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PETBioNewsNewsNew algorithm developed to improve personalised cancer therapy

BioNews

New algorithm developed to improve personalised cancer therapy

Published 30 April 2021 posted in News and appears in BioNews 1093

Author

Joseph Hawkins

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.

A new algorithm could improve the personalisation of cancer medicine by recognising tumours which may be sensitive to specific treatments...

A new algorithm could improve the personalisation of cancer medicine by recognising which tumours may be sensitive to specific treatments.

Designed by researchers at the University of Cambridge, the algorithm, known as MMRDetect, was developed using data obtained through the NHS 100,000 Genomes Project (see BioNews 979). The MMRDetect algorithm identifies DNA repair defects among tumour cells, allowing cancer patients to receive personalised treatments specific to their tumours.   

Senior author, Dr Serena Nik-Zainal, said: 'When we knock out different DNA repair genes, we find a kind of fingerprint of that gene or pathway being erased. We can then use those fingerprints to figure out which repair pathways have stopped working in each person's tumour, and what treatments should be used specifically to treat their cancer.'

The study, published in the journal Nature Cancer, identified nine DNA repair genes that are essential for repairing the human genome in response to damage caused by water and oxygen, as well as errors that arise during cell division.

The researchers used CRISPR/Cas9-based genome editing to knock out (disable) these repair genes in human stem cells. By doing so, the researchers observed distinct mutational changes which can serve as signals, or 'biomarkers', for the failure of those genes and the repair pathways they are involved in.

The authors indicated that the MMRDetect algorithm would be most effective if it is applied as soon as a patient receives a cancer diagnosis and their tumour has been screened by genome sequencing. By understanding which genes are malfunctioning, doctors can tailor treatment to the individual patient by using medicines that are known to be most effective against those genes.

Moving forward, the MMRDetect algorithm will be applied to all cancers identified by Genomics England. This study has highlighted the importance of the 100,000 Genomes Project, a ground-breaking national genome sequencing effort aimed at advancing the personalisation of medicine.

'We are very excited to see such impactful research being supported by the 100,000 Genomes Project, and that our data has helped to develop a clinically significant tool. This is a fantastic example of how the sheer size and richness of the 100,000 Genomes Project data can contribute to important research,' said Parker Moss, chief commercial and partnerships officer at Genomics England.

Sources and References

  • 27/04/2021
    University of Cambridge
    New cancer algorithm flags genetic weaknesses in tumours
  • 26/04/2021
    Nature Cancer
    A systematic CRISPR screen defines mutational mechanisms underpinning signatures caused by replication errors and endogenous DNA damage
  • 27/04/2021
    Genomics England
    New algorithm flags genetic weaknesses in cancer tumours
  • 28/04/2021
    Healthcare IT News
    New algorithm could help personalise cancer therapies
  • 27/04/2021
    The Times
    Artificial intelligence tool that reads cancer's DNA may lead to new treatments

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