117
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Identification of Valid Reference Genes for the Normalization of RT-qPCR Expression Studies in Human Breast Cancer Cell Lines Treated with and without Transient Transfection

      research-article

      Read this article at

      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

          Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is a powerful technique for examining gene expression changes during tumorigenesis. Target gene expression is generally normalized by a stably expressed endogenous reference gene; however, reference gene expression may differ among tissues under various circumstances. Because no valid reference genes have been documented for human breast cancer cell lines containing different cancer subtypes treated with transient transfection, we identified appropriate and reliable reference genes from thirteen candidates in a panel of 10 normal and cancerous human breast cell lines under experimental conditions with/without transfection treatments with two transfection reagents. Reference gene expression stability was calculated using four algorithms (geNorm, NormFinder, BestKeeper and comparative delta Ct), and the recommended comprehensive ranking was provided using geometric means of the ranking values using the RefFinder tool. GeNorm analysis revealed that two reference genes should be sufficient for all cases in this study. A stability analysis suggests that 18S rRNA-ACTB is the best reference gene combination across all cell lines; ACTB-GAPDH is best for basal breast cancer cell lines; and HSPCB-ACTB is best for ER + breast cancer cells. After transfection, the stability ranking of the reference gene fluctuated, especially with Lipofectamine 2000 transfection reagent in two subtypes of basal and ER + breast cell lines. Comparisons of relative target gene ( HER2) expression revealed different expressional patterns depending on the reference genes used for normalization. We suggest that identifying the most stable and suitable reference genes is critical for studying specific cell lines under certain circumstances.

          Related collections

          Most cited references28

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR

          Background Control genes, which are often referred to as housekeeping genes, are frequently used to normalise mRNA levels between different samples. However, the expression level of these genes may vary among tissues or cells and may change under certain circumstances. Thus, the selection of housekeeping genes is critical for gene expression studies. To address this issue, 7 candidate housekeeping genes including several commonly used ones were investigated in isolated human reticulocytes. For this, a simple ΔCt approach was employed by comparing relative expression of 'pairs of genes' within each sample. On this basis, stability of the candidate housekeeping genes was ranked according to repeatability of the gene expression differences among 31 samples. Results Initial screening of the expression pattern demonstrated that 1 of the 7 genes was expressed at very low levels in reticulocytes and was excluded from further analysis. The range of expression stability of the other 6 genes was (from most stable to least stable): GAPDH (glyceraldehyde 3-phosphate dehydrogenase), SDHA (succinate dehydrogenase), HPRT1 (hypoxanthine phosphoribosyl transferase 1), HBS1L (HBS1-like protein) and AHSP (alpha haemoglobin stabilising protein), followed by B2M (beta-2-microglobulin). Conclusion Using this simple approach, GAPDH was found to be the most suitable housekeeping gene for expression studies in reticulocytes while the commonly used B2M should be avoided.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Choosing the right cell line for breast cancer research

            Breast cancer is a complex and heterogeneous disease. Gene expression profiling has contributed significantly to our understanding of this heterogeneity at a molecular level, refining taxonomy based on simple measures such as histological type, tumour grade, lymph node status and the presence of predictive markers like oestrogen receptor and human epidermal growth factor receptor 2 (HER2) to a more sophisticated classification comprising luminal A, luminal B, basal-like, HER2-positive and normal subgroups. In the laboratory, breast cancer is often modelled using established cell lines. In the present review we discuss some of the issues surrounding the use of breast cancer cell lines as experimental models, in light of these revised clinical classifications, and put forward suggestions for improving their use in translational breast cancer research.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              How to do successful gene expression analysis using real-time PCR.

              Reverse transcription quantitative PCR (RT-qPCR) is considered today as the gold standard for accurate, sensitive and fast measurement of gene expression. Unfortunately, what many users fail to appreciate is that numerous critical issues in the workflow need to be addressed before biologically meaningful and trustworthy conclusions can be drawn. Here, we review the entire workflow from the planning and preparation phase, over the actual real-time PCR cycling experiments to data-analysis and reporting steps. This process can be captured with the appropriate acronym PCR: plan/prepare, cycle and report. The key message is that quality assurance and quality control are essential throughout the entire RT-qPCR workflow; from living cells, over extraction of nucleic acids, storage, various enzymatic steps such as DNase treatment, reverse transcription and PCR amplification, to data-analysis and finally reporting. Copyright 2009 Elsevier Inc. All rights reserved.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2015
                24 January 2015
                : 10
                : 1
                : e0117058
                Affiliations
                [1 ]Laboratory for Conservation and Utilization of Bio-resource, Yunnan University, Kunming, China
                [2 ]Department of Endocrine Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
                [3 ]Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
                [4 ]State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
                INRS, CANADA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: HZ YPZ. Performed the experiments: LLL HZ TFM FG. Analyzed the data: LLL HZ TFM. Contributed reagents/materials/analysis tools: CSC YPZ. Wrote the paper: LLL HZ CSC YPZ. Obtained permission for use of cell line: FG CSC.

                Article
                PONE-D-14-37574
                10.1371/journal.pone.0117058
                4305315
                25617865
                5ef1cbf5-9000-43cb-845e-d400f4f3b9d2
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 20 August 2014
                : 18 December 2014
                Page count
                Figures: 3, Tables: 5, Pages: 15
                Funding
                This work was supported by grants of the National Natural Science Foundation of China (Grant Nos. 31060302 and 31260032) ( http://www.nsfc.gov.cn), the Natural Science Foundation of Yunnan Province (Grant No. 2010CD010) ( http://www.ynstc.gov.cn) and Program for Innovative Research Team (in Science and Technology) in University of Yunnan Province ( http://www.ynjy.cn). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article