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PETBioNewsNewsMechanisms influencing cancer driver genes revealed

BioNews

Mechanisms influencing cancer driver genes revealed

Published 22 April 2022 posted in News and appears in BioNews 1141

Author

Sneha Krishnamurthy

Image by Peter Artymiuk via the Wellcome Collection. Depicts the shadow of a DNA double helix, on a background that shows the fluorescent banding of the output from a DNA sequencing machine.
CC BY 4.0
Image by Peter Artymiuk via the Wellcome Collection. Depicts the shadow of a DNA double helix, on a background that shows the fluorescent banding of the sequencing output from an automated DNA sequencing machine.

More human genes have been identified as driving cancer development than previously assumed...

More human genes have been identified as driving cancer development than previously assumed.

The study evaluated 12,767 human genes that interact, directly or indirectly, with certain core cancer genes, which are known to have a significant impact on the development of cancer. The genes were divided into categories depending on their distance to core cancer genes in terms of protein-protein interactions, and assessed for their impact on cancer biology, using in silico models. The results showed that a large spectrum of genes had varying degrees of cancer-relevance, potentially providing more therapeutic targets for future research.

'These findings substantially broaden the repertoire of cancer-relevant genes,' said lead author Dr Lajos Pusztai, from Yale Cancer Centre in New Haven, Connecticut. 'It is likely that their biologic contributions are cell-type and genomic context-dependent and that any given mutation may be functionally important in one person, but not in another individual.'

Current models of cancer genetics highlight 'driver genes', whose mutations have a direct impact on the biology of cancer cells. 'Passenger gene' mutations, on the other hand, are considered to have no direct impact on cancer biology, but occur at a low frequency, varying from cancer to cancer. The study, published in the Journal of the National Cancer Institute, provides a new perspective on the relevance of passenger genes to cancer development by evaluating them using four metrics.

The metrics used were (i) the gene dependency score, which measures the importance of the gene to the viability of the cell, (ii) the somatic mutation frequency, which tells us how often the gene is mutated, (iii) the effect size, which measures the extent to which a mutation in the gene improves the survival of the cell, and (iv) the negative selection pressure, which tells us how much of a negative effect the mutation of the gene has in healthy populations.

The results of this study showed that the impact of genes on cancer biology reduced with increasing 'distance' of genes from the core cancer genes.

The findings suggest that the dysregulation of passenger genes contributes to the overall biology of different cancers, and could vary between cancers or between individuals. This supports the idea that mutations in core cancer genes are insufficient to bring about malignant transformation on their own.

The authors concluded in their paper 'these findings suggest a biological model in which many somatic mutations in a cancer contribute some function and collectively determine the clinical behavior of the disease'. Furthermore, identification of these genes may potentially provide a wider scope for targeted therapeutics and personalised medicine in cancer.

Sources and References

  • 14/04/2022
    Yale School of Medicine
    Yale findings broaden the repertoire of cancer-relevant genes
  • 13/04/2022
    Journal of the National Cancer Institute
    Cancer relevance of human genes

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Image by Peter Artymiuk via the Wellcome Collection. Depicts the shadow of a DNA double helix, on a background that shows the fluorescent banding of the output from a DNA sequencing machine.
CC BY 4.0
Image by Peter Artymiuk via the Wellcome Collection. Depicts the shadow of a DNA double helix, on a background that shows the fluorescent banding of the sequencing output from an automated DNA sequencing machine.
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Image by Christoph Bock/Max Planck Institute for Informatics via Wikimedia Commons. Depicts a DNA molecule that is methylated on both strands on the centre cytosine.
CC BY-SA 3.0
Image by Christoph Bock/Max Planck Institute for Informatics via Wikimedia Commons. Depicts a DNA molecule that is methylated on both strands on the centre cytosine.
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