医学
胰腺导管腺癌
胰腺癌
癌症
肿瘤科
诊断生物标志物
内科学
生物标志物
腺癌
生物标志物发现
克拉斯
生物信息学
病理
生物
蛋白质组学
基因
生物化学
作者
Hongbeom Kim,Kyung Nam Kang,Yong Sam Shin,Yoonhyeong Byun,Youngmin Han,Wooil Kwon,Chul Woo Kim,Jin Young Jang
出处
期刊:Cancers
[MDPI AG]
日期:2020-06-01
卷期号:12 (6): 1443-1443
被引量:19
标识
DOI:10.3390/cancers12061443
摘要
A single tumor marker has a low diagnostic value in pancreatic cancer. Combinations of multiple biomarkers and unique analysis algorithms can be applied to overcome these limitations. This study sought to develop diagnostic algorithms using multiple biomarker panels and to validate their performance in the diagnosis of pancreatic ductal adenocarcinoma (PDAC). We used blood samples from 180 PDAC patients and 573 healthy controls. Candidate markers consisted of 11 markers that are commonly expressed in various cancers and which have previously demonstrated increased expression in pancreatic cancer. Samples were divided into training and validation sets. Five linear or non-linear classification methods were used to determine the optimal model. Differences were identified in 10 out of the 11 markers tested. We identified 2047 combinations, all of which were applied to 5 separate algorithms. The new biomarker combination consisted of 6 markers (ApoA1, CA125, CA19-9, CEA, ApoA2, and TTR). The area under the curve, specificity, and sensitivity were 0.992, 95%, and 96%, respectively, in the training set. Meanwhile, the measures were 0.993, 96%, and 93% in the validation set. This study demonstrated the utility of multiple biomarker combinations in the early detection of PDAC. A diagnostic panel of 6 biomarkers was developed and validated. These algorithms will assist in the early diagnosis of PDAC.
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