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

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.