Dataset Information

Liquid biopsies in patients with diffuse glioma.

ABSTRACT: Diffuse gliomas are the most common malignant primary tumors of the central nervous system. Like other neoplasms, these gliomas release molecular information into the circulation. Tumor-derived biomarkers include proteins, nucleic acids, and tumor-derived extracellular vesicles that accumulate in plasma, serum, blood platelets, urine and/or cerebrospinal fluid. Recently, also circulating tumor cells have been identified in the blood of glioma patients. Circulating molecules, vesicles, platelets, and cells may be useful as easily accessible diagnostic, prognostic and/or predictive biomarkers to guide patient management. Thereby, this approach may help to circumvent problems related to tumor heterogeneity and sampling error at the time of diagnosis. Also, liquid biopsies may allow for serial monitoring of treatment responses and of changes in the molecular characteristics of gliomas over time. In this review, we summarize the literature on blood-based biomarkers and their potential value for improving the management of patients with a diffuse glioma. Incorporation of the study of circulating molecular biomarkers in clinical trials is essential for further assessment of the potential of liquid biopsies in this context.

SUBMITTER: Best MG

PROVIDER: S-EPMC4436687 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Liquid biopsies in patients with diffuse glioma.

Best Myron G MG Sol Nik N Zijl Sebastiaan S Reijneveld Jaap C JC Wesseling Pieter P Wurdinger Thomas T

Acta neuropathologica 20150227 6

Diffuse gliomas are the most common malignant primary tumors of the central nervous system. Like other neoplasms, these gliomas release molecular information into the circulation. Tumor-derived biomarkers include proteins, nucleic acids, and tumor-derived extracellular vesicles that accumulate in plasma, serum, blood platelets, urine and/or cerebrospinal fluid. Recently, also circulating tumor cells have been identified in the blood of glioma patients. Circulating molecules, vesicles, platelets, ...[more]

PMID: 25720744

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Project 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.

Dataset Information

Liquid biopsies in patients with diffuse glioma.

Publications

Liquid biopsies in patients with diffuse glioma.

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