Dataset Information

Serum metabolomic profiles for distinguishing lung cancer from pulmonary tuberculosis: identification of rapid and noninvasive biomarker

ABSTRACT:

BACKGROUND: Pulmonary tuberculosis (TB) and lung cancer (LC) have similar clinical symptoms and atypical imaging findings which are easily misdiagnosed. There is an urgent need for a noninvasive, rapid and accurate biomarker for distinguishing LC from TB.

METHODS: A total of 694 subjects were enrolled and divided into discovery set (n=122), validation set (n=214) and another validation set (n=358). Metabolites were identified by multivariate and univariate analyses. The random forest (RF) algorithm and receiver operating characteristic curve analysis were used to evaluate the diagnostic efficacy of the biomarkers.

RESULTS: Seven metabolites were identified and validated. The mean decrease accuracy of phenylalanylphenylalanine ranked first in RF analysis. The area under the curve of phenylalanylphenylalanine was 0.8885 (95% CI 0.8444-0.9326), the sensitivity was 71.43%, and the specificity was 92.13%. Compared with that in NC subjects, the level of phenylalanylphenylalanine was elevated in LC patients (fold change = 2.92, p value < 0.01) and reduced in TB patients (fold change = 0.80, p value < 0.05).

CONCLUSIONS: The metabolomic profile of LC and TB was described and a key biomarker, phenylalanylphenylalanine, was identified. We produced a rapid and noninvasive method to supplement existing clinical diagnostic examinations for distinguishing LC from TB.

INSTRUMENT(S): Liquid Chromatography MS - positive - reverse phase

SUBMITTER: siyu chen

PROVIDER: MTBLS6990 | MetaboLights | 2024-01-16

REPOSITORIES: MetaboLights

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Publications

Serum Metabolomic Profiles for Distinguishing Lung Cancer From Pulmonary Tuberculosis: Identification of Rapid and Noninvasive Biomarker.

Chen Siyu S Li Chunyan C Qin Zhonghua Z Song Lili L Zhang Shiyuan S Sun Chongxiang C Zhuang Pengwei P Wang Yuming Y Yang Bin B Ning Li L Li Yubo Y

The Journal of infectious diseases 20231101 9

<h4>Background</h4>Pulmonary tuberculosis (PTB) and lung cancer (LC) have similar clinical symptoms and atypical imaging findings, which are easily misdiagnosed. There is an urgent need for a noninvasive and accurate biomarker to distinguish LC from PTB.<h4>Methods</h4>A total of 694 subjects were enrolled and divided into discovery set (n = 122), identification set (n = 214), and validation set (n = 358). Metabolites were identified by multivariate and univariate analyses. Receiver operating ch ...[more]

PMID: 37246562

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Project description:Bronchoscopy is a frequently used initial diagnostic procedure for patients with suspected lung cancer (LC). Cytological examinations of bronchial washing (BW) samples obtained during bronchoscopy often yield inconclusive results regarding LC diagnosis. The present study aimed to identify molecular biomarkers as a non-invasive method for LC diagnosis. Aberrant DNA methylation is used as a useful biomarker for LC. Therefore, microarray-based methylation profiling analyses on 13 patient-matched tumor tissues at stages I-III vs. non-tumor tissues were performed, and a group of highly differentially methylated genes was identified. A subsequent analysis using bisulfite-pyrosequencing with additional tissues and cell lines revealed six methylated genes [ADAM metallopeptidase with thrombospondin type 1 motif 20, forkhead box C2 (mesenchyme forkhead 1), NK2 transcription factor related, locus 5 (Drosophila), oligodendrocyte transcription factor 3, protocadherin γ subfamily A 12 (PCDHGA12) and paired related homeobox 1 (PRRX1)] associated with LC. Next, a highly sensitive and accurate detection method, linear target enrichment-quantitative methylation-specific PCR in a single closed tube, was applied for clinical validation using BW samples from patients with LC (n=68) and individuals with benign diseases (n=33). PCDHGA12 and PRRX1 methylation were identified as the best-performing biomarkers to detect LC. The two-marker combination showed a sensitivity of 82.4% and a specificity of 87.9%, with an area under the curve of 0.891. Notably, the sensitivity for small cell LC was 100%. The two-marker combination had a positive predictive value of 93.3% and a negative predictive value of 70.7%. The sensitivity was higher than that of cytology, which only had a sensitivity of 50%. The methylation status of the two-marker combination showed no association with sex, age or stage, but was associated with tumor location and histology. In conclusion, the present study showed that the regulatory regions of PCDHGA12 and PRRX1 are highly methylated in LC and can be used to detect LC in BW specimens as a diagnostic adjunct to cytology in clinical practice.

Dataset Information

Serum metabolomic profiles for distinguishing lung cancer from pulmonary tuberculosis: identification of rapid and noninvasive biomarker

Publications

Serum Metabolomic Profiles for Distinguishing Lung Cancer From Pulmonary Tuberculosis: Identification of Rapid and Noninvasive Biomarker.

Similar Datasets

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