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Review
. 2020 Jul 2;5(1):113.
doi: 10.1038/s41392-020-00213-8.

Overcoming cancer therapeutic bottleneck by drug repurposing

Affiliations
Review

Overcoming cancer therapeutic bottleneck by drug repurposing

Zhe Zhang et al. Signal Transduct Target Ther. .

Abstract

Ever present hurdles for the discovery of new drugs for cancer therapy have necessitated the development of the alternative strategy of drug repurposing, the development of old drugs for new therapeutic purposes. This strategy with a cost-effective way offers a rare opportunity for the treatment of human neoplastic disease, facilitating rapid clinical translation. With an increased understanding of the hallmarks of cancer and the development of various data-driven approaches, drug repurposing further promotes the holistic productivity of drug discovery and reasonably focuses on target-defined antineoplastic compounds. The "treasure trove" of non-oncology drugs should not be ignored since they could target not only known but also hitherto unknown vulnerabilities of cancer. Indeed, different from targeted drugs, these old generic drugs, usually used in a multi-target strategy may bring benefit to patients. In this review, aiming to demonstrate the full potential of drug repurposing, we present various promising repurposed non-oncology drugs for clinical cancer management and classify these candidates into their proposed administration for either mono- or drug combination therapy. We also summarize approaches used for drug repurposing and discuss the main barriers to its uptake.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The estimated time and main steps in de novo drug discovery and development and drug repurposing for cancer therapy. De novo drug discovery and development for cancer therapy takes 10–17 years and comprises basic discovery, drug design, in vitro and in vivo experimentation (including identifying safety and efficacy), clinical trials and finally drug registration into the market. In contrast, drug repurposing for cancer therapy takes only 3–9 years as it can bypass several processes that have been completed for the original indication if the anticancer potential of the candidates is confirmed
Fig. 2
Fig. 2
Identification of drug candidates targeting the hallmarks of the cancer cell using drug repurposing enabled by recapitulative signaling networks. The complex signaling interactions contributing to the hallmarks of cancer cells can be orchestrated, rationalizing the complexities of neoplastic disease. Drug candidates interfering with cancer capabilities are shown. CAFs cancer-associated fibroblasts, CTLs cytotoxic T lymphocytes, ECM extracellular matrix, MDSCs myeloid-derived suppressor cells, NK cells natural killer cells, Tregs regulatory T cells
Fig. 3
Fig. 3
Signaling pathways mediated by aspirin. Multiple signaling pathways regulated by aspirin is shown, acting on diverse hallmarks of cancer including tumor-promoting inflammation, deregulating energy metabolism, angiogenesis, cancer metastasis and immune evasion, are shown
Fig. 4
Fig. 4
Signaling pathways mediated by metformin. Direct or indirect protein targeting by Metformin is shown. These influences diverse hallmarks of cancer including regulating cell proliferation, self-renewal, cancer metastasis, angiogenesis and energy metabolism
Fig. 5
Fig. 5
Partially repurposed drugs emanating from our laboratory. In addition to itraconazole, ivermectin, ketoconazole and brefeldin A which target brain, breast, liver and colon cancer, respectively, antifungal agent ciclopirox olamine, anthelminthic drug pyrvinium, and natural products quercetin, 3′-epi-12β-hydroxyfroside and toxicarioside O have also been studied
Fig. 6
Fig. 6
The evolution of screening and therapeutic strategies in drug repurposing for cancer. With the development of biochemical techniques and bioinformatics, treatments based on targeted therapy mainly focus on computational approaches of drug repurposing. Currently, drug repurposing typically depends on a flexible and collaborative use of both experimental and computational approaches to screen multi-targeted agents

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