Chemoresistive Nanosensors Employed to Detect Blood Tumor Markers in Patients Affected by Colorectal Cancer in a One-Year Follow Up

SIMPLE SUMMARY: Since colorectal cancer represents one of the most diffused pathologies worldwide, usually lacking specific symptoms, it is crucial to develop and validate innovative low-invasive techniques to detect it. Here, a device based on an array of nanostructured gas sensors has been employed to analyze and discriminate the exhalations of blood samples collected from colorectal cancer-affected patients at different stages of their pre- and post-surgery therapeutic path. The device was clearly able to distinguish between the pre-surgery samples, where the tumor was present, and the one-year post-surgery ones, following the tumor removal. These results raise high hopes for the device’s clinical validation and its future use in clinical follow-up protocols, patient health status monitoring, and to detect possible post-treatment relapses. ABSTRACT: Colorectal cancer (CRC) represents 10% of the annual tumor diagnosis and deaths occurring worldwide. Given the lack of specific symptoms, which could determine a late diagnosis, the research for specific CRC biomarkers and for innovative low-invasive methods to detect them is crucial. Therefore, on the basis of previously published results, some volatile organic compounds (VOCs), detectable through gas sensors, resulted in particularly promising CRC biomarkers, making these sensors suitable candidates to be employed in CRC screening devices. A new device was employed here to analyze the exhalations of blood samples collected from CRC-affected patients at different stages of their pre- and post-surgery therapeutic path, in order to assess the sensor’s capability for discriminating among these samples. The stages considered were: the same day of the surgical treatment (T1); before the hospital discharge (T2); after one month and after 10–12 months from surgery (T3 and T4, respectively). This device, equipped with four different sensors based on different metal–oxide mixtures, enabled a distinction between T1 and T4 with a sensitivity and specificity of 93% and 82%, respectively, making it suitable for clinical follow-up protocols, patient health status monitoring and to detect possible post-treatment relapses.