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News > Research buzz > Researchers map the effects of all potential changes in key cancer gene

Researchers map the effects of all potential changes in key cancer gene

8 Jul 2024
Written by Amandeep Jaspal
Research buzz

Researchers at the Crick have mapped all the possible outcomes of changes to a tumour-suppressing gene called VHL, the first step in a huge research endeavour to unpick the outcomes of tens of thousands of genetic variations in genes associated with cancer.

This VHL map could help clinicians work out which patients are at risk of developing kidney cancer or might respond to certain drugs.

Genetic changes or variants happen when one or more building blocks in DNA are altered. Both acquired and inherited variants in the VHL gene can increase the risk of kidney cancer. But many people are diagnosed with ‘variants of unknown significance’ in VHL and don’t know what this means for their cancer risk.

In research published today in Nature Genetics, researchers at the Crick used a new method called saturation genome editing to track the function of over 2,000 different VHL variants in human cells over time.

Most of the VHL variants analysed did not impact the survival of the cells, suggesting that people with these variants may not have a significantly higher risk. However, other variants were shown to be faulty for the first time, meaning patients with these variants may now be offered regular screening to reduce their cancer risk. 

The most harmful variants caused the cells to die. The team found that the faulty VHL gene increased the activity of another gene called HIF. This gene is needed to help cells survive in low oxygen, but too much HIF protein can cause tumours.

Removing HIF from cells with these VHL mutations kept the cells alive, showing that the negative effects of VHL are dependent on HIF.

Belzutifan, a drug that inhibits the HIF protein, only works for people with mutations impacting the amount of HIF present in cells . The scoring system developed by the Crick team could identify people with VHL mutations who would benefit from belzutifan treatment.

Finally, the researchers compared their scoring system with publicly available databases on kidney cancer, finding that their method could predict cancer-causing variants previously identified in the clinic with 100% accuracy.

Lots of people are told they have a ‘variant of unknown significance’ in the VHL gene and they’re in the dark about what that means for their cancer risk. Our variant function score could be a clinically useful test to categorise patients. In fact, we show that patients with the lowest scoring VHL variants tend to get kidney cancer at the highest rate. We are now working to apply this method to more genes to bring this level of diagnostic precision to more people.

Greg Findlay, Group Leader of the Genome Function Laboratory

By fine-tuning the saturation genome editing method, we’ve shown that a relatively simple test can identify what different VHL mutations do in human cells. Surprisingly, lots of variants potentially linked to cancer had neutral scores in this test, suggesting that the scoring system could bring clarity to patients in limbo about what their VHL diagnosis means.

Megan Buckley, first author and current PhD student at the University of Cambridge

The lab is now working with the Cancer Dynamics Laboratory at the Crick to track how well the function score can predict tumour growth and response to treatment in patients with VHL mutations. They are also working with the Wellcome Sanger Institute and The Institute of Cancer Research, London to map all variant effects across 15 other cancer risk genes.

This study was performed in collaboration with Zhenya Ivakine’s lab at the Hospital for Sick Children in Toronto, Canada, the Crick’s Cancer Dynamics Laboratory led by Samra Turajlic, and Athina Ganner and colleagues at the University of Freiburg in Germany. Funding was provided by the Francis Crick Institute, Cancer Research UK, VHL UK/Ireland, and the German Research Foundation.

(Article copied from CrickNet, written by Claire Green). Full uncropped imagery/details here.

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