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References
Ferlay, J. et al Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int. J. Cancer 136, E359 (2015).
Arnold, M. et al. Predicting the future burden of esophageal cancer by histological subtype: international trends in incidence up to 2030. Am. J. Gastroenterol. 112, 1247–1255 (2017).
Zeng, H. et al Esophageal cancer statistics in China, 2011: estimates based on 177 cancer registries. Thorac. Cancer 7, 232 (2016).
Napier, K. J., Scheerer, M. & Misra, S. Esophageal cancer: a review of epidemiology, pathogenesis, staging workup and treatment modalities. World J. Gastrointest. Oncol. 6, 112 (2014).
Ma, K., Cao, B. & Guo, M. The detective, prognostic, and predictive value of DNA methylation in human esophageal squamous cell carcinoma. Clin. Epigenetics 8, 1–9 (2016).
Chen, K. et al Loss of 5-hydroxymethylcytosine is linked to gene body hypermethylation in kidney cancer. Cell Res. 26, 103 (2016).
Vasanthakumar, A. & Godley, L. A. 5-hydroxymethylcytosine in cancer: significance in diagnosis and therapy. Cancer Genet. 208, 167–77 (2015).
Song, C. et al. 5-hydroxymethylcytosine signatures in cell-free DNA provide information about tumor types and stages. Cell Res. 27, 1231–42 (2017).
Li, W., Xu, Z. & Lu, X. 5-hydroxymethylcytosine signatures in circulating cell-free DNA as diagnostic biomarkers for human cancers. Cell Res. 27, 1243–57 (2017).
Han, D. L. et al A highly sensitive and robust method for genome-wide 5hmC profiling of rare cell populations. Mol. Cell. 63, 711 (2016).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Chen, T. & Guestrin, C. XGBoost: a scalable tree boosting system. In: Proc. 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA. 785–794 (ACM, New York, NY, 2016).
Acknowledgements
This work was supported by the National Key R&D Program of China 2016YFC0900300, NSFC 31670895/U1504831/31741074, Major Science and Technology Project of Henan Province (161100310100), CAS Strategic Priority Research Program XDA16010108/XDB14030300, CAS Hundred Talent Program, Youth Innovation Promotion Association, CAS 2016097. Shanghai Epican Genetech sponsor part of the sequencing cost.
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Q.K., Y.-G.Y., and C.H. conceived the idea. X.T., J.Z., X.L., Z.Q., X.Z., Y.X., R.L., X.L. Y.-G.Y., and Q.K. design the experiments, recruited patients, collected blood and organized clinical information. Shanghai Epican Genetech finished all the hmC-Seal experiments with their protocol. C.C., C.G., B.S., L.W., and X.H. perform bioinformatics analysis under the supervision of D.H. B.S., C.C., C.G., J.Z., D.H. and Y.-G.Y. wrote the manuscript with input from all authors.
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Tian, X., Sun, B., Chen, C. et al. Circulating tumor DNA 5-hydroxymethylcytosine as a novel diagnostic biomarker for esophageal cancer. Cell Res 28, 597–600 (2018). https://doi.org/10.1038/s41422-018-0014-x
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DOI: https://doi.org/10.1038/s41422-018-0014-x
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