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Straightforward and sensitive RT-qPCR based gene expression analysis of FFPE samples.

ABSTRACT: Fragmented RNA from formalin-fixed paraffin-embedded (FFPE) tissue is a known obstacle to gene expression analysis. In this study, the impact of RNA integrity, gene-specific reverse transcription and targeted cDNA preamplification was quantified in terms of reverse transcription polymerase chain reaction (RT-qPCR) sensitivity by measuring 48 protein coding genes on eight duplicate cultured cancer cell pellet FFPE samples and twenty cancer tissue FFPE samples. More intact RNA modestly increased gene detection sensitivity by 1.6 fold (earlier detection by 0.7 PCR cycles, 95% CI = 0.593-0.850). Application of gene-specific priming instead of whole transcriptome priming during reverse transcription further improved RT-qPCR sensitivity by a considerable 4.0 fold increase (earlier detection by 2.0 PCR cycles, 95% CI = 1.73-2.32). Targeted cDNA preamplification resulted in the strongest increase of RT-qPCR sensitivity and enabled earlier detection by an average of 172.4 fold (7.43 PCR cycles, 95% CI = 6.83-7.05). We conclude that gene-specific reverse transcription and targeted cDNA preamplification are adequate methods for accurate and sensitive RT-qPCR based gene expression analysis of FFPE material. The presented methods do not involve expensive or complex procedures and can be easily implemented in any routine RT-qPCR practice.

SUBMITTER: Zeka F

PROVIDER: S-EPMC4761903 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Straightforward and sensitive RT-qPCR based gene expression analysis of FFPE samples.

Zeka Fjoralba F Vanderheyden Katrien K De Smet Els E Cuvelier Claude A CA Mestdagh Pieter P Vandesompele Jo J

Scientific reports 20160222

Fragmented RNA from formalin-fixed paraffin-embedded (FFPE) tissue is a known obstacle to gene expression analysis. In this study, the impact of RNA integrity, gene-specific reverse transcription and targeted cDNA preamplification was quantified in terms of reverse transcription polymerase chain reaction (RT-qPCR) sensitivity by measuring 48 protein coding genes on eight duplicate cultured cancer cell pellet FFPE samples and twenty cancer tissue FFPE samples. More intact RNA modestly increased g ...[more]

PMID: 26898768

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Project description:BackgroundRT-qPCR is routinely used in expression profiling of toxicity pathway genes. However, genetic and molecular level studies used to determine, understand and clarify potential risks of engineered nanomaterials (ENMs) are still incomplete. Concerns regarding possible interference caused by intracellular ENMs during analyses have been raised. The aim of this study was to verify a qPCR procedure for gene expression assays, which can be used in toxicity and exposure assessments.ResultsAmplification of ten reference genes was performed to test the expression stability. A preliminary study was performed on RNA from BEAS-2B cells that had been treated with AuNPs. Also, a reference total RNA standard from ten cell lines was spiked with various amounts of the same AuNP. This treatment mimics exposure assessment studies, where assay-interference may be caused by intracellular residual ENMs still being present in the biological samples (during and after isolation/purification procedures). Both types of RNA samples were reverse transcribed and then amplified by qPCR. The qPCR-related software and statistical programs used included BestKeeper, NormFinder, REST and qBase+. These results proved that using standard qPCR analysis and statistical programs should not be the only procedure applied to verify the assay for gene expression assessment related to ENMs. A comparison of SYBR Green to EVA Green was discussed, in addition to a comparison to the latest reports regarding the influence of ENM thermal conductivity, surface interactions with ENMs, effects of ENM size and charge, as well as, the limit of detection in a qPCR assay.ConclusionsAuNPs have the potential to interfere with the assay mechanism of RT-qPCR, thus, assay verification is required for AuNP-related gene expression studies used to evaluate toxicity. It is recommended to use HSP90 and YWHAZ as reference genes, i.e. these were the most stable in our study, irrespective of the source of the RNA, or, the point at which the AuNPs interacted with the assay. This report describes steps that can be utilised to generate a suitable method for gene expression studies associated with toxicity testing of various ENMs. For example, RNA standards that have been spiked with known amounts of ENMs should be run in conjunction with the unknown samples, in order to verify any RT-qPCR assay and determine the degree of error.

Project description:Cutaneous T-cell lymphomas (CTCLs) are a heterogeneous group of malignancies with courses ranging from indolent to potentially lethal. We recently studied in a 157 patient cohort gene expression profiles generated by the TruSeq targeted RNA gene expression sequencing. We observed that the sequencing library quality and depth from formalin-fixed paraffin-embedded (FFPE) skin samples were significantly lower when biopsies were obtained prior to 2009. We also observed that the fresh CTCL samples clustered together, even though they included stage I-IV disease. In this study, we compared TruSeq gene expression patterns in older (≤2008) vs. more recent (≥2009) FFPE samples to determine whether these clustering analyses and earlier described differentially expressed gene findings are robust when analyzed based on the year of biopsy. We also explored biases found in FFPE samples when subjected to the TruSeq analysis of gene expression. Our results showed that ≤2008 and ≥2009 samples clustered equally well to the full data set and, importantly, both analyses produced nearly identical trends and findings. Specifically, both analyses enriched nearly identical DEGs when comparing benign vs. (1) stage I-IV and (2) stage IV (alone) CTCL samples. Results obtained using either ≤2008 or ≥2009 samples were strongly correlated. Furthermore, by using subgroup analyses, we were able to identify additional novel differentially expressed genes (DEGs), which did not reach statistical significance in the prior full data set analysis. Those included CTCL-upregulated BCL11A, SELL, IRF1, SMAD1, CASP1, BIRC5, and MAX and CTCL-downregulated MDM4, SERPINB3, and THBS4 genes. With respect to sample biases, no matter if we performed subgroup analyses or full data set analysis, fresh samples tightly clustered together. While principal component analysis revealed that fresh samples were spatially closer together, indicating some preprocessing batch effect, they remained in the proximity to other normal/benign and FFPE CTCL samples and were not clustering as outliers by themselves. Notably, this did not affect the determination of DEGs when analyzing ≥2009 samples (fresh and FFPE biopsies) vs. ≥2009 FFPE samples alone.

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Straightforward and sensitive RT-qPCR based gene expression analysis of FFPE samples.

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Straightforward and sensitive RT-qPCR based gene expression analysis of FFPE samples.

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