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 were 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 CpG 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.
Sequencing data have been deposited in GEO under accession code GSE155856R-scripts are available in Source Code 1 fileThe datasets supporting the conclusions of this article are included within the article and the following Supplementary files
DNA methylome combined with chromosome cluster-oriented analysis provides an early signature for cutaneous melanoma aggressivenessNCBI Gene Expression Omnibus, GSE155856.
- Paola B Arimondo
- Paola B Arimondo
- Paola B Arimondo
- Paola B Arimondo
- Dave SB Hoon
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: Tumour samples from melanoma patients were obtained from the tumour tissue bank at the Department of Pathology, IUCT-O Toulouse Hospital (France). The study was carried out in accordance with the institutional review board-approved protocols (CRB, AC-2013-1955) and the procedures followed were in accordance with the Helsinki Declaration.This study was approved by the institutional ethics committee of IPO Porto (CES-IPOP-FG13/2016).
- C Daniela Robles-Espinoza, International Laboratory for Human Genome Research, Mexico
- Received: March 11, 2022
- Accepted: September 18, 2022
- Accepted Manuscript published: September 20, 2022 (version 1)
© 2022, Carrier et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
How cells control gene expression is a fundamental question. The relative contribution of protein-level and RNA-level regulation to this process remains unclear. Here, we perform a proteogenomic analysis of tumors and untransformed cells containing somatic copy number alterations (SCNAs). By revealing how cells regulate RNA and protein abundances of genes with SCNAs, we provide insights into the rules of gene regulation. Protein complex genes have a strong protein-level regulation while non-complex genes have a strong RNA-level regulation. Notable exceptions are plasma membrane protein complex genes, which show a weak protein-level regulation and a stronger RNA-level regulation. Strikingly, we find a strong negative association between the degree of RNA-level and protein-level regulation across genes and cellular pathways. Moreover, genes participating in the same pathway show a similar degree of RNA- and protein-level regulation. Pathways including translation, splicing, RNA processing, and mitochondrial function show a stronger protein-level regulation while cell adhesion and migration pathways show a stronger RNA-level regulation. These results suggest that the evolution of gene regulation is shaped by functional constraints and that many cellular pathways tend to evolve one predominant mechanism of gene regulation at the protein level or at the RNA level.
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