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bioRxiv · 10.1101/2020.01.18.911172

Finding new cancer epigenetic and genetic biomarkers from cell-free DNA by combining SALP-seq and machine learning：esophageal cancer as an example

Liu, S.·Wu, J.·Xia, Q.·Liu, H.·Li, W.·Xia, X.·Wang, J.
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Abstract

BackgroundCancer is an important public health problem worldwide and its early diagnosis and effective prognosis are critical for its treatment. In recent years, as a good material for cancer liquid biopsy, plasma cell-free DNA (cfDNA) has been widely analyzed by next generation sequencing (NGS) for finding new molecular markers for cancer diagnosis such as size, methylation and end coordinate. However, the current studies did not still involve esophageal cancer (ESCA), a main cancer that seriously threatens human health and life in China. Here we therefore tried to find new biomarkers for this cancer from cfDNA. Materials & methodsThirty cfDNA samples from 26 ESCA patients and 4 healthy people were used to construct the NGS libraries and sequenced by using SALP-seq. The sequencing data were analyzed with variant bioinformatics methods for finding ESCA molecular biomarkers. Results & conclusionWe identified 103 epigenetic markers (including 54 genome-wide and 49 promoter markers) and 37 genetic markers for ESCA. These markers provide new molecular biomarkers for ESCA diagnosis, prognosis and therapy. Importantly, this study provides a new pipeline for finding new molecular markers for cancers from cfDNA by combining SALP-seq and machine learning. Finally, by finding new molecular markers for ESCA from cfDNA, this study sheds important new insights on the clinical worth of cfDNA.

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Liu, S., Wu, J., Xia, Q., Liu, H., Li, W., Xia, X., Wang, J.. 2020-01-18. Finding new cancer epigenetic and genetic biomarkers from cell-free DNA by combining SALP-seq and machine learning：esophageal cancer as an example. https://doi.org/10.1101/2020.01.18.911172

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