RESUMEN
Gliomas are the most common primary malignant intracranial brain tumors. Their proliferative and invasive behavior is controlled by various epigenetic mechanisms. 5-hydroxymethylcytosine (5-hmC) is one of the epigenetic DNA modifications that employs ten-eleven translocation (TET) enzymes to its oxidation. Previous studies demonstrated altered expression of 5-hmC across gliomagenesis. However, its contribution to the initiation and progression of human gliomas still remains unknown. To characterize the expression profiles of 5-hmC and TET in human glioma samples we used the EpiJET 5-hmC and 5-mC Analysis Kit, quantitative real-time PCR, and Western blot analysis. A continuous decline of 5-hmC levels was observed in solid tissue across glioma grades. However, in glioblastoma (GBM), we documented uncommon heterogeneity in 5-hmC expression. Further analysis showed that the levels of TET proteins, but not their transcripts, may influence the 5-hmC abundance in GBM. Early tumor-related biomarkers may also be provided by the study of aberrant DNA hydroxymethylation in the blood of glioma patients. Therefore, we explored the patterns of TET transcripts in plasma samples and we found that their profiles were variously regulated, with significant value for TET2. The results of our study confirmed that DNA hydroxymethylation is an important mechanism involved in the pathogenesis of gliomas, with particular reference to glioblastoma. Heterogeneity of 5-hmC and TET proteins expression across GBM may provide novel insight into define subtype-specific patterns of hydroxymethylome, and thus help to interpret the heterogeneous outcomes of patients with the same disease.
RESUMEN
Correct selection of the reference gene(s) is the most important step in gene expression analysis. The aims of this study were to identify and evaluate the panel of possible reference genes in neural stem cells (NSC), early neural progenitors (eNP) and neural progenitors (NP) obtained from human-induced pluripotent stem cells (hiPSC). The stability of expression of genes commonly used as the reference in cells during neural differentiation is variable and does not meet the criteria for reference genes. In the present work, we evaluated the stability of expression of 16 candidate reference genes using the four most popular algorithms: the ΔCt method, BestKeeper, geNorm and NormFinder. All data were analysed using the online tool RefFinder to obtain a comprehensive ranking. Our results indicate that NormFinder is the best tool for reference gene selection in early stages of hiPSC neural differentiation. None of the 16 tested genes is suitable as reference gene for all three stages of development. We recommend using different genes (panel of genes) to normalise RT-qPCR data for each of the neural differentiation stages.
