Kit to predict the risk of relapse in breast cancer
Relapse in cancer occurs when the disease reappears after the treatment. There are two types of relapse: local or distant (metastasis) and in turn, it may be an early recurrence (iatrogenic effect resulting from the surgical removal of the primary tumor) or late recurrence (natural evolution of the disease).
After the resection of the tumor, the risk of relapse (recurrence) is not constant over time. The prediction of early recurrence in breast cancer represents a major challenge in clinical practice, since such recurrence is associated with a more aggressive tumor, fewer treatment options and poor prognosis.
MicroRNAs (miRNAs) regulate in a negative manner gene expression by inhibiting translation of its target mRNA and causing gene silencing. However, to date it has not been documented which particular miRNAs might be associated with early recurrence (2 years after treatment) of a particular tumor.
Because the reason mentioned above and the need to identify biomarkers to predict the risk of recurrence in breast cancer after surgery or specific treatment, the research group has developed a specific method and kit for determining the risk its recurrence. The kit is based on measuring the expression levels of a set of 5 specific miRNAs to determine the low or high risk of developing breast cancer again.
The results show that the signature set of miRNAs is a very strong predictive value in discriminating tumors from patients who developed early recurrence from those who are free of disease. This value is reflected in obtaining an area under the curve (AUC) of 0.993.
Currently clinical validation studies in different patient cohorts are being undergoing.
It decides with reliability the risk of relapse in patients treated for breast cancer.
It allows the establishment of groups of patients according to risk.
It could help selecting the appropriate therapy.
It could allow adequate monitoring of patients.
- Oncology and Hematology
- Women’s Health
Inventores de IBIMA
Isabel GuerreroUnidad de Innovación IBIMA
María MengualUnidad de Innovación IBIMA
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