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      mRNA transcript quantification in archival samples using multiplexed, color-coded probes

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          Abstract

          Background

          A recently developed probe-based technology, the NanoString nCounter™ gene expression system, has been shown to allow accurate mRNA transcript quantification using low amounts of total RNA. We assessed the ability of this technology for mRNA expression quantification in archived formalin-fixed, paraffin-embedded (FFPE) oral carcinoma samples.

          Results

          We measured the mRNA transcript abundance of 20 genes ( COL3A1, COL4A1, COL5A1, COL5A2, CTHRC1, CXCL1, CXCL13, MMP1, P4HA2, PDPN, PLOD2, POSTN, SDHA, SERPINE1, SERPINE2, SERPINH1, THBS2, TNC, GAPDH, RPS18) in 38 samples (19 paired fresh-frozen and FFPE oral carcinoma tissues, archived from 1997-2008) by both NanoString and SYBR Green I fluorescent dye-based quantitative real-time PCR (RQ-PCR). We compared gene expression data obtained by NanoString vs. RQ-PCR in both fresh-frozen and FFPE samples. Fresh-frozen samples showed a good overall Pearson correlation of 0.78, and FFPE samples showed a lower overall correlation coefficient of 0.59, which is likely due to sample quality. We found a higher correlation coefficient between fresh-frozen and FFPE samples analyzed by NanoString (r = 0.90) compared to fresh-frozen and FFPE samples analyzed by RQ-PCR (r = 0.50). In addition, NanoString data showed a higher mean correlation (r = 0.94) between individual fresh-frozen and FFPE sample pairs compared to RQ-PCR (r = 0.53).

          Conclusions

          Based on our results, we conclude that both technologies are useful for gene expression quantification in fresh-frozen or FFPE tissues; however, the probe-based NanoString method achieved superior gene expression quantification results when compared to RQ-PCR in archived FFPE samples. We believe that this newly developed technique is optimal for large-scale validation studies using total RNA isolated from archived, FFPE samples.

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          Most cited references12

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          Direct multiplexed measurement of gene expression with color-coded probe pairs.

          We describe a technology, the NanoString nCounter gene expression system, which captures and counts individual mRNA transcripts. Advantages over existing platforms include direct measurement of mRNA expression levels without enzymatic reactions or bias, sensitivity coupled with high multiplex capability, and digital readout. Experiments performed on 509 human genes yielded a replicate correlation coefficient of 0.999, a detection limit between 0.1 fM and 0.5 fM, and a linear dynamic range of over 500-fold. Comparison of the NanoString nCounter gene expression system with microarrays and TaqMan PCR demonstrated that the nCounter system is more sensitive than microarrays and similar in sensitivity to real-time PCR. Finally, a comparison of transcript levels for 21 genes across seven samples measured by the nCounter system and SYBR Green real-time PCR demonstrated similar patterns of gene expression at all transcript levels.
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            Thirteen Ways to Look at the Correlation Coefficient

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              Determinants of RNA Quality from FFPE Samples

              The large archives of formalin-fixed paraffin-embedded (FFPE) tissue specimens that exist are a highly valuable source of sample material for molecular biological analysis, including gene expression profiling. However, current data on adverse effects of standard pathological practice on the usefulness of biomolecular analytes obtained from such archived specimens is largely anecdotal. Here, we present a systematic examination of the most relevant parameters for integrity and useability of RNA obtained from FFPE samples, including storage time and conditions, fixation time, and specimen size. The results are particularly relevant for any application relying on cDNA synthesis as an initial step of the procedure, such as RT-PCR, and microarray analysis.
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                Author and article information

                Journal
                BMC Biotechnol
                BMC Biotechnology
                BioMed Central
                1472-6750
                2011
                9 May 2011
                : 11
                : 46
                Affiliations
                [1 ]Division of Applied Molecular Oncology, Princess Margaret Hospital, Ontario Cancer Institute, University Health Network, Toronto, ON, Canada
                [2 ]Dept. of Computer Science, University of Toronto, Toronto, ON, Canada
                [3 ]Ontario Cancer Institute and the Campbell Family Institute for Cancer Research, Toronto, ON, Canada
                [4 ]Dept. of Medical Biophysics, University of Toronto, Toronto, ON, Canada
                [5 ]Dept. of Biostatistics, Princess Margaret Hospital, Ontario Cancer Institute, University Health Network, Toronto, ON, Canada
                [6 ]Dept. of Pathology, Toronto General Hospital, Ontario Cancer Institute, Toronto, ON, Canada
                [7 ]Dept. of Otolaryngology/Surgical Oncology, Princess Margaret Hospital, Ontario Cancer Institute, University Health Network, Toronto, ON, Canada
                [8 ]Dept. of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
                Article
                1472-6750-11-46
                10.1186/1472-6750-11-46
                3103428
                21549012
                89ad0313-e564-4fe3-8879-038bddaa0c75
                Copyright ©2011 Reis et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 January 2011
                : 9 May 2011
                Categories
                Methodology Article

                Biotechnology
                Biotechnology

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