Classification of breast cancer precursors through exhaled breath
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Certain benign breast diseases are considered to be precursors of invasive breast cancer. Currently available techniques for diagnosing benign breast conditions lack accuracy. The purpose of this study was to deliver a proof-of-concept for a novel method that is based on breath testing to identify breast cancer precursors. Within this context, the authors explored the possibility of using exhaled alveolar breath to identify and distinguish between benign breast conditions, malignant lesions, and healthy states, using a small-scale, case-controlled, cross-sectional clinical trial. Breath samples were collected from 36 volunteers and were analyzed using a tailor-made nanoscale artificial NOSE (NA-NOSE). The NA-NOSE signals were analyzed using two independent methods: (i) principal component analysis, ANOVA and Student’s t-test and (ii) support vector machine analysis to detect statistically significant differences between the sub-populations. The NA-NOSE could distinguish between all studied test populations. Breath testing with a NA-NOSE holds future potential as a cost-effective, fast, and reliable diagnostic test for breast cancer risk factors and precursors, with possible future potential as screening method.
KeywordsBreast cancer Benign Classification Volatile biomarkers Breath Sensor NA-NOSE
Infiltrating ductal carcinoma
Ductal carcinoma in situ
Nanoscale artificial NOSE
Principle component analysis
Support vector machine
The research was funded by the Marie Curie Excellence Grant of the European Commission’s FP6 program (H.H.), the Alfred Mann Institute (H.H.), and the Friends for an Earlier Breast Cancer Test (H.H.). The authors acknowledge Ms. Rana Bassal and Ms. Nisreen Shehada (Technion-IIT) for their assistance in breath collection. H.H. is a Knight of the Order of Academic Palms and holds the Horev Chair for Leaders in Science and Technology.
Conflicts of interest
All co-authors declare no competing interests related to the study.
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