cfDNA genoom-brede methylatieprofilering voor pre-symptomatische kanker detectie en typering

Circulating cell-free plasma DNA (cfDNA) comprises DNA fragments that enter the bloodstream mainly through apoptosis, necrosis or active release mechanisms. These fragments primarily originate from hematopoietic cells and to less extent from solid tissues, including vascular endothelial cells and the liver, with additional contributions from the placenta in pregnant individuals. cfDNA retains the genetic and epigenetic characteristics of the tissues of origin, including single nucleotide variants (SNVs), copy number variations (CNVs), nucleosome-driven fragmentation patterns and DNA methylation profiles. In recent years, plasma cfDNA emerged as a powerful minimally invasive biomarker for monitoring various physiological and pathological conditions. In prenatal care, the cfDNA fragments derived from the placenta are analysed to assess the risk of foetal aneuploidies by non-invasive prenatal screening (NIPS). In oncology, non-invasive profiling of tumour-derived cfDNA can provide crucial insights into cancer (epi)genetics. For instance, the investigation in cfDNA of tumour-specific mutations can guide therapy selection, monitor treatment response, and improve patient care. In this thesis, we explored the utility of DNA methylation patterns for cancer detection and typing using cfDNA. Being tissue- and cell-type specific DNA methylation patterns allow the identification of the different contributors to the cfDNA pool. We envisioned that in the presence of malignancy, these patterns might help determine the tissue of origin of the cancer.

Publication Details

Journal
Lirias
Published
2025-04-24
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

cfDNA genoom-brede methylatieprofilering voor pre-symptomatische kanker detectie en typering

Lirias
Cancer Genomics and Diagnostics
article

cfDNA genoom-brede methylatieprofilering voor pre-symptomatische kanker detectie en typering

article en

Abstract

Circulating cell-free plasma DNA (cfDNA) comprises DNA fragments that enter the bloodstream mainly through apoptosis, necrosis or active release mechanisms. These fragments primarily originate from hematopoietic cells and to less extent from solid tissues, including vascular endothelial cells and the liver, with additional contributions from the placenta in pregnant individuals. cfDNA retains the genetic and epigenetic characteristics of the tissues of origin, including single nucleotide variants (SNVs), copy number variations (CNVs), nucleosome-driven fragmentation patterns and DNA methylation profiles. In recent years, plasma cfDNA emerged as a powerful minimally invasive biomarker for monitoring various physiological and pathological conditions. In prenatal care, the cfDNA fragments derived from the placenta are analysed to assess the risk of foetal aneuploidies by non-invasive prenatal screening (NIPS). In oncology, non-invasive profiling of tumour-derived cfDNA can provide crucial insights into cancer (epi)genetics. For instance, the investigation in cfDNA of tumour-specific mutations can guide therapy selection, monitor treatment response, and improve patient care. In this thesis, we explored the utility of DNA methylation patterns for cancer detection and typing using cfDNA. Being tissue- and cell-type specific DNA methylation patterns allow the identification of the different contributors to the cfDNA pool. We envisioned that in the presence of malignancy, these patterns might help determine the tissue of origin of the cancer.

Lirias
Good health and well-being
Openalex Percentile: Top 36%
Cancer Genomics and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.