The DNA of cancer cells is different from that of normal cells, and mutations in the DNA of cancer cells are partly responsible for their abnormal growth. Cancer cells carrying specific mutations can be targeted by certain drugs for treatment, known as targeted therapies. For example, an EGFR mutated lung cancer is sensitive to treatment by the drug erlotinib. How does a cancer patient determine which drugs might work for their tumour?
Tumour biopsies are sent to labs such as ours, where we sequence the DNA in these tumours to identify cancer-causing mutations that can be targeted for treatment. This process can involve the narrowing down of several hundred genes to just a handful. Take for instance, lung adenocarcinomas which have been seen to possess over 1,000 somatic mutations over 600 genes. Of these, mutations in less than 30 genes are currently implicated in tumourigenesis and render sensitivity or resistance to approved drugs for cancer treatment.
Further, the level of evidence supporting this sensitivity of resistance might vary. Variants in just 7 genes (including EGFR), have the highest level of evidence as recorded by the many studies that have led to approved targeted therapies. Mutations in the rest of these genes have lesser evidence as recorded in smaller clinical studies as published in the literature, pointing to ongoing clinical trials that the patient could enrol in. Additionally, in a large percentage (≈75% in lung cancer) of the patients, there would be multiple mutations that act in concert and accentuate or nullify each other (e.g., while EGFR mutations in exons 18, 19 and 21 respond well to TKIs, the acquisition of a secondary EGFR T790M mutation will lead to resistance). This filtration from several hundred mutations to a simple few is what goes on behind the scenes in creating an automated report [Ref].
At Strand, we’ve spent years honing our interpretation of cancer mutations, and StrandIRIS is the result of that experience. StrandIRIS is two things. First, it’s an interface to automate practically all cancer mutation reporting, for rapid on-the-go interpretation. Second, to enable this automation, StrandIRIS has an exhaustive knowledgebase of the targeted cancer therapy landscape, containing 524 genes, over 16,250 variants annotated with functional significance and AMP Tiers, 104 FDA approved targeted therapies, and over 80,000 clinical trials from clinicaltrials.gov as well as WHO ICTRP. The technology behind StrandIRIS has been used to generate over 3,000 reports in our CAP-CLIA labs in India and the US.
Of course, there are dozens of subtleties in the process. Look out for our next post where we discuss one such novel use case of StrandIRIS in interpreting the effects of variants with differing AMP Tiers (levels of evidence) within the C-KIT gene.
Learn more in this brochure