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CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA

We propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood samp...

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Detalles Bibliográficos
Autores principales: Kang, Shuli, Li, Qingjiao, Chen, Quan, Zhou, Yonggang, Park, Stacy, Lee, Gina, Grimes, Brandon, Krysan, Kostyantyn, Yu, Min, Wang, Wei, Alber, Frank, Sun, Fengzhu, Dubinett, Steven M., Li, Wenyuan, Zhou, Xianghong Jasmine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5364586/
https://www.ncbi.nlm.nih.gov/pubmed/28335812
http://dx.doi.org/10.1186/s13059-017-1191-5
Descripción
Sumario:We propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. CancerLocator outperforms two established multi-class classification methods on simulations and real data, even with the low proportion of tumor-derived DNA in the cell-free DNA scenarios. CancerLocator also achieves promising results on patient plasma samples with low DNA methylation sequencing coverage. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-017-1191-5) contains supplementary material, which is available to authorized users.