Finding new cancer epigenetic and genetic biomarkers from cell-free DNA by combining SALP-seq and machine learning

Authors:Shicai Liu; Jian Wu; Qiang Xia; Hongde Liu; Weiwei Li; Xinyi Xia; Jinke Wang
Source:Computational and Structural Biotechnology Journal, 2020.
DOI:10.1016/j.csbj.2020.06.042

Summary


The effective non-invasive diagnosis and prognosis are critical for cancer treatment. The plasma cell-free DNA (cfDNA) provides a good material for cancer liquid biopsy and its worth in this field is increasingly explored. Here we describe a new pipeline for effectively finding new cfDNA-based biomarkers for cancers by combining SALP-seq and machine learning. Using the pipeline, thirty cfDNA samples from 26 esophageal cancer (ESCA) patients and 4 healthy people were analyzed as an example. As a result, 103 epigenetic markers (including 54 genome-wide and 49 promoter markers) and 37 genetic markers were identified for this cancer. These markers provide new biomarkers for ESCA diagnosis, prognosis and therapy. Importantly, these markers, especially epigenetic markers, not only shed important new insights on the regulatory mechanisms of this cancer, but also could be used to classify the cfDNA samples. We developed a new pipeline for effectively finding new cfDNA-based biomarkers for cancers by combining SALP-seq and machine learning. This study discovered new clinical worth of cfDNA distinct from the other reported characters.

  • Institution
    东南大学

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