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

Circulating 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.

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Journal
Scientific Reports
Published
2026-03-07
DOI
https://doi.org/10.1038/s41598-026-41660-7
Primary Topic
MicroRNA in disease regulation
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article
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article

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

Thalía Belmonte, Victor Moreno, Jéssica Alonso-Molero, P. Amiano et al.
Scientific Reports
MicroRNA in disease regulation
article

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

Thalía Belmonte, Victor Moreno, Jéssica Alonso-Molero, P. Amiano, Rosana Burgui, Trinidad Dierssen-Sotos, M. Pollán, Sara Valero-Dominguez, Beatriz Pérez-Gómez, Juan Alguacil, Inés Gómez-Acebo, Gemma Castaño-Vinyals, Ana Molina-Barceló, Javier Llorca, Aina Romaguera, Vicente Martín, Paz Rodríguez-Cundín
article en

Abstract

Circulating 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.

Scientific Reports
Universidad de Cantabria (ES), Universitat Pompeu Fabra (ES), Basque Government (ES), Instituto de Salud Carlos III (ES), Instituto de Salud Pública de Navarra (ES), Institut d'Investigació Biomédica de Bellvitge (ES), Josep Carreras Leukaemia Research Institute (ES), Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (ES), Marqués de Valdecilla University Hospital (ES), Biogipuzkoa Health Research Institute (ES), Institut Català d'Oncologia (ES), Instituto de Investigación Marqués de Valdecilla (ES), Institut d'Investigació Biomèdica de Girona (ES), Barcelona Institute for Global Health (ES), Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (ES), Hospital del Mar Research Institute (ES), Instituto de Investigación Sanitaria del Principado de Asturias (ES), Universitat de Barcelona (ES), Universidad de Huelva (ES), Universidad de León (ES)
Centres de Recerca de Catalunya, European Commission, Generalitat de Catalunya, Ministerio de Economía y Competitividad, Generalitat Valenciana, Ministerio de Ciencia e Innovación, Universidad de Oviedo, Junta de Andalucía, Junta de Castilla y León, Fundación Marqués de Valdecilla, Agència de Gestió d'Ajuts Universitaris i de Recerca, Instituto de Salud Carlos III
Good health and well-being
Openalex Percentile: Top 29%
MicroRNA in disease regulation
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