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CpG-Islands as Markers for Liquid Biopsies of Cancer Patients
The analysis of tumours using biomarkers in blood is transforming cancer diagnosis and therapy. Cancers are characterised by evolving genetic alterations, making it difficult to develop reliable and broadly applicable DNA-based biomarkers for liquid biopsy. In contrast to the variability in gene mut...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7465093/ https://www.ncbi.nlm.nih.gov/pubmed/32752173 http://dx.doi.org/10.3390/cells9081820 |
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author | Sprang, Maximilian Paret, Claudia Faber, Joerg |
author_facet | Sprang, Maximilian Paret, Claudia Faber, Joerg |
author_sort | Sprang, Maximilian |
collection | PubMed |
description | The analysis of tumours using biomarkers in blood is transforming cancer diagnosis and therapy. Cancers are characterised by evolving genetic alterations, making it difficult to develop reliable and broadly applicable DNA-based biomarkers for liquid biopsy. In contrast to the variability in gene mutations, the methylation pattern remains generally constant during carcinogenesis. Thus, methylation more than mutation analysis may be exploited to recognise tumour features in the blood of patients. In this work, we investigated the possibility of using global CpG (CpG means a CG motif in the context of methylation. The p represents the phosphate. This is used to distinguish CG sites meant for methylation from other CG motifs or from mentions of CG content) island methylation profiles as a basis for the prediction of cancer state of patients utilising liquid biopsy samples. We retrieved existing GEO methylation datasets on hepatocellular carcinoma (HCC) and cell-free DNA (cfDNA) from HCC patients and healthy donors, as well as healthy whole blood and purified peripheral blood mononuclear cell (PBMC) samples, and used a random forest classifier as a predictor. Additionally, we tested three different feature selection techniques in combination. When using cfDNA samples together with solid tumour samples and healthy blood samples of different origin, we could achieve an average accuracy of 0.98 in a 10-fold cross-validation. In this setting, all the feature selection methods we tested in this work showed promising results. We could also show that it is possible to use solid tumour samples and purified PBMCs as a training set and correctly predict a cfDNA sample as cancerous or healthy. In contrast to the complete set of samples, the feature selections led to varying results of the respective random forests. ANOVA feature selection worked well with this training set, and the selected features allowed the random forest to predict all cfDNA samples correctly. Feature selection based on mutual information could also lead to better than random results, but LASSO feature selection would not lead to a confident prediction. Our results show the relevance of CpG islands as tumour markers in blood. |
format | Online Article Text |
id | pubmed-7465093 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-74650932020-09-04 CpG-Islands as Markers for Liquid Biopsies of Cancer Patients Sprang, Maximilian Paret, Claudia Faber, Joerg Cells Article The analysis of tumours using biomarkers in blood is transforming cancer diagnosis and therapy. Cancers are characterised by evolving genetic alterations, making it difficult to develop reliable and broadly applicable DNA-based biomarkers for liquid biopsy. In contrast to the variability in gene mutations, the methylation pattern remains generally constant during carcinogenesis. Thus, methylation more than mutation analysis may be exploited to recognise tumour features in the blood of patients. In this work, we investigated the possibility of using global CpG (CpG means a CG motif in the context of methylation. The p represents the phosphate. This is used to distinguish CG sites meant for methylation from other CG motifs or from mentions of CG content) island methylation profiles as a basis for the prediction of cancer state of patients utilising liquid biopsy samples. We retrieved existing GEO methylation datasets on hepatocellular carcinoma (HCC) and cell-free DNA (cfDNA) from HCC patients and healthy donors, as well as healthy whole blood and purified peripheral blood mononuclear cell (PBMC) samples, and used a random forest classifier as a predictor. Additionally, we tested three different feature selection techniques in combination. When using cfDNA samples together with solid tumour samples and healthy blood samples of different origin, we could achieve an average accuracy of 0.98 in a 10-fold cross-validation. In this setting, all the feature selection methods we tested in this work showed promising results. We could also show that it is possible to use solid tumour samples and purified PBMCs as a training set and correctly predict a cfDNA sample as cancerous or healthy. In contrast to the complete set of samples, the feature selections led to varying results of the respective random forests. ANOVA feature selection worked well with this training set, and the selected features allowed the random forest to predict all cfDNA samples correctly. Feature selection based on mutual information could also lead to better than random results, but LASSO feature selection would not lead to a confident prediction. Our results show the relevance of CpG islands as tumour markers in blood. MDPI 2020-08-01 /pmc/articles/PMC7465093/ /pubmed/32752173 http://dx.doi.org/10.3390/cells9081820 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sprang, Maximilian Paret, Claudia Faber, Joerg CpG-Islands as Markers for Liquid Biopsies of Cancer Patients |
title | CpG-Islands as Markers for Liquid Biopsies of Cancer Patients |
title_full | CpG-Islands as Markers for Liquid Biopsies of Cancer Patients |
title_fullStr | CpG-Islands as Markers for Liquid Biopsies of Cancer Patients |
title_full_unstemmed | CpG-Islands as Markers for Liquid Biopsies of Cancer Patients |
title_short | CpG-Islands as Markers for Liquid Biopsies of Cancer Patients |
title_sort | cpg-islands as markers for liquid biopsies of cancer patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7465093/ https://www.ncbi.nlm.nih.gov/pubmed/32752173 http://dx.doi.org/10.3390/cells9081820 |
work_keys_str_mv | AT sprangmaximilian cpgislandsasmarkersforliquidbiopsiesofcancerpatients AT paretclaudia cpgislandsasmarkersforliquidbiopsiesofcancerpatients AT faberjoerg cpgislandsasmarkersforliquidbiopsiesofcancerpatients |