Robust molecular subgrouping and copy-number profiling of medulloblastoma from small amounts of archival tumour material using high-density DNA methylation arrays.
Ontology highlight
ABSTRACT:
SUBMITTER: Hovestadt V
PROVIDER: S-EPMC3661908 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Soft tissue sarcomas (STS) often present a significant diagnostic challenge as many STS bear histologic resemblance, but are known to have very different clinical and biologic characteristics. Some STS subtypes are characterized by specific genetic abnormalities and this has helped in their classification, diagnosis and even treatment. However, a large majority of STS have no known specific genetic aberrations even though they almost always have highly aberrant karyotypes. We therefore hypothesize that the latter subgroup of STS bear genetic abnormalities that are sub-type specific, but as yet unidentified. High-resolution mapping of copy number aberrations in cancer genomes is a valuable way of identifying recurrent genomic changes that could be of pathogenetic significance. Traditionally, this has been done using high quality DNA obtained from fresh frozen tissue or cells and archived tissue is generally regarded as unsuitable because of the degradative effects of formalin fixation on DNA. Utility of archival tumour material for such molecular genetic analysis is vital, especially for rare cancers like STS but recent efforts to accomplish this have produced variable results. We therefore set out, in addition to optimize a protocol for obtaining genomic copy number data from formalin-fixed, paraffin-embedded (FFPE) STS material that is comparable to that from fresh frozen (FF) material. Microarray-based Comparative Genomic Hybridization (aCGH), a high- resolution, genome-wide method was used to identify somatic copy number aberrations (SCNAs) in primary STS samples (fresh frozen and archival FFPE), using an optimized protocol for labeling DNA. Findings were confirmed using Conventional Cytogenetics and Fluorescence in-situ Hybridization (FISH). Data obtained from paired samples (FF and FFPE) of the same tumours showed similar results and array results were consistently of good quality. On-going analysis of the recurrent SCNAs in combination with expression data and clinical correlates may serve to identify specific patterns that can serve as diagnostic markers, characterize subgroups with prognostic implication or identify potential therapeutic targets.
2015-07-24 | GSE39663 | GEO
Project description:Affymetrix U133 Plus 2.0 arrays were hybridized with varying amounts of starting material to determine whether different measurements of gene expression were observed. Keywords: Affymetrix starting material study
2006-07-25 | GSE3062 | GEO
Project description:Microarray data is subject to noise and systematic variation that negatively affects the resolution of copy number analysis. We describe Rawcopy, an R package for processing of Affymetrix CytoScan HD, CytoScan 750k and SNP 6.0 microarray raw intensities (CEL files). Noise characteristics of a large number of reference samples are used to estimate log ratio and B-allele frequency for total and allele-specific copy number analysis. Rawcopy achieves better signal-to-noise ratio and higher proportion of validated alterations than commonly used free and proprietary alternatives. In addition, Rawcopy visualizes each microarray sample for assessment of technical quality, patient identity and genome-wide absolute copy number states. Software and instructions are available at http://rawcopy.org.
| S-EPMC5086940 | biostudies-literature
Project description:Soft tissue sarcomas (STS) often present a significant diagnostic challenge as many STS bear histologic resemblance, but are known to have very different clinical and biologic characteristics. Some STS subtypes are characterized by specific genetic abnormalities and this has helped in their classification, diagnosis and even treatment. However, a large majority of STS have no known specific genetic aberrations even though they almost always have highly aberrant karyotypes. We therefore hypothesize that the latter subgroup of STS bear genetic abnormalities that are sub-type specific, but as yet unidentified. High-resolution mapping of copy number aberrations in cancer genomes is a valuable way of identifying recurrent genomic changes that could be of pathogenetic significance. Traditionally, this has been done using high quality DNA obtained from fresh frozen tissue or cells and archived tissue is generally regarded as unsuitable because of the degradative effects of formalin fixation on DNA. Utility of archival tumour material for such molecular genetic analysis is vital, especially for rare cancers like STS but recent efforts to accomplish this have produced variable results. We therefore set out, in addition to optimize a protocol for obtaining genomic copy number data from formalin-fixed, paraffin-embedded (FFPE) STS material that is comparable to that from fresh frozen (FF) material. Microarray-based Comparative Genomic Hybridization (aCGH), a high- resolution, genome-wide method was used to identify somatic copy number aberrations (SCNAs) in primary STS samples (fresh frozen and archival FFPE), using an optimized protocol for labeling DNA. Findings were confirmed using Conventional Cytogenetics and Fluorescence in-situ Hybridization (FISH). Data obtained from paired samples (FF and FFPE) of the same tumours showed similar results and array results were consistently of good quality. On-going analysis of the recurrent SCNAs in combination with expression data and clinical correlates may serve to identify specific patterns that can serve as diagnostic markers, characterize subgroups with prognostic implication or identify potential therapeutic targets. To identify common CNAs among LMS fresh and FFPE. 25 samples in total: 22 individual FFPE cases; 3 cases also obtained fresh. Reference DNA was obtained from same patient when possible, otherwise commercial genomic DNA was used [Promega® UK with Cat Nos. G1471 (male) and G1521 (female)].
2015-07-24 | E-GEOD-39663 | biostudies-arrayexpress
Project description:High-density SNP microarrays provide insight into the genomic events that occur in diseases like cancer through their capability to measure both LOH and genomic copy numbers. Where currently available methods are restricted to the use of fresh frozen tissue, we now describe the design and validation of copy number measurements using the Illumina BeadArray platform and the application of this technique to formalin-fixed, paraffin-embedded (FFPE) tissue. In fresh frozen tissue from a set of colorectal tumors with numerous chromosomal aberrations, our method measures copy number patterns that are comparable to values from established platforms, like Affymetrix GeneChip and BAC array-CGH. Moreover, paired comparisons of fresh frozen and FFPE tissues showed nearly identical patterns of genomic change. We conclude that this method enables the use of paraffin-embedded material for research into both LOH and numerical chromosomal abnormalities. These findings make the large pathological archives available for genomic analysis, which could be especially relevant for hereditary disease where fresh material from affected relatives is rarely available.
| S-EPMC1800928 | biostudies-literature
Project description:Affymetrix Human Gene 1.1 ST Array profiling of 285 primary medulloblastoma samples. Total RNA was extracted from primary medulloblastoma samples and hybridized to Affymetrix Human Gene 1.1 ST Arrays (24-Array Plates) according to the manufacturer's instructions.
| S-ECPF-GEOD-37382 | biostudies-other
Project description:Copy Number Alterations arrays from 21 patients and 24 samples performed by Affymetrix 6.0, Agilent 1M and Oncoscan CNV platforms
| EGAD00010001581 | EGA
Project description:BackgroundUsing whole exome sequencing to predict aberrations in tumours is a cost effective alternative to whole genome sequencing, however is predominantly used for variant detection and infrequently utilised for detection of somatic copy number variation.ResultsWe propose a new method to infer copy number and genotypes using whole exome data from paired tumour/normal samples. Our algorithm uses two Hidden Markov Models to predict copy number and genotypes and computationally resolves polyploidy/aneuploidy, normal cell contamination and signal baseline shift. Our method makes explicit detection on chromosome arm level events, which are commonly found in tumour samples. The methods are combined into a package named ADTEx (Aberration Detection in Tumour Exome). We applied our algorithm to a cohort of 17 in-house generated and 18 TCGA paired ovarian cancer/normal exomes and evaluated the performance by comparing against the copy number variations and genotypes predicted using Affymetrix SNP 6.0 data of the same samples. Further, we carried out a comparison study to show that ADTEx outperformed its competitors in terms of precision and F-measure.ConclusionsOur proposed method, ADTEx, uses both depth of coverage ratios and B allele frequencies calculated from whole exome sequencing data, to predict copy number variations along with their genotypes. ADTEx is implemented as a user friendly software package using Python and R statistical language. Source code and sample data are freely available under GNU license (GPLv3) at http://adtex.sourceforge.net/.
| S-EPMC4162913 | biostudies-literature
Project description:Copy number alterations(CNAs) are the most common genetic changes observed in many cancers, reflecting the innate chromosomal instability of this disorder. Yet, how these alterations affect gene function to promote metastases across different tumor types has not been established. In this study, we developed a pan-cancer metastasis potential score (panMPS) based on observed CNAs. panMPS predicts metastasis and metastasis-free survival in cohorts of patients with prostate cancer, triple negative breast cancer and lung adenocarcinoma, and overall survival in the Metabric breast cancer cohort and three cohorts from The Cancer Genome Atlas (TCGA), including prostate, breast and lung adenocarcinoma. These CNAs are present in cell lines of metastatic tumors from eight different origins, reflected by an elevated panMPS for all cell lines. Many copy number alterations involve large chromosomal segments that encompass multiple genes ("clumps"). We show that harnessing this structural information to select only one gene per clump captures the contributions of other genes within the clump, resulting in a robust predictor of metastasis outcome. These sets of selected genes are distinct from cancer drivers that undergo mutation, and in fact, metastasis-related functions have been published for over half of them.
| S-EPMC5931251 | biostudies-literature
Project description:Systematic tumour profiling is essential for biomarker research and clinically for assessing response to therapy. Solving the challenge of delivering informative copy number (CN) profiles from formalin-fixed paraffin embedded (FFPE) material, the only likely readily available biospecimen for most cancers, involves successful processing of small quantities of degraded DNA. To investigate the potential for analysis of such lesions, whole-genome CNVseq was applied to 300 FFPE primary tumour samples, obtained from a large-scale epidemiological study of melanoma. The quality and the discriminatory power of CNVseq was assessed. Libraries were successfully generated for 93% of blocks, with input DNA quantity being the only predictor of success (success rate dropped to 65% if <20 ng available); 3% of libraries were dropped because of low sequence alignment rates. Technical replicates showed high reproducibility. Comparison with targeted CN assessment showed consistency with the Next Generation Sequencing (NGS) analysis. We were able to detect and distinguish CN changes with a resolution of ≤10 kb. To demonstrate performance, we report the spectrum of genomic CN alterations (CNAs) detected at 9p21, the major site of CN change in melanoma. This successful analysis of CN in FFPE material using NGS provides proof of principle for intensive examination of population-based samples.
| S-EPMC6586881 | biostudies-literature