The Francis Crick Institute
s13059-022-02607-z.pdf (3.29 MB)

Comparative assessment of genes driving cancer and somatic evolution in non-cancer tissues: an update of the Network of Cancer Genes (NCG) resource.

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journal contribution
posted on 2022-01-31, 09:20 authored by Lisa Dressler, Michele Bortolomeazzi, Mohamed Reda Keddar, Hrvoje Misetic, Giulia Sartini, Amelia Acha-Sagredo, Lucia Montorsi, Neshika Wijewardhane, Dimitra Repana, Joel Nulsen, Jacki Goldman, Marc Pollitt, Patrick Davis, Amy Strange, Karen Ambrose, Francesca D Ciccarelli
BACKGROUND: Genetic alterations of somatic cells can drive non-malignant clone formation and promote cancer initiation. However, the link between these processes remains unclear and hampers our understanding of tissue homeostasis and cancer development. RESULTS: Here, we collect a literature-based repertoire of 3355 well-known or predicted drivers of cancer and non-cancer somatic evolution in 122 cancer types and 12 non-cancer tissues. Mapping the alterations of these genes in 7953 pan-cancer samples reveals that, despite the large size, the known compendium of drivers is still incomplete and biased towards frequently occurring coding mutations. High overlap exists between drivers of cancer and non-cancer somatic evolution, although significant differences emerge in their recurrence. We confirm and expand the unique properties of drivers and identify a core of evolutionarily conserved and essential genes whose germline variation is strongly counter-selected. Somatic alteration in even one of these genes is sufficient to drive clonal expansion but not malignant transformation. CONCLUSIONS: Our study offers a comprehensive overview of our current understanding of the genetic events initiating clone expansion and cancer revealing significant gaps and biases that still need to be addressed. The compendium of cancer and non-cancer somatic drivers, their literature support, and properties are accessible in the Network of Cancer Genes and Healthy Drivers resource at .


Crick (Grant ID: 10233, Grant title: STP Scientific Computing)