Volatile Organic Compounds (VOCs) Profile in Colorectal Cancer Patients and Healthy Controls.

2020 ◽  
Author(s):  
Keyword(s):  
Colorectal Cancer ◽  
Volatile Organic Compounds ◽  
Cancer Patients ◽  
Organic Compounds ◽  
Healthy Controls ◽  
Volatile Organic ◽  
Colorectal Cancer Patients

scholarly journals A prediction model using 2-propanol and 2-butanone in urine distinguishes breast cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shoko Kure ◽  
Sera Satoi ◽  
Toshihiko Kitayama ◽  
Yuta Nagase ◽  
Nobuo Nakano ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Volatile Organic Compounds ◽  
Cancer Patients ◽  
Organic Compounds ◽  
External Validation ◽  
Healthy Controls ◽  
Breast Cancer Patients ◽  
Training Set ◽  
Volatile Organic ◽  
Validation Set

AbstractSafe and noninvasive methods for breast cancer screening with improved accuracy are urgently needed. Volatile organic compounds (VOCs) in biological samples such as breath and blood have been investigated as noninvasive novel markers of cancer. We investigated volatile organic compounds in urine to assess their potential for the detection of breast cancer. One hundred and ten women with biopsy-proven breast cancer and 177 healthy volunteers were enrolled. The subjects were divided into two groups: a training set and an external validation set. Urine samples were collected and analyzed by gas chromatography and mass spectrometry. A predictive model was constructed by multivariate analysis, and the sensitivity and specificity of the model were confirmed using both a training set and an external set with reproducibility tests. The training set included 60 breast cancer patients (age 34–88 years, mean 60.3) and 60 healthy controls (age 34–81 years, mean 58.7). The external validation set included 50 breast cancer patients (age 35–85 years, mean 58.8) and 117 healthy controls (age 18–84 years, mean 51.2). One hundred and ninety-one compounds detected in at least 80% of the samples from the training set were used for further analysis. The predictive model that best-detected breast cancer at various clinical stages was constructed using a combination of two of the compounds, 2-propanol and 2-butanone. The sensitivity and specificity in the training set were 93.3% and 83.3%, respectively. Triplicated reproducibility tests were performed by randomly choosing ten samples from each group, and the results showed a matching rate of 100% for the breast cancer patient group and 90% for the healthy control group. Our prediction model using two VOCs is a useful complement to the current diagnostic tools. Further studies inclusive of benign tumors and non-breast malignancies are warranted.

scholarly journals Are Volatile Organic Compounds Accurate Markers in the Assessment of Colorectal Cancer and Inflammatory Bowel Diseases? A Review

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2361
Author(s):  
Filippo Vernia ◽  
Marco Valvano ◽  
Stefano Fabiani ◽  
Gianpiero Stefanelli ◽  
Salvatore Longo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Inflammatory Bowel Diseases ◽  
Screening Programs ◽  
Inflammatory Status ◽  
Incidence And Mortality ◽  
Volatile Organic ◽  
Bowel Diseases ◽  
Inflammatory Bowel

Colorectal cancer (CRC) is one of the leading causes of cancer-related death in the Western world. Early detection decreases incidence and mortality. Screening programs based on fecal occult blood testing help identify patients requiring endoscopic examination, but accuracy is far from optimal. Among the alternative strategies, volatile organic compounds (VOCs) represent novel potentially useful biomarkers of colorectal cancer. They also represent a promising tool for the screening of both intestinal inflammation and related CRC. The review is focused on the diagnostic potential of VOCs in sporadic CRC and in inflammatory bowel diseases (IBD), which increase the risk of CRC, analyzing future clinical applications. Despite limitations related to inadequate strength of evidence, differing analytical platforms identify different VOCs, and this unconventional approach for diagnosing colorectal cancer is promising. Some VOC profiles, besides identifying inflammation, seem disease-specific in inflammatory bowel diseases. Thus, breath, urine, and fecal VOCs provide a new and promising clinical approach to differential diagnosis, evaluation of the inflammatory status, and possibly the assessment of treatment efficacy in IBD. Conversely, specific VOC patterns correlating inflammatory bowel disease and cancer risk are still lacking, and studies focused on this issue are strongly encouraged. No prospective studies have assessed the risk of CRC development by using VOCs in samples collected before the onset of disease, both in the general population and in patients with IBD.

scholarly journals Target Analysis of Volatile Organic Compounds in Exhaled Breath for Lung Cancer Discrimination from Other Pulmonary Diseases and Healthy Persons

Metabolites ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 317
Author(s):  
Michalis Koureas ◽  
Paraskevi Kirgou ◽  
Grigoris Amoutzias ◽  
Christos Hadjichristodoulou ◽  
Konstantinos Gourgoulianis ◽  
...  
Keyword(s):  
Machine Learning ◽  
Computed Tomography ◽  
Lung Cancer ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Ambient Air ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Healthy Controls ◽  
Volatile Organic

The aim of the present study was to investigate the ability of breath analysis to distinguish lung cancer (LC) patients from patients with other respiratory diseases and healthy people. The population sample consisted of 51 patients with confirmed LC, 38 patients with pathological computed tomography (CT) findings not diagnosed with LC, and 53 healthy controls. The concentrations of 19 volatile organic compounds (VOCs) were quantified in the exhaled breath of study participants by solid phase microextraction (SPME) of the VOCs and subsequent gas chromatography-mass spectrometry (GC-MS) analysis. Kruskal–Wallis and Mann–Whitney tests were used to identify significant differences between subgroups. Machine learning methods were used to determine the discriminant power of the method. Several compounds were found to differ significantly between LC patients and healthy controls. Strong associations were identified for 2-propanol, 1-propanol, toluene, ethylbenzene, and styrene (p-values < 0.001–0.006). These associations remained significant when ambient air concentrations were subtracted from breath concentrations. VOC levels were found to be affected by ambient air concentrations and a few by smoking status. The random forest machine learning algorithm achieved a correct classification of patients of 88.5% (area under the curve—AUC 0.94). However, none of the methods used achieved adequate discrimination between LC patients and patients with abnormal computed tomography (CT) findings. Biomarker sets, consisting mainly of the exogenous monoaromatic compounds and 1- and 2- propanol, adequately discriminated LC patients from healthy controls. The breath concentrations of these compounds may reflect the alterations in patient’s physiological and biochemical status and perhaps can be used as probes for the investigation of these statuses or normalization of patient-related factors in breath analysis.

scholarly journals Global Plasma Profiling for Colorectal Cancer-Associated Volatile Organic Compounds: a Proof-of-Principle Study

2019 ◽  
Vol 57 (5) ◽  
pp. 385-396 ◽  
Author(s):  
Seongho Kim ◽  
Xinmin Yin ◽  
Md Aminul Islam Prodhan ◽  
Xiang Zhang ◽  
Zichun Zhong ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Volatile Organic ◽  
Proof Of Principle

scholarly journals Breath Analysis for Early Detection of Malignant Pleural Mesothelioma: Volatile Organic Compounds (VOCs) Determination and Possible Biochemical Pathways

Cancers ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1262 ◽  
Author(s):  
Alessia Di Gilio ◽  
Annamaria Catino ◽  
Angela Lombardi ◽  
Jolanda Palmisani ◽  
Laura Facchini ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Early Detection ◽  
Organic Compounds ◽  
Malignant Pleural Mesothelioma ◽  
Breath Analysis ◽  
Machine Learning Algorithms ◽  
Diagnostic Methods ◽  
Pleural Mesothelioma ◽  
Healthy Controls ◽  
Volatile Organic

Malignant pleural mesothelioma (MPM) is a rare neoplasm, mainly caused by asbestos exposure, with a high mortality rate. The management of patients with MPM is controversial due to a long latency period between exposure and diagnosis and because of non-specific symptoms generally appearing at advanced stage of the disease. Breath analysis, aimed at the identification of diagnostic Volatile Organic Compounds (VOCs) pattern in exhaled breath, is believed to improve early detection of MPM. Therefore, in this study, breath samples from 14 MPM patients and 20 healthy controls (HC) were collected and analyzed by Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC/MS). Nonparametric test allowed to identify the most weighting variables to discriminate between MPM and HC breath samples and multivariate statistics were applied. Considering that MPM is an aggressive neoplasm leading to a late diagnosis and thus the recruitment of patients is very difficult, a promising data mining approach was developed and validated in order to discriminate between MPM patients and healthy controls, even if no large population data are available. Three different machine learning algorithms were applied to perform the classification task with a leave-one-out cross-validation approach, leading to remarkable results (Area Under Curve AUC = 93%). Ten VOCs, such as ketones, alkanes and methylate derivates, as well as hydrocarbons, were able to discriminate between MPM patients and healthy controls and for each compound which resulted diagnostic for MPM, the metabolic pathway was studied in order to identify the link between VOC and the neoplasm. Moreover, five breath samples from asymptomatic asbestos-exposed persons (AEx) were exploratively analyzed, processed and tested by the validated statistical method as blinded samples in order to evaluate the performance for the early recognition of patients affected by MPM among asbestos-exposed persons. Good agreement was found between the information obtained by gold-standard diagnostic methods such as computed tomography CT and model output.

Volatile organic compounds as new biomarkers for colorectal cancer: a review

2016 ◽  
Vol 18 (7) ◽  
pp. 654-663 ◽  
Author(s):  
M. Di Lena ◽  
F. Porcelli ◽  
D. F. Altomare
Keyword(s):  
Colorectal Cancer ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Volatile Organic ◽  
New Biomarkers
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