4.7 Article

Urinary Volatiles and Chemical Characterisation for the Non-Invasive Detection of Prostate and Bladder Cancers

期刊

BIOSENSORS-BASEL
卷 11, 期 11, 页码 -

出版社

MDPI
DOI: 10.3390/bios11110437

关键词

bladder cancer; prostate cancer; urinary biomarkers; urinary VOCs; machine olfaction; GC-IMS; GC-TOF-MS

向作者/读者索取更多资源

Bladder cancer and prostate cancer are commonly diagnosed with invasive techniques, but a non-invasive diagnostic approach using volatile organic compounds (VOCs) shows promise. Analysis of urinary VOC profiles using GC-IMS and GC-TOF-MS can effectively distinguish between BCa and PCa, offering potential for cancer diagnosis.
Bladder cancer (BCa) and prostate cancer (PCa) are some of the most common cancers in the world. In both BCa and PCa, the diagnosis is often confirmed with an invasive technique that carries a risk to the patient. Consequently, a non-invasive diagnostic approach would be medically desirable and beneficial to the patient. The use of volatile organic compounds (VOCs) for disease diagnosis, including cancer, is a promising research area that could support the diagnosis process. In this study, we investigated the urinary VOC profiles in BCa, PCa patients and non-cancerous controls by using gas chromatography-ion mobility spectrometry (GC-IMS) and gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) to analyse patient samples. GC-IMS separated BCa from PCa (area under the curve: AUC: 0.97 (0.93-1.00)), BCa vs. non-cancerous (AUC: 0.95 (0.90-0.99)) and PCa vs. non-cancerous (AUC: 0.89 (0.83-0.94)) whereas GC-TOF-MS differentiated BCa from PCa (AUC: 0.84 (0.73-0.93)), BCa vs. non-cancerous (AUC: 0.81 (0.70-0.90)) and PCa vs. non-cancerous (AUC: 0.94 (0.90-0.97)). According to our study, a total of 34 biomarkers were found using GC-TOF-MS data, of which 13 VOCs were associated with BCa, seven were associated with PCa, and 14 VOCs were found in the comparison of BCa and PCa.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据