Evaluation of the quality of RNA extracted from archival FFPE glioblastoma and epilepsy surgical samples for gene expression assays

Abstract

<jats:sec><jats:title>Aims</jats:title><jats:p>Histopathological tissue samples are being increasingly used as sources of nucleic acids in molecular pathology translational research. This study investigated the suitability of glioblastoma and control central nervous system (CNS) formalin-fixed paraffin embedded (FFPE) tissue-derived RNA for gene expression analyses.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Total RNA was extracted from control (temporal lobe resection tissue) and glioblastoma FFPE tissue samples. RNA purity (260/280 ratios) was determined and RNA integrity number (RIN) analysis was performed. RNA was subsequently used for RT-qPCR for two reference genes, <jats:italic>18S</jats:italic> and <jats:italic>GAPDH</jats:italic>.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Reference gene expression was equivalent between control and glioblastoma tissue when using RNA extracted from FFPE tissue, which has key implications for biological normalisation for CNS gene expression studies. There was a significant difference between the mean RIN values of control and glioblastoma FFPE tissue. There was no significant correlation between 260/280 or RIN values versus total RNA yield. The age of the tissue blocks did not influence RNA yield, fragmentation or purity. There was no significant correlation between RIN or 260/280 ratios and mean qPCR cycle threshold for either reference gene.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>This study showed that routinely available CNS FFPE tissue is suitable for RNA extraction and downstream gene expression studies, even after 60 months of storage. Substantial RNA fragmentation associated with glioblastoma and control FFPE tissue blocks did not preclude downstream RT-qPCR gene expression analyses. Cross validation with both archival and prospectively collated FFPE specimens is required to further demonstrate that CNS tissue blocks can be used in novel translational molecular biomarker studies.</jats:p></jats:sec>

Analysis of RNA Interference (RNAi) Biopesticides: Double-Stranded RNA (dsRNA) Extraction from Agricultural Soils and Quantification by RT-qPCR

“…We first investigated the impact of inhibitory substances in soil solutions on dsRNA quantification by RT-qPCR by comparing quantification metrics in the presence and absence of soil components. In the absence of any inhibitory compounds, we successfully quantified dsRNA at concentrations as low as 10 –2 ng/L (the lowest dsRNA concentration tested) (Figure A), corresponding to 36 copies per reaction and consistent with values reported in other RT-qPCR studies (4–4000 copies/reaction). , At this dsRNA concentration, the mean Ct was 38.2 (Figure A), below the typical upper limit of Ct (∼40) for detection and quantification. , Across all dsRNA concentrations tested, the maximum range of Ct ( R Ct ) was 1.2 (Figure A), which is comparable with previous studies. , We then assessed the inhibition of inhibitory substances in soil on RT-qPCR. Here, we used soil solutions of fine sandy loam soil rather than that of silty clay loam soil because the former soil solutions had higher UV absorbance at 230 nm (Figure S2), suggesting higher organic matter content.…”

“…37,38 Across all dsRNA concentrations tested, the maximum range of Ct (R Ct ) was 1.2 (Figure 1A), which is comparable with previous studies. 39,40 We then assessed the inhibition of inhibitory substances in soil on RT-qPCR. Here, with fine sandy loam soil.…”

Gene Expression Studies in Formalin-Fixed Paraffin-Embedded Samples of Cutaneous Cancer: The Need for Reference Genes

“…Fixation and paraffin embedding of the tissue influence both the yield and quality of RNA [22,34,35], especially when archival FFPE tissue is used, where storage and conservation conditions are unknown. There is no method that is easily capable of accurately assessing the quality of these types of samples.…”

Real‐life data from standardized preanalytical coding (SPREC) in tissue biobanking and its dual use for sample characterization and process optimization

“…Additionally, we are aware that particularly FIT might further vary if specimens from external medical departments are collected via long‐distance transportation or the postal system. Our study also did not systematically investigate biological parameters such as RIN values [ 32 ], phosphoprotein amounts [ 33 ], or hypoxia‐induced factors [ 16 , 34 ] as known actionable biomarkers for preanalytic research. An outreach to other biobanks and Institutes of Pathology in a multicentric way is warranted to develop a picture close to routine healthcare processes.…”