Genome-scale discovery of DNA-methylation biomarkers for blood-based detection of colorectal cancer.

Genome-scale discovery of DNA-methylation biomarkers for blood-based detection of colorectal cancer.
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DOI:
10.1371/journal.pone.0050266
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发表时间:
2012
期刊:
影响因子:
3.7
通讯作者:
Laird PW
Laird PW
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Lange CP;Campan M;Hinoue T;Schmitz RF;van der Meulen-de Jong AE;Slingerland H;Kok PJ;van Dijk CM;Weisenberger DJ;Shen H;Tollenaar RA;Laird PW

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There is an increasing demand for accurate biomarkers for early non-invasive colorectal cancer detection. We employed a genome-scale marker discovery method to identify and verify candidate DNA methylation biomarkers for blood-based detection of colorectal cancer. We used DNA methylation data from 711 colorectal tumors, 53 matched adjacent-normal colonic tissue samples, 286 healthy blood samples and 4,201 tumor samples of 15 different cancer types. DNA methylation data were generated by the Illumina Infinium HumanMethylation27 and the HumanMethylation450 platforms, which determine the methylation status of 27,578 and 482,421 CpG sites respectively. We first performed a multistep marker selection to identify candidate markers with high methylation across all colorectal tumors while harboring low methylation in healthy samples and other cancer types. We then used pre-therapeutic plasma and serum samples from 107 colorectal cancer patients and 98 controls without colorectal cancer, confirmed by colonoscopy, to verify candidate markers. We selected two markers for further evaluation: methylated THBD (THBD-M) and methylated C9orf50 (C9orf50-M). When tested on clinical plasma and serum samples these markers outperformed carcinoembryonic antigen (CEA) serum measurement and resulted in a high sensitive and specific test performance for early colorectal cancer detection. Our systematic marker discovery and verification study for blood-based DNA methylation markers resulted in two novel colorectal cancer biomarkers, THBD-M and C9orf50-M. THBD-M in particular showed promising performance in clinical samples, justifying its further optimization and clinical testing.
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