SNP-based Predictor of Risk for 17 Common Cancers
The multi-cancer panel provides an inexpensive and convenient personalized genetic report that outperforms family history as a predictor of risk for 17 common cancers, including high incidence cancers reported by the NIH: colorectal, breast, ovarian, prostate and lung.
Many cancer deaths could be avoided through proactive screening – a method of identifying asymptomatic cancer at an early and treatable stage, and the first step in preventing some cancers.
Currently, screening guidelines are informed largely by family history, which stratifies risk for various cancers and in turn, informs the timing and frequency of cancer screening.
Current methods of cancer risk assessment (i.e. family history) underreport the extent of cancer due to:
- Limited knowledge of family history
- Inaccurate or false memory of events and outcomes in relatives
- Complexity of blended families
- Cultural variability in openness of family members about medical histories
- Cancer type, location and severity may not lead to accurate correlations
- Different risk among siblings and cannot assess personal cancer risk
Family history does not differentiate risk among siblings and cannot provide a personalized cancer risk assessment.
The multi-cancer panel is a blood- or saliva-based test that can be administered in the primary care setting. The test identifies many single nucleotide polymorphisms (SNPs) throughout the DNA that together generate a measure of risk for 17 common cancers. A resulting genetic risk score is calculated from a combination of risk-associated SNPs.
The test kit includes a microarray chip containing the known cancer risk-associated SNPs, a software package used to calculate a genetic risk score for each cancer from genotype, and a visual aid for physicians and patients to facilitate the interpretation and understanding of results.
The multi-cancer panel identifies higher-risk individuals for whom targeted cancer screening protocols and preventative interventions would be beneficial.
Available for CLIA approval as a laboratory-developed test
Available for clinical testing as an in vitro diagnostic
- Jianfeng Xu, PhD, Genomics and Personalized Medicine Research
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Dean Stell, MBA