Screening for volatile biomarkers of colorectal cancer by analyzing breath and fecal samples using thermal desorption combined with GC-MS (TD-GC-MS)

Abstract

Breath and fecal volatile organic compounds (VOCs), among others, represent a new and encouraging clinical practice for the differential diagnosis of colorectal cancer (CRC). The purpose of our research was to identify VOCs present in exhaled air and feces of 20 healthy volunteers (HV) and 15 CRC patients. For collection of gas phase released from feces, emission microchambers were applied. Sorption tubes were used to enrich analytes for both breath and fecal samples. Thermal desorption (TD) technique combined with gas chromatography coupled with mass spectrometry was used at the separation and identification step. The combination of statistical methods was used to evaluate the ability of VOCs to classify control group and CRC patients. Heptanoic acid, acetone, 2,6,10-trimethyldodecane, n-hexane, skatole, and dimethyl trisulfide are observed in elevated amounts in the patients group. The performance of diagnostic models on the tested data set was above 90%. This study is the first attempt to document the using of TD-GC-MS to analyze both breath and fecal samples to search for volatile biomarkers of CRC. A full evaluation of the results described herein requires further studies involving a larger number of samples. Moreover, it is particularly important to understand the metabolic pathways of substances postulated as tumor biomarkers.

Breath Fingerprint of Colorectal Cancer Patients Based on the Gas Chromatography–Mass Spectrometry Analysis

“…for CRC, identified key VOCs (tetradecane, ethylbenzene, and benzaldehyde) that overlap with those found in our study, lending further credibility to these compounds as potential biomarkers [17]. Additionally, Śmiełowska et al's study on both breath and fecal samples from CRC patients demonstrates not only the diversity in VOCs but also the differences in their concentrations across different sample types, indicating that the VOC profile might be more pronounced in breath samples [36].…”

Advancing Colorectal Cancer Diagnosis with AI-Powered Breathomics: Navigating Challenges and Future Directions

“…Other forms of preprocessing align more to the quality assurance of the data. Such procedures include the removal of artefacts, suppression of noise, and handling the missing values via imputation [34]. These types of transformations can also enhance the performance of ML algorithms in terms of faster convergence in the optimization process, robustness of results, and accuracy [75].…”

“…Searching for statistically significant differences between breath profiles of CRC patients and healthy controls, one needs to take into account the multiple comparison problem to ensure no false discoveries [33]. Today, breath-based VOCs reported as biomarkers for CRC detection exhibit a substantial amount of variation in the scientific literature [8,[34][35][36][37][38][39][40][41][42][43][44]. Fifth, achieving strong predictive values for disease diagnosis and monitoring large-scale, multicenter clinical trials with blind validation are required [30].…”