Cross-platform array comparative genomic hybridization meta-analysis separates hematopoietic and mesenchymal from epithelial tumors

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.

Genome instability model of metastatic neuroblastoma tumorigenesis by a dictionary learning algorithm

Background

Metastatic neuroblastoma (NB) occurs in pediatric patients as stage 4S or stage 4 and it is characterized by heterogeneous clinical behavior associated with diverse genotypes. Tumors of stage 4 contain several structural copy number aberrations (CNAs) rarely found in stage 4S. To date, the NB tumorigenesis is not still elucidated, although it is evident that genomic instability plays a critical role in the genesis of the tumor. Here we propose a mathematical approach to decipher genomic data and we provide a new model of NB metastatic tumorigenesis.

Method

We elucidate NB tumorigenesis using Enhanced Fused Lasso Latent Feature Model (E-FLLat) modeling the array comparative chromosome hybridization (aCGH) data of 190 metastatic NBs (63 stage 4S and 127 stage 4). This model for aCGH segmentation, based on the minimization of functional dictionary learning (DL), combines several penalties tailored to the specificities of aCGH data. In DL, the original signal is approximated by a linear weighted combination of atoms: the elements of the learned dictionary.

Results

The hierarchical structures for stage 4S shows at the first level of the oncogenetic tree several whole chromosome gains except to the unbalanced gains of 17q, 2p and 2q. Conversely, the high CNA complexity found in stage 4 tumors, requires two different trees. Both stage 4 oncogenetic trees are marked diverged, up to five sublevels and the 17q gain is the most common event at the first level (2/3 nodes). Moreover the 11q deletion, one of the major unfavorable marker of disease progression, occurs before 3p loss indicating that critical chromosome aberrations appear at early stages of tumorigenesis. Finally, we also observed a significant (p = 0.025) association between patient age and chromosome loss in stage 4 cases.

Conclusion

These results led us to propose a genome instability progressive model in which NB cells initiate with a DNA synthesis uncoupled from cell division, that leads to stage 4S tumors, primarily characterized by numerical aberrations, or stage 4 tumors with high levels of genome instability resulting in complex chromosome rearrangements associated with high tumor aggressiveness and rapid disease progression.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0132-y) contains supplementary material, which is available to authorized users.

Immortalization of epithelial cells in oral carcinogenesis as revealed by genome-wide array comparative genomic hybridization: A meta-analysis

BACKGROUND

This purpose of this meta-analysis study was to identify the most frequent and potentially significant copy number alteration (CNA) in oral carcinogenesis.

METHODS

Seven oral squamous cell carcinoma (OSCC)-related publications, corresponding to 312 samples, were identified for this meta-analysis. The data were analyzed in a 4-step process that included the genome assembly coordination of multiple platforms, assignment of chromosomal position anchors, calling gains and losses, and functional annotation analysis.

RESULTS

Gains were more frequent than losses in the entire dataset. High-frequency gains were identified in chromosomes 5p, 14q, 11q, 7p, 17q, 20q, 8q, and 3q, whereas high-frequency losses were identified in chromosomes 3p, 8p, 6p, 18q, and 4q. Ingenuity pathway analysis showed that the top biological function was associated with immortalization of the epithelial cells (p = 1.93E-04).

CONCLUSION

This study has identified multiple recurrent CNAs that are involved in various biological annotations associated with oral carcinogenesis. © 2015 Wiley Periodicals, Inc. Head Neck 38: E783-E797, 2016.

Platform comparisons for identification of breast cancers with a BRCA-like copy number profile

Previously, we employed bacterial artificial chromosome (BAC) array comparative genomic hybridization (aCGH) profiles from BRCA1 and -2 mutation carriers and sporadic tumours to construct classifiers that identify tumour samples most likely to harbour BRCA1 and -2 mutations, designated 'BRCA1 and -2-like' tumours, respectively. The classifiers are used in clinical genetics to evaluate unclassified variants, and patients for which no good quality germline DNA is available. Furthermore, we have shown that breast cancer patients with BRCA-like tumour aCGH profiles benefit substantially from platinum-based chemotherapy, potentially due to their inability to repair DNA double strand breaks (DSB), providing a further important clinical application for the classifiers. The BAC array technology has been replaced with oligonucleotide arrays. To continue clinical use of existing classifiers, we mapped oligonucleotide aCGH data to the BAC domain, such that the oligonucleotide profiles can be employed as in the BAC classifier. We demonstrate that segmented profiles derived from oligonucleotide aCGH show high correlation with BAC aCGH profiles. Furthermore, we trained a support vector machine score to objectify aCGH profile quality. Using the mapped oligonucleotide aCGH data, we show equivalence in classification of biologically relevant cases between BAC and oligonucleotide data. Furthermore, the predicted benefit of DSB inducing chemotherapy due to a homologous recombination defect is retained. We conclude that oligonucleotide aCGH data can be mapped to and used in the previously developed and validated BAC aCGH classifiers. Our findings suggest that it is possible to map copy number data from any other technology in a similar way.

Detection limits of DNA copy number alterations in heterogeneous cell populations

BACKGROUND

Array Comparative Genomic Hybridization (aCGH) is a widely used technique to assess chromosomal copy number alterations. Chromosomal content, however, is often not uniform throughout cell populations. Here we evaluated to what extent aCGH can detect DNA copy number alterations in heterogeneous cell populations. A systematic evaluation is currently lacking, despite its importance in diagnostics and research. The detection limits reported are a compound of analytical software and laboratory techniques and do not account for the number of probes in relation to sample homogeneity.

METHODS

Detection limits were explored with DNA isolated from a patient with intellectual disability (ID) and from tumor cell line BT474. Both were diluted with increasing amounts of normal DNA to simulate different levels of cellularity. Samples were hybridized on microarrays containing 180,880 oligonucleotides evenly distributed over the genome (spacing ~17 kb).

RESULTS

Single copy number alterations, represented by down to 249 probes (4 Mb) and present in 10 % of a cell population, could be detected. Alterations encompassing as few as 14 probes (~238 Kb) could also be detected, but for this a 35 % mosaic level was required.

CONCLUSIONS

DNA copy number alterations can be detected in cell populations containing 10 % abnormal cells. Detection of sub-megabase alterations requires a higher percentage of abnormal cells or microarrays with a higher probe density.

Oncogenomics methods and resources

Today, cancer is viewed as a genetic disease and many genetic mechanisms of oncogenesis are known. The progression from normal tissue to invasive cancer is thought to occur over a timescale of 5-20 years. This transformation is driven by both inherited genetic factors and somatic genetic alterations and mutations, and it results in uncontrolled cell growth and, in many cases, death. In this article, we review the main types of genomic and genetic alterations involved in cancer, namely copy-number changes, genomic rearrangements, somatic mutations, polymorphisms, and epigenomic alterations in cancer. We then discuss the transcriptomic consequences of these alterations in tumor cells. The use of "next-generation" sequencing methods in cancer research is described in the relevant sections. Finally, we discuss different approaches for candidate prioritization and integration and analysis of these complex data.

High-resolution copy number profiling by array CGH using DNA isolated from formalin-fixed, paraffin-embedded tissues

We describe protocols to acquire high-quality DNA from formalin-fixed, paraffin-embedded (FFPE) tissues for the use in array comparative genome hybridization (CGH). Formalin fixation combined with paraffin embedding is routine procedure for solid malignancies in the diagnostic practice of the pathologist. As a consequence, large archives of FFPE tissues are available in pathology institutes across the globe. This archival material is for many research questions an invaluable resource, with long-term clinical follow-up and survival data available. FFPE is, thus, highly attractive for large genomics studies, including experiments requiring samples for test/learning and validation. Most larger array CGH studies have, therefore, made use of FFPE material and show that CNAs have tumor- and tissue-specific traits (Chin et al. Cancer Cell 10: 529-541, 2006; Fridlyand et al. BMC Cancer 6: 96, 2006; Weiss et al. Oncogene 22: 1872-1879, 2003; Jong et al. Oncogene 26: 1499-1506, 2007). The protocols described are tailored to array CGH of FFPE solid malignancies: from sectioning FFPE blocks to specific cynosures for pathological revisions of sections, DNA isolation, quality testing, and amplification. The protocols are technical in character and elaborate up to the labeling of isolated DNA while further processes and interpretation and data analysis are beyond the scope.

A meta-analysis of array-CGH studies implicates antiviral immunity pathways in the development of hepatocellular carcinoma

Background

The development and progression of hepatocellular carcinoma (HCC) is significantly correlated to the accumulation of genomic alterations. Array-based comparative genomic hybridization (array CGH) has been applied to a wide range of tumors including HCCs for the genome-wide high resolution screening of DNA copy number changes. However, the relevant chromosomal variations that play a central role in the development of HCC still are not fully elucidated.

Methods

In present study, in order to further characterize the copy number alterations (CNAs) important to HCC development, we conducted a meta-analysis of four published independent array-CGH datasets including total 159 samples.

Results

Eighty five significant gains (frequency ≥25%) were mostly mapped to five broad chromosomal regions including 1q, 6p, 8q, 17q and 20p, as well as two narrow regions 5p15.33 and 9q34.2-34.3. Eighty eight significant losses (frequency ≥25%) were most frequently present in 4q, 6q, 8p, 9p, 13q, 14q, 16q, and 17p. Significant correlations existed between chromosomal aberrations either located on the same chromosome or the different chromosomes. HCCs with different etiologies largely exhibited surprisingly similar profiles of chromosomal aberrations with only a few exceptions. Furthermore, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the genes affected by these chromosomal aberrations were significantly enriched in 31 canonical pathways with the highest enrichment observed for antiviral immunity pathways.

Conclusions

Taken together, our findings provide novel and important clues for the implications of antiviral immunity-related gene pathways in the pathogenesis and progression of HCC.

Small bowel adenocarcinoma copy number profiles are more closely related to colorectal than to gastric cancers

BACKGROUND

Small bowel adenocarcinoma (SBA) is a rare cancer and consequently, the options for clinical trials are limited. As they are treated according to either a colorectal or a gastric cancer regimen and the molecular biology of a tumor is a pivotal determinant for therapy response, chromosomal copy number aberrations were compared with the colorectal and gastric adenocarcinomas.

MATERIALS AND METHODS

A total of 85 microsatellite stable (MSS) adenocarcinomas from the stomach, colorectum and small bowel were selected from existing array comparative genomic hybridization (aCGH) datasets. We compared the aCGH profiles of the three tumor sites by supervised analysis and hierarchical clustering.

RESULTS

Hierarchical clustering revealed substantial overlap of 27 SBA copy number profiles with matched colorectal adenocarcinomas but less overlap with profiles of gastric adenocarcinomas. DNA copy number aberrations located at chromosomes 1p36.3-p34.3, 4p15.3-q35.2, 9p24.3-p11.1, 13q13.2-q31.3 and 17p13.3-p13.2 were the strongest features discriminating SBAs and colorectal adenocarcinomas from gastric adenocarcinomas.

CONCLUSIONS

We show that MSS SBAs are more similar to colorectal than to gastric cancer, based on the 27 genome-wide DNA copy number profiles that are currently available. These molecular similarities provide added support for treatment of MSS small bowel cancers according to colorectal cancer regimens.

Wavelet-based identification of DNA focal genomic aberrations from single nucleotide polymorphism arrays

Background

Copy number aberrations (CNAs) are an important molecular signature in cancer initiation, development, and progression. However, these aberrations span a wide range of chromosomes, making it hard to distinguish cancer related genes from other genes that are not closely related to cancer but are located in broadly aberrant regions. With the current availability of high-resolution data sets such as single nucleotide polymorphism (SNP) microarrays, it has become an important issue to develop a computational method to detect driving genes related to cancer development located in the focal regions of CNAs.

Results

In this study, we introduce a novel method referred to as the wavelet-based identification of focal genomic aberrations (WIFA). The use of the wavelet analysis, because it is a multi-resolution approach, makes it possible to effectively identify focal genomic aberrations in broadly aberrant regions. The proposed method integrates multiple cancer samples so that it enables the detection of the consistent aberrations across multiple samples. We then apply this method to glioblastoma multiforme and lung cancer data sets from the SNP microarray platform. Through this process, we confirm the ability to detect previously known cancer related genes from both cancer types with high accuracy. Also, the application of this approach to a lung cancer data set identifies focal amplification regions that contain known oncogenes, though these regions are not reported using a recent CNAs detecting algorithm GISTIC: SMAD7 (chr18q21.1) and FGF10 (chr5p12).

Conclusions

Our results suggest that WIFA can be used to reveal cancer related genes in various cancer data sets.

Genome-wide comparison of paired fresh frozen and formalin-fixed paraffin-embedded gliomas by custom BAC and oligonucleotide array comparative genomic hybridization: facilitating analysis of archival gliomas

Array comparative genomic hybridization (aCGH) is a powerful tool for detecting DNA copy number alterations (CNA). Because diffuse malignant gliomas are often sampled by small biopsies, formalin-fixed paraffin-embedded (FFPE) blocks are often the only tissue available for genetic analysis; FFPE tissues are also needed to study the intratumoral heterogeneity that characterizes these neoplasms. In this paper, we present a combination of evaluations and technical advances that provide strong support for the ready use of oligonucleotide aCGH on FFPE diffuse gliomas. We first compared aCGH using bacterial artificial chromosome (BAC) arrays in 45 paired frozen and FFPE gliomas, and demonstrate a high concordance rate between FFPE and frozen DNA in an individual clone-level analysis of sensitivity and specificity, assuring that under certain array conditions, frozen and FFPE DNA can perform nearly identically. However, because oligonucleotide arrays offer advantages to BAC arrays in genomic coverage and practical availability, we next developed a method of labeling DNA from FFPE tissue that allows efficient hybridization to oligonucleotide arrays. To demonstrate utility in FFPE tissues, we applied this approach to biphasic anaplastic oligoastrocytomas and demonstrate CNA differences between DNA obtained from the two components. Therefore, BAC and oligonucleotide aCGH can be sensitive and specific tools for detecting CNAs in FFPE DNA, and novel labeling techniques enable the routine use of oligonucleotide arrays for FFPE DNA. In combination, these advances should facilitate genome-wide analysis of rare, small and/or histologically heterogeneous gliomas from FFPE tissues.

An algorithm for classifying tumors based on genomic aberrations and selecting representative tumor models

Background

Cancer is a heterogeneous disease caused by genomic aberrations and characterized by significant variability in clinical outcomes and response to therapies. Several subtypes of common cancers have been identified based on alterations of individual cancer genes, such as HER2, EGFR, and others. However, cancer is a complex disease driven by the interaction of multiple genes, so the copy number status of individual genes is not sufficient to define cancer subtypes and predict responses to treatments. A classification based on genome-wide copy number patterns would be better suited for this purpose.

Method

To develop a more comprehensive cancer taxonomy based on genome-wide patterns of copy number abnormalities, we designed an unsupervised classification algorithm that identifies genomic subgroups of tumors. This algorithm is based on a modified genomic Non-negative Matrix Factorization (gNMF) algorithm and includes several additional components, namely a pilot hierarchical clustering procedure to determine the number of clusters, a multiple random initiation scheme, a new stop criterion for the core gNMF, as well as a 10-fold cross-validation stability test for quality assessment.

Result

We applied our algorithm to identify genomic subgroups of three major cancer types: non-small cell lung carcinoma (NSCLC), colorectal cancer (CRC), and malignant melanoma. High-density SNP array datasets for patient tumors and established cell lines were used to define genomic subclasses of the diseases and identify cell lines representative of each genomic subtype. The algorithm was compared with several traditional clustering methods and showed improved performance. To validate our genomic taxonomy of NSCLC, we correlated the genomic classification with disease outcomes. Overall survival time and time to recurrence were shown to differ significantly between the genomic subtypes.

Conclusions

We developed an algorithm for cancer classification based on genome-wide patterns of copy number aberrations and demonstrated its superiority to existing clustering methods. The algorithm was applied to define genomic subgroups of three cancer types and identify cell lines representative of these subgroups. Our data enabled the assembly of representative cell line panels for testing drug candidates.

High-resolution DNA analysis of human embryonic stem cell lines reveals culture-induced copy number changes and loss of heterozygosity

Prolonged culture of human embryonic stem cells (hESCs) can lead to adaptation and the acquisition of chromosomal abnormalities, underscoring the need for rigorous genetic analysis of these cells. Here we report the highest-resolution study of hESCs to date using an Affymetrix SNP 6.0 array containing 906,600 probes for single nucleotide polymorphisms (SNPs) and 946,000 probes for copy number variations (CNVs). Analysis of 17 different hESC lines maintained in different laboratories identified 843 CNVs of 50 kb-3 Mb in size. We identified, on average, 24% of the loss of heterozygosity (LOH) sites and 66% of the CNVs changed in culture between early and late passages of the same lines. Thirty percent of the genes detected within CNV sites had altered expression compared to samples with normal copy number states, of which >44% were functionally linked to cancer. Furthermore, LOH of the q arm of chromosome 16, which has not been observed previously in hESCs, was detected.

Identification of recurrent regions of Copy-Number Variants across multiple individuals

BACKGROUND

Algorithms and software for CNV detection have been developed, but they detect the CNV regions sample-by-sample with individual-specific breakpoints, while common CNV regions are likely to occur at the same genomic locations across different individuals in a homogenous population. Current algorithms to detect common CNV regions do not account for the varying reliability of the individual CNVs, typically reported as confidence scores by SNP-based CNV detection algorithms. General methodologies for identifying these recurrent regions, especially those directed at SNP arrays, are still needed.

RESULTS

In this paper, we describe two new approaches for identifying common CNV regions based on (i) the frequency of occurrence of reliable CNVs, where reliability is determined by high confidence scores, and (ii) a weighted frequency of occurrence of CNVs, where the weights are determined by the confidence scores. In addition, motivated by the fact that we often observe partially overlapping CNV regions as a mixture of two or more distinct subregions, regions identified using the two approaches can be fine-tuned to smaller sub-regions using a clustering algorithm. We compared the performance of the methods with sequencing-based results in terms of discordance rates, rates of departure from Hardy-Weinberg equilibrium (HWE) and average frequency and size of the identified regions. The discordance rates as well as the rates of departure from HWE decrease when we select CNVs with higher confidence scores. We also performed comparisons with two previously published methods, STAC and GISTIC, and showed that the methods we consider are better at identifying low-frequency but high-confidence CNV regions.

CONCLUSIONS

The proposed methods for identifying common CNV regions in multiple individuals perform well compared to existing methods. The identified common regions can be used for downstream analyses such as group comparisons in association studies.

Preprocessing and downstream analysis of microarray DNA copy number profiles

Analysis of DNA copy number profiles requires methods tailored to the specific nature of these data. The number of available data analysis methods has grown enormously in the last 5 years. We discuss the typical characteristics of DNA copy number data, as measured by microarray technology and review the extensive literature on preprocessing methods such as segmentation and calling. Subsequently, the focus narrows to applications of DNA copy number in cancer, in particular, several downstream analyses of multi-sample data sets such as testing, clustering and classification. Finally, we look ahead: what should we prepare for and which methodology-related topics may deserve attention in the near future?

Anti-proliferative action of vitamin D in MCF7 is still active after siRNA-VDR knock-down

Background

The active form of Vitamin D, 1,25-dihydroxyvitamin D₃ (1,25D), has strong anti-proliferative effects, yet the molecular mechanisms underneath this effect remain unclear. In contrast, the molecular mechanism of 1,25D for the regulation of calcium homeostasis has principally been resolved, demonstrating a pivotal role for the vitamin D receptor (VDR).

Results

We first addressed the question whether the anti-proliferative effects of 1,25D are influenced by VDR. Knockdown of VDR by siRNA did not affect the anti-proliferative effects of 1,25D in MCF7 breast cancer cells. This unanticipated finding led us to take an alternative approach using genome wide screens to study the molecular mechanisms of 1,25D in proliferation. For that purpose, four independently developed and stable 1,25D resistant MCF7 cell lines were analyzed. Array CGH identified a copy number alteration in a region of 13.5 Mb at chromosome 11q13.4-14.1 common to all four 1,25D resistant cell lines. Expression arrays revealed that no single gene was differentially expressed between the sensitive and resistant cells, but multiple membrane receptor signaling pathways were altered in the 1,25D resistant cell lines. Importantly, in the genome wide experiments neither VDR, CYP24A1 nor other known vitamin D signaling pathway genes were associated with 1,25D resistance.

Conclusion

In conclusion, siRNA and genome wide studies both suggest that the anti-proliferative effects of 1,25D in MCF7 breast tumor cell lines do not rely on classical Vitamin D pathway per se.

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

Copy number gain at 8q12.1-q22.1 is associated with a malignant tumor phenotype in salivary gland myoepitheliomas

Salivary gland myoepithelial tumors are relatively uncommon tumors with an unpredictable clinical course. More knowledge about their genetic profiles is necessary to identify novel predictors of disease. In this study, we subjected 27 primary tumors (15 myoepitheliomas and 12 myoepithelial carcinomas) to genome-wide microarray-based comparative genomic hybridization (array CGH). We set out to delineate known chromosomal aberrations in more detail and to unravel chromosomal differences between benign myoepitheliomas and myoepithelial carcinomas. Patterns of DNA copy number aberrations were analyzed by unsupervised hierarchical cluster analysis. Both benign and malignant tumors revealed a limited amount of chromosomal alterations (median of 5 and 7.5, respectively). In both tumor groups, high frequency gains (> or =20%) were found mainly at loci of growth factors and growth factor receptors (e.g., PDGF, FGF(R)s, and EGFR). In myoepitheliomas, high frequency losses (> or =20%) were detected at regions of proto-cadherins. Cluster analysis of the array CGH data identified three clusters. Differential copy numbers on chromosome arm 8q and chromosome 17 set the clusters apart. Cluster 1 contained a mixture of the two phenotypes (n = 10), cluster 2 included mostly benign tumors (n = 10), and cluster 3 only contained carcinomas (n = 7). Supervised analysis between malignant and benign tumors revealed a 36 Mbp-region at 8q being more frequently gained in malignant tumors (P = 0.007, FDR = 0.05). This is the first study investigating genomic differences between benign and malignant myoepithelial tumors of the salivary glands at a genomic level. Both unsupervised and supervised analysis of the genomic profiles revealed chromosome arm 8q to be involved in the malignant phenotype of salivary gland myoepitheliomas.

Predicting drug susceptibility of non-small cell lung cancers based on genetic lesions

Somatic genetic alterations in cancers have been linked with response to targeted therapeutics by creation of specific dependency on activated oncogenic signaling pathways. However, no tools currently exist to systematically connect such genetic lesions to therapeutic vulnerability. We have therefore developed a genomics approach to identify lesions associated with therapeutically relevant oncogene dependency. Using integrated genomic profiling, we have demonstrated that the genomes of a large panel of human non-small cell lung cancer (NSCLC) cell lines are highly representative of those of primary NSCLC tumors. Using cell-based compound screening coupled with diverse computational approaches to integrate orthogonal genomic and biochemical data sets, we identified molecular and genomic predictors of therapeutic response to clinically relevant compounds. Using this approach, we showed that v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations confer enhanced Hsp90 dependency and validated this finding in mice with KRAS-driven lung adenocarcinoma, as these mice exhibited dramatic tumor regression when treated with an Hsp90 inhibitor. In addition, we found that cells with copy number enhancement of v-abl Abelson murine leukemia viral oncogene homolog 2 (ABL2) and ephrin receptor kinase and v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (avian) (SRC) kinase family genes were exquisitely sensitive to treatment with the SRC/ABL inhibitor dasatinib, both in vitro and when it xenografted into mice. Thus, genomically annotated cell-line collections may help translate cancer genomics information into clinical practice by defining critical pathway dependencies amenable to therapeutic inhibition.

Identification of genes putatively involved in the pathogenesis of diffuse large B-cell lymphomas by integrative genomics

Diffuse large B-cell lymphomas (DLBCL) are highly heterogeneous with regard to clinical presentation and outcome. DLBCL copy number aberrations have been identified previously, of which the deletion at 6q21-24 was significantly associated with a highly favorable clinical response to chemotherapy. In this study, we aimed to identify genes implicated in this and other genomic regions with recurrent losses and/or gains. To identify implicated genes, we superimposed array comparative genomic hybridization (aCGH) data onto a microarray expression dataset of 42 clinically well-characterized primary nodal DLBCL biopsies. We confirmed that loss of 6q21-24 is significantly associated with a highly favorable clinical response to chemotherapy. Our approach identified 316 significant genes restricted to 32 chromosomal regions, including 24 genes identified at 6q21-24. In an independent dataset, 18% of overexpressed genes in gained regions and 55% of down-regulated genes in deleted regions were validated. In summary, using integrative genomics novel onco and tumor suppressor genes were identified in DLBCL that were not recognized by expression profiling alone.

Overall genomic pattern is a predictor of outcome in neuroblastoma

PURPOSE

For a comprehensive overview of the genetic alterations of neuroblastoma, their association and clinical significance, we conducted a whole-genome DNA copy number analysis.

PATIENTS AND METHODS

A series of 493 neuroblastoma (NB) samples was investigated by array-based comparative genomic hybridization in two consecutive steps (224, then 269 patients).

RESULTS

Genomic analysis identified several types of profiles. Tumors presenting exclusively whole-chromosome copy number variations were associated with excellent survival. No disease-related death was observed in this group. In contrast, tumors with any type of segmental chromosome alterations characterized patients with a high risk of relapse. Patients with both numerical and segmental abnormalities clearly shared the higher risk of relapse of segmental-only patients. In a multivariate analysis, taking into account the genomic profile, but also previously described individual genetic and clinical markers with prognostic significance, the presence of segmental alterations with (HR, 7.3; 95% CI, 3.7 to 14.5; P < .001) or without MYCN amplification (HR, 4.5; 95% CI, 2.4 to 8.4; P < .001) was the strongest predictor of relapse; the other significant variables were age older than 18 months (HR, 1.8; 95% CI, 1.2 to 2.8; P = .004) and stage 4 (HR, 1.8; 95% CI, 1.2 to 2.7; P = .005). Finally, within tumors showing segmental alterations, stage 4, age, MYCN amplification, 1p and 11q deletions, and 1q gain were independent predictors of decreased overall survival.

CONCLUSION

The analysis of the overall genomic pattern, which probably unravels particular genomic instability mechanisms rather than the analysis of individual markers, is essential to predict relapse in NB patients. It adds critical prognostic information to conventional markers and should be included in future treatment stratification.

Salivary gland carcinosarcoma: oligonucleotide array CGH reveals similar genomic profiles in epithelial and mesenchymal components

In this study, we present a case of parotid gland de novo carcinosarcoma. Salivary gland carcinosarcoma (or true malignant mixed tumor) is a rare biphasic neoplasm, composed of both malignant epithelial and malignant mesenchymal components. It is yet unclear whether these two phenotypes occur by collision of two independent tumors or if they are of clonal origin. To analyze the clonality of the different morphologic tumor components, oligonucleotide microarray-based comparative genomic hybridization (oaCGH) was performed on the carcinoma and the sarcoma entity separately. This technique enables a high-resolution, genome-wide overview of the chromosomal alterations in the distinct tumor elements. Analysis of both fractions showed a high number of DNA copy number changes. Losses were more prevalent than gains (82 and 49, respectively). The carcinomatous element displayed more chromosomal aberrations than the sarcomatous component. Specific amplifications of MUC20 (in mesenchymal element) and BMI-1 (in both elements) loci were observed. Overall homology between the two genomic profiles was 75%. DNA copy number profiles of the epithelial and mesenchymal components in this salivary gland carcinosarcoma displayed extensive overlap, indicating a monoclonal origin. Since losses are shared to a larger extent than gains, they seem to be more essential for initial oncogenic events. Furthermore, specific amplifications of a mucin and a Polycomb group gene imply these proteins in the tumorigenesis of carcinosarcomas.

The array CGH and its clinical applications

Array comparative genomic hybridization (aCGH) is a technique enabling high-resolution, genome-wide screening of segmental genomic copy number variations (CNVs). It is becoming an essential and a routine clinical diagnostic tool and is gradually replacing cytogenetic methods. Most of the clinically available aCGH platforms are designed to detect aneuploidies, well-characterized microdeletion/microduplication syndromes and subtelomeric or other unbalanced chromosomal rearrangements. In addition, aCGH can uncover numerous CNVs of unclear significance scattered throughout the human genome. But this technology is not able to identify balanced chromosomal imbalances such as translocations and inversions and some ploidies. aCGH increased the ability to detect segmental genomic CNVs in patients with global developmental delay, mental retardation, autism, multiple congenital anomalies and dysmorphism, and is becoming a powerful tool in disease gene discovery and prenatal diagnostics. This tool is also showing promising data in cancer research and in the diagnosis, classification and prognostication of different malignancies.

Integrative analysis reveals the direct and indirect interactions between DNA copy number aberrations and gene expression changes

MOTIVATION

DNA copy number aberrations (CNAs) and gene expression (GE) changes provide valuable information for studying chromosomal instability and its consequences in cancer. While it is clear that the structural aberrations and the transcript levels are intertwined, their relationship is more complex and subtle than initially suspected. Most studies so far have focused on how a CNA affects the expression levels of those genes contained within that CNA.

RESULTS

To better understand the impact of CNAs on expression, we investigated the correlation of each CNA to all other genes in the genome. The correlations are computed over multiple patients that have both expression and copy number measurements in brain, bladder and breast cancer data sets. We find that a CNA has a direct impact on the gene amplified or deleted, but it also has a broad, indirect impact elsewhere. To identify a set of CNAs that is coordinately associated with the expression changes of a set of genes, we used a biclustering algorithm on the correlation matrix. For each of the three cancer types examined, the aberrations in several loci are associated with cancer-type specific biological pathways that have been described in the literature: CNAs of chromosome (chr) 7p13 were significantly correlated with epidermal growth factor receptor signaling pathway in glioblastoma multiforme, chr 13q with NF-kappaB cascades in bladder cancer, and chr 11p with Reck pathway in breast cancer. In all three data sets, gene sets related to cell cycle/division such as M phase, DNA replication and cell division were also associated with CNAs. Our results suggest that CNAs are both directly and indirectly correlated with changes in expression and that it is beneficial to examine the indirect effects of CNAs.

AVAILABILITY

The code is available upon request.

CGH microarrays and cancer

Genetic alterations are a key feature of cancer cells and typically target biological processes and pathways that contribute to cancer pathogenesis. Array-based comparative genomic hybridization (aCGH) has provided a wealth of new information on copy number changes in cancer on a genome-wide level and aCGH data have also been utilized in cancer classification. More importantly, aCGH analyses have allowed highly accurate localization of specific genetic alterations that, for example, are associated with tumor progression, therapy response, or patient outcome. The genes involved in these aberrations are likely to contribute to cancer pathogenesis, and the high-resolution mapping by aCGH greatly facilitates the subsequent identification of these cancer-associated genes.

Getting it right: designing microarray (and not 'microawry') comparative genomic hybridization studies for cancer research

The development of high-resolution microarray-based comparative genomic hybridization (aCGH), using cDNA, bacterial artificial chromosome (BAC) and oligonucleotide probes, is providing tremendous opportunities for translational research by facilitating detailed analysis of entire cancer genomes in a single experiment. However, this technology will only fulfil its promise if studies incorporating aCGH are designed with a full understanding of its current limitations and the strategies available to circumvent them. While there have been several excellent reviews on the current status of this technology, there is currently very little guidance available regarding the appropriate design of experiments incorporating aCGH (including the strengths and weaknesses of each platform), and how best to combine the results obtained from aCGH with other 'omic' technologies, including gene expression. In this review, we present the key design issues that need to be considered in order to optimize aCGH studies, including sample selection, the definition of appropriate experimental objectives, arguments for and against the various microarray platforms that are currently available, and methods for data validation and integration. It is envisaged that future well-designed aCGH studies will enhance our understanding of the genetic basis of cancer, and lead to the identification of novel predictive and prognostic cancer biomarkers, as well as molecular therapeutic targets in cancer.

Cancer cell lines as genetic models of their parent histology: analyses based on array comparative genomic hybridization

Tumor-derived cell lines are used as in vitro cancer models, but their ability to accurately reflect the phenotype and genotype of the parental histology remains questionable, given the prevalence of documented cell line-specific cytogenetic changes. We have addressed the issue of whether copy number alterations seen in tumor-derived cell lines reflect those observed in studies of fresh tissue by carrying out a meta-analysis of array-based comparative genomic hybridization data that considers both copy number alteration frequencies and the occurrence of cancer gene amplifications and homozygous deletions. Pairwise correlation comparisons between the data sets of seven diagnosis-specific matched tumor and cell line groups indicate that the trends in aberration frequencies are highly correlated between tumors and cell line sets of matched cancer histology relative to unmatched pairings. Despite their similarities, cell lines showed uniformly higher locus-specific alteration frequencies (P = 0.004) and several recurring cell line-specific alterations emerged. These include the previously documented losses of 13q and 9p and gains of 20q, as well as additional undescribed cell line-specific gains of 5p, 7p, and 17q and losses of 18q and 4q. These results indicate that, on average, cell lines preserve in vitro the genetic aberrations that are unique to the parent histology from which they were derived while acquiring additional locus-specific alterations. These data may enable a more predictive understanding of individual cell lines as in vitro models of cancer biology and therapy.

Three methods for optimization of cross-laboratory and cross-platform microarray expression data

Microarray gene expression data becomes more valuable as our confidence in the results grows. Guaranteeing data quality becomes increasingly important as microarrays are being used to diagnose and treat patients (1–4). The MAQC Quality Control Consortium, the FDA's Critical Path Initiative, NCI's caBIG and others are implementing procedures that will broadly enhance data quality. As GEO continues to grow, its usefulness is constrained by the level of correlation across experiments and general applicability. Although RNA preparation and array platform play important roles in data accuracy, pre-processing is a user-selected factor that has an enormous effect. Normalization of expression data is necessary, but the methods have specific and pronounced effects on precision, accuracy and historical correlation. As a case study, we present a microarray calibration process using normalization as the adjustable parameter. We examine the impact of eight normalizations across both Agilent and Affymetrix expression platforms on three expression readouts: (1) sensitivity and power, (2) functional/biological interpretation and (3) feature selection and classification error. The reader is encouraged to measure their own discordant data, whether cross-laboratory, cross-platform or across any other variance source, and to use their results to tune the adjustable parameters of their laboratory to ensure increased correlation.

Automated array-CGH optimized for archival formalin-fixed, paraffin-embedded tumor material

Background

Array Comparative Genomic Hybridization (aCGH) is a rapidly evolving technology that still lacks complete standardization. Yet, it is of great importance to obtain robust and reproducible data to enable meaningful multiple hybridization comparisons. Special difficulties arise when aCGH is performed on archival formalin-fixed, paraffin-embedded (FFPE) tissue due to its variable DNA quality. Recently, we have developed an effective DNA quality test that predicts suitability of archival samples for BAC aCGH.

Methods

In this report, we first used DNA from a cancer cell-line (SKBR3) to optimize the aCGH protocol for automated hybridization, and subsequently optimized and validated the procedure for FFPE breast cancer samples. We aimed for highest throughput, accuracy, and reproducibility applicable to FFPE samples, which can also be important in future diagnostic use.

Results

Our protocol of automated array-CGH on archival FFPE ULS-labeled DNA showed very similar results compared with published data and our previous manual hybridization method.

Conclusion

This report combines automated aCGH on unamplified archival FFPE DNA using non-enzymatic ULS labeling, and describes an optimized protocol for this combination resulting in improved quality and reproducibility.