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Knowing which people are at higher risk of developing breast cancer would allow a more exhaustive follow-up in order to early detect the possible formation of tumors in the future.
A study led by the Biomedical Research in Cancer Stem Cells group at Vall d’Hebron Research Institute (VHIR) has identified a group of biomarkers that would help detect a higher risk of breast cancer in healthy women. In this way, a more exhaustive monitoring of these people could be carried out. Therefore, if a tumor appears in the future, it could be detected early thus improving the prognosis of the disease and its survival. The work had the participation of VHIR, Vall d’Hebron Institute of Oncology (VHIO), CAP Vallcarca-Sant Gervasi in Barcelona, IOB Institute of Oncology, the University Clinic of Navarra (Madrid) and the CIBER of Cancer (CIBERONC). The results have been published in the journal Frontiers in Oncology.
In Spain, one in every 8 women will develop invasive breast cancer over the course of their life. In order to improve the survival of these patients, the researchers have found a set of 5 biomarkers in the blood, known as microRNAs, which allow them to know the personalized risk of developing breast cancer. microRNAs are a type of small molecules that are responsible for inactivating some genes and preventing some proteins from being expressed in cells. Previous studies have already shown its relationship with the development of certain types of cancer, but until now there was no precise risk prediction model for breast cancer.
The aim of the study led by VHIR was to detect cancer at the molecular level in the blood before its symptoms appear or before it can be detected by conventional tests. Dr. Matilde Lleonart, head of the Biomedical Research in Cancer Stem Cells group at VHIR and researcher at the CIBERONC highlights that “finding these molecular alterations in the blood of a patient means that there are some changes in some cells, but it doesn’t always have clinical implications. Signs and symptoms of the disease may never develop, which is what has an impact on life. This finding, therefore, allows us to detect a high risk of suffering from breast cancer in the future, but it doesn’t imply a diagnosis of the disease”.
Five microRNAs with predictability
To carry out the study, the researcher obtained tumor and normal tissue, as well as serum from 96 breast cancer patients and compared them with the serum of 92 healthy patients. In all of them, up to 30 microRNAs were analyzed, which in previous studies had been shown to be able of differentiating normal and tumor tissues.
“Of all microRNAs that were studied, we identified five that, according to their expression levels, allowed us to know if a specific serum sample belonged to a control or cancer patient. Thus, they form a molecular signature capable of predicting breast cancer”, explains Dr. Lleonart. Specifically, the molecular signature was based on the following microRNAs: miR-125b, miR-29c, miR-16, miR-1260 and miR-451. Thus, depending on whether the levels of each of these microRNAs are higher of lower, there is higher or lower risk that the patient will develop breast cancer. “This molecular signature could predict, therefore, which patients should undergo a more exhaustive follow-up that could be carried out by ultrasound scans, which are less aggressive and involve less risk at the radiation level than other techniques such as mammograms”, says Dr. Lleonart.
This tool was later validated by the same researchers with samples from another group of 20 breast cancer patients and 60 healthy women and they found that this molecular signature has an accuracy of 86%, a sensitivity of 100% and a specificity of 81%. “The most important thing is that this methodology doesn’t have false negatives, that is, all women with cancer obtain the pattern of microRNAs that we expect for cancer patients”, emphasizes Dr. Lleonart. Amongh the healthy volunteers, 11 of them obtained this pattern (18.3%), which could correspond to a higher risk of developing cancer in the future.
CD44, a protein linked to breast cancer
Among the microRNAs of the molecular signature described by the VHIR study is miR-16. As with all microRNAs, miR-16 is responsible for silencing several genes and, therefore, preventing the corresponding proteins from being formed. In this case, miR-16 controls the CD44 protein. Thus, when miR-16 levels are high, CD44 is very poorly expressed and, in the same way, if miR-16 levels are low, CD44 levels are very high.
Previous studies had described elevated levels of CD44 in serum in a very aggressive type of breast cancer, the triple negative. These results support the idea that CD44 could be a marker for other molecular subtypes of breast cancer. “It is interesting that we have also found this marker in luminal tumors A and B which, although they are less aggressive, can cause long-term recurrences and reappear like aggressive metastases over the years”, concludes Dr. Lleonart.
From Vall d’Hebron, the study has been led by the Biomedical Research in Cancer Stem Cells group at VHIR with the collaboration of the research group in Translational Molecular Pathology group at VHIR, the Breast Pathology Unit, the Radiation Oncology Service and the Medical Oncology Service at Vall d’Hebron University Hospital and the Breast Cancer and Melanoma Group at VHIO. The work has also had the active participation of the Statistics and Bioinformatics Unit (UEB) at VHIR, the CSIC/UAB Proteomics Laboratory, the Hemotherapy and Hemodonation Center in Castilla y León and the “Banc de Sang i Teixits” in Catalonia.
This work was supported by ISCIII (Instituto de Salud Carlos III) Ref. FIS PI15/01262, co-financed by the European Regional Development Fund (ERDF) and AECC Project GEC Ref. GC16173720CARR (ML). AF, YG-M, and CM were granted with P-FIS, VHIR, and iP-FIS fellowships, respectively.
Feliciano A, González L, García-Mayea Y, Mir C, Artola M, Barragán N, Martín R, Altés A, Castellvi J, Benavente S, Ramón y Cajal S, Espinosa-Bravo M, Cortés J, Rubio IT and LLeonart ME (2020) Five microRNAs in Serum Are Able to Differentiate Breast Cancer Patients From Healthy Individuals. Front. Oncol. 10:586268. doi: 10.3389/fonc.2020.586268
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