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dc.contributor.authorCaballero Vázquez, Alberto
dc.contributor.authorGarcía Cerezo, Marta
dc.contributor.authorFernandez Castro, Laura R.
dc.contributor.authorMorales-Garcia, Concepcion
dc.contributor.authorLáinez-Ramos-Bossini, Antonio Jesús
dc.contributor.authorVergara Rubio, Fabian
dc.contributor.authorOrtega Sánchez, Francisco Gabriel
dc.contributor.authorSánchez Maldonado, José Manuel
dc.date.accessioned2026-02-11T11:36:20Z
dc.date.available2026-02-11T11:36:20Z
dc.date.issued2026-01-29
dc.identifier.citationCaballero-Vazquez, A., Garcia-Cerezo, M., Fernandez-Castro, L.R. et al. Liquid biopsy biomarkers for accurate detection of malignant pulmonary nodules: a meta-analytic approach. Discov Onc 17, 178 (2026). https://doi.org/10.1007/s12672-025-03646-1es_ES
dc.identifier.urihttps://hdl.handle.net/10481/110880
dc.description.abstractPulmonary nodules are a common radiological finding that can be classified as either benign or Malignant, with significant clinical implications. The early detection of malignant nodules is critically important for improving the prognosis of lung cancer, which remains the leading cause of cancer-related mortality worldwide. Traditional imaging techniques have Limitations in accurately classifying pulmonary nodules. Liquid biopsy, a minimally invasive method that evaluates circulating components in the Blood, presents promising diagnostic potential in this context. This study aims to evaluate the diagnostic capacity of multiple liquid biopsy biomarkers for early and accurate differentiation between benign and Malignant pulmonary nodules. Accordingly, we conducted a comprehensive study involving a meta-analysis, selecting 16 eligible studies that utilised liquid biopsy to assess various circulating biomarkers in the diagnostic yield. The most significant results were linked to circulating free DNA (cfDNA). However, other components, including circulating tumour cells (CTCs), microRNAs/pfeRNAs, extracellular vesicles (EVs), serological markers, and imaging techniques, also provided valuable information. Similarly, integrating multi-omics data with machine learning models has been shown to enhance the ability to differentiate between benign and malignant pulmonary nodules, thereby supporting early diagnosis and improved management for patients with lung cancer.es_ES
dc.description.sponsorshipGENYO (Pfizer–University of Granada–Andalusian Regional Government), Instituto de Salud Carlos III - (PI22/01275, PI19/01578)es_ES
dc.description.sponsorshipUniversity of Granada - (P32/22/02)es_ES
dc.description.sponsorshipConsejería de Salud y Familia, Junta de Andalucía - (RH-0074-2020)es_ES
dc.description.sponsorshipEuropean Union’s Horizon 2020 - (H2020-MSCAeIFe2019-895664)es_ES
dc.language.isoenges_ES
dc.publisherSpringer Naturees_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectliquid biopsyes_ES
dc.subjectPulmonary noduleses_ES
dc.subjectCirculating biomarkerses_ES
dc.titleLiquid biopsy biomarkers for accurate detection of malignant pulmonary nodules: a meta-analytic approaches_ES
dc.typejournal articlees_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/H2020-MSCAeIFe2019-895664es_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1007/s12672-025-03646-1
dc.type.hasVersionVoRes_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional