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Multiplex quantitation of 270 plasma protein markers to identify a signature for early detection of colorectal cancer

多路复用 结直肠癌 签名(拓扑) 医学 肿瘤科 癌症 内科学 计算生物学 生物 生物信息学 数学 几何学
作者
Megha Bhardwaj,Korbinian Weigl,Kaja Tikk,Tim Holland‐Letz,Petra Schrotz‐King,Christoph H. Borchers,Hermann Brenner
出处
期刊:European Journal of Cancer [Elsevier BV]
卷期号:127: 30-40 被引量:34
标识
DOI:10.1016/j.ejca.2019.11.021
摘要

Blood-based protein biomarker signatures might be an alternative or supplement to existing methods for early detection of colorectal cancer (CRC) for population-based screening. The objective of this study was to derive a protein biomarker signature for early detection of CRC and its precursor advanced adenoma (AA). In a two-stage design, 270 protein markers were measured by liquid chromatography/multiple reaction monitoring/mass spectrometry in plasma samples of discovery and validation sets. In the discovery set consisting of 100 newly diagnosed CRC cases and 100 age- and sex-matched controls free of neoplasm at screening colonoscopy, the algorithms predicting the presence of early- or late-stage CRC were derived by Lasso regression and .632 + bootstrap. The prediction algorithms were then externally validated in an independent validation set consisting of participants of screening colonoscopy including 56 participants with CRC, 99 with AA and 99 controls without any colorectal neoplasms. Three different signatures for all-, early- and late-stage CRC consisting of five-, three- and eight-protein markers were obtained in the discovery set with areas under the curves (AUCs) after .632 + bootstrap adjustment of 0.85, 0.83 and 0.96, respectively. External validation in the representative screening population yielded AUCs of 0.79 (95% CI, 0.70–0.86), 0.79 (95% CI, 0.66–0.89) and 0.80 (95% CI, 0.70–0.89) for all-, early- and late-stage CRCs, respectively. The three-marker early-stage algorithm yielded an AUC of 0.65 (95% CI, 0.56–0.73) for detection of AA in the validation set. Although not yet competitive with available stool-based tests for CRC early detection, the identified proteins may contribute to the development of powerful blood-based tests for early detection of CRC and its precursors AAs.
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