Noninvasive analysis of exhaled breath for gastric cancer diagnosis using paper-based smartphone nano-optoelectronic noses

A paper-based colorimetric sensor array with an integrated smartphone was developed to detect a wide range of volatile organic compounds (VOCs) and used for an exhaled-breath analysis of VOCs associated with gastric cancer (GC). The sensor array combines functionalized nanoplasmonic materials and chemically responsive organic dyes which change color when they come in chemical contact with VOCs. Parts per billion (ppb)-level detection is achieved based on color changes of the array. Gas chromatography-mass spectroscopy (GC-MS) analysis of the exhaled gas from GC patients and healthy candidates indicated 25 different VOCs which may be used as the biomarkers. The paper-based smartphone nano-optoelectronic nose, used in combination with orthogonal partial least squares discriminant analysis (OPLS-DA), was able to differentiate between VOCs associated with GC patients and healthy candidates with an accuracy of 90 %. This cost-effective sensor platform paves a way for further clinical breath analysis on the noninvasive screening of GC and potentially other gas detection in medical diagnosis and environmental monitoring.

Automated summary

A paper-based colorimetric sensor array combined with a smartphone was developed for detecting various VOCs and analyzing exhaled-breath for VOCs related to gastric cancer. The sensor array utilizes functionalized nanoplasmonic materials and chemically responsive organic dyes that change color upon chemical contact with VOCs. The array achieves detection at parts per billion (ppb) level based on color changes. Gas chromatography-mass spectroscopy analysis shows the presence of 25 different VOCs that can serve as biomarkers. By employing orthogonal partial least squares discriminant analysis (OPLS-DA), the paper-based smartphone nano-optoelectronic nose is capable of distinguishing between VOCs associated with gastric cancer patients and healthy candidates with 90% accuracy. This cost-effective sensor platform enables noninvasive screening of gastric cancer and other gas detection in medical diagnosis and environmental monitoring.