期刊
CANCERS
卷 13, 期 9, 页码 -出版社
MDPI
DOI: 10.3390/cancers13092190
关键词
colorectal cancer; multiple reaction monitoring; tandem mass spectrometer; wheat germ agglutinin; plasma; machine learning algorithm
类别
资金
- Academia Sinica Core Facility and Innovative Instrument Project [AS-CFII-108-107]
Colorectal cancer is the third leading cause of cancer-related mortality globally. The study developed a detection method combining WGA chromatography with mass spectrometry to identify potential biomarkers for early diagnosis of CRC with high sensitivity and specificity. The research demonstrated the effectiveness of combining WGA-captured plasma PF4, ITIH4, and APOE levels as highly effective early diagnostic biomarkers for CRC patients.
Simple Summary Colorectal cancer (CRC) is currently the third leading cause of cancer death worldwide. Early diagnosis of CRC is important for increasing the opportunity for treatment and receiving a good prognosis. The aim of our study was to develop a detection method that combined wheat germ agglutinin (WGA) chromatography with mass spectrometry (MS) for early detection of CRC. Further, machine learning algorithms and logistic regression were applied to combine multiple biomarkers we discovered. We validated in a population of 286 plasma samples the diagnostic performance of peptides corresponding to WGA-captured protein and its combination, which received a sensitivity of 84.5% and a specificity of 97.5% in the diagnoses of CRC. Proteomic biomarkers combined with algorithms can provide a powerful tool for discriminating patients with CRC and health controls (HCs). Measurements of WGA-captured PF4, ITIH4, and APOE with MS are then useful for early detection of CRC. Additionally, our study revealed the potential of applying lectin chromatography with MS for disease diagnosis. Colorectal cancer (CRC) is currently the third leading cause of cancer-related mortality in the world. U.S. Food and Drug Administration-approved circulating tumor markers, including carcinoembryonic antigen, carbohydrate antigen (CA) 19-9 and CA125 were used as prognostic biomarkers of CRC that attributed to low sensitivity in diagnosis of CRC. Therefore, our purpose is to develop a novel strategy for novel clinical biomarkers for early CRC diagnosis. We used mass spectrometry (MS) methods such as nanoLC-MS/MS, targeted LC-MS/MS, and stable isotope-labeled multiple reaction monitoring (MRM) MS coupled to test machine learning algorithms and logistic regression to analyze plasma samples from patients with early-stage CRC, late-stage CRC, and healthy controls (HCs). On the basis of our methods, 356 peptides were identified, 6 differential expressed peptides were verified, and finally three peptides corresponding wheat germ agglutinin (WGA)-captured proteins were semi-quantitated in 286 plasma samples (80 HCs and 206 CRCs). The novel peptide biomarkers combination of PF4(54-62), ITIH4(429-438), and APOE(198-207) achieved sensitivity 84.5%, specificity 97.5% and an AUC of 0.96 in CRC diagnosis. In conclusion, our study demonstrated that WGA-captured plasma PF4(54-62), ITIH4(429-438), and APOE(198-207) levels in combination may serve as highly effective early diagnostic biomarkers for patients with CRC.
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。
推荐
暂无数据