NantHealth presents sequencing study at #ASCO18

Results to be presented during the tumor biology session at the American Society of Clinical Oncology (ASCO) 2018 Annual Meeting

NantWorks, LLC today announced that its affiliate companies, NantHealth, Inc., (NASDAQ: NH), a leading next-generation, evidence-based, personalized healthcare company and NantOmics, LLC, the leader in molecular analysis and a member of the NantWorks ecosystem of companies, will present findings on how 17 percent of next generation sequencing (NGS) 50 gene panel variants are not expressed in RNA sequencing during the tumor biology session at the American Society of Clinical Oncology (ASCO) 2018 Annual Meeting, an event bringing together 30,000 oncology professionals from June 1-5, 2018 at McCormick Place in Chicago, Illinois. NantWorks will be exhibiting at booth #7147 during the event.

“By determining the frequency of non-expressed variants that would be tested by a standard NGS panel, our data shows that the identification of these genes can yield improved testing algorithms and treatment strategies,” said Patrick Soon-Shiong, MD, founder of NantWorks. “We’re excited to share this data and look forward to further exploring how NGS can be used for target therapy in oncology.”

Presentation Details

Seventeen percent of NGS 50 gene panel variants are not expressed in RNAseq, Abstract #12118
WHO: NantHealth, LLC and NantOmics, LLC
WHAT: Tumor Biology Session
WHEN: June 4, 1:15-4:45 PM CST
WHERE: Hall A, McCormick Place

Presentation Summary

This study analyzed the frequency of non-expressed variants that would be tested by a standard NGS panel through retrospective analysis of a database from a commercial DNA tumor: normal and RNAseq platform. In the 992 samples that were identified with paired DNA (WGS or WES) / RNAseq NGS, a total of 225,727 SNVs were detected. Across 37 tumor types the range of expression was 57% (melanoma) – 100% (uterine). In this analysis, 17 percent of detected variants were not expressed in the RNA sequence. As a result, the lack of RNA expression may contribute to less than expected clinical benefit with molecularly targeted therapies. Since the distribution is non-uniform, identification of these genes can yield improved testing algorithms and treatment strategies.

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