| Literature DB >> 28417948 |
Nico Jacobi1, Rita Seeboeck2, Elisabeth Hofmann3, Andreas Eger4.
Abstract
ErbB family members represent important biomarkers and drug targets for modern precision therapy. They have gained considerable importance as paradigms for oncoprotein addiction and personalized medicine. This review summarizes the current understanding of ErbB proteins in cell signalling and cancer and describes the molecular rationale of prominent cases of ErbB oncoprotein addiction in different cancer types. In addition, we have highlighted experimental technologies for the development of innovative cancer cell models that accurately predicted clinical ErbB drug efficacies. In the future, such cancer models might facilitate the identification and validation of physiologically relevant novel forms of oncoprotein and non-oncoprotein addiction or synthetic lethality. The identification of genotype-drug response relationships will further advance personalized oncology and improve drug efficacy in the clinic. Finally, we review the most important drugs targeting ErbB family members that are under investigation in clinical trials or that made their way already into clinical routine. Taken together, the functional characterization of ErbB oncoproteins have significantly increased our knowledge on predictive biomarkers, oncoprotein addiction and patient stratification and treatment.Entities:
Keywords: 3D cell culture; ErbB family; drug discovery; oncogene addiction; personalized medicine; precision therapy; synthetic lethality; tumour modeling
Year: 2017 PMID: 28417948 PMCID: PMC5406708 DOI: 10.3390/cancers9040033
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639
Figure 1Multiparametric drug discovery for precision medicine. Conventional 2D cultures and complex 3D in vitro and in vivo models are obtained from various biological starting materials and animals (cell lines, primary cells, primary tissues, mice). Databases and multi-omics sciences (e.g., genomics, transcriptomics, proteomics, metabolomics) are used to select and establish physiological culture conditions for tissue engineering and disease modeling (e.g., EGF, FGF10, gastrin, RSPO1, Wnt3a for pancreatic cancer [137]) and to identify proper animal models. Multi-omics sciences, innovative drug testing technologies and bioimaging are instrumental for defining novel genotype-drug response relationships and determining drug efficacy. This will facilitate the appropriate design of clinical trials and reduce drug attrition rates.