A mouse model-based screening platform for the identification of immune activating compounds such as natural products for novel cancer immunotherapies. Issue 23 (1st December 2019)

• Record Type: Journal Article
• Authors: Richter, Lisa; Kropp, Sonja; Proksch, Peter; Scheu, Stefanie
• Is Part Of: Bioorganic & medicinal chemistry. Volume 27:Issue 23(2019)
• Publication Date: 2019-12-01
• Subjects: Natural products -- Drug development -- Anti-cancer immunotherapy -- Immune activation -- Screening guidelines -- Mouse models; Bioorganic chemistry -- Periodicals; Pharmaceutical chemistry -- Periodicals; Biochemistry -- Periodicals; Chemistry, Clinical -- Periodicals; Chemistry, Organic -- Periodicals; Chimie bio-organique -- Périodiques; Chimie pharmaceutique -- Périodiques; 615.19
• DOI: 10.1016/j.bmc.2019.115145
• Languages: English
• ISSNs: 0968-0896

Abstract

Graphical abstract: Abstract: The therapy of cancer continues to be a challenge aggravated by the evolution of resistance against current medications. As an alternative for the traditional tripartite treatment options of surgery, radiation and chemotherapy, immunotherapy is gaining increasing attention due to the opportunity of more targeted approaches. Promising targets are antigen-presenting cells which drive innate and adaptive immune responses. The discovery and emergence of new drugs and lead structures can be inspired by natural products which comprise many highly bioactive molecules. The development of new drugs based on natural products is hampered by the current lack of guidelines for screening these structures for immune activating compounds. In this work, we describe a phenotypic preclinical screening pipeline for first-line identification of promising natural products using the mouse as a model system. Favorable compounds are defined to be non-toxic to immune target cells, to show direct anti-tumor effects and to be immunostimulatory at the same time. The presented screening pipeline constitutes a useful tool and aims to integrate immune activation in experimental approaches early on in drug discovery. It supports the selection of natural products for later chemical optimization, direct application in in vivo mouse models and clinical trials and promotes the emergence of new innovative drugs for cancer treatment.