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Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes.
Urzúa-Traslaviña, Carlos G; van Lieshout, Tijs; Boulogne, Floranne; Domanegg, Kevin; Zidan, Mahmoud; Bakker, Olivier B; Claringbould, Annique; de Ridder, Jeroen; Zwart, Wilbert; Westra, Harm-Jan; Deelen, Patrick; Franke, Lude.
Afiliación
  • Urzúa-Traslaviña CG; Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands.
  • van Lieshout T; Oncode Institute, Utrecht, The Netherlands.
  • Boulogne F; Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands.
  • Domanegg K; Oncode Institute, Utrecht, The Netherlands.
  • Zidan M; Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands.
  • Bakker OB; Oncode Institute, Utrecht, The Netherlands.
  • Claringbould A; Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands.
  • de Ridder J; Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands.
  • Zwart W; Wellcome Sanger Institute, Human Genetics, Hinxton, UK.
  • Westra HJ; Open Targets, Hinxton, UK.
  • Deelen P; Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands.
  • Franke L; EMBL Heidelberg, Structural and Computational Biology Unit, Heidelberg, Germany.
BMC Med Genomics ; 17(1): 186, 2024 Jul 15.
Article en En | MEDLINE | ID: mdl-39010058
ABSTRACT

BACKGROUND:

The genetic background of cancer remains complex and challenging to integrate. Many somatic mutations within genes are known to cause and drive cancer, while genome-wide association studies (GWAS) of cancer have revealed many germline risk factors associated with cancer. However, the overlap between known somatic driver genes and positional candidate genes from GWAS loci is surprisingly small. We hypothesised that genes from multiple independent cancer GWAS loci should show tissue-specific co-regulation patterns that converge on cancer-specific driver genes.

RESULTS:

We studied recent well-powered GWAS of breast, prostate, colorectal and skin cancer by estimating co-expression between genes and subsequently prioritising genes that show significant co-expression with genes mapping within susceptibility loci from cancer GWAS. We observed that the prioritised genes were strongly enriched for cancer drivers defined by COSMIC, IntOGen and Dietlein et al. The enrichment of known cancer driver genes was most significant when using co-expression networks derived from non-cancer samples of the relevant tissue of origin.

CONCLUSION:

We show how genes within risk loci identified by cancer GWAS can be linked to known cancer driver genes through tissue-specific co-expression networks. This provides an important explanation for why seemingly unrelated sets of genes that harbour either germline risk factors or somatic mutations can eventually cause the same type of disease.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Predisposición Genética a la Enfermedad / Redes Reguladoras de Genes / Estudio de Asociación del Genoma Completo / Neoplasias Límite: Humans Idioma: En Revista: BMC Med Genomics Asunto de la revista: GENETICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Predisposición Genética a la Enfermedad / Redes Reguladoras de Genes / Estudio de Asociación del Genoma Completo / Neoplasias Límite: Humans Idioma: En Revista: BMC Med Genomics Asunto de la revista: GENETICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Países Bajos
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