Findings Presented at the ASCO-SITC 2020 Clinical Immuno-Oncology Symposium
Orlando, FL and Culver City, CA – February 6, 2020 – NantHealth, Inc. (NASDAQ: NH), a next-generation, evidence-based, personalized healthcare company and NantOmics, LLC, the leader in molecular analysis, today announced Real-world data for differential expression of immunoregulatory molecules and targetable cancer genes may provide therapeutic insights into agnostic-driven trial designs during an oral presentation at the Real World Evidence in Immunotherapy Session at the Clinical Immuno-Oncology Symposium, sponsored by the American Society of Clinical Oncology (ASCO) and the Society for Immunotherapy in Cancer (SITC).
The Symposium, held at Rosen Shingle Creek in Orlando, FL from February 6-8, 2020 provides cutting-edge translational science and relevant clinical results to a diverse audience of leaders in oncology education, doctors and care teams.
“Our analysis shows that commonly evaluated mutations are associated with therapeutic targets for immunotherapy,” said Sandeep “Bobby” Reddy, MD, Chief Medical Officer, NantHealth. “For example we saw high IDO expression in in patient samples with FBXW7 mutations. IDO has failed in clinical trials in the past but perhaps the wrong patient population was assessed. This data may help design better clinical trials which match the molecular phenotype with the best possible combination of therapies.”
IDO1 (i.e. IDO) is the molecular target for several immunotherapy drugs (e.g. Epacadostat) that have failed in trials that selected patients based on tissue-type. FBXW7 mutants are significantly higher in IDO1 expression regardless of which tissue they show up in, and FXBW7 mutations are found in many tissue types. Agnostic-driven clinical trial designs using strategies to identify FBXW7 tumors that have higher expression of IDO1 may be a good strategy for these types of drugs.
In the study, authors utilized TCGA data and data collected from NantHealth’s GPS Cancer database on whole exome (WES) DNA tumor and paired normal and matched deep whole transcriptomic sequencing (RNA-Seq) to identify novel associations between oncogenic mutations and immune checkpoint therapeutic targets.
“CDKN2A mutation status was identified as associated with increased PD1 and CTLA4 expression while KRAS and APC mutations were assessed as associated with decreased PDL1/2 expression,” said Christopher Szeto, Director of Machine Learning. “These mutation associations remained significant after accounting for tissue-specific expression patterns.”
Title: “Real-world data validation for differential expression of immunoregulatory molecules and targetable cancer genes may provide therapeutic insights into agnostic-driven trial designs,” Abstract #10
Authors: Jacob J. Adashek, Christopher Szeto, Sandeep K. Reddy, Philippe E. Spiess
Poster Session and Number:
Who: NantHealth, Inc. and NantOmics, LLC
What: Real World Evidence in Immunotherapy Session
When: February 6-8, 2020
Location: Rosen Shingle Creek
NantHealth, a member of the NantWorks ecosystem of companies, provides leading solutions across the continuum of care for physicians, payors, patients and biopharmaceutical organizations. NantHealth enables the use of cutting-edge data and technology toward the goals of empowering clinical decision support and improving patient outcomes. NantHealth’s comprehensive product portfolio combines the latest technology in payor/provider platforms that exchange information in near-real time (NaviNet and Eviti and molecular profiling services that combine comprehensive DNA & RNA tumor-normal profiling with pharmacogenomics analysis (GPS Cancer®). For more information, please visit www.nanthealth.com or follow us on Twitter, Facebook and LinkedIn.
NantOmics, a member of the NantWorks ecosystem of companies, delivers molecular diagnostic and machine learning AI capabilities to provide actionable intelligence and molecularly driven decision support for patients and their providers. NantOmics is the first molecular in vitro diagnostics company to accurately identify mutations and true tumor mutation burden (TMB) from proprietary tumor-normal sequencing. The identified mutations and correlative calculation of true TMB, combined with proprietary expression analysis of immuno-oncology biomarkers and novel deep-learning derived digital pathology solutions, establish the framework for the appropriate use of targeted, chemo- and immunotherapies. NantOmics computational analysis engine, an organically grown, scalable, cloud-based infrastructure capable of processing and storing thousands of genomes per day, uses novel AI tools to combine expression analysis with near real-time genomic variance computing to generate precise N of 1 neoepitope vaccine therapies for cancer patients. For more information please visit www.nantomics.com and follow Dr. Soon-Shiong on Twitter @DrPatSoonShiong.
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