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Sci Rep. 2017 Feb 7;7:42190. doi: 10.1038/srep42190.

Bronchoalveolar Lavage Proteomics in Patients with Suspected Lung Cancer.

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Computational and Experimental Biology Group, Health Promotion and Chronic Diseases Department, National Institute of Health Dr Ricardo Jorge, Lisbon, Portugal.
Computational and Experimental Biology Group, CEDOC, Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Lisboa, Portugal.
Unidade de Técnicas Invasivas Pneumológicas, Pneumologia II, Hospital Pulido Valente, Centro Hospitalar Lisboa Norte, Lisbon, Portugal.
Instituto de Saúde Ambiental, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal.
Department of Pulmonology, Unidade Local de Saúde da Guarda, Faculty of Health Sciences, University of Beira Interior, Portugal.
Instituto de Investigação e Inovação em Saúde, Universidade do Porto (I3S), Porto, Portugal.
Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), Porto, Portugal.
Proteomics Platform, CIC bioGUNE, CIBERehd, ProteoRed-ISCIII, Bizkaia Science and Technology Park, Derio, Spain.
Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, William Duncan Building, 6 West Derby Street, Liverpool, L7 8TX, UK.


Lung cancer configures as one of the deadliest types of cancer. The future implementation of early screening methods such as exhaled breath condensate analysis and low dose computed tomography (CT) as an alternative to current chest imaging based screening will lead to an increased burden on bronchoscopy units. New approaches for improvement of diagnosis in bronchoscopy units, regarding patient management, are likely to have clinical impact in the future. Diagnostic approaches to address mortality of lung cancer include improved early detection and stratification of the cancers according to its prognosis and further response to drug treatment. In this study, we performed a detailed mass spectrometry based proteome analysis of acellular bronchoalveolar lavage (BAL) fluid samples on an observational prospective cohort consisting of 90 suspected lung cancer cases which were followed during two years. The thirteen new lung cancer cases diagnosed during the follow up time period clustered, based on liquid chromatography-mass spectrometry (LC-MS) data, with lung cancer cases at the time of BAL collection. Hundred and thirty-tree potential biomarkers were identified showing significantly differential expression when comparing lung cancer versus non-lung cancer. The regulated biomarkers showed a large overlap with biomarkers detected in tissue samples.

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