Project description:Background: The main bottleneck for genomic studies of tumors is the limited availability of fresh frozen (FF) samples collected from patients, coupled with comprehensive long-term clinical follow-up. This shortage could be alleviated by using existing large archives of routinely obtained and stored Formalin-Fixed Paraffin-Embedded (FFPE) tissues. However, since these samples are partially degraded, their RNA sequencing is technically challenging. Results: In an effort to establish a reliable and practical procedure, we compared three protocols for RNA sequencing using pairs of FF and FFPE samples, both taken from the same breast tumor. In contrast to previous studies, we compared the expression profiles obtained from the two matched sample types, using the same protocol for both. Three protocols were tested on low initial amounts of RNA, as little as 100 ng, to represent the possibly limited availability of clinical samples. For two of the three protocols tested, poly(A) selection (mRNA-seq) and ribosomal-depletion, the total gene expression profiles of matched FF and FFPE pairs were highly correlated. For both protocols, differential gene expression between two FFPE samples was in agreement with their matched FF samples. Notably, although expression levels of FFPE samples by mRNA-seq were mainly represented by the 3'-end of the transcript, they yielded very similar results to those obtained by ribosomal-depletion protocol, which produces uniform coverage across the transcript. Further, focusing on clinically relevant genes, we showed that the high correlation between expression levels persists at higher resolutions. Conclusions: Using the poly(A) protocol for FFPE exhibited, unexpectedly, similar efficiency to the ribosomal-depletion protocol, with the latter requiring much higher (2-3 fold) sequencing depth to compensate for the relative low fraction of reads mapped to the transcriptome. The results indicate that standard poly(A)-based RNA sequencing of archived FFPE samples is a reliable and cost-effective alternative for measuring mRNA-seq on FF samples. Expression profiling of FFPE samples by mRNA-seq can facilitate much needed extensive retrospective clinical genomic studies.

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)].

Project description:This experiment contains the RNA-Seq samples only. Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for clinical research. However, nucleic acids extracted from FFPE tissues are fragmented and chemically modified making them challenging to use in molecular studies. We analysed 23 fresh-frozen (FF), 35 FFPE and 38 paired FF/FFPE specimens, representing six different human tissue types (bladder, prostate and colon carcinoma; liver and colon normal tissue; reactive tonsil) in order to examine the potential use of FFPE samples in next-generation sequencing (NGS) based retrospective and prospective clinical studies. Two methods for DNA and three methods for RNA extraction from FFPE tissues were compared and were found to affect nucleic acid quantity and quality. DNA and RNA from selected FFPE and paired FF/FFPE specimens were used for exome and transcriptome analysis. Preparations of DNA Exome-Seq libraries was more challenging (29.5 % success) than that of RNA-Seq libraries, presumably because of modifications to FFPE tissue-derived DNA. Libraries could still be prepared from RNA isolated from two-decade old FFPE tissues. Data were analysed using the CLC Bio Genomics Workbench and revealed systematic differences between FF and FFPE tissue-derived nucleic acid libraries. In spite of this, pairwise analysis of DNA Exome-Seq data showed concordance for 70-80 % of variants in FF and FFPE samples stored for fewer than three years. RNA-Seq data showed high correlation of expression profiles in FF/FFPE pairs (Pearson Correlations of 0.90 +/- 0.05), irrespective of storage time (up to 244 months) and tissue type. A common set of 1,494 genes was identified with expression profiles that were significantly different between paired FF and FFPE samples irrespective of tissue type. Our results are promising and suggest that NGS can be used to study FFPE specimens in both prospective and retrospective archive-based studies in which FF specimens are not available.

Project description:In the study of tumor genetics, formalin-fixed paraffin-embedded (FFPE) tumors are the most readily available tissue samples. While DNA derived from FFPE tissue has been validated for array comparative genomic hybridization (aCGH) application, the suitability of such fragmented DNA for single-nucleotide polymorphism (SNP) array analysis has not been well examined. Furthermore, whole-genome amplification (WGA) has been used in the study of small precursor lesions to produce sufficient amount of DNA for aCGH analysis. It is unclear whether the same approach can be extended to SNP analysis. In this study, we examined the utility and limitations of genotyping platform performed on whole-genome amplified DNA from FFPE tumor samples for both copy number and SNP analyses. We analyzed the results obtained using DNA derived from matched FFPE and frozen tissue samples on Affymetrix 250K Nsp SNP array. Two widely used WGA methods, Qiagen (isothermal protocol) and Sigma (thermocycling protocol), were used to determine how WGA methods affect the results. We found that the use of DNA derived from FFPE tumors (without or with WGA) for high-resolution SNP array application can produce a significant amount of false positive and false negative findings. While some of these misinterpretations appear to cluster in genomic regions with high or low GC contents, the majority appears to occur randomly. Only large-scale chromosome LOH (>10Mb) can be reliably detected from FFPE tumor DNA samples (without or with WGA) but not smaller LOH or copy number alterations. Our findings here indicate a need for caution in SNP array data interpretation when using FFPE tumor-derived DNA, particularly with WGA. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from cryopreserved and FFPE mesenchymal tumor samples without or with WGA, as well as genomic snap-frozen non-neoplastic tissue DNA from 5 adult individuals to serve as reference DNA. WGA was performed using the REPLI-g® FFPE kit (Qiagen, Valencia, CA, USA) and GenomePlex® Tissue Whole Genome Amplification WGA5 kit (Sigma, Saint Louis, MO, USA) in parallel in accordance with the manufacturers’ protocols. A two- to eight-hour individualized reaction time was used in the Qiagen platform for each sample. A gradient amount of initial DNA (10ng, 30ng, 60ng, 100ng and 150ng) was tested followed by gel electrophoresis and qualitative multiplex PCR assay to determine the quality of post-WGA products. At least four independent experiments were concurrently performed per template amplification. Four separateWGA reaction products were pooled for each sample for subsequent microarray analysis to minimize the amplification bias and allele dropout. One of the Affymetrix GeneChip® Human Mapping 500K Array Set (Nsp 250K SNP array) was used for genotyping analysis. Four gastrointestinal stromal tumors with known cytogenetic aberrations were included. Two cases were sucessfullly amplified and passed the quality tests. A total of 12 samples were compared between each other, including frozen tissue DNA (as reference), frozen tissue DNA with WGA (two platforms), FFPE tissue DNA, and FFPE tissue DNA with WGA (two platforms) from each case.

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.

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Optimizations of DNA isolation and copy number analysis identifies regions of genomic gain/loss in early breast cancer

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