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

  • Author(s): 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
  • et al.
Abstract

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.

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