Optimized Biobanking Procedures for Preservation of RNA in Tissue: Comparison of Snap-Freezing and RNAlater-Fixation Methods
BIOPRESERVATION AND BIOBANKING
Authors: Hentze, Julie L.; Kringelbach, Tina M.; Novotny, Guy W.; Hamid, Bushra H.; Ravn, Vibeke; Christensen, Ib J.; Hogdall, Claus; Hogdall, Estrid
Abstract
Introduction: Personalized treatment, supported by biomarkers, would improve survival of ovarian cancer patients. RNA molecules are potentially important biomarkers. The Danish CancerBiobank provides an infrastructure for handling and storage of biological material, including RNA, from Danish cancer patients. The aim of this study was to investigate the effects of handling-time and fresh-freezing versus RNAlater (R) fixation on RNA degradation in solid tissue from pelvic mass samples. Materials and Methods: We evaluated RNA quality in surgical tissue from patients with a pelvic mass. Corresponding samples were either fresh-frozen or fixed in RNAlater, at eight different time points after the surgery. Integrity was measured using a bioanalyzer, and the amount and quality were further investigated by quantitative reverse transcription-polymerase chain reaction measuring the expression of housekeeping genes B2M and HPRT1. Results: Our results show that tissue RNA is stable up to at least 180 minutes after the surgery, as the quality was comparable to the quality of RNA handled immediately. Likewise, patient RNA was of acceptable quality after both fresh-frezing and RNAlater fixation, but RNAlater fixation was slightly more effective for RNA preservation. Discussion and Conclusion: Our data suggest that RNA in pelvic mass samples is relatively stable. Knowledge about RNA stability is an important prerequisite for research in RNA biomarkers, where the challenge is to balance the need for careful RNA handling and storage with the need for effective large-scale biobanking in a busy clinical setting where patient treatment is the main priority.
Reference genes for valid gene expression studies on rat dental, periodontal and alveolar bone tissue by means of RT-qPCR with a focus on orthodontic tooth movement and periodontitis
ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER
Authors: Kirschneck, Christian; Proff, Peter; Fanghaenel, Jochen; Wolf, Michael; Roldan, J. Camilo; Roemer, Piero
Abstract
Objectives: To obtain valid results in relative gene/mRNA-expression analyses by RT-qPCR, a careful selection of stable reference genes is required for normalization. Currently there is little information on reference gene stability in dental, periodontal and alveolar bone tissues of the rat, especially regarding orthodontic tooth movement and periodontitis. We therefore aimed to identify the best selection and number of reference genes under these experimental as well as physiological conditions. Materials and methods: In 7 male Fischer344-rats the upper left first and second molars were moved orthodontically for 2 weeks and in 7 more animals additionally subjected to an experimental periodontitis, whereas 7 animals were left untreated. Tissue samples of defined size containing both molars (without crowns) as well as the adjacent periodontal and alveolar bone tissue were retrieved and RNA extracted for RT-qPCR analyses. Nine candidate reference genes were evaluated and ranked according to their expression stability by 4 different algorithms (geNorm, NormFinder, BestKeeper, comparative Delta C-q). Results: PPIB/YWHAZ were the most stabile reference genes for the combined dental, periodontal and alveolar bone tissue of the rat overall, in untreated animals and rats with additional periodontitis, whereas PPIB/B2M performed best in orthodontically treated rats with YWHAZ ranking third. Gene-stability ranking differed considerably between investigated groups. A combination of two reference genes was found to be sufficient for normalization in all cases. Conclusions: The substantial differences in expression stability emphasize the need for valid reference genes, when aiming for meaningful results in relative gene expression analyses. Our results should enable researchers to optimize gene expression analysis in future studies by choosing the most suitable reference genes for normalization. (C) 2015 Published by Elsevier GmbH.