The diagnosis of cancer at an early stage can improve the survival rate of cancer patients worldwide. The conventional methods that used to detect cancer did not show improvement in the cancer patient‘s survival rate. Recently, the exploration of the electronic nose (E-Nose) in the biomedical field on detecting the cancer related volatile organic compound (VOCs) biomarker has shown significant potential as non-invasive cancer screening tool. The E-nose able to detect the VOCs released in the exhaled air breath of cancer patients and cancer cells during the cell growth. Thus, an improvement in the existing sensors and sensing materials in E-Nose system can lead to innovation of promising and efficient screening tool for an early stage of cancer diagnosis. As a way to the clinical reality, this project is fundamental study that aims to develop portable and reliable graphene based Quartz Crystal Microbalance (QCM) sensors for identification of cancer related VOCs. Therefore, this project conducted a preliminary study to investigate the VOCs released by cancer cell culture using commercialized E-nose system (Cyranose 320). The Cyranose 320 was used to analyze the VOCs pattern emitted by four different cell lines which are; A549 and CALU3 (LC cells), WI38VA13 (normal lung cell lines), MCF-7 (breast cancer cell lines) at an early stage of growth. The performance of the E-nose analyzed using few classification algorithms; Linear Discrimination Analysis (LDA), k-Nearest Neighbor (KNN), Probabilistic Neural Network (PNN), One versus All-Support Vector Machine (OVA-SVM) and Naïve Bayes (NB) were used. The LDA based OVA-SVM classification approach was outperformed the other classifier by classifying the VOCs of cancer cell with 99% successful performance rate at even 24th hours of cell growth. This gas sensor study has been complemented using solid phase microextraction gas chromatography mass spectrometry (SPME-GCMS) to detect the possible specific volatiles that helped the cells discrimination. The list of emitted compounds from the same samples has been analyzed and compared with documented volatile biomarkers to obtain the final specific cancer related volatiles. Finally, the highly sensitive E-nose system using a QCM sensor array was developed in this project to detect the targeted cancer VOCs. The graphene based sensing material able to be fulfilling the crucial sensor necessity and form a solid groundwork for the identification of cancer related VOC. Thus, the graphene oxide, reduced graphene oxide and non-covalently modified graphene oxide based sensing materials were coated to tune the sensor‘s sensitivity and selectivity toward the polar and non-polar group of VOCs. The frequency changes of each sensor due to the absorption of the targeted volatile molecules have been recorded and analyzed to test the performance of the gas sensor array. The study concluded that the graphene based sensing materials coated QCM gas sensors able to give high sensitivity, selectivity, reproducibility, repeatability and high response time for the detection of cancer related volatiles.
