Application of breathomics in early detection of lung cancer in indian population: a pilot study

Abstract

<b>Rationale:</b> Lung cancer is the most fatal cancer. Breathomics unveils opportunities for noninvasive biomarker discovery for lung cancer diagnosis. The exhaled air received from the respiratory tract consist of VOCs, proteins, and RNAs that may be unique to lung cancer morphology. <b>Objectives:</b> To co-relate the differential expression of miRNAs with breath prints in lung cancer patients. <b>Methods:</b> Treatment naïve patients with confirmed lung cancer were enrolled. Exhaled air was collected in a Tedlar bag and analyzed by E-Nose (Cyranose-320), and Exhaled Breath Condensate (EBC) was collected in R-Tubes and microRNAs profiling was performed by SBI kit. Breath print was analyzed by the formula of Rt-R0/R0 and by linear discriminant analysis on principal component in R-package. Differential expression of miRNAs was analyzed by unpaired t-test. <b>Results:</b> 20 healthy subjects [75% males, mean (SD) age: 38.2 (11.4)] and 20 confirmed lung cancer patients [70% males, mean (SD) age: 54.8 (9.6)] were enrolled. These included 14 adenocarcinoma &amp; 6 squamous cell carcinoma, with 9 stage-III &amp; 11 stage IV disease. The linear discriminant analysis could separate the breath prints of these two groups significantly (p&lt;0.05, accuracy=85%). Further, tumorigenic miRNAs were found to be up-regulated and anti-tumorigenic miRNAs were down regulated in the EBC samples, after applying multiple normalization algorithms and significant threshold of a P&lt;0.05. <b>Conclusion:</b> The exhaled breath analysis could accurately differentiate lung cancer patients from healthy controls. Corroborating the exhaled breath analysis, breathomics could be used as a potential non-invasive tool to identify lung cancer phenotype in early stage.