroendocrine marker expression (CD56 and chromogranin-A), the presence of identical genomic breakpoints and rearrangements indicated a common origin, with the presence of additional distinct genomic alterations in these two components indicating diverging clonal evolution. The absence of shared genome alteration features for the adenocarcinoma and large cell neuroendocrine carcinoma components suggested that these tumors evolved independently from the SCLC. Taken together, the array comparative genomic hybridization data demonstrate the development and evolution of three independent primary lung cancers in close proximity to each other to form a combined carcinoma. Application of whole genome analysis shows the potential utility of high resolution molecular tools in resolving the origin and delineating the clonal relationships of a tumor that contains heterogeneous histologic components leading to an ambiguous histogenesis.

Integrative genomic and gene expression analysis of chromosome 7 identified novel oncogene loci in non-small cell lung cancer

Lung cancer accounts for over a quarter of cancer deaths, with non-small cell lung cancer (NSCLC) accounting for approximately 80% of cases. Several genome studies have been undertaken in both cell models of NSCLC and clinical samples to identify alterations underlying disease behaviour, and many have identified recurring aberrations of chromosome 7. The presence of recurring chromosome 7 alterations that do not span the well-studied oncogenes EGFR (at 7p11.2) and MET (at 7q31.2) has raised the hypothesis of additional genes on this chromosome that contribute to tumourigenesis. In this study, we demonstrated that multiple loci on chromosome 7 are indeed amplified in NSCLC, and through integrative analysis of gene dosage alterations and parallel gene expression changes, we identified new lung cancer oncogene candidates, including FTSJ2, NUDT1, TAF6, and POLR2J. Activation of these key genes was confirmed in panels of clinical lung tumour tissue as compared with matched normal lung tissue. The detection of gene activation in multiple cohorts of samples strongly supports the presence of key genes involved in lung cancer that are distinct from the EGFR and MET loci on chromosome 7.

Cancer gene discovery in mouse and man

The elucidation of the human and mouse genome sequence and developments in high-throughput genome analysis, and in computational tools, have made it possible to profile entire cancer genomes. In parallel with these advances mouse models of cancer have evolved into a powerful tool for cancer gene discovery. Here we discuss the approaches that may be used for cancer gene identification in both human and mouse and discuss how a cross-species 'oncogenomics' approach to cancer gene discovery represents a powerful strategy for finding genes that drive tumourigenesis.

Multiple aberrations of chromosome 3p detected in oral premalignant lesions

The study of oral premalignant lesions (OPL) is crucial to the identification of initiating genetic events in oral cancer. However, these lesions are minute in size, making it a challenge to recover sufficient DNA from microdissected cells for comprehensive genomic analysis. As a step toward identifying genetic aberrations associated with oral cancer progression, we used tiling-path array comparative genomic hybridization to compare alterations on chromosome 3p for 71 OPLs against 23 oral squamous cell carcinomas. 3p was chosen because although it is frequently altered in oral cancers and has been associated with progression risk, its alteration status has only been evaluated at a small number of loci in OPLs. We identified six recurrent losses in this region that were shared between high-grade dysplasias and oral squamous cell carcinomas, including a 2.89-Mbp deletion spanning the FHIT gene (previously implicated in oral cancer progression). When the alteration status for these six regions was examined in 24 low-grade dysplasias with known progression outcome, we observed that they occurred at a significantly higher frequency in low-grade dysplasias that later progressed to later-stage disease (P < 0.003). Moreover, parallel analysis of all profiled tissues showed that the extent of overall genomic alteration at 3p increased with histologic stage. This first high-resolution analysis of chromosome arm 3p in OPLs represents a significant step toward predicting progression risk in early preinvasive disease and provides a keen example of how genomic instability escalates with progression to invasive cancer.

PanCGH: a genotype-calling algorithm for pangenome CGH data

MOTIVATION

Pangenome arrays contain DNA oligomers targeting several sequenced reference genomes from the same species. In microbiology, these can be employed to investigate the often high genetic variability within a species by comparative genome hybridization (CGH). The biological interpretation of pangenome CGH data depends on the ability to compare strains at a functional level, particularly by comparing the presence or absence of orthologous genes. Due to the high genetic variability, available genotype-calling algorithms can not be applied to pangenome CGH data.

RESULTS

We have developed the algorithm PanCGH that incorporates orthology information about genes to predict the presence or absence of orthologous genes in a query organism using CGH arrays that target the genomes of sequenced representatives of a group of microorganisms. PanCGH was tested and applied in the analysis of genetic diversity among 39 Lactococcus lactis strains from three different subspecies (lactis.cremoris, hordniae) and isolated from two different niches (dairy and plant). Clustering of these strains using the presence/absence data of gene orthologs revealed a clear separation between different subspecies and reflected the niche of the strains.

Comparative genomic hybridization on BAC arrays

Alterations in genomic DNA are a key feature of many constitutional disorders and cancer. The discovery of the underlying regions of gene dosage has thus been essential in dissecting complex disease phenotypes and identifying targets for therapeutic intervention and diagnostic testing. The development of array comparative genomic hybridization (aCGH) using bacterial artificial chromosomes (BACs) as hybridization targets has facilitated the discovery and fine mapping of novel genomic alterations allowing rapid identification of target genes. In BAC aCGH, DNA samples are first labeled with fluorescent dyes through a random priming reaction with 100-400 ng of genomic DNA. This probe is then co-hybridized to an array consisting of BAC clones, either tiling the genome (approximately 50 kbp resolution) or spaced at intervals (e.g., 1 Mbp resolution). The resulting arrays are then imaged and the signal at each locus is compared between a reference and test sample to determine the copy number status. The DNA samples to be analyzed may be derived from either fresh, frozen, or formalin-fixed paraffin-embedded material, and sample requirements are currently significantly lower than those for oligonucleotide platforms due to the high probe-binding capacity of BAC clone targets (approximately 150 kbp) compared to oligonucleotides (25-80 bp). In this chapter, we describe in detail the technical procedure required to perform copy number analysis of genomes with BAC aCGH.

Methylation analysis by DNA immunoprecipitation (MeDIP)

Alteration in epigenetic regulation of gene expression is a common event in human cancer and developmental disease. CpG island hypermethylation and consequent gene silencing is observed for many genes involved in a diverse range of functions and pathways that become deregulated in the disease state. Comparative profiling of the methylome is therefore useful in disease gene discovery. The ability to identify epigenetic alterations on a global scale is imperative to understanding the patterns of gene silencing that parallel disease progression. Methylated DNA immunoprecipitation (MeDIP) is a technique that isolates methylated DNA fragments by immunoprecipitating with 5'-methylcytosine-specific antibodies. The enriched methylated DNA can then be analyzed in a locus-specific manner using PCR assay or in a genome-wide fashion by comparative genomic hybridization against a sample without MeDIP enrichment. This article describes the detailed protocol for MeDIP and hybridization of MeDIP DNA to a whole-genome tiling path BAC array.

A comparative analysis of two tissue procurement approaches for the genomic profiling of clinical colorectal cancer samples

BACKGROUND

The basis for personalized medicine is the creation of a repository of knowledge about the genetic alterations involved in disease processes. Integral to achieving this goal is the querying of well-preserved, high-quality human tissue samples. Making these findings relevant involves the interrogation of large numbers of samples. The pace with which changes have occurred versus the potential pace with which changes can occur may be indicative of problems associated with traditional approaches on collecting biospecimens. Therefore, transforming personalized medicine from concept to reality may require an alternative approach in the field of tissue specimen procurement.

MATERIALS AND METHODS

"Exfoliation and Enrichment" (EE), a recently described rapid and cost-effective approach for procuring cells, was utilized and assessed relative to a more traditional but temporally and economically comparable approach. Material from the same tumor sample, one collected by EE but the other frozen, were procured, the DNA extracted, and the samples analyzed at the global and gene-specific level by array comparative genomic hybridization and quantitative polymerase chain reaction, respectively.

RESULTS

Both approaches resulted in the rapid procurement and retrieval of well-preserved cells and nucleic acids. The presence of "contaminating" normal cells in the more traditional approach masked the significance of genetic gains and losses, findings that were more readily apparent from the material derived by the EE method.

CONCLUSION

The EE approach represents a cost-effective alternative to traditional cell-procurement methods that results in the generation of superior genomic data.

SIGMA2: a system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes

Background

High throughput microarray technologies have afforded the investigation of genomes, epigenomes, and transcriptomes at unprecedented resolution. However, software packages to handle, analyze, and visualize data from these multiple 'omics disciplines have not been adequately developed.

Results

Here, we present SIGMA², a system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes. Multi-dimensional datasets can be simultaneously visualized and analyzed with respect to each dimension, allowing combinatorial integration of the different assays belonging to the different 'omics.

Conclusion

The identification of genes altered at multiple levels such as copy number, loss of heterozygosity (LOH), DNA methylation and the detection of consequential changes in gene expression can be concertedly performed, establishing SIGMA² as a novel tool to facilitate the high throughput systems biology analysis of cancer.

Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios

Background

Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples.

Results

We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illumina's proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the normalization strategy using 535 individual hybridizations from 10 data sets from the analysis of cancer genomes and normal blood samples generated on Illumina Infinium II 300 k version 1 and 2, 370 k and 550 k BeadChips. We show that the proposed normalization strategy successfully removes asymmetry in estimates of both allelic proportions and copy numbers. Additionally, the normalization strategy reduces the technical variation for copy number estimates while retaining the response to copy number alterations.

Conclusion

The proposed normalization strategy represents a valuable tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies.

Genome-wide profiling of follicular lymphoma by array comparative genomic hybridization reveals prognostically significant DNA copy number imbalances

The secondary genetic events associated with follicular lymphoma (FL) progression are not well defined. We applied genome-wide BAC array comparative genomic hybridization to 106 diagnostic biopsies of FL to characterize regional genomic imbalances. Using an analytical approach that defined regions of copy number change as intersections between visual annotations and a Hidden Markov model-based algorithm, we identified 71 regional alterations that were recurrent in at least 10% of cases. These ranged in size from approximately 200 kb to 44 Mb, affecting chromosomes 1, 5, 6, 7, 8, 10, 12, 17, 18, 19, and 22. We also demonstrated by cluster analysis that 46.2% of the 106 cases could be sub-grouped based on the presence of +1q, +6p/6q-, +7, or +18. Survival analysis showed that 21 of the 71 regions correlated significantly with inferior overall survival (OS). Of these 21 regions, 16 were independent predictors of OS using a multivariate Cox model that included the international prognostic index (IPI) score. Two of these 16 regions (1p36.22-p36.33 and 6q21-q24.3) were also predictors of transformation risk and independent of IPI. These prognostic features may be useful to identify high-risk patients as candidates for risk-adapted therapies.

A probe-density-based analysis method for array CGH data: simulation, normalization and centralization

MOTIVATION

Genomic instability is one of the fundamental factors in tumorigenesis and tumor progression. Many studies have shown that copy-number abnormalities at the DNA level are important in the pathogenesis of cancer. Array comparative genomic hybridization (aCGH), developed based on expression microarray technology, can reveal the chromosomal aberrations in segmental copies at a high resolution. However, due to the nature of aCGH, many standard expression data processing tools, such as data normalization, often fail to yield satisfactory results.

RESULTS

We demonstrated a novel aCGH normalization algorithm, which provides an accurate aCGH data normalization by utilizing the dependency of neighboring probe measurements in aCGH experiments. To facilitate the study, we have developed a hidden Markov model (HMM) to simulate a series of aCGH experiments with random DNA copy number alterations that are used to validate the performance of our normalization. In addition, we applied the proposed normalization algorithm to an aCGH study of lung cancer cell lines. By using the proposed algorithm, data quality and the reliability of experimental results are significantly improved, and the distinct patterns of DNA copy number alternations are observed among those lung cancer cell lines.

SUPPLEMENTARY INFORMATION

Source codes and.gures may be found at http://ntumaps.cgm.ntu.edu.tw/aCGH_supplementary.