Distance-based reconstruction of tree models for oncogenesis.

Comparative genomic hybridization (CGH) is a laboratory method to measure gains and losses in the copy number of chromosomal regions in tumor cells. It is hypothesized that certain DNA gains and losses are related to cancer progression and that the patterns of these changes are relevant to the clinical consequences of the cancer. It is therefore of interest to develop models which predict the occurrence of these events, as well as techniques for learning such models from CGH data. We continue our study of the mathematical foundations for inferring a model of tumor progression from a CGH data set that we started in Desper et al. (1999). In that paper, we proposed a class of probabilistic tree models and showed that an algorithm based on maximum-weight branching in a graph correctly infers the topology of the tree, under plausible assumptions. In this paper, we extend that work in the direction of the so-called distance-based trees, in which events are leaves of the tree, in the style of models common in phylogenetics. Then we show how to reconstruct the distance-based trees using tree-fitting algorithms developed by researchers in phylogenetics. The main advantages of the distance-based models are that 1) they represent information about co-occurrences of all pairs of events, instead of just some pairs, 2) they allow quantitative predictions about which events occur early in tumor progression, and 3) they bring into play the extensive methodology and software developed in the context of phylogenetics. We illustrate the distance-based tree method and how it complements the branching tree method, with a CGH data set for renal cancer.     

A Latent Class Model with Hidden Markov Dependence for Array CGH Data

Summary Array CGH is a high‐throughput technique designed to detect genomic alterations linked to the development and progression of cancer. The technique yields fluorescence ratios that characterize DNA copy number change in tumor versus healthy cells. Classification of tumors based on aCGH profiles is of scientific interest but the analysis of these data is complicated by the large number of highly correlated measures. In this article, we develop a supervised Bayesian latent class approach for classification that relies on a hidden Markov model to account for the dependence in the intensity ratios. Supervision means that classification is guided by a clinical endpoint. Posterior inferences are made about class‐specific copy number gains and losses. We demonstrate our technique on a study of brain tumors, for which our approach is capable of identifying subsets of tumors with different genomic profiles, and differentiates classes by survival much better than unsupervised methods.     

A method for calling gains and losses in array CGH data

Array CGH is a powerful technique for genomic studies of cancer. It enables one to carry out genome-wide screening for regions of genetic alterations, such as chromosome gains and losses, or localized amplifications and deletions. In this paper, we propose a new algorithm 'Cluster along chromosomes' (CLAC) for the analysis of array CGH data. CLAC builds hierarchical clustering-style trees along each chromosome arm (or chromosome), and then selects the 'interesting' clusters by controlling the False Discovery Rate (FDR) at a certain level. In addition, it provides a consensus summary across a set of arrays, as well as an estimate of the corresponding FDR. We illustrate the method using an application of CLAC on a lung cancer microarray CGH data set as well as a BAC array CGH data set of aneuploid cell strains.     

Genomic profiling by DNA amplification of laser capture microdissected tissues and array CGH

Comparative genomic hybridization by means of BAC microarrays (array CGH) allows high-resolution profiling of copy-number aberrations in tumor DNA. However, specific genetic lesions associated with small but clinically relevant tumor areas may pass undetected due to intra-tumor heterogeneity and/or the presence of contaminating normal cells. Here, we show that the combination of laser capture microdissection, 29 DNA polymerase-mediated isothermal genomic DNA amplification, and array CGH allows genomic profiling of very limited numbers of cells. Moreover, by means of simple statistical models, we were able to bypass the exclusion of amplification distortions and variability prone areas, and to detect tumor-specific chromosomal gains and losses. We applied this new combined experimental and analytical approach to the genomic profiling of colorectal adenomatous polyps and demonstrated our ability to accurately detect single copy gains and losses affecting either whole chromosomes or small genomic regions from as little as 2 ng of DNA or 1000 microdissected cells.     

A strategy combining flow sorting and comparative genomic hybridization for studying genetic aberrations at different stages of colorectal tumorigenesis in ulcerative colitis

BACKGROUND: DNA aneuploidy has been shown to increase the risk of developing dysplasia in ulcerative colitis (UC) and is related to tumorigenesis in the colorectum. Therefore, it is of particular interest to study genetic aberrations behind DNA aneuploidization during colorectal carcinogenesis. We wanted to elucidate further the relationship between mucosal morphology and DNA aberrations in UC. METHODS: DNA flow cytometry was applied to multiple lesions including regenerative, dysplastic, and carcinomatous mucosa from the colectomy specimen of a male patient with long-standing UC. The lesions harbored multiple DNA aneuploid stemlines that were subjected to flow sorting. We analyzed gene alterations by degenerate oligonucleotide primer (DOP; universal primers) polymerase chain reaction (PCR)-based comparative genomic hybridization (CGH) and fluorescent in situ hybridization (FISH) in diploid and aneuploid sorted cells. RESULTS: DOP-PCR-based CGH shows gains and losses that can be verified by FISH. We show that with this approach one can study genetic evolution of distinct DNA diploid and aberrant subpopulations through defined stages of colorectal tumorigenesis. This includes getting information related to tumor heterogeneity that cannot be obtained by CGH with DNA extracted from nonsorted cell populations. Genetic imbalance was also detected in diploid nondysplastic flow-sorted mucosal cells from the same bowel. CONCLUSIONS: Similar gains and losses were found in aneuploid dysplasias and carcinomas at widely separated locations in the same bowel, indicating a common selection pressure in different areas of the same bowel. The common aberrations may be of importance for progression from dysplasia to carcinoma.     

Analysis of array CGH data: from signal ratio to gain and loss of DNA regions

MOTIVATION: Genomic DNA regions are frequently lost or gained during tumor progression. Array Comparative Genomic Hybridization (array CGH) technology makes it possible to assess these changes in DNA in cancers, by comparison with a normal reference. The identification of systematically deleted or amplified genomic regions in a set of tumors enables biologists to identify genes involved in cancer progression because tumor suppressor genes are thought to be located in lost genomic regions and oncogenes, in gained regions. Array CGH profiles should also improve the classification of tumors. The achievement of these goals requires a methodology for detecting the breakpoints delimiting altered regions in genomic patterns and assigning a status (normal, gained or lost) to each chromosomal region. RESULTS: We have developed a methodology for the automatic detection of breakpoints from array CGH profile, and the assignment of a status to each chromosomal region. The breakpoint detection step is based on the Adaptive Weights Smoothing (AWS) procedure and provides highly convincing results: our algorithm detects 97, 100 and 94% of breakpoints in simulated data, karyotyping results and manually analyzed profiles, respectively. The percentage of correctly assigned statuses ranges from 98.9 to 99.8% for simulated data and is 100% for karyotyping results. Our algorithm also outperforms other solutions on a public reference dataset. AVAILABILITY: The R package GLAD (Gain and Loss Analysis of DNA) is available upon request.     

Identification of Networks of Co-Occurring,Tumor-Related DNA Copy Number Changes Using a Genome-Wide Scoring Approach

Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis. It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression. DNA copy number alterations (CNAs) are one of the ways in which cancer genes are deregulated in tumor cells. We hypothesized that synergistic interactions between cancer genes might be identified by looking for regions of co-occurring gain and/or loss. To this end we developed a scoring framework to separate truly co-occurring aberrations from passenger mutations and dominant single signals present in the data. The resulting regions of high co-occurrence can be investigated for between-region functional interactions. Analysis of high-resolution DNA copy number data from a panel of 95 hematological tumor cell lines correctly identified co-occurring recombinations at the T-cell receptor and immunoglobulin loci in T- and B-cell malignancies, respectively, showing that we can recover truly co-occurring genomic alterations. In addition, our analysis revealed networks of co-occurring genomic losses and gains that are enriched for cancer genes. These networks are also highly enriched for functional relationships between genes. We further examine sub-networks of these networks, core networks, which contain many known cancer genes. The core network for co-occurring DNA losses we find seems to be independent of the canonical cancer genes within the network. Our findings suggest that large-scale, low-intensity copy number alterations may be an important feature of cancer development or maintenance by affecting gene dosage of a large interconnected network of functionally related genes.     

Classification and feature selection algorithms for multi-class CGH data

Recurrent chromosomal alterations provide cytological and molecular positions for the diagnosis and prognosis of cancer. Comparative genomic hybridization (CGH) has been useful in understanding these alterations in cancerous cells. CGH datasets consist of samples that are represented by large dimensional arrays of intervals. Each sample consists of long runs of intervals with losses and gains. In this article, we develop novel SVM-based methods for classification and feature selection of CGH data. For classification, we developed a novel similarity kernel that is shown to be more effective than the standard linear kernel used in SVM. For feature selection, we propose a novel method based on the new kernel that iteratively selects features that provides the maximum benefit for classification. We compared our methods against the best wrapper-based and filter-based approaches that have been used for feature selection of large dimensional biological data. Our results on datasets generated from the Progenetix database, suggests that our methods are considerably superior to existing methods. AVAILABILITY: All software developed in this article can be downloaded from http://plaza.ufl.edu/junliu/feature.tar.gz.     

Molecular parameters associated with insulinoma progression: chromosomal instability versus p53 and CK19 status

Insulinomas represent the predominant syndromic subtype of endocrine pancreatic tumors (EPTs). Their metastatic potential cannot be predicted reliably using histopathological criteria. In the past few years, several attempts have been made to identify prognostic markers, among them TP53 mutations and immunostaining of p53 and recently cytokeratin 19 (CK19). In a previous study using conventional comparative genomic hybridization (CGH) we have shown that chromosomal instability (CIN) is associated with metastatic disease in insulinomas. It was our aim to evaluate these potential parameters in a single study. For the determination of CIN, we applied CGH to microarrays because it allows a high-resolution detection of DNA copy number changes in comparison with conventional CGH as well as the analysis of chromosomal regions close to the centromeres and telomeres, and at 1pter-->p32, 16p, 19 and 22. These regions are usually excluded from conventional CGH analysis, because they may show DNA gains in negative control hybridizations. Array CGH analysis of 30 insulinomas (15 tumors of benign, eight tumors of uncertain and seven tumors of malignant behavior) revealed that >or=20 chromosomal alterations and >or=6 telomeric losses were the best predictors of malignant progression. A subset of 22 insulinomas was further investigated for TP53 exon 5-8 gene mutations, and p53 and CK19 expression. Only one malignant tumor was shown to harbor an arginine 273 serine mutation and immunopositivity for p53. CK19 immunopositivity was detected in three malignant tumors and one tumor with uncertain behavior. In conclusion, our results indicate that CIN as well as telomeric loss are very powerful indicators for malignant progression in sporadic insulinomas. Our data do not support a critical role for p53 and CK19 as molecular parameters for this purpose.     

Spatial smoothing and hot spot detection for CGH data using the fused lasso

We apply the "fused lasso" regression method of (TSRZ2004) to the problem of "hot- spot detection", in particular, detection of regions of gain or loss in comparative genomic hybridization (CGH) data. The fused lasso criterion leads to a convex optimization problem, and we provide a fast algorithm for its solution. Estimates of false-discovery rate are also provided. Our studies show that the new method generally outperforms competing methods for calling gains and losses in CGH data.     

Estimation of Copy Number Alterations from Exome Sequencing Data

Exome sequencing constitutes an important technology for the study of human hereditary diseases and cancer. However, the ability of this approach to identify copy number alterations in primary tumor samples has not been fully addressed. Here we show that somatic copy number alterations can be reliably estimated using exome sequencing data through a strategy that we have termed exome2cnv. Using data from 86 paired normal and primary tumor samples, we identified losses and gains of complete chromosomes or large genomic regions, as well as smaller regions affecting a minimum of one gene. Comparison with high-resolution comparative genomic hybridization (CGH) arrays revealed a high sensitivity and a low number of false positives in the copy number estimation between both approaches. We explore the main factors affecting sensitivity and false positives with real data, and provide a side by side comparison with CGH arrays. Together, these results underscore the utility of exome sequencing to study cancer samples by allowing not only the identification of substitutions and indels, but also the accurate estimation of copy number alterations.     

Genome wide measurement of DNA copy number changes in neuroblastoma: dissecting amplicons and mapping losses, gains and breakpoints

In the past few years high throughput methods for assessment of DNA copy number alterations have witnessed rapid progress. Both 'in house' developed BAC, cDNA, oligonucleotide and commercial arrays are now available and widely applied in the study of the human genome, particularly in the context of disease. Cancer cells are known to exhibit DNA losses, gains and amplifications affecting tumor suppressor genes and proto-oncogenes. Moreover, these patterns of genomic imbalances may be associated with particular tumor types or subtypes and may have prognostic value. Here we summarize recent array CGH findings in neuroblastoma, a pediatric tumor of the sympathetic nervous system. A total of 176 primary tumors and 53 cell lines have been analyzed on different platforms. Through these studies the genomic content and boundaries of deletions, gains and amplifications were characterized with unprecedented accuracy. Furthermore, in conjunction with cytogenetic findings, array CGH allows the mapping of breakpoints of unbalanced translocations at a very high resolution.     

Collecting Duct Carcinomas Represent a Unique Tumor Entity Based on Genetic Alterations

Collecting duct carcinoma (CDC) is a rare renal neoplasm that is associated with poor prognosis due to its highly aggressive course and limited response to immuno- or chemotherapy. Histologically, CDC is defined as a subtype of renal cell carcinomas, but in some cases, it is difficult to differentiate from urothelial carcinomas (UC). Therefore the aim of this study was to determine genetic alterations of CDC in comparison to that of urothelial carcinomas of the upper urinary tract (UUT-UC) to clarify the histological origin of this rare tumor entity. Twenty-nine CDC samples were obtained from seven different German centers and compared with twenty-six urothelial carcinomas of the upper urinary tract. Comparative genomic hybridization (CGH) was used to investigate the genetic composition of patients’ tumors and allowed the detection of losses and gains of DNA copy numbers throughout the entire genome. The clinical data were correlated with CGH results. CGH analysis of CDC revealed DNA aberrations in many chromosomes. DNA losses were more frequently observed than gains, while high-level amplifications were not detected. The mean frequency of CDC chromosomal aberrations (4.9/case) was slightly lower than that in UUT-UC (5.4/case). Recurrent CDC DNA losses occurred at 8p (n=9/29), 16p (9/29), 1p (n=7/29) and 9p (n=7/29), and gains occurred in 13q (n=9/29). In contrast to CDC, the most frequently detected UUT-UC DNA aberration was a loss at 9q (n=13/26). DNA losses at 9q, 13q and 8q as well as gains at 8p showed significant variations in UUT-UC compared to CDC. There was no correlation between the patients’ clinical course and the presence or absence of these recurrent genetic alterations. CDCs are characterized by a different genetic pattern compared to UUT-UC. Regarding the published data on renal cell carcinoma, we conclude that CDC appears to be a unique entity among kidney carcinomas.     

Comparative genomic hybridization arrays in clinical pathology: progress and challenges

Array-based comparative genomic hybridization (array CGH) genome scanning is a powerful method for the global detection of gains and losses of genetic material in both congenital and neoplastic disorders. When used as a clinical diagnostic test, array CGH combines the whole genome perspective of traditional G-banded cytogenetics with the targeted identification of cryptic chromosomal abnormalities characteristic of fluorescence in situ hybridization (FISH). However, the presence of structural variants in the human genome can complicate analysis of patient samples, and array CGH does not provide morphologic information about chromosome structure, balanced translocations, or the actual chromosomal location of segmental duplications. Identification of such anomalies has significant diagnostic and prognostic implications for the patient. We therefore propose that array CGH should be used as a guide to the presence of genomic structural rearrangements in germline and tumor genomes that can then be further characterized by FISH or G-banding, depending on the clinical scenario. In this article, we share some of our experiences with diagnostic array CGH and discuss recent progress and challenges involved with the integration of array CGH into clinical laboratory medicine.     

Focal DNA Copy Number Changes in Neuroblastoma Target MYCN Regulated Genes

Neuroblastoma is an embryonic tumor arising from immature sympathetic nervous system cells. Recurrent genomic alterations include MYCN and ALK amplification as well as recurrent patterns of gains and losses of whole or large partial chromosome segments. A recent whole genome sequencing effort yielded no frequently recurring mutations in genes other than those affecting ALK. However, the study further stresses the importance of DNA copy number alterations in this disease, in particular for genes implicated in neuritogenesis. Here we provide additional evidence for the importance of focal DNA copy number gains and losses, which are predominantly observed in MYCN amplified tumors. A focal 5 kb gain encompassing the MYCN regulated miR-17∼92 cluster as sole gene was detected in a neuroblastoma cell line and further analyses of the array CGH data set demonstrated enrichment for other MYCN target genes in focal gains and amplifications. Next we applied an integrated genomics analysis to prioritize MYCN down regulated genes mediated by MYCN driven miRNAs within regions of focal heterozygous or homozygous deletion. We identified RGS5, a negative regulator of G-protein signaling implicated in vascular normalization, invasion and metastasis, targeted by a focal homozygous deletion, as a new MYCN target gene, down regulated through MYCN activated miRNAs. In addition, we expand the miR-17∼92 regulatory network controlling TGFß signaling in neuroblastoma with the ring finger protein 11 encoding gene RNF11, which was previously shown to be targeted by the miR-17∼92 member miR-19b. Taken together, our data indicate that focal DNA copy number imbalances in neuroblastoma (1) target genes that are implicated in MYCN signaling, possibly selected to reinforce MYCN oncogene addiction and (2) serve as a resource for identifying new molecular targets for treatment.     

Characterization of breast cancer by array comparative genomic hybridization.

Cancer progression is due to the accumulation of recurrent genomic alterations that induce growth advantage and clonal expansion. Most of these genomic changes can be detected using the array comparative genomic hybridization (CGH) technique. The accurate classification of these genomic alterations is expected to have an important impact on translational and basic research. Here we review recent advances in CGH technology used in the characterization of different features of breast cancer. First, we present bioinformatics methods that have been developed for the analysis of CGH arrays; next, we discuss the use of array CGH technology to classify tumor stages and to identify and stratify subgroups of patients with different prognoses and clinical behaviors. We finish our review with a discussion of how CGH arrays are being used to identify oncogenes, tumor suppressor genes, and breast cancer susceptibility genes.     

DNA ploidy and chromosomal imbalances in invasive ductal breast cancer. A comparative study of DNA image cytometry and comparative genomic hybridization (CGH).

Chromosomal imbalances were analyzed in 62 breast cancers with different DNA ploidy by CGH. The results of DNA image cytometry and CGH are consistent with peridiploid and aneuploid cases. The peritetraploid tumors harbored a high number of chromosomal imbalances, as a hint for an unfavorable prognosis. The quantitative analysis of imbalances highlighted the role of different physical constituents of the chromosome, and of chromosomal losses in different DNA ploidy groups. The peritetraploid and aneuploid tumors differed from the peridiploid tumors in losses at 8p and 18q. The peritetraploid cancers exhibited more gains at 8q, the aneuploid tumors more losses at 17p than their peridiploid counterparts. The aneuploid cases differed from the peritetraploid tumors in a higher number of losses at 11q and 14q. Combinations of imbalances provide further insights into the genetic background of DNA ploidy. Hypotheses for the progression from peridiploid to nondiploid breast cancers are given.     

Chromosomal imbalances are associated with metastasis-free survival in breast cancer patients.

Multiple chromosomal imbalances have been identified in breast cancer using comparative genomic hybridization (CGH). Their association with the primary tumors' potential for building distant metastases is unknown. In this study we have investigated 39 invasive breast carcinomas with a mean follow-up period of 99 months (max. 193 months) by CGH to determine the prognostic value of chromosomal gains and losses.The mean number of chromosomal imbalances per tumor was 6.5+/-0.7 (range 2 to 18). The most frequent alterations identified in more than 1/3 of cases were gains on chromosomes 11q13, 12q24, 16, 17, and 20q, and losses on 2q and 13q. A significantly different frequency of chromosomal aberrations (p相似文献   

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

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

Detection of DNA copy number changes in human endometriosis by comparative genomic hybridization

Endometriosis is characterized by infertility and pelvic pain in 10-15% of women of reproductive age. The genetic events involved in endometriotic cell expansion remain in large part unknown. To identify genomic changes involved in development of this disease, we examined a panel of 18 selected endometriotic tissues by comparative genomic hybridization (CGH), a molecular cytogenetic method that allows screening of the entire genome for chromosomal gains and/or losses. The study was performed on native, nonamplified DNA extracted from manually dissected endometriotic lesions. Recurrent copy number losses on several chromosomes were detected in 15 of 18 cases. Loss of chromosome 1p and 22q were detected in 50% of the cases. Additional common losses occurred on chromosomes 5p (33%), 6q (27%), 7p(22%), 9q (22%), 16 (22%) as well as on 17q in one case. Gain of DNA sequences were seen at 6q, 7q and 17q in three cases. To validate the CGH data, selective dual-color FISH was performed using probes for the deleted regions on chromosomes 1, 7 and 22 in parallel with the corresponding centromeric probes. Cases showing deletion by CGH all had two signals at 1p36, 7p22.1 and 22q12 in less than 30% of the nuclei in comparison to the double centromeric labels found in more than 85% of the cells. These findings indicate that genes localized to previously undescribed chromosomal regions play a role in development and progression of endometriosis.