Finding new cancer epigenetic and genetic biomarkers from cell-free DNA by combining SALP-seq and machine learning
| Autor: | Xin-Yi Xia, Weiwei Li, Hongde Liu, Jinke Wang, Qiang Xia, Jian Wu, Shicai Liu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
TF
transcription factor Esophageal cancer computer.software_genre CTC circulating tumor cell Biochemistry TFBS TF binding site Cell-free DNA 0302 clinical medicine Structural Biology ATAC-seq Assay for Transposase-Accessible Chromatin-sequencing and high-throughput sequencing miRNA microRNA cfMeDIP-seq cell-free methylated DNA immunoprecipitation and high-throughput sequencing ctDNA cell-free tumor DNA 0303 health sciences SALP-seq Single strand Adaptor Library Preparation-sequencing SNP single nucleotide polymorphism mRNA messenger RNA Computer Science Applications Cancer treatment NIPT noninvasive prenatal testing Cell-free fetal DNA 030220 oncology & carcinogenesis SALP-seq Biotechnology Research Article lcsh:Biotechnology Biophysics Machine learning Tv transversion DNA sequencing 03 medical and health sciences lcsh:TP248.13-248.65 Next generation sequencing Genetics medicine Epigenetics Liquid biopsy AUC Area Under Curve 030304 developmental biology ComputingMethodologies_COMPUTERGRAPHICS PCA principal component analysis business.industry SNV single nucleotide variant Cancer cfDNA cell-free DNA NGS next generation sequencing medicine.disease Genetic marker ESCA esophageal cancer TSS transcription start site TCGA The Cancer Genome Atlas Artificial intelligence business computer Ti transitions Biomarkers |
| Zdroj: | Computational and Structural Biotechnology Journal Computational and Structural Biotechnology Journal, Vol 18, Iss, Pp 1891-1903 (2020) |
| ISSN: | 2001-0370 |
| Popis: | Graphical abstract 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, 30 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 therefore developed a new pipeline for effectively finding new cfDNA-based biomarkers for cancers by combining SALP-seq and machine learning. In this study, we also discovered new clinical worth of cfDNA distinct from other reported characters. |
| Databáze: | OpenAIRE |
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