Detection of Lung Cancer through Metabolic Changes Measured in Blood Plasma. Issue 4 (April 2016)
- Record Type:
- Journal Article
- Title:
- Detection of Lung Cancer through Metabolic Changes Measured in Blood Plasma. Issue 4 (April 2016)
- Main Title:
- Detection of Lung Cancer through Metabolic Changes Measured in Blood Plasma
- Authors:
- Louis, Evelyne
Adriaensens, Peter
Guedens, Wanda
Bigirumurame, Theophile
Baeten, Kurt
Vanhove, Karolien
Vandeurzen, Kurt
Darquennes, Karen
Vansteenkiste, Johan
Dooms, Christophe
Shkedy, Ziv
Mesotten, Liesbet
Thomeer, Michiel - Abstract:
- ABSTRACT : Introduction: : Low‐dose computed tomography, the currently used tool for lung cancer screening, is characterized by a high rate of false‐positive results. Accumulating evidence has shown that cancer cell metabolism differs from that of normal cells. Therefore, this study aims to evaluate whether the metabolic phenotype of blood plasma allows detection of lung cancer. Methods: : The proton nuclear magnetic resonance spectrum of plasma is divided into 110 integration regions, representing the metabolic phenotype. These integration regions reflect the relative metabolite concentrations and were used to train a classification model in discriminating between 233 patients with lung cancer and 226 controls. The validity of the model was examined by classifying an independent cohort of 98 patients with lung cancer and 89 controls. Results: : The model makes it possible to correctly classify 78% of patients with lung cancer and 92% of controls, with an area under the curve of 0.88. Important moreover is the fact that the model is convincing, which is demonstrated by validation in the independent cohort with a sensitivity of 71%, a specificity of 81%, and an area under the curve of 0.84. Patients with lung cancer have increased glucose and decreased lactate and phospholipid levels. The limited number of patients in the subgroups and their heterogeneous nature do not (yet) enable differentiation between histological subtypes and tumor stages. Conclusions: : MetabolicABSTRACT : Introduction: : Low‐dose computed tomography, the currently used tool for lung cancer screening, is characterized by a high rate of false‐positive results. Accumulating evidence has shown that cancer cell metabolism differs from that of normal cells. Therefore, this study aims to evaluate whether the metabolic phenotype of blood plasma allows detection of lung cancer. Methods: : The proton nuclear magnetic resonance spectrum of plasma is divided into 110 integration regions, representing the metabolic phenotype. These integration regions reflect the relative metabolite concentrations and were used to train a classification model in discriminating between 233 patients with lung cancer and 226 controls. The validity of the model was examined by classifying an independent cohort of 98 patients with lung cancer and 89 controls. Results: : The model makes it possible to correctly classify 78% of patients with lung cancer and 92% of controls, with an area under the curve of 0.88. Important moreover is the fact that the model is convincing, which is demonstrated by validation in the independent cohort with a sensitivity of 71%, a specificity of 81%, and an area under the curve of 0.84. Patients with lung cancer have increased glucose and decreased lactate and phospholipid levels. The limited number of patients in the subgroups and their heterogeneous nature do not (yet) enable differentiation between histological subtypes and tumor stages. Conclusions: : Metabolic phenotyping of plasma allows detection of lung cancer, even in an early stage. Increased glucose and decreased lactate levels are pointing to an increased gluconeogenesis and are in accordance with recently published findings. Furthermore, decreased phospholipid levels confirm the enhanced membrane synthesis. … (more)
- Is Part Of:
- Journal of thoracic oncology. Volume 11:Issue 4(2016)
- Journal:
- Journal of thoracic oncology
- Issue:
- Volume 11:Issue 4(2016)
- Issue Display:
- Volume 11, Issue 4 (2016)
- Year:
- 2016
- Volume:
- 11
- Issue:
- 4
- Issue Sort Value:
- 2016-0011-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2016-04
- Subjects:
- Lung cancer -- 1H‐NMR spectroscopy -- Metabolic phenotype -- Blood plasma biomarker -- Risk model
Chest -- Cancer -- Periodicals
Thoracic Neoplasms -- Periodicals
616.99494005 - Journal URLs:
- http://gateway.ovid.com/ovidweb.cgi?T=JS&MODE=ovid&NEWS=n&PAGE=toc&D=ovft&AN=01243894-000000000-00000 ↗
http://gateway.ovid.com/ovidweb.cgi?T=JS&MODE=ovid&PAGE=toc&D=ovft&AN=01243894-200601000-00001 ↗
http://www.sciencedirect.com/science/journal/15560864/ ↗
http://journals.lww.com/pages/default.aspx ↗ - DOI:
- 10.1016/j.jtho.2016.01.011 ↗
- Languages:
- English
- ISSNs:
- 1556-0864
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5069.124000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 11127.xml