Oncogenic microRNAs to predict relapse in early breast cancer patients
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10366006" target="_blank" >RIV/00216208:11320/17:10366006 - isvavai.cz</a>
Výsledek na webu
<a href="http://ascopubs.org/doi/abs/10.1200/JCO.2017.35.15_suppl.e23021" target="_blank" >http://ascopubs.org/doi/abs/10.1200/JCO.2017.35.15_suppl.e23021</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1200/JCO.2017.35.15_suppl.e23021" target="_blank" >10.1200/JCO.2017.35.15_suppl.e23021</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Oncogenic microRNAs to predict relapse in early breast cancer patients
Popis výsledku v původním jazyce
Background: Early breast cancer is a frequent female disease with different outcomes. New approaches are needed in order to improve its prognosis. MicroRNAs (miRs) are modulators of gene expression and act as oncogenes and function to inhibit tumor suppressors and to promote metastasizing. Monitoring of miRs could be of benefit to the prognosis of EBC patients. Results: EBC patients significantly over-express miRs in time point I. In time point II the levels of miR-155, miR-181b, miR-24 significantly decreased (p< 0.05). miR-19a decreased in time point III (p= 0.00869). Levels of miR-155, miR-19a, miR-181b, miR-24 are significantly more abundant in high-risk in comparison to low-risk patients (p< 0.05) and decrease upon therapy. The multivariate GEE model revealed that miR-155, miR-24 were predictive of the relapse (p= 0.025 and 0.041). miR-19a, miR-181b are insignificant with respect to the relapse (p> 0.05). Triple-negativity, HER2+, grade III, LN+ have no effect on the probability of relapse (p> 0.05) when miRs are simultaneously taken into an account. The only risk factor that makes the prediction of relapse more precise is Ki-67 > 20% (p= 0.013 in case of miR-155 and p= 0.023 in case of miR-24). Conclusions: OncomiRs are significantly more abundant in EBC patients at diagnosis and decline after therapy. Differences in miR levels reflect EBC risk groups. The data shows that miR-155 and miR-24 enable monitoring of EBC and predict relapse independently of clinical/pathological risk factors. Combining the miR levels with Ki-67 expression further specifies the relapse probability.
Název v anglickém jazyce
Oncogenic microRNAs to predict relapse in early breast cancer patients
Popis výsledku anglicky
Background: Early breast cancer is a frequent female disease with different outcomes. New approaches are needed in order to improve its prognosis. MicroRNAs (miRs) are modulators of gene expression and act as oncogenes and function to inhibit tumor suppressors and to promote metastasizing. Monitoring of miRs could be of benefit to the prognosis of EBC patients. Results: EBC patients significantly over-express miRs in time point I. In time point II the levels of miR-155, miR-181b, miR-24 significantly decreased (p< 0.05). miR-19a decreased in time point III (p= 0.00869). Levels of miR-155, miR-19a, miR-181b, miR-24 are significantly more abundant in high-risk in comparison to low-risk patients (p< 0.05) and decrease upon therapy. The multivariate GEE model revealed that miR-155, miR-24 were predictive of the relapse (p= 0.025 and 0.041). miR-19a, miR-181b are insignificant with respect to the relapse (p> 0.05). Triple-negativity, HER2+, grade III, LN+ have no effect on the probability of relapse (p> 0.05) when miRs are simultaneously taken into an account. The only risk factor that makes the prediction of relapse more precise is Ki-67 > 20% (p= 0.013 in case of miR-155 and p= 0.023 in case of miR-24). Conclusions: OncomiRs are significantly more abundant in EBC patients at diagnosis and decline after therapy. Differences in miR levels reflect EBC risk groups. The data shows that miR-155 and miR-24 enable monitoring of EBC and predict relapse independently of clinical/pathological risk factors. Combining the miR levels with Ki-67 expression further specifies the relapse probability.
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
—
OECD FORD obor
30204 - Oncology
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2017
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů