Integrating circulating microRNAs with epidemiological factors enhances breast cancer detection across subtypes: the MCC-Spain study

dc.contributor.authorGómez Acebo, Inés
dc.contributor.authorValero Dominguez, Sara
dc.contributor.authorLlorca Díaz, Javier
dc.contributor.authorAlonso-Molero, Jéssica
dc.contributor.authorBelmonte, Thalía
dc.contributor.authorCastaño-Vinyals, Gemma
dc.contributor.authorMoreno Aguado, Víctor
dc.contributor.authorRomaguera, Aina
dc.contributor.authorAmiano, Pilar
dc.contributor.authorAlguacil, Juan
dc.contributor.authorMartín, Vicente
dc.contributor.authorPérez Gómez, Beatriz
dc.contributor.authorBurgui, Rosana
dc.contributor.authorMolina Barceló, Ana
dc.contributor.authorRodríguez Cundín, Paz
dc.contributor.authorKogevinas, Manolis
dc.contributor.authorPollán, Marina
dc.contributor.authorDierssen Sotos, Trinidad
dc.date.accessioned2026-05-26T17:49:22Z
dc.date.available2026-05-26T17:49:22Z
dc.date.issued2026-03-07
dc.date.updated2026-05-26T17:49:26Z
dc.description.abstractCirculating microRNAs (miRNAs) are promising non-invasive biomarkers for cancer detection; however, their diagnostic performance across breast cancer molecular subtypes and their incremental value beyond demographic and epidemiological variables remain incompletely characterized. We conducted a multicenter case–control study including 317 breast cancer cases and 127 population-based controls. Serum levels of 44 literature-derived miRNAs were quantified by RT-qPCR. Feature selection was performed using LASSO penalization, followed by multivariable logistic regression to estimate odds ratios (ORs) with 95% confidence intervals (CIs). Models were adjusted for demographic and epidemiological covariates. Predictive performance was assessed using repeated fivefold cross-validation and reported as area under the curve (AUC) with bootstrap bias-corrected 95% CIs. Incorporating demographic and epidemiological covariates enhanced discrimination overall (AUC = 0.908 vs. 0.802 unadjusted) and across subtypes. The most notable improvements were observed in Luminal A (0.896 vs. 0.751) and Luminal B (0.894 vs. 0.768), while HER2-positive and Basal-like tumors already showed high performance (AUC = 0.965 and 0.989, respectively). Among the 12 miRNAs selected by LASSO, miR-21-5p and miR-423-3p were consistently elevated in cases, particularly in HER2-positive and Basal-like tumors, whereas miR-101-3p, miR-146a-5p, and miR-29a-3p showed reproducibly lower levels across multiple subtypes, consistent with oncogenic and tumor-suppressive roles, respectively. Circulating miRNA signatures, especially when integrated with demographic and epidemiological information, demonstrate high discriminatory power for breast cancer detection across molecular subtypes. These results support subtype-aware, minimally invasive strategies for screening and risk stratification using miRNA-based models. Prospective validation in independent cohorts is warranted to confirm clinical utility.
dc.format.extent16 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec770113
dc.identifier.issn2045-2322
dc.identifier.pmid41792206
dc.identifier.urihttps://hdl.handle.net/2445/229714
dc.language.isoeng
dc.publisherNature Publishing Group
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1038/s41598-026-41660-7
dc.relation.ispartofScientific Reports, 2026, vol. 16
dc.relation.urihttps://doi.org/10.1038/s41598-026-41660-7
dc.rightscc-by (c) Gómez-Acebo, I. et al., 2026
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceArticles publicats en revistes (Ciències Clíniques)
dc.subject.classificationCàncer de mama
dc.subject.classificationMicro RNAs
dc.subject.otherBreast cancer
dc.subject.otherMicroRNAs
dc.titleIntegrating circulating microRNAs with epidemiological factors enhances breast cancer detection across subtypes: the MCC-Spain study
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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