| Literature DB >> 33996531 |
Yoon Ju Jung1, Ho Seok Seo1, Ji Hyun Kim1, Kyo Young Song1, Cho Hyun Park1, Han Hong Lee1.
Abstract
BACKGROUND: Screening endoscopy is considered to be the most accurate tool for early detection of gastric cancer, but it is both invasive and costly. It is therefore essential to develop cost-effective and non-invasive diagnostic tools for gastric cancer. The aim of this study is to investigate the presence of certain volatile organic compounds (VOCs) associated with gastric cancer and to survey the usefulness of VOCs as screening tools of gastric cancer.Entities:
Keywords: breath analysis; diagnosis; screening; stomach neoplasm; volatile organic compound
Year: 2021 PMID: 33996531 PMCID: PMC8116791 DOI: 10.3389/fonc.2021.560591
Source DB: PubMed Journal: Front Oncol ISSN: 2234-943X Impact factor: 6.244
Figure 1The analysis of volatile organic compounds (VOCs) from exhaled breath via Proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS). This analysis is based on the concept that VOCs are not derived directly from the lung or GI organs but from the metabolic origin through the blood circulating system. Participants’ exhaled breaths samples were repeatedly collected through the mouth inlet of PTR-TOF-MS.
Counts per second of the VOCs according to the Cancer Stages.
| Normal (N=17) | EGC (N=16) | AGC (N=10) | P value | |
|---|---|---|---|---|
|
| 15127.0 | 35272.2 | 51243.3 | 0.003 |
|
| 942.5 | 1801.5 | 3070.6 | 0.007 |
|
| 2096.0 | 5232.7 | 6179.1 | 0.020 |
|
| 37.9 | 159.0 | 216.7 | 0.025 |
|
| 658.0 | 413.5 | 569.0 | 0.137 |
|
| 92.0 | 61.5 | 64.5 | 0.098 |
|
| 18.0 | 11.5 | 14.0 | 0.050 |
|
| 95.0 | 40.0 | 49.5 | 0.021 |
|
| 92.0 | 36.0 | 50.5 | 0.016 |
The median values were presented and the numbers in square brackets mean ranges. Chi square test was used to evaluate between-group differences in categorical variables and a p value < 0.05 was deemed to indicate statistical significance. EGC, Early gastric cancer; AGC, Advanced gastric cancer.
Figure 2Box plot for the volatile organic compounds (VOCs) according to cancer status. (A–D) When patients were grouped according to cancer stage, four VOCs were seen to gradually increase as cancer advanced (Propanal, Aceticamide, Isoprene, and 1,3 propanediol, respectively (P = 0.003, P = 0.007, P = 0.020 and P = 0.025, respectively). (E, F) The two the VOCs showed no significant differences among the three groups (methyl isobutyl ketone, P = 0.998 and acetic acid, P = 0.050). (G, H) Two of the VOCs that were lower in cancer patients than in controls showed significant differences among the three groups, but these were not correlated with cancer stage (m-tolualdehyde, P = 0.021, and 1, 3, 5-trimethylbenzene, P = 0.016).
Accuracy, sensitivity and specificity for the Volatile organic compounds for the gastric cancer prediction model.
| Accuracy (AUC) | Sensitivity | Specificity | Negative predictive value | Positive predictive value | |
|---|---|---|---|---|---|
|
| 78.1% | 53.8% | 100.0% | 58.6% | 100% |
|
| 75.6% | 61.5% | 88.2% | 60.0% | 88.9% |
|
| 74.4% | 84.6% | 64.7% | 64.7% | 78.6% |
|
| 73.1% | 73.1% | 76.5% | 65.0% | 82.6% |
|
| 84.2% | 61.5% | 94.1% | 61.5% | 94.1% |
*When a VOC level was higher than its cut-off value, the VOC was defined as positive and a new Receiver Operating Characteristic curve was constructed based on the positivity status of the four VOCs. AUC, Area under curve.
Figure 3The Receiver operating characteristic (ROC) curves for the effectiveness of volatile organic compounds (VOCs) to predict gastric cancer. The ROC curves were constructed for the four VOCs that increased with cancer stage. The areas under the curve (AUC) for gastric cancer prediction ranged from 0.731 to 0.781 among the VOCs. Propanal showed highest level of AUC of 0.781 with cutoff value of 40 445.87 cps.
Figure 4The Receiver operating characteristic (ROC) curve of a new predicting model including the four volatile organic compounds (VOCs). When a VOC level was higher than its cut-off value, the VOC was defined as positive, and a new ROC curve was constructed based on the positivity status of the four VOCs. This model showed the highest AUC of 0.842 with 61% sensitivity and 94% specificity when more than two VOCs were positive.