Systems biology has shown great promise in providing a better understanding of human disease and in identifying new disease targets. These methods typically leave off once the target is identified, and further research transitions to established paradigms for drug discovery. However, the vast majority of molecular pathways that function in human disease are not specific to humans, but rather are conserved across vertebrates and even to very distantly related organisms. The remarkable growth of genetic data from tractable model organisms implies that most genetic modules relevant to human biology are currently best characterized in non-human species. Such evolutionary conservation, even when the homology of the systems to the human case is distant or perhaps non-obvious, should enable new drug design strategies.
Clearly, identification of deeply conserved gene networks in distant organisms opens the possibility of pursuing drug discovery in those organisms. While traditional methods of drug discovery focus on gene-by-gene rather than network- or system-level similarities, we suggest that phenologs—gene networks that while orthologous may nonetheless produce different phenotypes due to altered usage or organismal contexts
[1]—can provide a basis not just for screening against a single protein, but also for simultaneous drug discovery efforts against multiple targets in parallel. Given the key roles that model organisms already play in biomedical research, identification of such deep homologies should also allow us to better leverage the particular strengths of the wide variety of animal models in order to rapidly test candidate drugs found from such an approach.
We recently developed a method for systematically discovering phenologs, and this approach identified a conserved module that is relevant to lovastatin sensitivity in yeast and is also responsible for regulating angiogenesis in vertebrates
[1]. Angiogenesis, the process of forming new blood vessels, plays an essential role in development, reproduction, and tissue repair
[2]. Because the vascular network supplies oxygen and nutrients to cancer cells as well as to normal cells, angiogenesis also governs the growth of many types of tumors, and is central to malignancy
[2]–
[5]. The vasculature is thus considered to be a major therapeutic target for drug development. Some cancers, such as the most common and deadly brain neoplasm, glioblastoma multiformae
[6], are heavily vascularized, but have not responded to current angiogenesis inhibitors
[7],
[8]. Because new agents that target the vasculature would increase our arsenal for battling cancers resistant to current therapies
[2]–
[5], there is a clear clinical need for novel approaches to their identification.
Here, we have exploited data mining of genetic interactions in yeast, in vivo time-lapse imaging in a non-mammalian vertebrate, loss-of-function analysis in cultured human cells, and preclinical xenografts in mice to identify and characterize a novel anti-angiogenic small molecule (). Excitingly, this compound is already FDA approved for use in treating certain infections in humans, making it an excellent candidate for rapid translation to the clinic. This research exemplifies a general strategy for exploiting deeply conserved genetic modules for drug screening, characterized by screens focused not on single genes but rather on conserved genetic modules and by a strong reliance on tractable model organisms in order to speed the discovery of therapeutics.