Genome-Wide Analysis of Long Non-Coding RNA Profiles in Canine Oral Melanomas.
Christophe HitteCéline Le BéguecEdouard CadieuValentin WucherAline PrimotAnaïs ProuteauNadine BotherelBenoît HédanKerstin Lindblad-TohCatherine AndréThomas DerrienPublished in: Genes (2019)
Mucosal melanomas (MM) are rare aggressive cancers in humans, and one of the most common forms of oral cancers in dogs. Similar biological and histological features are shared between MM in both species, making dogs a powerful model for comparative oncology studies of melanomas. Although exome sequencing recently identified recurrent coding mutations in canine MM, little is known about changes in non-coding gene expression, and more particularly, in canine long non-coding RNAs (lncRNAs), which are commonly dysregulated in human cancers. Here, we sampled a large cohort (n = 52) of canine normal/tumor oral MM from three predisposed breeds (poodles, Labrador retrievers, and golden retrievers), and used deep transcriptome sequencing to identify more than 400 differentially expressed (DE) lncRNAs. We further prioritized candidate lncRNAs by comparative genomic analysis to pinpoint 26 dog-human conserved DE lncRNAs, including SOX21-AS, ZEB2-AS, and CASC15 lncRNAs. Using unsupervised co-expression network analysis with coding genes, we inferred the potential functions of the DE lncRNAs, suggesting associations with cancer-related genes, cell cycle, and carbohydrate metabolism Gene Ontology (GO) terms. Finally, we exploited our multi-breed design to identify DE lncRNAs within breeds. This study provides a unique transcriptomic resource for studying oral melanoma in dogs, and highlights lncRNAs that may potentially be diagnostic or therapeutic targets for human and veterinary medicine.
Keyphrases
- genome wide analysis
- long non coding rna
- network analysis
- genome wide identification
- poor prognosis
- cell cycle
- endothelial cells
- gene expression
- transcription factor
- single cell
- genome wide
- induced pluripotent stem cells
- cell proliferation
- rna seq
- palliative care
- stem cells
- dna methylation
- signaling pathway
- machine learning
- copy number
- epithelial mesenchymal transition
- lymph node metastasis
- squamous cell