Clinical OMICS

JUL-AUG 2019

Healthcare magazine for research scientists, labs, pathologists, hospitals, cancer centers, physicians and biopharma companies providing news articles, expert interviews and videos about molecular diagnostics in precision medicine

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26 Clinical OMICs July/August 2019 www.clinicalomics.com of biomedical knowledge, evidence and reference sets to support a broader and deeper understanding of complex biology systemsand evidence-based analysis and interpre- tation." This effort is tied to the company's belief that evi- dence-based "interpretation is, and will continue to be, the rate limiting factor for broad adoption of high-throughput sequencing platforms." Foundation Medicine, which offers specialized can- cer screening panels, sequences thousands of patients per week. Using these data, the company has created what it describes as "one of the largest consolidated genomic profiling knowl- edgebases in the country." Their FoundationCORE database contains more than 300,000 cases and is continually updated. "Our tests are designed to be as evergreen as possi- ble," says David Fabrizio, vice president of product development. That means markers will be added and dropped from their panels based on accrued evidence. At this point "about a third of cases who get tested with the CDX panel end up with a match to an approved therapy," Fabrizio says. "About 80% overall get some type of recom- mendation." Those with no genetic marker found are usual better candidates for traditional chemotherapy. An expanding horizon While advances in sequencing instruments will continue to impact the sequencing field, "there has been a major industry shift from a focus on instrumentation to insight, with more emphasis and resources going towards the infor- matics phase of NGS," said Scott. One of the major challenges for NGS will be addressing complex disorders. Most inherited complex diseases, such as autism or arthritis, involve more than one gene and have variable phenotypes. With NGS, researchers can test a large number of genes simultaneously in a cost-effective manner, such as by using targeted gene panels, or by performing whole-exome (WES) or whole-genome (WGS) sequenc- ing. However, even as the cost of sequencing drops, it is expected that large numbers of patients will be needed to conduct such studies successfully. But the use of sequencing in the clinic is expected to continue growing in prenatal screening, rare diseases, and oncology as its use becomes more accepted and broadly adopted. A recent study from Color, for example, found that a large proportion of patients at risk of cancer are not being tested because they don't meet current guideline cri- teria. From a pool of more than 23,000 patients tested, the researchers found that more than 2,500 individuals had positive results for cancer risk, although they did not meet clinical guidelines for testing. Most of those results were pathogenic variants in BRCA1 and BRCA2. (Neben et al. Journal of Molecular Diagnostics, 2019) Researchers and clinicians are also incorporating more different types of data with sequencing results. SOPHiA for Radiomics analyzes medical images and combines them with biological and clinical data to predict tumor evolution. It's designed to go beyond the usual RECIST and PERCIST cri- teria, to deliver finer biomarkers and support clinicians in matching cancer patients to treatments. SOPHiA's artificial intelligence platform (see below) uses techniques such as sta- tistical inference, pattern recognition, and machine learning. Foundation Medicine, meanwhile, partnered with Flat- iron Health to create a clinico-genomic database. A study recently published in JAMA (May 28, 2019) based on that partnership demonstrated the potential of real-world data for improving personalized cancer care. It looked at associ- ations between tumor genomics and patient characteristics as well as clinical outcomes in 4064 patients with NSCLC. Rehm is a principal investigator for the NIH-funded ClinGen and a vice chair of the Global Alliance for Genomics and Health (GA4GH). She continues to focus on data sharing, both through centralized databases such as ClinVar as well as federated platforms. "ClinVar allows groups to share and compare interpreted variants, whereas evidence, such as patient data, is best shared through federated patforms where we access data through APIs using standards being developed by GA4GH." Like ClinVar, gnomad is another collaborative database with information about variants. ClinGen convenes experts around the world to develop standards and consensus in the interpretation of genes and variants. There's also hope that wider sharing will improve the eth- nic diversity of the data. A number of ethnic populations are poorly represented in current databases. All this amid the growing evidence of substantive genetic differences between populations that drive diseases and disease progression. "There's a debate about whether we should have multiple reference genomes to deal with regions with major structural Heidi Rehm, Ph.D., Massachusetts General Hospital (continued from page 24)

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