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A role for whole genome sequencing in cancer predisposition testing?

Last month the nation participated in observance of breast cancer awareness. This month the focus is on lung cancer awareness. Early next year the annual cycle will begin again, with more than two dozen awareness campaigns undertaken for cancer throughout the year. With inherited mutations estimated to play a role in 5 to 10% of all cancers, screening for cancer predisposition is an important tool for raising awareness of an individual’s risk. Which leads us to consider the current state of cancer predisposition screening and whether it could be improved.

Isolation of the BRCA1 and BRCA2 genes in 1994 and 1995 respectively led to the launch of the first clinical testing service for cancer risk more than two decades ago. Since that time cancer predisposition tests have evolved significantly. First of all, they cover more genes as our knowledge of predisposing mutations has grown. There are now hundreds of genes linked to more than 50 inherited cancer syndromes. Secondly, they increasingly take advantage of technological advances, most notably next generation sequencing. Yet, despite these advances in knowledge and technology, we find that the approach to testing has not changed all that much.

Currently, a test is selected based on the type of cancer believed to run in the patient’s family. Or a test designed to survey the most common forms of cancer may be selected for broader coverage. Both types screen a defined set of genes, selected a priori, based on known cancer risk mutations. The patient’s blood is drawn, DNA is isolated, the relevant assay for the selected genes is performed and the results are reported to the patient. But our understanding of cancer grows continuously. A year from now, new predisposing mutations, in potentially new genes, will have been identified. For a comprehensive view of a patient’s risk using these new markers, a new test would need to be performed with a new blood sample.

In addition, individual tests are often optimized for specific types of variants and may miss more complex variants. Variants such as the polymorphic GGC repeat in the NPAS2 gene that has recently been associated with melanoma, or the polymorphic CAG repeat in the AR gene that is associated with susceptibility to prostate cancer. For a truly comprehensive view of a patient’s risk such complex mutations need to be assessed.

As the price of whole genome sequencing (WGS) continues to drop, we foresee an increasing role for the technology in addressing the current gaps in cancer predisposition screening. PCR-free WGS provides unique opportunities for simultaneous detection of short tandem repeats (such as those described for NPAS2 and AR), in addition to other structural variants and small sequence changes. Because the DNA regions of interest are not predetermined in WGS, and because it already provides comprehensive coverage, one blood sample and sequencing run can support many analyses. No additional sequencing is required as our knowledge grows – just a simple update of the underlying source annotation databases is sufficient to identify new predisposing variants.

With its comprehensive coverage, WGS often raises the concern that there is greater potential of identifying, and therefore needing to report, incidental findings to patients. Particularly in phenotypically healthy individuals who are most likely to undergo cancer predisposition testing. Thanks to in silico panel technology, it’s possible to leverage the benefits of WGS without the concerns of identifying significant numbers of unrelated incidental findings. In silico panels (learn more about them here) enable discrete slices of sequenced DNA ranging in size from a single gene to hundreds of genes to be analyzed. A focused panel can be employed to selectively screen for predisposition to a particular condition while limiting the likelihood of identifying, and therefore limiting the need to report, incidental findings. If concerns about another condition arise at a later date, it’s a simple matter to analyze the data from the original sequencing run with a new, appropriately focused in silico panel.

Considering its independence from a priori disease-mutation knowledge, its comprehensive coverage of small and complex variants alike and the ability to use in silico panels to minimize incidental findings, we believe WGS does indeed hold great promise for providing a comprehensive view of cancer risk. And as such, has an important role in cancer predisposition screening.

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