Non–Small Cell Lung Cancer Coverage from Every Angle
Advertisement
Advertisement

Novel Approach to Predicting Adverse and Beneficial Effects of Immunologic Interventions

By: Sarah Campen, PharmD
Posted: Thursday, April 11, 2019

As the immune system is manipulated to treat cancer or autoimmunity, the vital mechanisms that regulate self-tolerance and antimicrobial resistance often become unbalanced. Researchers in the Netherlands have developed a new method to predict the risk/benefit balance of those immune interventions. Their study, published in Frontiers in Immunology, describes their “systems biology approach” as a tool to identify key immune pathways involved in immune health endpoints.

“This systems biology approach forms a good starting point to predict relevant genes and (immune) biomarkers to assess the effects of the immune interventions,” stated Marjolein Meijerink, PhD, of the Netherlands Organization for Applied Scientific Research, Zeist, Netherlands, and colleagues. “This proposed approach could support a faster way to screen the effects of immune interventions.”

Dr. Meijerink and colleagues performed a literature search to identify genes involved in 4 immune health endpoints: hypersensitivity (184 genes), autoimmunity (564 genes), resistance to infection (357 genes), and cancer (3,173 genes). They also determined a sequence of key biologic processes which drive the development of immune health disturbances in the same four categories.

After evaluating the genes in relation to the immune health endpoints, they discovered that many genes play a role in multiple endpoints, whereas others are unique to one endpoint. The researchers identified 15 molecules that overlapped between all 4 immune checkpoints, including tumor necrosis factor, albumin, interferon gamma, and several interleukin factors. They also identified candidate biomarkers by filtering down all proteins indicated by the Comparative Toxicogenomics Database as secreted proteins. The researchers concluded that their “promising” strategy may be used in the future to “find both negatively and positively correlated interactions.”

Disclosure: The study authors’ disclosure information may be found at frontiersin.org.



By continuing to browse this site you permit us and our partners to place identification cookies on your browser and agree to our use of cookies to identify you for marketing. Read our Privacy Policy to learn more.