Minimally invasive classification of paediatric solid tumours using reduced representation bisulphite sequencing of cell-free DNA: a proof-of-principle study.
Ruben Van PaemelAndries De KokerCharlotte VandeputteLieke M J van ZogchelTim LammensGeneviève LaureysJo VandesompeleGudrun SchleiermacherMathieu ChicardNadine Van RoyAles VichaGodelieve A M TytgatNico CallewaertKatleen De PreterBram De WildePublished in: Epigenetics (2020)
In the clinical management of paediatric solid tumours, histological examination of tumour tissue obtained by a biopsy remains the gold standard to establish a conclusive pathological diagnosis. The DNA methylation pattern of a tumour is known to correlate with the histopathological diagnosis across cancer types and is showing promise in the diagnostic workup of tumour samples. This methylation pattern can be detected in the cell-free DNA. Here, we provide proof-of-concept of histopathologic classification of paediatric tumours using cell-free reduced representation bisulphite sequencing (cf-RRBS) from retrospectively collected plasma and cerebrospinal fluid samples. We determined the correct tumour type in 49 out of 60 (81.6%) samples starting from minute amounts (less than 10 ng) of cell-free DNA. We demonstrate that the majority of misclassifications were associated with sample quality and not with the extent of disease. Our approach has the potential to help tackle some of the remaining diagnostic challenges in paediatric oncology in a cost-effective and minimally invasive manner.
Keyphrases
- minimally invasive
- intensive care unit
- dna methylation
- cell free
- emergency department
- machine learning
- cerebrospinal fluid
- deep learning
- single cell
- genome wide
- gene expression
- palliative care
- big data
- robot assisted
- risk assessment
- artificial intelligence
- climate change
- squamous cell
- quality improvement
- neural network
- circulating tumor cells