Gómez-Acebo, InésLlorca, JavierAlonso-Molero, JéssicaDíaz-Martínez, MartaPérez-Gómez, BeatrizAmiano, PilarBelmonte, ThalíaMolina, Antonio J.Burgui, RosanaCastaño Vinyals, GemmaMoreno, VíctorMolina-Barceló, AnaMarcos-Gragera, RafaelKogevinas, ManolisPollán, MarinaDierssen Sotos, Trinidad2024-02-162024-02-162023Gómez-Acebo I, Llorca J, Alonso-Molero J, Díaz-Martínez M, Pérez-Gómez B, Amiano P, Belmonte T, Molina AJ, Burgui R, Castaño-Vinyals G, Moreno V, Molina-Barceló A, Marcos-Gragera R, Kogevinas M, Pollán M, Dierssen-Sotos T. Circulating miRNAs signature on breast cancer: the MCC-Spain project. Eur J Med Res. 2023 Nov 4;28(1):480. DOI: 10.1186/s40001-023-01471-20949-2321http://hdl.handle.net/10230/59117Purpose: To build models combining circulating microRNAs (miRNAs) able to identify women with breast cancer as well as different types of breast cancer, when comparing with controls without breast cancer. Method: miRNAs analysis was performed in two phases: screening phase, with a total n = 40 (10 controls and 30 BC cases) analyzed by Next Generation Sequencing, and validation phase, which included 131 controls and 269 cases. For this second phase, the miRNAs were selected combining the screening phase results and a revision of the literature. They were quantified using RT-PCR. Models were built using logistic regression with LASSO penalization. Results: The model for all cases included seven miRNAs (miR-423-3p, miR-139-5p, miR-324-5p, miR-1299, miR-101-3p, miR-186-5p and miR-29a-3p); which had an area under the ROC curve of 0.73. The model for cases diagnosed via screening only took in one miRNA (miR-101-3p); the area under the ROC curve was 0.63. The model for disease-free cases in the follow-up had five miRNAs (miR-101-3p, miR-186-5p, miR-423-3p, miR-142-3p and miR-1299) and the area under the ROC curve was 0.73. Finally, the model for cases with active disease in the follow-up contained six miRNAs (miR-101-3p, miR-423-3p, miR-139-5p, miR-1307-3p, miR-331-3p and miR-21-3p) and its area under the ROC curve was 0.82. Conclusion: We present four models involving eleven miRNAs to differentiate healthy controls from different types of BC cases. Our models scarcely overlap with those previously reported.application/pdfeng© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1186/s40001-023-01471-2Breast cancerDiagnosisPrognosisScreeningmiRNAinfo:eu-repo/semantics/openAccess