For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
16
views
22
references
 Top references
cited by
3
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
1 collections
    0
    shares
      193
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Selection of reference genes suitable for normalization of RT-qPCR data in glioma stem cells

      research-article

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Considering the importance of gene expression studies for understanding the biology of glioma stem cells (GSCs), we aimed to identify the reliable reference genes in GSCs that were derived from the glioma cell lines T98G, LN229, 090116 and 091214. Quantitative real-time reverse-transcription PCR was employed using 11 reference genes identified through a PubMed literature search, and the assessment of stability through the geNorm, Normfinder and coefficient of variation methods was performed to select suitable reference genes. We found that HPRT1 and RPL13A were the most suitable reference genes, and validated the geometric mean of these genes to normalize the expression of stemness genes by GSCs. Therefore, it is necessary to select novel cell-specific reference genes with greater expression stability for gene expression studies in GSCs.

          METHOD SUMMARY

          We employed the geNorm, Normfinder and coefficient of variation methods to identify novel reference genes, with greater expression stability in glioma stem cells, for the study of gene expression.

          Graphical abstract

          Most cited references22

          • Record: found
          • Abstract: found
          • Article: not found

          Real-time PCR for mRNA quantitation

          Marisa Wong, Juan F Medrano (2005)
          Real-time PCR has become one of the most widely used methods of gene quantitation because it has a large dynamic range, boasts tremendous sensitivity, can be highly sequence-specific, has little to no post-amplification processing, and is amenable to increasing sample throughput. However, optimal benefit from these advantages requires a clear understanding of the many options available for running a real-time PCR experiment. Starting with the theory behind real-time PCR, this review discusses the key components of a real-time PCR experiment, including one-step or two-step PCR, absolute versus relative quantitation, mathematical models available for relative quantitation and amplification efficiency calculations, types of normalization or data correction, and detection chemistries. In addition, the many causes of variation as well as methods to calculate intra- and inter-assay variation are addressed.
          Article 0 comments Cited 435 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Accurate and objective copy number profiling using real-time quantitative PCR.

            Barbara D’haene, Jo Vandesompele, Jan Hellemans (2010)
            Copy number changes are known to be involved in numerous human genetic disorders. In this context, qPCR-based copy number screening may serve as the method of choice for targeted screening of the relevant disease genes and their surrounding regulatory landscapes. qPCR has many advantages over alternative methods, such as its low consumable and instrumentation costs, fast turnaround and assay development time, high sensitivity and open format (independent of a single supplier). In this chapter we provide all relevant information for a successfully implement of qPCR-based copy number analysis. We emphasize the significance of thorough in silico and empirical validation of the primers, the need for a well thought-out experiment design, and the importance of quality controls along the entire workflow. Furthermore, we suggest an appropriate and practical way to calculate copy numbers and to objectively interpret the results. The provided guidelines will most certainly improve the quality and reliability of your qPCR-based copy number screening. Copyright 2010 Elsevier Inc. All rights reserved.
            Article 0 comments Cited 128 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              NCCN Guidelines Insights: Central Nervous System Cancers, Version 1.2017.

              Paul L Moots, Jana Portnow, Mario Ammirati … (2017)
              For many years, the diagnosis and classification of gliomas have been based on histology. Although studies including large populations of patients demonstrated the prognostic value of histologic phenotype, variability in outcomes within histologic groups limited the utility of this system. Nonetheless, histology was the only proven and widely accessible tool available at the time, thus it was used for clinical trial entry criteria, and therefore determined the recommended treatment options. Research to identify molecular changes that underlie glioma progression has led to the discovery of molecular features that have greater diagnostic and prognostic value than histology. Analyses of these molecular markers across populations from randomized clinical trials have shown that some of these markers are also predictive of response to specific types of treatment, which has prompted significant changes to the recommended treatment options for grade III (anaplastic) gliomas.
              Article 0 comments Cited 79 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (publisher-id): BTN
                Title: BioTechniques
                Publisher: Future Science Ltd (London, UK )
                ISSN (Print): 0736-6205
                ISSN (Electronic): 1940-9818
                Publication date (Electronic, pub): 24 December 2019
                Publication date (Print, pub): December 2019
                Volume: 0
                Issue: 0
                Affiliations
                1Institute of Pathology & Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
                2Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, China
                Author notes
                [* ]Author for correspondence: zhangxia45@ 123456yahoo.com
                Article
                DOI: 10.2144/btn-2019-0098
                PubMed ID: 31870167
                SO-VID: 7839e8ad-0e38-4b4d-8f6f-ffe1e3399605
                Copyright © © 2019 Weiqi Dang and Xia Zhang
                License:

                This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License

                History
                Date received : 08 August 2019
                Date accepted : 26 November 2019
                Date: 24 December 2019
                Page count
                Pages: 8
                Categories
                Subject: Reports

                ScienceOpen disciplines: General life sciences,Cell biology,Molecular biology,Biotechnology,Genetics,Life sciences
                Keywords: stemness-related genes,quantitative real-time PCR,tumor-initiating cells,glioma stem cells,reference genes
                Data availability:
                ScienceOpen disciplines: General life sciences, Cell biology, Molecular biology, Biotechnology, Genetics, Life sciences
                Keywords: stemness-related genes, quantitative real-time PCR, tumor-initiating cells, glioma stem cells, reference genes

                Comments

                Comment on this article

                scite_

                Similar content193

                See all similar

                Cited by3

                See all cited by

                Most referenced authors782

                See all reference authors