Project description:High-resolution microarray-based whole genome genotyping (WGG) techniques based on SNP analysis have successfully been applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Problems in data interpretation arise when WGG is applied on tumor tissue specimens, in which normal cell components and tumor subpopulations frequently exist. Such heterogeneity may lead to reduced detection of cancer cell specific genomic alterations. To circumvent problems with sample heterogeneity, we propose using a segmentation strategy derived from DNA copy number analysis for detection of LOH and allelic imbalance. We generated an experimental dilution series of a tumor cell line mixed with its paired normal cell line and simulated data for such dilutions to test the strategy. We also used data sets generated on both Affymetrix and Illumina WGG platforms, including paired tumor-normal samples and tumors previously characterized by FISH. We tested the segmentation strategy against several reported algorithms. We demonstrate high sensitivity and specificity of the segmentation strategy for detecting both minute and gross allelic imbalances originating from DNA copy number gain, loss, and neutral events in tumor specimens. For example, hemizygous copy number loss can be detected in samples containing only 20-25% tumor cells. Furthermore, the strategy can identify cell subpopulation specific events and accurately estimate the fraction of cells affected by an allelic imbalance. Thus, the segmentation strategy extends the usefulness of WGG platforms for investigation of allelic imbalances in heterogeneous tumor genomes.
Project description:We describe a method for automatic detection of absolute segmental copy numbers and genotype status in complex cancer genome profiles measured by SNP arrays. The method is based on pattern recognition of segmented and smoothed copy number and allelic imbalance profiles. Overall copy number assignments were verified by DNA indexes of breast carcinomas and karyotypes of cell lines. The method performs well even for poor quality data, low tumor content, and highly rearranged tumor genomes.
Project description:We describe a method for automatic detection of absolute segmental copy numbers and genotype status in complex cancer genome profiles measured by SNP arrays. The method is based on pattern recognition of segmented and smoothed copy number and allelic imbalance profiles. Overall copy number assignments were verified by DNA indexes of breast carcinomas and karyotypes of cell lines. The method performs well even for poor quality data, low tumor content, and highly rearranged tumor genomes. To investigate the efficiency of the method 19 primary breast carcinoma samples and 2 breast cancer cell lines were analyzed using 300K Illumina SNP arrays (Illumina HumanHap300-Duov2 Genotyping BeadChip)
Project description:Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross-platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy-number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform-specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large-scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested.
Project description:Genome-wide copy number analysis using SNP-arrays (OncoScans) in multinodular goitres from individuals with the c.1552G>A;p.E518K mutation in DGCR8 show allelic imbalance at Chr22 in all samples. Likewise this event is confirmed in papillary thyroid tumors harboring the same alteration somatically. The only alteration common in all MNG and FvPTC samples was the allelic imbalance at the Chr22 in line with all samples showing an homozygous genotype at the DGCR8 locus
Project description:Near-haploid chromosome numbers have been found in less than 1% of cytogenetically reported tumors, but seem to be more common in certain neoplasms including the malignant cartilage-producing tumor chondrosarcoma. By a literature survey of published karyotypes from chondrosarcomas we could confirm that loss of chromosomes resulting in hyperhaploid-hypodiploid cells is common and that these cells may polyploidize. Sixteen chondrosarcomas were investigated by single nucleotide polymorphism (SNP) array and the majority displayed SNP patterns indicative of a hyperhaploid-hypodiploid origin, with or without subsequent polyploidization. Except for chromosomes 5, 7, 19, 20 and 21, autosomal loss of heterozygosity was commonly found, resulting from chromosome loss and subsequent duplication of monosomic chromosomes giving rise to uniparental disomy. Additional gains, losses and rearrangements of genetic material, and even repeated rounds of polyploidization, may affect chondrosarcoma cells resulting in highly complex karyotypes. Loss of chromosomes and subsequent polyploidization was not restricted to a particular chondrosarcoma subtype and, although commonly found in chondrosarcoma, binucleated cells did not seem to be involved in these events. Tumor DNA was hybridized onto Illumina Human Omni-Quad v1.0 BeadChip or Human CNV370-Quad v3.0 BeadChip (Illumina, San Diego, CA, USA), following standard protocols supplied by the manufacturer. Data were extracted from the GenomeStudio software (Illumina), and subsequently normalized and segmented using thresholded quantile normalization (tQN) and BAFsegmentation, respectively (Staaf et al. Normalization of array-CGH data: influence of copy number imbalances. BMC Genomics 2007, 8:382; Staaf et al. Segmentation-based detection of allelic imbalance and loss-of-heterozygosity in cancer cells using whole genome SNP arrays. Genome Biol 2008, 9:R136). Base pair positions are indicated according to the NCBI build 36 (hg18).
Project description:Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross-platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy-number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform-specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large-scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested. 10 chronic lymphocytic leukemia (CLL) samples was analyzed using four different high-resolution platforms: 32K BAC arrays, 185K Agilent oligonucleotide arrays, 250K Affymetrix SNP arrays and 317K Illumina SNP arrays.
Project description:Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples. We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illumina’s proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the normalization strategy using 535 individual hybridizations from 10 data sets from the analysis of cancer genomes and normal blood samples generated on Illumina Infinium II 300k version 1 and 2, 370k and 550k BeadChips. We show that the proposed normalization strategy successfully removes asymmetry in estimates of both allelic proportions and copy numbers. Additionally, the normalization strategy reduces the technical variation for copy number estimates while retaining the response to copy number alterations. The proposed normalization strategy represents a valuable low-level analysis tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies.
Project description:Renal tumors with complex morphology require extensive workup for accurate classification. Chromosomal aberrations that define subtypes of renal epithelial neoplasms have been reported. We explored if whole-genome chromosome copy number and loss-of-heterozygosity analysis with single nucleotide polymorphism (SNP) arrays can be used to identify these aberrations. Keywords: Chromosome copy number and LOH analysis with SNP Genotyping Arrays
Project description:SNP arrays was combined with next generation sequencing (NGS) to identify an LOH in 16q together with an unreported CTCF missense variant in its zinc finger domain. CTCF is within 16q LOH. We found that germline heterozygous variant I446K became homozygous in the tumor due to a loss of heterozygosity rearrangement affecting the whole q arm on chromosome 16. Based on CTCF role in regulating the epigenetic architechture of the genome, our findings reveal CTCF variant I446K as a link between MRD21 and Wilms tumor predisposition.