Researchers from Cambridge University have developed an algorithm classifier called MMRDetect, where application to 7,695 whole-genome-sequenced cancers showed enhanced detection of MMR-deficient tumors, with implications for responsiveness to immunotherapies. The study was published today in Nature Cancer.
The team also identified nine repair genes. Then, they used CRISPR-Cas9 to silence these repair genes in healthy human stem cells. In doing so, they observed strong mutation patterns, or mutational signatures, which offer useful markers of those genes and the repair pathways they are involved in, failing. Their results also suggest that these signatures of repair pathway defects are on-going and could therefore serve as crucial biomarkers in precision medicine.
Senior author Serena Nik-Zainal says, "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 tumor, and what treatments should be used specifically to treat their cancer."
MMRDetect uses the mutational signatures that were identified in the knockout experiments, and was trained on whole genome sequencing data from NHS cancer patients in the 100,000 Genomes Project, to identify tumors with mismatch repair deficiences, which makes them sensitive to checkpoint inhibitors. Having developed the algorithm on tumors in this study, the plan now is to roll it out across all cancers picked up by Genomics England. To be most effective, the MMRDetect algorithm could be used as soon as a patient has received a cancer diagnosis and their tumor characterized by genome sequencing. The team believes that this tool could help to transform the way a wide range of cancers are treated.