Abstract
Background: Recent research indicates that long non-coding RNAs (lncRNA) represent a new family of RNAs that is of fundamental importance for controlling transcription and translation. Thereby, there is increasing evidence that lncRNAs are also important in tumourigenesis. Thereby valid expression profiling using quantitative PCR requires suitable, stably expressed normalisers to achieve reliable and reproducible data. However, no systematic analysis of suitable references in lncRNA studies in human glioma has been performed yet. Methods: In this study, we investigated 90 lncRNAs in 30 tissue specimen for the expression stability in human diffuse astrocytoma (WHO-Grade II),anaplastic astrocytoma (WHO-Grade III) and glioblastoma (WHO-Grade IV) both alone as well as in comparison with normal white matter. Our identification procedure included a rigorous bioinformatical selection process that resulted in the inclusion of only highly abundant, equally expressed lncRNAs for further analysis. Additionally, lncRNAs were classified according to their stability value using the NormFinder algorithm. Results: We identified 24 appropriate normalisers suitable for studies in diffuse astrocytoma, 22 for studies in anaplastic astrocytoma and 12 for studies in glioblastoma. Comparing all three glioma entities 7 lncRNAs showed stable expression levels. Addition of normal brain tissue resulted in only 4 suitable lncRNAs. Conclusions: Our findings indicate that 4 lncRNAs (HOXA6as, H19 upstream conserved 1 and 2, Zfhx2as and BC200) are suitable as normalisers in glioma and normal brain. These lncRNAs may thus be regarded as universal references being applicable for the accurate normalisation of lncRNA expression profiling in various glioma (WHO-Grades II-IV) alone and in combination with brain tissue. This enables to perform valid longitudinal studies, e.g. of glioma before and after malignisation to identify changes of lncRNA expressions probably driving malignant transformation.
Dokumententyp: | Zeitschriftenartikel |
---|---|
Fakultät: | Medizin > Institut für Neuropathologie |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-34590-5 |
ISSN: | 1837-9664 |
Sprache: | Englisch |
Dokumenten ID: | 34590 |
Datum der Veröffentlichung auf Open Access LMU: | 15. Feb. 2017, 16:04 |
Letzte Änderungen: | 04. Nov. 2020, 13:13 |