OBJECTIVE: The aim of this study was to determine whether the volatile organic compounds (VOCs) pattern in colorectal cancer (CRC) patients is modified by curative surgery for a potential application in the oncologic follow-up. BACKGROUND: CRC has been proved to induce metabolic derangements detectable by high through-output techniques in exhaled breath showing a specific pattern of VOCs. METHODS: Forty-eight CRC patients and 55 healthy controls (HC) entered the study. Thirty-two patients (M/F: 1.4; mean age 63 years) attended the oncologic follow-up (mean 24 months) and were found disease-free. Breath samples were collected under similar environmental conditions into a Tedlar bags and processed offline by thermal-desorption gas chromatography-mass spectrometry (TD-GC-MS). VOCs were selected by U test to build a Probabilistic Neural Network (PNN) model to set-up a training phase, which was cross-validated using the leave-one out method. RESULTS: A total of 11 VOCs were finally selected for their excellent discriminant performance in identifying disease-free patients in follow-up from CRC patients before surgery, (sensitivity 100%, specificity 97.92%, accuracy 98.75%, and AUC: 1). The same VOCs pattern discriminated follow-up patients from HC, with a sensitivity of 100%, specificity of 90.91%, accuracy of 94.25%, and AUC 0.959. CONCLUSIONS: Exhaled VOCs pattern from CRC patients is modified by cancer removal confirming the tight relationship between tumor metabolism and exhaled VOCs. PNN analysis provides a high discriminatory tool to identify patients disease-free after curative surgery suggesting potential implications in CRC screening and secondary prevention.
OBJECTIVE: The aim of this study was to determine whether the volatile organic compounds (VOCs) pattern in colorectal cancer (CRC) patients is modified by curative surgery for a potential application in the oncologic follow-up. BACKGROUND: CRC has been proved to induce metabolic derangements detectable by high through-output techniques in exhaled breath showing a specific pattern of VOCs. METHODS: Forty-eight CRC patients and 55 healthy controls (HC) entered the study. Thirty-two patients (M/F: 1.4; mean age 63 years) attended the oncologic follow-up (mean 24 months) and were found disease-free. Breath samples were collected under similar environmental conditions into a Tedlar bags and processed offline by thermal-desorption gas chromatography-mass spectrometry (TD-GC-MS). VOCs were selected by U test to build a Probabilistic Neural Network (PNN) model to set-up a training phase, which was cross-validated using the leave-one out method. RESULTS: A total of 11 VOCs were finally selected for their excellent discriminant performance in identifying disease-free patients in follow-up from CRC patients before surgery, (sensitivity 100%, specificity 97.92%, accuracy 98.75%, and AUC: 1). The same VOCs pattern discriminated follow-up patients from HC, with a sensitivity of 100%, specificity of 90.91%, accuracy of 94.25%, and AUC 0.959. CONCLUSIONS: Exhaled VOCs pattern from CRC patients is modified by cancer removal confirming the tight relationship between tumor metabolism and exhaled VOCs. PNN analysis provides a high discriminatory tool to identify patients disease-free after curative surgery suggesting potential implications in CRC screening and secondary prevention.
Authors: D F Altomare; F Porcelli; A Picciariello; M Pinto; M Di Lena; O Caputi Iambrenghi; I Ugenti; A Guglielmi; L Vincenti; G De Gennaro Journal: Tech Coloproctol Date: 2016-03-21 Impact factor: 3.781
Authors: Caroline E Boulind; Oliver Gould; Ben de Lacy Costello; Joanna Allison; Paul White; Paul Ewings; Alfian N Wicaksono; Nathan J Curtis; Anne Pullyblank; David Jayne; James A Covington; Norman Ratcliffe; Claire Turner; Nader K Francis Journal: Cancers (Basel) Date: 2022-04-24 Impact factor: 6.575
Authors: Feiko J M de Jong; Thijs T Wingelaar; Paul Brinkman; Pieter-Jan A M van Ooij; Anke-Hilse Maitland-van der Zee; Marcus W Hollmann; Rob A van Hulst Journal: Front Physiol Date: 2022-05-10 Impact factor: 4.755
Authors: Ashley Bond; Rosemary Greenwood; Stephen Lewis; Bernard Corfe; Sanchoy Sarkar; Paul O'Toole; Paul Rooney; Michael Burkitt; Georgina Hold; Chris Probert Journal: Aliment Pharmacol Ther Date: 2019-03-03 Impact factor: 8.171