Literature DB >> 22035139

Investigation of lung cancer biomarkers by hyphenated separation techniques and chemometrics.

Bogusław Buszewski1, Agnieszka Ulanowska, Tomasz Kowalkowski, Krzysztof Cieśliński.   

Abstract

BACKGROUND: Volatile organic compounds (VOCs) present in breath of lung cancer patients and released by lung cancer cells were determined. As a reference sample breath collected from healthy volunteers and lung segments of cells with proper morphology were used.
METHODS: Solid phase microextraction and gas chromato-graphy mass spectrometry (SPME-GC/MS) method was applied for VOC analysis. Statistical methods have been developed to find similarities between patterns of investigated compounds within three populations of samples: exhaled air samples from patients with lung cancer, headspace of lung tissues with healthy and cancer cells.
RESULTS: Quantitative analysis of VOCs in the headspace of lung tissues revealed that cancer cells released higher concentrations of ethanol, acetone, carbon disulfide, dimethyl sulfide, 1-propanol, 2-propanol, 2-butanone and 2-pentanone than healthy tissues. The increase of concentration of the same compounds was observed in the breath of patients with lung cancer in comparison to breath from healthy non-smoking volunteers.
CONCLUSIONS: Detection of lung cancer is possible by volatile biomarkers analysis in breath.

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Year:  2011        PMID: 22035139     DOI: 10.1515/CCLM.2011.769

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


  14 in total

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2.  Volatile organic compounds of biofluids for detecting lung cancer by an electronic nose based on artificial neural network.

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3.  Accuracy and Methodologic Challenges of Volatile Organic Compound-Based Exhaled Breath Tests for Cancer Diagnosis: A Systematic Review and Meta-analysis.

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Review 4.  Current Challenges in Volatile Organic Compounds Analysis as Potential Biomarkers of Cancer.

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Review 5.  Breath analysis as a potential and non-invasive frontier in disease diagnosis: an overview.

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7.  Development of an Exhaled Breath Monitoring System with Semiconductive Gas Sensors, a Gas Condenser Unit, and Gas Chromatograph Columns.

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Journal:  Nat Genet       Date:  2017-12-18       Impact factor: 38.330

9.  In-silico prediction of key metabolic differences between two non-small cell lung cancer subtypes.

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