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Cathy Tie, CEO and co-founder of RanomicsToronto-based biotech startup, Ranomics, has launched a database that for the first time, provides functional studies on the impact of 2,000 variants of BRCA1, which is a gene associated with hereditary breast and ovarian cancers.

The company hopes to help resolve Variants of Unknown Significance (VUS) in genetic testing, which Cathy Tie, CEO and co-founder of Ranomics, told Bioscience Technology poses a major impediment in the diagnosis of hereditary diseases. About 60 percent of genetic tests for hereditary cancers contain an unknown variant, which means it isn’t clear whether the variant is harmful or not until there is a deeper study of the genotype and corresponding phenotype. 

“It is the largest factor leading to inconclusive genetic test results and will continue to be a major bottleneck for patients and clinicians using genetic testing as a tool,” Tie said.

The functional study results, based on wet lab assays, are intended for clinical genetic testing labs and are meant to help scientists and clinicians understand the effects of previously unknown variants. Once the company explores the functionality of each genetic variant, it relies on data from the organisms to show if that particular variant is harmful for that particular gene.

Through Ramonics’ web application or third party API channels, datasets that include a report with a calculated functional score and suggested harmful or benign classification for the variant, are available to clinical labs and genetic testing companies. 


“Our data fits nicely within the variant interpretation framework proposed by the American College of Medical Genetics (ACMG) and can complement clinical data, and predictive software data to provide a conclusive and better variant classification for scientists and clinicians,” Tie said.

Currently, the ACMG guidelines only name family co-segregation data as stronger pieces of evidence than functional data.  While this is a strong method, it may not be as efficient as it’s nearly impossible to study every variant using co-segregation studies.  Tie said that there are also downsides to this approach, such as expense, and that the VUS is usually specific to the patient and not found in other family members.  Another way to classify a VUS is through predictive algorithms.  While this approach can be applied to all VUSs and has potential, Tie says the burden of proof for using computer predictions to make clinical decisions is still very high.

According to Tie there are about 37,000 possible single missense BRCA1 variants, which are variations of BRCA1 that only have one amino acid change.  The database currently includes functional studies for 2,000 of these variants.

In addition to BRCA1, Ranomics expects to cover 20 to 25 of the most commonly tested hereditary cancer genes.  Currently they are working on genes TP53 and CDK4.

Contributing Editor/Science Writer
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