Therapy response monitoring in blood plasma from esophageal adenocarcinoma patients using cell-free DNA methylation profiling.

Esophageal adenocarcinoma (EAC) is an aggressive cancer characterized by a high risk of relapse post-surgery. Current follow-up methods (serum carcinoembryonic antigen detection and PET-CT) lack sensitivity and reliability, necessitating a novel approach. Analyzing cell-free DNA (cfDNA) from blood plasma emerges as a promising avenue.

Diagnosis of pediatric central nervous system tumors using methylation profiling of cfDNA from cerebrospinal fluid.

Pediatric central nervous system tumors remain challenging to diagnose. Imaging approaches do not provide sufficient detail to discriminate between different tumor types, while the histopathological examination of tumor tissue shows high inter-observer variability. Recent studies have demonstrated the accurate classification of central nervous system tumors based on the DNA methylation profile of a tumor biopsy.

Computational deconvolution of DNA methylation data from mixed DNA samples.

In this review, we provide a comprehensive overview of the different computational tools that have been published for the deconvolution of bulk DNA methylation (DNAm) data. Here, deconvolution refers to the estimation of cell-type proportions that constitute a mixed sample. The paper reviews and compares 25 deconvolution methods (supervised, unsupervised or hybrid) developed between 2012 and 2023 and compares the strengths and limitations of each approach.