KC-SMARTR: An R package for detection of statistically significant aberrations in multi-experiment aCGH data

Background: Most approaches used to find recurrent or differential DNA Copy Number Alterations (CNA) in array Comparative Genomic Hybridization (aCGH) data from groups of tumour samples depend on the discretization of the aCGH data to gain, loss or no-change states. This causes loss of valuable biological information in tumour samples, which are frequently heterogeneous. We have previously developed an algorithm, KC-SMART, that bases its estimate of the magnitude of the CNA at a given genomic location on kernel convolution (Klijn et al., 2008). This accounts for the intensity of the probe signal, its local genomic environment and the signal distribution across multiple samples. Results: Here we extend the approach to allow comparative analyses of two groups of samples and introduce the R implementation of these two approaches. The comparative module allows for a supervised analysis to be performed, to enable the identification of regions that are differentially aberrated between two user-defined classes. We analyzed data from a series of B- and T-cell lymphomas and were able to retrieve all positive control regions (VDJ regions) in addition to a number of new regions. A t-test employing segmented data, that we implemented, was also able to locate all the positive control regions and a number of new regions but these regions were highly fragmented. Conclusions: KC-SMARTR offers recurrent CNA and class specific CNA detection, at different genomic scales, in a single package without the need for additional segmentation. It is memory efficient and runs on a wide range of machines. Most importantly, it does not rely on data discretization and therefore maximally exploits the biological information in the aCGH data.MediamaticsElectrical Engineering, Mathematics and Computer Scienc

Single-cell chromosomal imbalances detection by array CGH

Genomic imbalances are a major cause of constitutional and acquired disorders. Therefore, aneuploidy screening has become the cornerstone of preimplantation, prenatal and postnatal genetic diagnosis, as well as a routine aspect of the diagnostic workup of many acquired disorders. Recently, array comparative genomic hybridization (array CGH) has been introduced as a rapid and high-resolution method for the detection of both benign and disease-causing genomic copy-number variations. Until now, array CGH has been performed using a significant quantity of DNA derived from a pool of cells. Here, we present an array CGH method that accurately detects chromosomal imbalances from a single lymphoblast, fibroblast and blastomere within a single day. Trisomy 13, 18, 21 and monosomy X, as well as normal ploidy levels of all other chromosomes, were accurately determined from single fibroblasts. Moreover, we showed that a segmental deletion as small as 34 Mb could be detected. Finally, we demonstrated the possibility to detect aneuploidies in single blastomeres derived from preimplantation embryos. This technique offers new possibilities for genetic analysis of single cells in general and opens the route towards aneuploidy screening and detection of unbalanced translocations in preimplantation embryos in particular

A comparison of genomic copy number calls by Partek Genomics Suite, Genotyping Console and Birdsuite algorithms to quantitative PCR

<p>Abstract</p> <p>Background</p> <p>Copy number variants are >1 kb genomic amplifications or deletions that can be identified using array platforms. However, arrays produce substantial background noise that contributes to high false discovery rates of variants. We hypothesized that quantitative PCR could finitely determine copy number and assess the validity of calling algorithms.</p> <p>Results</p> <p>Using data from 29 Affymetrix SNP 6.0 arrays, we determined copy numbers using three programs: Partek Genomics Suite, Affymetrix Genotyping Console 2.0 and Birdsuite. We compared array calls at 25 chromosomal regions to those determined by qPCR and found nearly identical calls in regions of copy number 2. Conversely, agreement differed in regions called variant by at least one method. The highest overall agreement in calls, 91%, was between Birdsuite and quantitative PCR. Partek Genomics Suite calls agreed with quantitative PCR 76% of the time while the agreement of Affymetrix Genotyping Console 2.0 with quantitative PCR was 79%.</p> <p>Conclusions</p> <p>In 38 independent samples, 96% of Birdsuite calls agreed with quantitative PCR. Analysis of three copy number calling programs and quantitative PCR showed Birdsuite to have the greatest agreement with quantitative PCR.</p

Using next-generation sequencing for high resolution multiplex analysis of copy number variation from nanogram quantities of DNA from formalin-fixed paraffin-embedded specimens

The use of next-generation sequencing technologies to produce genomic copy number data has recently been described. Most approaches, however, reply on optimal starting DNA, and are therefore unsuitable for the analysis of formalin-fixed paraffin-embedded (FFPE) samples, which largely precludes the analysis of many tumour series. We have sought to challenge the limits of this technique with regards to quality and quantity of starting material and the depth of sequencing required. We confirm that the technique can be used to interrogate DNA from cell lines, fresh frozen material and FFPE samples to assess copy number variation. We show that as little as 5 ng of DNA is needed to generate a copy number karyogram, and follow this up with data from a series of FFPE biopsies and surgical samples. We have used various levels of sample multiplexing to demonstrate the adjustable resolution of the methodology, depending on the number of samples and available resources. We also demonstrate reproducibility by use of replicate samples and comparison with microarray-based comparative genomic hybridization (aCGH) and digital PCR. This technique can be valuable in both the analysis of routine diagnostic samples and in examining large repositories of fixed archival material

Array-CGH in patients with Kabuki-like phenotype: Identification of two patients with complex rearrangements including 2q37 deletions and no other recurrent aberration

Background: Kabuki syndrome (KS) is a multiple congenital anomaly syndrome characterized by specific facial features, mild to moderate mental retardation, postnatal growth delay, skeletal abnormalities, and unusual dermatoglyphic patterns with prominent fingertip pads. A 3.5 Mb duplication at 8p23.1-p22 was once reported as a specific alteration in KS but has not been confirmed in other patients. The molecular basis of KS remains unknown. Methods: We have studied 16 Spanish patients with a clinical diagnosis of KS or KS-like to search for genomic imbalances using genome-wide array technologies. All putative rearrangements were confirmed by FISH, microsatellite markers and/or MLPA assays, which also determined whether the imbalance was de novo or inherited. Results: No duplication at 8p23.1-p22 was observed in our patients. We detected complex rearrangements involving 2q in two patients with Kabuki-like features: 1) a de novo inverted duplication of 11 Mb with a 4.5 Mb terminal deletion, and 2) a de novo 7.2 Mb-terminal deletion in a patient with an additional de novo 0.5 Mb interstitial deletion in 16p. Additional copy number variations (CNV), either inherited or reported in normal controls, were identified and interpreted as polymorphic variants. No specific CNV was significantly increased in the KS group. Conclusion: Our results further confirmed that genomic duplications of 8p23 region are not a common cause of KS and failed to detect other recurrent rearrangement causing this disorder. The detection of two patients with 2q37 deletions suggests that there is a phenotypic overlap between the two conditions, and screening this region in the Kabuki-like patients should be considered.This work was funded by grants from the Spanish Ministry of Health (FIS PI042063), Genome Spain and the European Commission (FP6-2005-037627). IC was supported by a Juan de la Cierva Postdoctoral fellowship

Copy Number Variation across European Populations

Genome analysis provides a powerful approach to test for evidence of genetic variation within and between geographical regions and local populations. Copy number variants which comprise insertions, deletions and duplications of genomic sequence provide one such convenient and informative source. Here, we investigate copy number variants from genome wide scans of single nucleotide polymorphisms in three European population isolates, the island of Vis in Croatia, the islands of Orkney in Scotland and the South Tyrol in Italy. We show that whereas the overall copy number variant frequencies are similar between populations, their distribution is highly specific to the population of origin, a finding which is supported by evidence for increased kinship correlation for specific copy number variants within populations

Genome-Wide Screening for Genetic Alterations in Esophageal Cancer by aCGH Identifies 11q13 Amplification Oncogenes Associated with Nodal Metastasis

Esophageal squamous cell carcinoma (ESCC) is highly prevalent in China and other Asian countries, as a major cause of cancer-related mortality. ESCC displays complex chromosomal abnormalities, including multiple structural and numerical aberrations. Chromosomal abnormalities, such as recurrent amplifications and homozygous deletions, directly contribute to tumorigenesis through altering the expression of key oncogenes and tumor suppressor genes.To understand the role of genetic alterations in ESCC pathogenesis and identify critical amplification/deletion targets, we performed genome-wide 1-Mb array comparative genomic hybridization (aCGH) analysis for 10 commonly used ESCC cell lines. Recurrent chromosomal gains were frequently detected on 3q26-27, 5p15-14, 8p12, 8p22-24, 11q13, 13q21-31, 18p11 and 20q11-13, with frequent losses also found on 8p23-22, 11q22, 14q32 and 18q11-23. Gain of 11q13.3-13.4 was the most frequent alteration in ESCC. Within this region, CCND1 oncogene was identified with high level of amplification and overexpression in ESCC, while FGF19 and SHANK2 was also remarkably over-expressed. Moreover, a high concordance (91.5%) of gene amplification and protein overexpression of CCND1 was observed in primary ESCC tumors. CCND1 amplification/overexpression was also significantly correlated with the lymph node metastasis of ESCC.These findings suggest that genomic gain of 11q13 is the major mechanism contributing to the amplification. Novel oncogenes identified within the 11q13 amplicon including FGF19 and SHANK2 may play important roles in ESCC tumorigenesis

The CIN4 chromosomal instability qPCR classifier defines tumor aneuploidy and stratifies outcome in grade 2 breast cancer.

Purpose: Quantifying chromosomal instability (CIN) has both prognostic and predictive clinical utility in breast cancer. In order to establish a robust and clinically applicable gene expression-based measure of CIN, we assessed the ability of four qPCR quantified genes selected from the 70-gene Chromosomal Instability (CIN70) expression signature to stratify outcome in patients with grade 2 breast cancer. Methods: AURKA, FOXM1, TOP2A and TPX2 (CIN4), were selected from the CIN70 signature due to their high level of correlation with histological grade and mean CIN70 signature expression in silico. We assessed the ability of CIN4 to stratify outcome in an independent cohort of patients diagnosed between 1999 and 2002. 185 formalin-fixed, paraffin-embedded (FFPE) samples were included in the qPCR measurement of CIN4 expression. In parallel, ploidy status of tumors was assessed by flow cytometry. We investigated whether the categorical CIN4 score derived from the CIN4 signature was correlated with recurrence-free survival (RFS) and ploidy status in this cohort. Results: We observed a significant association of tumor proliferation, defined by Ki67 and mitotic index (MI), with both CIN4 expression and aneuploidy. The CIN4 score stratified grade 2 carcinomas into good and poor prognostic cohorts (mean RFS: 83.864.9 and 69.4 +- 8.2 months, respectively, p = 0.016) and its predictive power was confirmed by multivariate analysis outperforming MI and Ki67 expression. Conclusions: The first clinically applicable qPCR derived measure of tumor aneuploidy from FFPE tissue, stratifies grade 2 tumors into good and poor prognosis groups