Validation of N-glycan markers that improve the performance of CA19-9 in pancreatic cancer
| Autor: | Mengmeng Wang, Weiping Ji, Yue-Peng Yin, Ping-Ting Zhou, Hao Wang, Gang Jin, Chunfang Gao, Yun-Peng Zhao, Meng Fang |
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| Rok vydání: | 2015 |
| Předmět: |
0301 basic medicine
Oncology Adult Male medicine.medical_specialty Glycosylation CA-19-9 Antigen Bioinformatics General Biochemistry Genetics and Molecular Biology Diagnosis Differential 03 medical and health sciences 0302 clinical medicine Polysaccharides Internal medicine Pancreatic cancer medicine Biomarkers Tumor Humans Glycomics Aged Receiver operating characteristic business.industry Case-control study General Medicine Stepwise regression Middle Aged medicine.disease Neoplasm Proteins Pancreatic Neoplasms 030104 developmental biology Logistic Models Carbohydrate Sequence Pancreatitis ROC Curve 030220 oncology & carcinogenesis Area Under Curve Case-Control Studies Biomarker (medicine) CA19-9 Female Differential diagnosis business |
| Zdroj: | Clinical and experimental medicine. 17(1) |
| ISSN: | 1591-9528 |
| Popis: | Pancreatic cancer (PC) has a high mortality rate because it is usually diagnosed late. Glycosylation of proteins is known to change in tumor cells during the development of PC. The objectives of this study were to identify and validate the diagnostic value of novel biomarkers based on N-glycomic profiling for PC. In total, 217 individuals including subjects with PC, pancreatitis, and healthy controls were divided randomly into a training group (n = 164) and validation groups (n = 53). Serum N-glycomic profiling was analyzed by DSA-FACE. The diagnostic model was constructed based on N-glycan markers with logistic stepwise regression. The diagnostic performance of the model was assessed further in validation cohort. The level of total core fucose residues was increased significantly in PC. Two diagnostic models designated GlycoPCtest and PCmodel (combining GlycoPCtest and CA19-9) were constructed to differentiate PC from normal. The area under the receiver operating characteristic curve (AUC) of PCmodel was higher than that of CA19-9 (0.925 vs. 0.878). The diagnostic models based on N-glycans are new, valuable, noninvasive alternatives for identifying PC. The diagnostic efficacy is improved by combined GlycoPCtest and CA19-9 for the discrimination of patients with PC from healthy controls. |
| Databáze: | OpenAIRE |
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