Abstract
Breast cancer is the cancer with the most incidence and mortality in women. microRNAs are emerging as novel prognosis/diagnostic tools. Our aim was to identify a serum microRNA signature useful to predict cancer development. We focused on studying the expression levels of 30 microRNAs in the serum of 96 breast cancer patients vs. 92 control individuals. Bioinformatic studies provide a microRNA signature, designated as a predictor, based on the expression levels of five microRNAs. Then, we tested the predictor in a group of 60 randomly chosen women. Lastly, a proteomic study unveiled the overexpression and downregulation of proteins differently expressed in the serum of breast cancer patients vs. that of control individuals. Twenty-six microRNAs differentiate cancer tissue from healthy tissue, and 16 microRNAs differentiate the serum of cancer patients from that of the control group. The tissue expression of miR-99a, miR-497, miR-362, and miR-1274, and the serum levels of miR-141 correlated with patient survival. Moreover, the predictor consisting of miR-125b, miR-29c, miR-16, miR-1260, and miR-451 was able to differentiate breast cancer patients from controls. The predictor was validated in 20 new cases of breast cancer patients and tested in 60 volunteer women, assigning 11 out of 60 women to the cancer group. An association of low levels of miR-16 with a high content of CD44 protein in serum was found. Circulating microRNAs in serum can represent biomarkers for cancer prediction. Their clinical relevance and the potential use of the predictor here described are discussed.
Highlights
Breast cancer is one of the most frequent carcinomas and the second leading cause of death in women [1]
The pathological and clinical characteristics of the patients include the presence of estrogen receptor (ER), progesterone receptor (PR), Ki-67 expression, p53, tumor grade determined by tumor heterogeneity, tumor stage determined by the size of the tumor and its infiltrating capacity to neighboring local areas (T1b, T1c, or T2), subtype of breast cancer, presence of metastasis, disease-free survival, and overall survival
For the selection of the microRNAs studied here, they were selected: (a) the 17 most significantly deregulated microRNAs in breast cancer based on our previous work and (b) the potentially relevant microRNAs in the serum of breast cancer patients [8,9,10,11, 17]
Summary
Breast cancer is one of the most frequent carcinomas and the second leading cause of death in women [1]. In the United States and Europe, about 1 in 8 women (12.5%) will develop invasive breast cancer over the course of their life. There is no precise model to estimate breast cancer risk. Most of the predictor models consider clinical factors, including the density of breast tissue, biopsy history, and several clinical parameters. Such models are not informative at an individual level. The liquid biopsy is being used to establish the biomarkers that are able to predict or envisage a potential future cancer development risk [3]
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