| Autor: |
Nóra Ördög, Barbara N Borsos, Hajnalka Majoros, Zsuzsanna Ujfaludi, Gabriella Pankotai-Bodó, Sarolta Bankó, Farkas Sükösd, Levente Kuthi, Tibor Pankotai |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Translational Oncology, Vol 20, Iss , Pp 101420- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1936-5233 |
| DOI: |
10.1016/j.tranon.2022.101420 |
| Popis: |
Patients diagnosed with clear cell renal cell carcinoma (ccRCC) have poor prognosis for recurrence and approximately 30–40% of them will later develop metastases. For this reason, the appropriate diagnosis and the more detailed molecular characterisation of the primary tumour, including its susceptibility to metastasis, are crucial to select the proper adjuvant therapy by which the most prosperous outcome can be achieved. Nowadays, clinicopathological variables are used for classification of the tumours. Apart from these, molecular biomarkers are also necessary to improve risk classification, which would be the most beneficial amongst modern adjuvant therapies. As a potential molecular biomarker, to follow the transcriptional kinetics in ccRCC patients (n=30), we analysed epigenetic changes (γH2A.X, H3K4me3, and H3K9me3) and the alterations in the level of RNA polymerase II (RNAPII) by immunohistochemical staining on dissected tissue sections. The variabilities between the tumorous and non-tumorous parts of the tissue were detected using quantitative image analysis by monitoring 30 cells from different positions of either the tumorous or the non-tumorous part of the tissue sections. Data obtained from the analyses were used to identify potential prognostic features and to associate them with the progression. These markers might have a value to predict patient outcomes based on their individual cellular background. These results also support that detection of any alteration in the level of H3K4me3, H3K9me3, and γH2A.X can account for valuable information for presuming the progression of ccRCC and the clinical benefits to select the most efficient personalised therapy. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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