Pleural Liquid Biopsy for Oncological Practice: A Narrative Review

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Background: Pleural effusion is a common clinical presentation in both benign and malignant conditions. The advent of liquid biopsy allowed new possibilities for non-invasive molecular profiling using body fluids. Pleural fluid, by virtue of its proximity to thoracic malignancies and its rich tumour-derived content, represents a particularly compelling matrix for liquid biopsy analysis. This review synthesises current evidence regarding the diagnostic, predictive, and prognostic utility of pleural liquid biopsy in clinical medicine. Methods: A narrative review was conducted using PubMed, MEDLINE, and EMBASE databases. Search terms included combinations of “pleural effusion”, “liquid biopsy”, “circulating tumour DNA”, “circulating tumour cells”, “exosomes”, “next-generation sequencing”, and “biomarkers”. Priority was given to original research articles, systematic reviews, and meta-analyses published between 2013 and 2026. Results: Pleural fluid contains a diverse repertoire of tumour-derived analytes, including cell-free and circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), exosomes, and soluble proteins. These biomarkers enable molecular characterisation of underlying malignancies with sensitivity that often exceeds that of plasma-based liquid biopsy and complements histological tissue biopsy. Detection of actionable mutations, including EGFR, ALK, KRAS, and BRAF alterations, directly informs targeted therapy selection. Furthermore, serial sampling facilitates real-time monitoring of therapeutic resistance, disease progression, and clonal evolution. Conclusions: Pleural liquid biopsy offers a minimally invasive, reproducible, and clinically informative approach to molecular profiling in patients with pleural disease, particularly those with thoracic malignancies. Despite existing challenges in standardisation and analytical sensitivity, its integration into routine clinical pathways holds significant promise for advancing personalised oncological care. Multi-omics integration and artificial intelligence may further consolidate its role in therapeutic decision-making.

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