Identification of valid endogenous control genes for determining gene expression in human glioma.

In human glioma, quantitative real-time reverse-transcription PCR (qPCR) is a frequently used research tool. However, no systematic analysis of suitable reference genes for reliable gene expression analysis has been performed so far. In the current study, we tested 19 commonly used reference genes for their expression stability in human astrocytoma WHO Grade II, astrocytoma WHO Grade III, and glioblastoma (WHO Grade IV) both alone and compared with normal brain. First, equivalence tests for equal expression of candidate genes were applied, and those genes showing differential expression were ruled out from further analyses. Second, expression stability of the remaining candidate genes was determined by the NormFinder software. Generally, glioblastoma exhibited the highest expression levels and largest variability of candidate genes, whereas the opposite was true for normal brain. Even though Normfinder analyses revealed a large number of genes suitable for normalization in each of the tumor subgroups and across these groups, this number was drastically reduced after inclusion of normal brain into the analyses: Only GAPDH, IPO8, RPL13A, SDHA, and TBP were expected not to be differentially expressed; NormFinder analysis indicated favorable stability values for all of these genes, with TBP and IPO8 being the most stable ones. These 5 genes represent different physiological pathways and may be regarded as universal reference genes applicable for accurate normalization of gene expression in human astrocytomas of different grades (WHO Grades II-IV) alone and compared with normal brain, thereby enabling longitudinally designed studies (eg, in astrocytoma before and after malignant transformation).

[1]  K. Hoang-Xuan,et al.  Identification of regions correlating MGMT promoter methylation and gene expression in glioblastomas. , 2009, Neuro-oncology.

[2]  C. Plass,et al.  Copy number gain and oncogenic activity of YWHAZ/14‐3‐3ζ in head and neck squamous cell carcinoma , 2009, International journal of cancer.

[3]  A. von Deimling,et al.  RASSF1A, BLU, NORE1A, PTEN and MGMT Expression and Promoter Methylation in Gliomas and Glioma Cell Lines and Evidence of Deregulated Expression of de novo DNMTs , 2009, Brain pathology.

[4]  C. Scrideli,et al.  Selection of suitable housekeeping genes for expression analysis in glioblastoma using quantitative RT-PCR , 2009, BMC Molecular Biology.

[5]  G. Callard,et al.  Characterization of housekeeping genes in zebrafish: male-female differences and effects of tissue type, developmental stage and chemical treatment , 2008, BMC Molecular Biology.

[6]  T. Waldman,et al.  Conspirators in a capital crime: co-deletion of p18INK4c and p16INK4a/p14ARF/p15INK4b in glioblastoma multiforme. , 2008, Cancer research.

[7]  Yuquan Wei,et al.  Proteomics Identification of Cyclophilin A as a Potential Prognostic Factor and Therapeutic Target in Endometrial Carcinoma* , 2008, Molecular & Cellular Proteomics.

[8]  Y-E Cho,et al.  Suppression of putative tumour suppressor gene GLTSCR2 expression in human glioblastomas , 2008, The Journal of pathology.

[9]  S. Dunner,et al.  Evaluation of suitable reference genes for gene expression studies in bovine muscular tissue , 2008, BMC Molecular Biology.

[10]  K. Akashi,et al.  Enhanced expression of NADPH oxidase Nox4 in human gliomas and its roles in cell proliferation and survival , 2008, International journal of cancer.

[11]  Santosh Kesari,et al.  Malignant gliomas in adults. , 2008, The New England journal of medicine.

[12]  Thomas D. Schmittgen,et al.  Analyzing real-time PCR data by the comparative CT method , 2008, Nature Protocols.

[13]  G. Keilhoff,et al.  Bmc Molecular Biology Selection of Reference Genes for Quantitative Real-time Pcr in a Rat Asphyxial Cardiac Arrest Model , 2022 .

[14]  F. Angileri,et al.  Nuclear factor‐κB activation and differential expression of survivin and Bcl‐2 in human grade 2–4 astrocytomas , 2008, Cancer.

[15]  Webster K. Cavenee,et al.  Feedback Circuit among INK4 Tumor Suppressors Constrains Human Glioblastoma Development , 2008, Cancer cell.

[16]  G. Wegener,et al.  Reference genes for normalization: A study of rat brain tissue , 2008, Synapse.

[17]  Pedro Martínez,et al.  Identification of survival‐related genes of the phosphatidylinositol 3′‐kinase signaling pathway in glioblastoma multiforme , 2008, Cancer.

[18]  A. Carracedo,et al.  Cannabinoids inhibit glioma cell invasion by down-regulating matrix metalloproteinase-2 expression. , 2008, Cancer research.

[19]  S. Qiu,et al.  Selection of reference genes for real-time PCR in human hepatocellular carcinoma tissues , 2008, Journal of Cancer Research and Clinical Oncology.

[20]  G. Reifenberger,et al.  Intratumoral homogeneity of MGMT promoter hypermethylation as demonstrated in serial stereotactic specimens from anaplastic astrocytomas and glioblastomas , 2007, International journal of cancer.

[21]  Jochen Herms,et al.  FET PET for the evaluation of untreated gliomas: correlation of FET uptake and uptake kinetics with tumour grading , 2007, European Journal of Nuclear Medicine and Molecular Imaging.

[22]  Y. Katayama,et al.  Aberrant Hypermethylation of p14ARF and O6‐methylguanine‐DNA Methyltransferase Genes in Astrocytoma Progression , 2007, Brain pathology.

[23]  Tania Nolan,et al.  Quantification of mRNA using real-time RT-PCR , 2006, Nature Protocols.

[24]  K. Mishima,et al.  Increased expression of podoplanin in malignant astrocytic tumors as a novel molecular marker of malignant progression , 2006, Acta Neuropathologica.

[25]  Björn Sjögreen,et al.  The real-time polymerase chain reaction. , 2006, Molecular aspects of medicine.

[26]  W. Koch,et al.  Analysis of 18F-FET PET for grading of recurrent gliomas: is evaluation of uptake kinetics superior to standard methods? , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[27]  K Dheda,et al.  The implications of using an inappropriate reference gene for real-time reverse transcription PCR data normalization. , 2005, Analytical biochemistry.

[28]  Juan F Medrano,et al.  Real-time PCR for mRNA quantitation. , 2005, BioTechniques.

[29]  K Dheda,et al.  Real-time RT-PCR normalisation; strategies and considerations , 2005, Genes and Immunity.

[30]  Claus Lindbjerg Andersen,et al.  Normalization of Real-Time Quantitative Reverse Transcription-PCR Data: A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets , 2004, Cancer Research.

[31]  A. Moorman,et al.  Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data , 2003, Neuroscience Letters.

[32]  Mario Pazzagli,et al.  Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies. , 2002, Analytical biochemistry.

[33]  F. Speleman,et al.  Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes , 2002, Genome Biology.

[34]  M. Pfaffl,et al.  A new mathematical model for relative quantification in real-time RT-PCR. , 2001, Nucleic acids research.

[35]  J. Eberwine,et al.  Amplified RNA synthesized from limited quantities of heterogeneous cDNA. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[36]  W. D. den Dunnen,et al.  The angiopoietin 1/angiopoietin 2 balance as a prognostic marker in primary glioblastoma multiforme. , 2009, Journal of neurosurgery.

[37]  P. Bauer,et al.  Accurate Real-time Reverse Transcription Quantitative PCR. , 2009, Methods in molecular biology.

[38]  D. Louis WHO classification of tumours of the central nervous system , 2007 .