Cargando…

Cancer Is Associated with Alterations in the Three-Dimensional Organization of the Genome

The human genome is organized into topologically associating domains (TADs), which represent contiguous regions with a higher frequency of intra-interactions as opposed to inter-interactions. TADs contribute to gene expression regulation by restricting the interactions between their regulatory eleme...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Lifei, Barth, Nicolai K. H., Pilarsky, Christian, Taher, Leila
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6966451/
https://www.ncbi.nlm.nih.gov/pubmed/31783642
http://dx.doi.org/10.3390/cancers11121886
Descripción
Sumario:The human genome is organized into topologically associating domains (TADs), which represent contiguous regions with a higher frequency of intra-interactions as opposed to inter-interactions. TADs contribute to gene expression regulation by restricting the interactions between their regulatory elements, and TAD disruption has been associated with cancer. Here, we provide a proof of principle that mutations within TADs can be used to predict the survival of cancer patients. Specifically, we constructed a set of 1467 consensus TADs representing the three-dimensional organization of the human genome and used Cox regression analysis to identify a total of 35 prognostic TADs in different cancer types. Interestingly, only 46% of the 35 prognostic TADs comprised genes with known clinical relevance. Moreover, in the vast majority of such cases, the prognostic value of the TAD was not directly related to the presence/absence of mutations in the gene(s), emphasizing the importance of regulatory mutations. In addition, we found that 34% of the prognostic TADs show strong structural perturbations in the cancer genome, consistent with the widespread, global epigenetic dysregulation often observed in cancer patients. In summary, this study elucidates the mechanisms through which non-coding variants may influence cancer progression and opens new avenues for personalized medicine.