Feliciano Andrea, González Lucila, Garcia-Mayea Yoelsis, Mir Cristina, Artola Mireia, Barragán Nieves, Martín Remedios, Altés Anna, Castellvi Josep, Benavente Sergi, Ramón Y Cajal Santiago, Espinosa-Bravo Martín, Cortés Javier, Rubio Isabel T, LLeonart Matilde E
Biomedical Research in Cancer Stem Cells Group, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain.
Primary Care Center CAP-Vallcarca-Sant Gervasi, Barcelona, Spain.
Front Oncol. 2020 Nov 3;10:586268. doi: 10.3389/fonc.2020.586268. eCollection 2020.
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 . 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 . 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.
乳腺癌是女性中发病率和死亡率最高的癌症。微小RNA正成为新型的预后/诊断工具。我们的目的是确定一种有助于预测癌症发展的血清微小RNA特征。我们着重研究了96例乳腺癌患者及92例对照个体血清中30种微小RNA的表达水平。生物信息学研究基于5种微小RNA的表达水平提供了一种被指定为预测指标的微小RNA特征。然后，我们在一组随机选择的60名女性中测试了该预测指标。最后，一项蛋白质组学研究揭示了乳腺癌患者血清中与对照个体血清中差异表达的蛋白质的过表达和下调情况。26种微小RNA可区分癌组织与健康组织，16种微小RNA可区分癌症患者血清与对照组血清。miR-99a、miR-497、miR-362和miR-1274的组织表达以及miR-141的血清水平与患者生存相关。此外，由miR-125b、miR-29c、miR-16、miR-1260和miR-451组成的预测指标能够区分乳腺癌患者与对照。该预测指标在20例新的乳腺癌患者中得到验证，并在60名志愿者女性中进行测试，将60名女性中的11名归入癌症组。发现血清中miR-16水平低与CD44蛋白含量高有关。血清中的循环微小RNA可作为癌症预测的生物标志物。本文讨论了它们的临床相关性以及这里所描述的预测指标的潜在用途。
