Promoter methylation analysis of O6-methylguanine-DNA methyltransferase in glioblastoma: detection by locked nucleic acid based quantitative PCR using an imprinted gene (SNURF) as a reference

<p>Abstract</p> <p>Background</p> <p>Epigenetic silencing of the <it>MGMT </it>gene by promoter methylation is associated with loss of <it>MGMT </it>expression, diminished DNA-repair activity and longer overall survival in patients with glioblastoma who, in addition to radiotherapy, received alkylating chemotherapy with carmustine or temozolomide. We describe and validate a rapid methylation sensitive quantitative PCR assay (MS-qLNAPCR) using Locked Nucleic Acid (LNA) modified primers and an imprinted gene as a reference.</p> <p>Methods</p> <p>An analysis was made of a database of 159 GBM patients followed between April 2004 and October 2008. After bisulfite treatment, methylated and unmethylated CpGs were recognized by LNA primers and molecular beacon probes. The <it>SNURF </it>promoter of an imprinted gene mapped on 15q12, was used as a reference. This approach was used because imprinted genes have a balanced copy number of methylated and unmethylated alleles, and this feature allows an easy and a precise normalization.</p> <p>Results</p> <p>Concordance between already described nested MS-PCR and MS-qLNAPCR was found in 158 of 159 samples (99.4%). The MS-qLNAPCR assay showed a PCR efficiency of 102% and a sensitivity of 0.01% for LNA modified primers, while unmodified primers revealed lower efficiency (69%) and lower sensitivity (0.1%). <it>MGMT </it>promoter was found to be methylated using MS-qLNAPCR in 70 patients (44.02%), and completely unmethylated in 89 samples (55.97%). Median overall survival was of 24 months, being 20 months and 36 months, in patients with <it>MGMT </it>unmethylated and methylated, respectively. Considering <it>MGMT </it>methylation data provided by MS-qLNAPCR as a binary variable, overall survival was different between patients with GBM samples harboring <it>MGMT </it>promoter unmethylated and other patients with any percentage of <it>MGMT </it>methylation (p = 0.003). This difference was retained using other cut off values for <it>MGMT </it>methylation rate (i.e. 10% and 20% of methylated allele), while the difference was lost when 50% of <it>MGMT </it>methylated allele was used as cut-off.</p> <p>Conclusions</p> <p>We report and clinically validate an accurate, robust, and cost effective MS-qLNAPCR protocol for the detection and quantification of methylated <it>MGMT </it>alleles in GBM samples. Using MS-qLNAPCR we demonstrate that even low levels of <it>MGMT </it>promoter methylation have to be taken into account to predict response to temozolomide-chemotherapy.</p

Hemophilia B: Molecular pathogenesis and mutation analysis

Hemophilia B is an X-chromosome-linked inherited bleeding disorder primarily affecting males, but those carrier females with reduced factor IX activity (FIX:C) levels may also experience some bleeding. Genetic analysis has been undertaken for hemophilia B since the mid-1980s, through linkage analysis to track inheritance of an affected allele, and to enable determination of the familial mutation. Mutation analysis using PCR and Sanger sequencing along with dosage analysis for detection of large deletions/duplications enables mutation detection in > 97% of patients with hemophilia B. The risk of the development of inhibitory antibodies, which are reported in ~ 2% of patients with hemophilia B, can be predicted, especially in patients with large deletions, and these individuals are also at risk of anaphylaxis, and nephrotic syndrome if they receive immune tolerance induction. Inhibitors also occur in patients with nonsense mutations, occasionally in patients with small insertions/deletions or splice mutations, and rarely in patients with missense mutations (p.Gln237Lys and p.Gln241His). Hemophilia B results from several different mechanisms, and those associated with hemophilia B Leyden, ribosome readthrough of nonsense mutations and apparently ‘silent’ changes that do not alter amino acid coding are explored. Large databases of genetic variants in healthy individuals and patients with a range of disorders, including hemophilia B, are yielding useful information on sequence variant frequency to help establish possible variant pathogenicity, and a growing range of algorithms are available to help predict pathogenicity for previously unreported variants