DNA methylome combined with chromosome cluster-oriented analysis provides an early signature for cutaneous melanoma aggressiveness.
Arnaud CarrierCécile DesjobertLoic PongerLaurence LamantMatias BustosJorge Torres-FerreiraRui HenriqueCarmen JeronimoLuisa LanfranconeAudrey DelmasGilles FavreAntoine DaunayFlorence BusatoDave S B HoonJorg TostChantal EtievantJoëlle RiondPaola Barbara ArimondoPublished in: eLife (2022)
Aberrant DNA methylation is a well-known feature of tumours and has been associated with metastatic melanoma. However, since melanoma cells are highly heterogeneous, it has been challenging to use affected genes to predict tumour aggressiveness, metastatic evolution, and patients' outcomes. We hypothesized that common aggressive hypermethylation signatures should emerge early in tumorigenesis and should be shared in aggressive cells, independent of the physiological context under which this trait arises. We compared paired melanoma cell lines with the following properties: (i) each pair comprises one aggressive counterpart and its parental cell line and (ii) the aggressive cell lines were each obtained from different host and their environment (human, rat, and mouse), though starting from the same parent cell line. Next, we developed a multi-step genomic pipeline that combines the DNA methylome profile with a chromosome cluster-oriented analysis. A total of 229 differentially hypermethylated genes was commonly found in the aggressive cell lines. Genome localization analysis revealed hypermethylation peaks and clusters, identifying eight hypermethylated gene promoters for validation in tissues from melanoma patients. Five Cytosine-phosphate-Guanine (CpGs) identified in primary melanoma tissues were transformed into a DNA methylation score that can predict survival (log-rank test, p=0.0008). This strategy is potentially universally applicable to other diseases involving DNA methylation alterations.
Keyphrases
- genome wide
- dna methylation
- end stage renal disease
- copy number
- gene expression
- ejection fraction
- chronic kidney disease
- peritoneal dialysis
- endothelial cells
- squamous cell carcinoma
- small cell lung cancer
- oxidative stress
- single molecule
- skin cancer
- type diabetes
- circulating tumor
- patient reported outcomes
- genome wide identification
- transcription factor
- metabolic syndrome
- cell proliferation
- glycemic control
- neural network
- induced pluripotent stem cells