High-Resolution SNP Microarray Investigation of Copy Number Variations on Chromosome 18 in a Control Cohort

2013 ◽  
Vol 141 (1) ◽  
pp. 16-25
Author(s):  
N.L. Chia ◽  
M. Bryce ◽  
P.E. Hickman ◽  
J.M. Potter ◽  
N. Glasgow ◽  
...  
Placenta ◽  
2011 ◽  
Vol 32 ◽  
pp. S282
Author(s):  
Paola Scaruffi ◽  
Sara Stigliani ◽  
Annamaria Jane Nicoletti ◽  
Pier Luigi Venturini ◽  
Gian Paolo Tonini ◽  
...  

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 230-230
Author(s):  
Ilaria Iacobucci ◽  
E. Ottaviani ◽  
A. Astolfi ◽  
S. Soverini ◽  
N. Testoni ◽  
...  

Abstract The Ph chromosome is the most frequent cytogenetic aberration associated with ALL and it represents the single most significant adverse prognostic marker. Despite the encouraging results achieved with imatinib, resistance develops rapidly and is quickly followed by disease progression. Some mechanisms of resistance have been widely described but the full knowledge of contributing factors driving both the disease and resistance remains to be defined. In order to identify at submicroscopic level genetic lesions driving leukemogenesis and resistance, we profiled until now the genomes of 18 patients, out of 55 Ph+ ALL patients treated in our institute, at diagnosis (n=11) or at the time of haematological relapse (n=7) during therapy with imatinib or dasatinib. 250 ng of genomic DNA were processed on 500K single nucleotide polymorphism (SNP) array according to protocols provided by the manufacturer (Affymetrix Inc., Santa Clara, CA, USA). The median SNP call rate of analysed samples was 96%. Raw signal data were analyzed by BRLMM algorithm and copy number state was calculated with respect to a set of 48 Hapmap normal individuals and a diploid reference set of samples obtained from acute leukaemia cases in remission. Regions of amplification and deletion were visualized by Integrated Genome Browser and mapped to RefSeq to identify the specific genes involved in the lesion. Our analysis identified multiple copy number alterations per case, with deletions outnumbering amplification almost 3:1. Lesions varied from loss or gain of complete chromosome arms (trisomy 4, monosomy 7, loss of 9p, 10q, 14q, 16q and gain of 1q and 17q) to microdeletions and microduplications targeting genomic intervals. The recurring microdeletions that we detected in at least 50% of patients (both at diagnosis and at relapse) included 1p36.21 (PRAMEF), 3q29 (TFCR), 7p14.1 (AMPH), 8p23 (DEFB105A), 14q11.2 (DAD1), 16p13.11 (PDXDC1, NTAN1, RRN3), 16p11.2 (SNP) and 19p13.2 (CARM1, SMARCA4). A common microamplification was 4q13.2 (TMPRSS11E) and 17q21.31. Some genomic alterations were identified in genes regulating B-lymphocyte differentiation, such as PAX5 (n=3), BLNK (n=1) and VPREB1 (n=6) and in genes with an established role in leukemogenesis, such as MDS, BTG1, MLLT3 and RUNX1. Furthermore, many of the deletions detected included genes encoded for phosphatase proteins (e.g. PTPRD, PPP1R9B, PTPN18) and for zinc-finger proteins without any difference between diagnosis and resistance. It is noteworthy that some lesions felt in regions lacking annotated genes (loss: 2p11.2, 3p12.3, 7q11.21 and 14q32.33; gain: 8q23.3 and 13q21.1). Using high-resolution genome wide approach we showed that Ph+ ALL is a more complex disease characterized by multiple genomic anomalies which may provide new insights into the mechanisms underlying leukemogenesis and may be used as targets for existing or novel drugs. Supported by: European LeukemiaNet, COFIN 2003, Novartis Oncology Clinical Development, AIL.


Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 672-672
Author(s):  
Andrea Rinaldi ◽  
Michael Mian ◽  
Davide Rossi ◽  
Francesco Forconi ◽  
Clara Deambrogi ◽  
...  

Abstract Abstract 672 BACKGROUND: CLL is the most common adult-onset leukemia in the Western world. The most common known genetic lesion is the 13q14.3 deletion targeting MIR15/MIR16. We applied a very high resolution array to identify new genetic lesions in CLL. METHODS: 266 CLL samples were analyzed with Affymetrix Human Mapping 6.0 arrays, comprising over 1,8 million probes with a median distance of less than 1 Kb. Copy number was inferred using the circulary binary segmentation (CBS) algorithm. Minimal common regions (MCR) were defined using a modified version of the algorithm by Lenz et al. (PNAS 2008), specifically altered to identify very small genomic losses covered by only 2-9 probes and occurring in at least 5% of the cases (mMCRs). mMCRs having 100% overlap with known copy number variations were discarded. RESULTS: mMCRs occurred in 75 known genes. The most commonly affected genes were CDC73 (cell division 73; 63% of the cases, 3 probes), RREB1 (ras responsive element binding protein 1; 60%, 5 probes), JAK2 (47%, 8 probes), CCDC88A (AKT-phosphorylation enhancer,; 47%, 3 probes), AKT3 (43%, 4 probes). Other affected genes at a lower frequency were PIK3CA (26%), EGFR (25%), XRCC4 (18%), JAK1 (18%), PTPRK (15%), RB1 (14%), ERBB2 (10%), PDGFRA (8%), FHIT (7%). A functional analysis performed with DAVID 2008 (http://david.abcc.ncifcrf.gov/) identified the terms “anti-oncogene” and “tyrosine-protein kinase” and five KEGG (http://www.genome.jp/kegg/) pathways (“prostate cancer”, “non-small cell lung cancer”, “pancreatic cancer”, “endometrial” cancer”) as enriched among the 75 genes with a statistically significant p-value <0.05 after Benjamini multiple test correction. Besides tumor suppressor genes such as RB1 and FHIT, very interestingly, many of the genes appeared to code for kinases and for oncogenes. The mMCRs occurred in intronic regions, and apparently targeted highly conserved regions. These regions might represent regulatory loci and their loss may cause gene activation. Validation of selected genes is on-going. CONCLUSIONS: The application of high resolution arrays on a large series of CLL samples has shown frequent small interstitial deletions targeting a discrete number of genes, highly enriched for transcripts coding for kinases. A potential mechanism of action might be the loss of regulatory regions determining gene activation. Once validated, the current data would provide the basis to explore the rationale for the use of kinase inhibitors in the treatment of CLL. Disclosures: No relevant conflicts of interest to declare.


2013 ◽  
Vol 133 (5) ◽  
pp. 535-545 ◽  
Author(s):  
Pawel Borun ◽  
Lukasz Kubaszewski ◽  
Tomasz Banasiewicz ◽  
Jaroslaw Walkowiak ◽  
Marzena Skrzypczak-Zielinska ◽  
...  

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 2491-2491
Author(s):  
Daniel Dworkis ◽  
Paola Sebastiani ◽  
Efthymia Melista ◽  
Jason Parente ◽  
Griffin Lester ◽  
...  

Abstract Fetal hemoglobin (HbF) can inhibit the polymerization of sickle hemoglobin, and the HbF level is an important modulator of the severity and course of sickle cell anemia. Genetic regulation of HbF levels is complex and under active investigation. Although multiple quantitative trait loci have been discovered, it is estimated that half of the genetic variance of HbF levels remains unaccounted for. Genomic copy number variations (CNVs), defined as inherited duplications or deletions of kilo-to mega-base lengths of DNA, represent a significant source of genetic heterogeneity among humans that might be involved in HbF regulation. Additionally, CNVs can significantly alter assumptions about genotype frequencies in their genomic region, and are therefore important to locate for multiple types of genetic association studies. Here, we present a novel method for the high-resolution discovery of CVNs related to HbF levels in sickle cell anemia, using genome-wide association study (GWAS) data. We used the Illumina 610K single nucleotide polymorphism (SNP) genotyping array to examine 727 adult subjects with sickle cell anemia, with or without a thalassemia, who were enrolled in the Cooperative Study of Sickle Cell Disease (CSSCD; aged 18 to 69 years, mean age 31 years; 44% male; not on hydroxyurea therapy). The Illumina array consisted of ~610K probes spread across the entire genome. At each locus, the relative amount of DNA detected was compared to a reference and expressed as the log R ratio score (LRR). Normal diploid regions of DNA have LRRs close to zero, whereas regions with CNVs have LRRs that are either higher for areas of duplication or lower for areas of deletion. Using LRR information in the context of a GWAS, we developed a novel, two-step signal-processing technique that combines CNV discovery with subsequent phenotypical association analysis. First, the distribution of LRR values at each locus is stratified using a +/− 1.5 standard deviation band-pass filter. This created three groups: a central major group comprised of people with diploid amounts of DNA, and two minor variant groups, one composed of people with elevated LRRs, suggesting &gt;2 DNA copies, and one of people with decreased LRRs, suggesting &lt;2 DNA copies at that locus. To reduce noise, loci without at least one minor group containing &gt;5% of the sample were excluded from further analysis. In the second step, a two-sample Student’s t-test was used at each locus to examine the variation in distributions of HbF between the major, diploid group and any variant groups with &gt;5% of the population. Using this method, we examined chromosomes 2, 6, and 11, which include regions known to modulate HbF in patients with sickle cell anemia, individuals with β thalassemia, and in the normal population. We successfully detected multiple clear duplications and deletions (approx. 1 per 6–22 mbp, depending on the chromosome) that showed typical CNV LRR distributions with &gt;10% of the population exhibiting the polymorphism. Several of these were mildly related to HbF levels (p&lt;0.05), including deletions in ASB1 on chromosome 2, and HACE1 on chromosome 6, both ankyrin motif containing proteins involved in the ubiquitin ligase system, as well as an upstream duplication and intragenic deletion involving HLA-DRB5 on chromosome 6. None of these clear CNVs, however, overlapped regions known to affect HbF concentration. Additional potential CNVs were detected throughout each chromosome, many exhibiting atypical LRR distributions not easily classified as either a normal diploid or clear CNV region. Further studies are required to confirm the presence of a CNV at these atypical loci. With this method, we were able to detect CNVs and CNV breakpoints across a population with a single-probe resolution, to within &lt;1kb in some cases. This resolution offers a distinct advantage over other detection methods that utilize a multiple-probe, sliding-window approach to detect LRR deviations in an individual sample. In conclusion, this two-step method of high-resolution detection of CNVs followed by analysis of phenotypical associations shows promise for explaining variations in expressed protein levels, such as those typical of HbF in sickle cell anemia, and possibly for future exploration of differences in HbF responses to therapeutics in sickle cell anemia.


2014 ◽  
Vol 13 ◽  
pp. CIN.S19519 ◽  
Author(s):  
Oscar Krijgsman ◽  
Christian Benner ◽  
Gerrit A. Meijer ◽  
Mark A. van de Wiel ◽  
Bauke Ylstra

In order to identify somatic focal copy number aberrations (CNAs) in cancer specimens and to distinguish them from germ-line copy number variations (CNVs), we developed the software package FocalCall. FocalCall enables user-defined size cutoffs to recognize focal aberrations and builds on established array comparative genomic hybridization segmentation and calling algorithms. To distinguish CNAs from CNVs, the algorithm uses matched patient normal signals as references or, if this is not available, a list with known CNVs in a population. Furthermore, FocalCall differentiates between homozygous and heterozygous deletions as well as between gains and amplifications and is applicable to high-resolution array and sequencing data. AVAILABILITY AND IMPLEMENTATION: FocalCall is available as an R-package from: https://github.com/OscarKrijgsman/focalCall . The R-package will be available in Bioconductor.org as of release 3.0.


2016 ◽  
Vol 38 (9) ◽  
pp. 775-785 ◽  
Author(s):  
Megha N. Murthy ◽  
Avinash M. Veerappa ◽  
Keshava B. Seshachalam ◽  
Nallur B. Ramachandra

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