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New algorithm detects tumour weaknesses

A new study funded by Cancer Research UK and published in Nature Cancer has described a new algorithm – called MMRDetect. This algorithm is able to identify tumours which would be sensitive to particular cancer therapies.

Mutational signatures

Both endogenous and exogenous processes lead to the acquisition of somatic mutations that mark the genome with distinctive patterns. These patterns are known as mutational signatures. While advancements have been made in identifying these patterns across human cancers, our understanding of the aetiology and mechanisms underpinning these patterns remains unclear.

A lot of researchers have used cellular models to systematically study the effects of exogenous sources on DNA damage. Therefore, the next stage is to explore genome-wide mutagenic consequences of endogenous sources. Water and oxygen are two of the most mutagenic molecules to DNA. Errors during replication are also an important source of DNA changes. Fortunately, our cells are equipped with a host of cellular machinery that can specifically repair these changes.

MMRDetect algorithm

Here, researchers generated CRISPR-Cas9 knockouts of 43 DNA repair genes in human induced pluripotent stem cells. Subsequently, the team performed whole-genome sequencing of 173 subclones to obtain mechanistic insights into the formation of mutational signatures. From this, the team found that mismatch repair (MMR) deficiency signatures were caused by oxidative damage and differential misincorporation by replicative polymerases.

Using the mutational signatures that were identified from the knockout experiments and also trained on whole-genome sequencing data from the 100,000 Genomes Project, the researchers created a new mutational signature-based classifier – MMRDetect. This algorithm is specifically able to identify tumours with MMR deficiency – which makes them sensitive to specific immunotherapies. Identifying which genes are failing in specific tumours will ultimately allow doctors to prescribe medicines that work most effectively on those genes. The plan is next to roll this assay out across all cancers that are being investigated by Genomics England.

Michelle Mitchell, Chief Executive of Cancer Research UK, said:

“Determining the right treatments for patients will give them the best chance of surviving their disease. Immunotherapy in particular can be powerful, but it doesn’t work on everyone, so figuring out how to tell when it will work is vital to making it the most useful treatment it can be.

Our ability to map and mine useful information from the genomes of tumours has improved massively over the past decade. Thanks to initiatives like the 100,000 Genomes Project, we are beginning to see how we might use this information to benefit patients. We look forward to seeing how this research develops, and its possibilities in helping future patients.”

Image credit: By Science Photo Library – canva

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Algorithm / Immunotherapy / Tumour