Klaus von Grafenstein
A5093768295- Chromosomal and Genetic Variations
- Cancer Genomics and Diagnostics
- vaccines and immunoinformatics approaches
- Cholangiocarcinoma and Gallbladder Cancer Studies
École des Hautes Études en Santé Publique
2024
Université de Rennes
2024
Institut de Recherche en Santé, Environnement et Travail
2024
Inserm
2024
Génétique Quantitative et Évolution Le Moulon
2022
<p>Fig S9. Age has a minor effect on L1PA DNA methylation patterns and is not confounding factor in this study</p>
<p>Fig S5. Comparison of tumor and plasma paired samples</p>
<p>Fig S8. DIAMOND profiles and performances in the validation versus discovery cohorts</p>
<p>Fig S11. 2 step-models integrating CNA signal extracted from DIAMOND data</p>
<p>Fig S6. Classifier performances: feature types, calculation parameters, cancer subtypes and stages</p>
<p>Fig S8. DIAMOND profiles and performances in the validation versus discovery cohorts</p>
<p>Fig S10. Comparison of multiple classifiers (expert, all, stack and blind models) prognostic value L1PA hypomethylation</p>
<p>Fig S5. Comparison of tumor and plasma paired samples</p>
<p>Fig S3. Preparation of L1PA targeted bisulfite sequencing libraries and analysis workflow</p>
<p>Fig S1. cfDNA extraction methods did not impact the L1PA methylation patterns</p>
<p>Fig S9. Age has a minor effect on L1PA DNA methylation patterns and is not confounding factor in this study</p>
<p>Fig S4. DIAMOND features: CpG calling and contribution of CG positions or haplotypes</p>
<p>Fig S2. Methylation profiles obtained with bisulfite or enzymatic conversion are similar</p>
<div>AbstractPurpose:<p>The detection of ctDNA, which allows noninvasive tumor molecular profiling and disease follow-up, promises optimal individualized management patients with cancer. However, detecting small fractions DNA released when the burden is reduced remains a challenge.</p>Experimental Design:<p>We implemented new, highly sensitive strategy to detect bp resolution methylation patterns from plasma assessed potential hypomethylation long interspersed nuclear...
<p>Fig S6. Classifier performances: feature types, calculation parameters, cancer subtypes and stages</p>
<p>Fig S11. 2 step-models integrating CNA signal extracted from DIAMOND data</p>
<p>Fig S4. DIAMOND features: CpG calling and contribution of CG positions or haplotypes</p>
<p>Fig S2. Methylation profiles obtained with bisulfite or enzymatic conversion are similar</p>
<p>Fig S3. Preparation of L1PA targeted bisulfite sequencing libraries and analysis workflow</p>
<p>Fig S7. Extraction of L1PA DNA hypomethylation signal from whole genome data</p>
<p>Fig S7. Extraction of L1PA DNA hypomethylation signal from whole genome data</p>
Abstract Purpose: The detection of ctDNA, which allows noninvasive tumor molecular profiling and disease follow-up, promises optimal individualized management patients with cancer. However, detecting small fractions DNA released when the burden is reduced remains a challenge. Experimental Design: We implemented new, highly sensitive strategy to detect bp resolution methylation patterns from plasma assessed potential hypomethylation long interspersed nuclear element-1 retrotransposons as...
Abstract Purpose The detection of circulating tumor DNA, which allows non-invasive molecular profiling and disease follow-up, promises optimal individualized management patients with cancer. However, detecting small fractions DNA released when the burden is reduced remains a challenge. Experimental Design We implemented new highly sensitive strategy to detect base-pair resolution methylation patterns from plasma assessed potential hypomethylation LINE-1 retrotransposons as multi-cancer...