The investigation of the volatile metabolites of lung cancer from the microenvironment of malignant pleural effusion

For malignant pleural effusions, pleural fluid cytology is a diagnostic method, but sensitivity is low. The pleural fluid contains metabolites directly released from cancer cells. The objective of this study was to diagnose lung cancer with malignant pleural effusion using the volatilomic profiling method. We recruited lung cancer patients with malignant pleural effusion and patients with nonmalignant diseases with pleural effusion as controls. We analyzed the headspace air of the pleural effusion by gas chromatography-mass spectrometry. We used partial least squares discriminant analysis (PLS-DA) to identify metabolites and the support vector machine (SVM) to establish the prediction model. We split data into a training set (80%) and a testing set (20%) to validate the accuracy. A total of 68 subjects were included in the final analysis. The PLS-DA showed high discrimination with an R2 of 0.95 and Q2 of 0.58. The accuracy of the SVM in the test set was 0.93 (95% CI 0.66, 0.998), the sensitivity was 83%, the specificity was 100%, and kappa was 0.85, and the area under the receiver operating characteristic curve was 0.96 (95% CI 0.86, 1.00). Volatile metabolites of pleural effusion might be used in patients with cytology-negative pleural effusion to rule out malignancy.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:11

Enthalten in:

Scientific reports - 11(2021), 1 vom: 30. Juni, Seite 13585

Sprache:

Englisch

Beteiligte Personen:

Chen, Ke-Cheng [VerfasserIn]
Tsai, Shih-Wei [VerfasserIn]
Zhang, Xiang [VerfasserIn]
Zeng, Chian [VerfasserIn]
Yang, Hsiao-Yu [VerfasserIn]

Links:

Volltext

Themen:

Clinical Trial
Journal Article
Research Support, Non-U.S. Gov't
Volatile Organic Compounds

Anmerkungen:

Date Completed 05.11.2021

Date Revised 05.11.2021

published: Electronic

Citation Status MEDLINE

doi:

10.1038/s41598-021-93032-y

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM327406925