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.

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)].

Dataset Information

Robust molecular subgrouping and copy-number profiling of medulloblastoma from small amounts of archival tumour material using high-density DNA methylation arrays.

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