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PETBioNewsNewsOesophageal cancer detection may be accelerated by genome sequencing

BioNews

Oesophageal cancer detection may be accelerated by genome sequencing

Published 11 September 2020 posted in News and appears in BioNews 1063

Author

Joanne Delange

Genetics Editor
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 statistical model that uses genomic data to calculate which patients are most likely to develop oesophageal cancer eight years before diagnosis has been developed...

A statistical model that uses genomic data to calculate which patients are most likely to develop oesophageal cancer eight years before diagnosis has been developed.

It is known that the DNA of tumours has areas that are either deleted or repeated as the cells copy and multiply. This is not found in healthy tissues. Using whole genome sequencing scientists were able to use this information to help diagnose patients earlier by developing a statistical model that was able to determine whether a patient was at a high or low risk of developing cancer in the future.

Professor Rebecca Fitzgerald, from the Medical Research Council (MRC) Cancer Unit at the University of Cambridge, explained: 'Early diagnosis of cancer is one of the best strategies to improve patient survival and decrease the side-effects from treatments. However, this strategy can result in overtreatment – patients incorrectly identified as high-risk and given unnecessary treatments. We need to find new ways to accurately spot cancer progression at a very early stage to help us identify those patients at greatest risk.'

Scientists at the University of Cambridge and EMBL's European Bioinformatics Institute (EMBL-EBI) in Cambridge sequenced the DNA of 88 patients diagnosed with Barrett's oesophagus, which is a condition that can lead to oesophageal cancer. They compared the sequences to 777 DNA samples from healthy people. The scientists identified differences between patients who went on to develop cancer and those who did not, and from there they developed a statistical model determining each patient's specific risk.

Published in Nature Medicine, the researchers stated that their model accurately identified 50 percent of the patients later diagnosed with oesophageal cancer more than eight years before their diagnosis, which increased to 70 percent one to two years before their diagnosis.

Significantly, the model was also able to identify patients who were at low risk of developing oesophageal cancer, saving these patients from regular invasive monitoring or unnecessary treatment.

Joint first author Dr Sarah Killcoyne from the MRC Cancer Unit at the University of Cambridge and EMBL-EBI, said: 'Our research shows the power of genomic medicine for the early detection of cancer. We combined low-cost sequencing of standard tissue biopsies with statistical modelling to identify which patients were at greatest risk of progressing from Barrett's oesophagus to oesophageal cancer.'

Genomic mutations that lead to cancer may arise several years before a patient is diagnosed with the disease, therefore this new approach may have the ability to improve early diagnosis and treatment.

Sources and References

  • 07/09/2020
    Nature Medicine
    Genomic copy number predicts esophageal cancer years before transformation
  • 07/09/2020
    University of Cambridge
    New model predicts oesophageal cancer eight years early for half of all patients
  • 07/09/2020
    Daily Mail
    DNA testing 'can predict throat cancer up to eight years' in advance for patients with pre-cancerous condition that causes acid reflux, study finds
  • 09/09/2020
    Cosmos
    Genome sequencing may help cancer detection

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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 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.
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