The Transcriptome and Proteome Networks of Malignant Tumours Reveal Atavistic Attractors of Polyploidy-Related Asexual Reproduction.
Ninel M VainshelbaumAlessandro GiulianiKristine SalminaDace PjanovaJekaterina ErenpreisaPublished in: International journal of molecular sciences (2022)
The expression of gametogenesis-related (GG) genes and proteins, as well as whole genome duplications (WGD), are the hallmarks of cancer related to poor prognosis. Currently, it is not clear if these hallmarks are random processes associated only with genome instability or are programmatically linked. Our goal was to elucidate this via a thorough bioinformatics analysis of 1474 GG genes in the context of WGD. We examined their association in protein-protein interaction and coexpression networks, and their phylostratigraphic profiles from publicly available patient tumour data. The results show that GG genes are upregulated in most WGD-enriched somatic cancers at the transcriptome level and reveal robust GG gene expression at the protein level, as well as the ability to associate into correlation networks and enrich the reproductive modules. GG gene phylostratigraphy displayed in WGD+ cancers an attractor of early eukaryotic origin for DNA recombination and meiosis, and one relative to oocyte maturation and embryogenesis from early multicellular organisms. The upregulation of cancer-testis genes emerging with mammalian placentation was also associated with WGD. In general, the results suggest the role of polyploidy for soma-germ transition accessing latent cancer attractors in the human genome network, which appear as pre-formed along the whole Evolution of Life.
Keyphrases
- genome wide
- poor prognosis
- dna methylation
- copy number
- protein protein
- gene expression
- genome wide identification
- long non coding rna
- papillary thyroid
- small molecule
- single cell
- endothelial cells
- bioinformatics analysis
- childhood cancer
- genome wide analysis
- squamous cell
- case report
- dna damage
- dna repair
- young adults
- multidrug resistant
- network analysis
- machine learning
- transcription factor
- gram negative
- circulating tumor
- cell proliferation
- lymph node metastasis
- electronic health record
- squamous cell carcinoma
- single molecule