A statistical approach for array CGH data analysis

BACKGROUND: Microarray-CGH experiments are used to detect and map chromosomal imbalances, by hybridizing targets of genomic DNA from a test and a reference sample to sequences immobilized on a slide. These probes are genomic DNA sequences (BACs) that are mapped on the genome. The signal has a spatial coherence that can be handled by specific statistical tools. Segmentation methods seem to be a natural framework for this purpose. A CGH profile can be viewed as a succession of segments that represent homogeneous regions in the genome whose BACs share the same relative copy number on average. We model a CGH profile by a random Gaussian process whose distribution parameters are affected by abrupt changes at unknown coordinates. Two major problems arise : to determine which parameters are affected by the abrupt changes (the mean and the variance, or the mean only), and the selection of the number of segments in the profile. RESULTS: We demonstrate that existing methods for estimating the number of segments are not well adapted in the case of array CGH data, and we propose an adaptive criterion that detects previously mapped chromosomal aberrations. The performances of this method are discussed based on simulations and publicly available data sets. Then we discuss the choice of modeling for array CGH data and show that the model with a homogeneous variance is adapted to this context. CONCLUSIONS: Array CGH data analysis is an emerging field that needs appropriate statistical tools. Process segmentation and model selection provide a theoretical framework that allows precise biological interpretations. Adaptive methods for model selection give promising results concerning the estimation of the number of altered regions on the genome

Microarray-based ultra-high resolution discovery of genomic deletion mutations

BACKGROUND: Oligonucleotide microarray-based comparative genomic hybridization (CGH) offers an attractive possible route for the rapid and cost-effective genome-wide discovery of deletion mutations. CGH typically involves comparison of the hybridization intensities of genomic DNA samples with microarray chip representations of entire genomes, and has widespread potential application in experimental research and medical diagnostics. However, the power to detect small deletions is low. RESULTS: Here we use a graduated series of Arabidopsis thaliana genomic deletion mutations (of sizes ranging from 4 bp to ~5 kb) to optimize CGH-based genomic deletion detection. We show that the power to detect smaller deletions (4, 28 and 104 bp) depends upon oligonucleotide density (essentially the number of genome-representative oligonucleotides on the microarray chip), and determine the oligonucleotide spacings necessary to guarantee detection of deletions of specified size. CONCLUSIONS: Our findings will enhance a wide range of research and clinical applications, and in particular will aid in the discovery of genomic deletions in the absence of a priori knowledge of their existence

Trisomy 19 ependymoma, a newly recognized genetico-histological association, including clear cell ependymoma

Ependymal tumors constitute a clinicopathologically heterogeneous group of brain tumors. They vary in regard to their age at first symptom, localization, morphology and prognosis. Genetic data also suggests heterogeneity. We define a newly recognized subset of ependymal tumors, the trisomy 19 ependymoma. Histologically, they are compact lesions characterized by a rich branched capillary network amongst which tumoral cells are regularly distributed. When containing clear cells they are called clear cell ependymoma. Most trisomy 19 ependymomas are supratentorial WHO grade III tumors of the young. Genetically, they are associated with trisomy 19, and frequently with a deletion of 13q21.31-31.2, three copies of 11q13.3-13.4, and/or deletions on chromosome 9. These altered chromosomal regions are indicative of genes and pathways involved in trisomy 19 ependymoma tumorigenesis. Recognition of this genetico-histological entity allows better understanding and dissection of ependymal tumors

Identification of prefoldin amplification (1q23.3-q24.1) in bladder cancer using comparative genomic hybridization (CGH) arrays of urinary DNA

Background: Array-CGH represents a comprehensive tool to discover genomic disease alterations that could potentially be applied to body fluids. In this report, we aimed at applying array-CGH to urinary samples to characterize bladder cancer. Methods: Urinary DNA from bladder cancer patients and controls were hybridized on 44K oligonucleotide arrays. Validation analyses of identified regions and candidates included fluorescent in situ hybridization (FISH) and immunohistochemistry in an independent set of bladder tumors spotted on custom-made tissue arrays (n = 181). Results: Quality control of array-CGH provided high reproducibility in dilution experiments and when comparing reference pools. The most frequent genomic alterations (minimal recurrent regions) among bladder cancer urinary specimens included gains at 1q and 5p, and losses at 10p and 11p. Supervised hierarchical clustering identified the gain at 1q23.3-q24.1 significantly correlated to stage (p = 0.011), and grade (p = 0.002). The amplification and overexpression of Prefoldin (PFND2), a selected candidate mapping to 1q23.3-q24.1, correlated to increasing stage and tumor grade by means of custom-designed and optimized FISH (p = 0.013 and p = 0.023, respectively), and immunohistochemistry (p ≤0.0005 and p = 0.011, respectively), in an independent set of bladder tumors included in tissue arrays. Moreover, PFND2 overexpression was significantly associated with poor disease-specific survival (p ≤0.0005). PFND2 was amplified and overexpressed in bladder tumors belonging to patients providing urinary specimens where 1q23.3q24.1 amplification was detected by array-CGH. Conclusions: Genomic profiles of urinary DNA mirrowed bladder tumors. Molecular profiling of urinary DNA using array-CGH contributed to further characterize genomic alterations involved in bladder cancer progression. PFND2 was identified as a tumor stratification and clinical outcome prognostic biomarker for bladder cancer patients

Multiple myeloma primary cells show a highly rearranged unbalanced genome with amplifications and homozygous deletions irrespective of the presence of immunoglobulin-related chromosome translocations

Background and Objectives Multiple myeloma (MM) is a malignant plasma cell neoplasia in which genetic studies have shown that genomic changes may affect almost all chromosomes, as shown by fluorescence in situ hybridization (FISH) and comparative genomic hybridization (CGH). Our objective was the genomic characterization of CD 138 positive primary MM samples by means of a high resolution array CGH platform. Design and Methods For the first time, a high resolution array CGH with more than 40,000 probes, has been used to analyze 26 primary MM samples after the enrichment of CD138-positive plasma cells. Results This approach identified copy number imbalances in all cases. Bioinformatics strategies were optimized to perform data analysis allowing the segregation of hyperdiploid and non-hyperdiploid cases by array CGH. Additional analysis showed that structural chromosome rearrangements were more frequently seen in hyperdiploid cases. We also identified the same Xq21 duplication in nearly 20% of the cases, which originated through unbalanced chromosome translocations. High level amplifications and homozygous deletions were recurrently observed in our series and involved genes with meaningful function in cancer biology. Interpretation and Conclusions High resolution array CGH allowed us to identify copy number changes in 100% of the primary MM samples. We segregated different MM subgroups based on their genomic profiles which made it possible to identify homozygous deletions and amplifications of great genetic relevance in MM

Genomic alterations in primary gastric adenocarcinomas correlate with clinicopathological characteristics and survival.

Background & aimsPathogenesis of gastric cancer is driven by an accumulation of genetic changes that to a large extent occur at the chromosomal level. In order to investigate the patterns of chromosomal aberrations in gastric carcinomas, we performed genome-wide microarray based comparative genomic hybridisation (microarray CGH). With this recently developed technique chromosomal aberrations can be studied with high resolution and sensitivity.MethodsArray CGH was applied to a series of 35 gastric adenocarcinomas using a genome-wide scanning array with 2275 BAC and P1 clones spotted in triplicate. Each clone contains at least one STS for linkage to the sequence of the human genome. These arrays provide an average resolution of 1.4 Mb across the genome. DNA copy number changes were correlated with clinicopathological tumour characteristics as well as survival.ResultsAll thirty-five cancers showed chromosomal aberrations and 16 of the 35 tumours showed one or more amplifications. The most frequent aberrations are gains of 8q24.2, 8q24.1, 20q13.12, 20q13.2, 7p11.2, 1q32.3, 8p23.1-p23.3, losses of 5q14.1, 18q22.1, 19p13.12-p13.3, 9p21.3-p24.3, 17p13.1-p13.3, 13q31.1, 16q22.1, 21q21.3, and amplifications of 7q21-q22, and 12q14.1-q21.1. These aberrations were correlated to clinicopathological characteristics and survival. Gain of 1q32.3 was significantly correlated with lymph node status (p=0.007). Tumours with loss of 18q22.1, as well as tumours with amplifications were associated with poor survival (p=0.02, both).ConclusionsMicroarray CGH has revealed several chromosomal regions that have not been described before in gastric cancer at this frequency and resolution, such as amplification of at 7q21-q22 and 12q14.1-q21.1, as well gains at 1q32.3, 7p11.2, and losses at 13q13.1. Interestingly, gain of 1q32.3 and loss of 18q22.1 are associated with a bad prognosis indicating that these regions could harbour gene(s) that may determine aggressive tumour behaviour and poor clinical outcome

Joint segmentation of many aCGH profiles using fast group LARS

Array-Based Comparative Genomic Hybridization (aCGH) is a method used to search for genomic regions with copy numbers variations. For a given aCGH profile, one challenge is to accurately segment it into regions of constant copy number. Subjects sharing the same disease status, for example a type of cancer, often have aCGH profiles with similar copy number variations, due to duplications and deletions relevant to that particular disease. We introduce a constrained optimization algorithm that jointly segments aCGH profiles of many subjects. It simultaneously penalizes the amount of freedom the set of profiles have to jump from one level of constant copy number to another, at genomic locations known as breakpoints. We show that breakpoints shared by many different profiles tend to be found first by the algorithm, even in the presence of significant amounts of noise. The algorithm can be formulated as a group LARS problem. We propose an extremely fast way to find the solution path, i.e., a sequence of shared breakpoints in order of importance. For no extra cost the algorithm smoothes all of the aCGH profiles into piecewise-constant regions of equal copy number, giving low-dimensional versions of the original data. These can be shown for all profiles on a single graph, allowing for intuitive visual interpretation. Simulations and an implementation of the algorithm on bladder cancer aCGH profiles are provided

Genetical stability and osteogenic ability of mesenchimal stem cells on demineralized bone matrices

Journal of Osseointegration Volume 7, Issue 1, 1 March 2015, Pages 2-7 Open Access Genetical stability and osteogenic ability of mesenchimal stem cells on demineralized bone matrices (Article) Pozzuoli, A.a, Gardin, C.b, Aldegheri, R.a, Bressan, E.c, Isola, M.d, Calvo-Guirado, J.L.e, Biz, C.a, Arrigoni, P.a, Feroni, L.b, Zavan, B.b a Department of Surgical,Oncological and Gastroenterological Sciences, University of Padua, Padua, Italy b Department of Biomedical Sciences, University of Padua, Padua, Italy c Department of Neurosciences, University of Padua, Padua, Italy d Department of Animal Medicine, Production and Health (MAPS), Italy e Department of General Dentistry, Faculty of Medicine and Dentistry, University of Murcia, Murcia, Spain Hide additional affiliations View references (44) Abstract Aim: Tissue engineering is a rapidly expanding field with regard to the use of biomaterials and stem cells in the orthopedic surgery. Many experimental studies have been done to understand the best characteristics of cells, materials and laboratory methods for safe clinical applications. The aim of this study was to compare the ability of 2 different human demineralized bone matrices (DBMs), the one enriched and the other not enriched with hyaluronic acid, to stimulate in vitro the proliferation and the osteogenic differentiation of human adipose-derived stem cells (ADSCs) seeded onto an osteoconductive scaffold. Materials and Methods: ADSCs were isolated, by enzymatic digestion, from abdominal adipose tissue of 5 patients undergoing cosmetic lipoaspiration surgery. ADSCs were then seeded onto a 3D scaffold in the presence of the two different osteoinductive matrices of human demineralized bone and evaluated for proliferation and osteogenic differentiation. The safety of the methods was verified using array-Comparative Genomic Hybridization (array-CGH). Results: ADSCs were able to differentiate in osteogenic sense. Both DBMs showed the ability to induce osteogenic differentiation of the cells. Conclusion: array-CGH showed no changes at genome level, thus confirming the safety of materials and method