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

Abstract

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 http://www.network-cancer-genes.org/.

Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine

“…Furthermore, a recently proposed hallmark of aging, extracellular matrix stiffness, was associated with 30 target genes identified by PandaOmics in this study, consisting of 18 high confidence ( AKT1 , CHUK , CASP3 , DNMT1 , EGFR , FGF2 , HGF , IGF1 , ITGAV , LOX , MMP1 , MMP2 , MMP7 , MMP9 , MTOR , SIRT1 , SPP1 , TRAF6 ), 8 medium novel ( FAM20C , GALNT1 , ITGB5 , MMP25 , PLOD1 , PLOD3 , RAB14 , TNIK ), and 4 highly novel targets ( ADAMTS14 , ITGA11 , RAP2C , RNF14 ). Among the 145 genes associated with hallmarks of aging, 55 genes are known cancer drivers ( Figure 3 ) [ 33 ], pointing to the aging components underlying cancer pathogenesis.…”

“…All genes associated with hallmarks of aging were included, along with their literature evidence and PubMed ID ( Supplementary Table 2 ). Among the genes included, those that are known cancer drivers were annotated by the data of the NCG7.0 database [ 33 ].…”

Somatic Variation in Normal Tissues: Friend or Foe of Cancer Early Detection?

“…Genes acquiring somatic mutations that increase cell fitness and drive clonal expansion (somatic drivers) are identified using similar approaches to those used for cancer drivers, preferentially detecting frequently mutated genes 4 . So far, these approaches have identified 147 somatic drivers across nine tissues (Supplementary Table S1).…”

“…These studies have also expanded our knowledge on the genetic basis of cancer. The analysis of thousands of cancer exomes and genomes has led to the identification of more than 3,000 mutated genes with a proven or predicted driver role in cancer 4,5 .…”

“…Currently, the cancer driver activity of a gene is either assessed experimentally or predicted with computational approaches that measure the evolutionary forces acting on it or the effect and properties of its alterations 6,7 . With only few notable exceptions, the vast majority of known or predicted cancer drivers promote cancer only in specific tissues 4 . Moreover, the majority of cancer genomes bear mutations in more than one driver, supporting early theoretical work on the need of multiple hits to initiate tumourigenesis 8 .…”