Elsevier

Drug Resistance Updates

Volume 52, September 2020, 100713
Drug Resistance Updates

Repurposing old drugs to fight multidrug resistant cancers

https://doi.org/10.1016/j.drup.2020.100713Get rights and content

Abstract

Overcoming multidrug resistance represents a major challenge for cancer treatment. In the search for new chemotherapeutics to treat malignant diseases, drug repurposing gained a tremendous interest during the past years. Repositioning candidates have often emerged through several stages of clinical drug development, and may even be marketed, thus attracting the attention and interest of pharmaceutical companies as well as regulatory agencies. Typically, drug repositioning has been serendipitous, using undesired side effects of small molecule drugs to exploit new disease indications. As bioinformatics gain increasing popularity as an integral component of drug discovery, more rational approaches are needed. Herein, we show some practical examples of in silico approaches such as pharmacophore modelling, as well as pharmacophore- and docking-based virtual screening for a fast and cost-effective repurposing of small molecule drugs against multidrug resistant cancers. We provide a timely and comprehensive overview of compounds with considerable potential to be repositioned for cancer therapeutics. These drugs are from diverse chemotherapeutic classes. We emphasize the scope and limitations of anthelmintics, antibiotics, antifungals, antivirals, antimalarials, antihypertensives, psychopharmaceuticals and antidiabetics that have shown extensive immunomodulatory, antiproliferative, pro-apoptotic, and antimetastatic potential. These drugs, either used alone or in combination with existing anticancer chemotherapeutics, represent strong candidates to prevent or overcome drug resistance. We particularly focus on outcomes and future perspectives of drug repositioning for the treatment of multidrug resistant tumors and discuss current possibilities and limitations of preclinical and clinical investigations.

Introduction

The number of published articles referring to the term 'drug repositioning', or its siblings 'drug repurposing', 'drug reprofiling', 'drug redirecting' and/or 'drug rediscovery' have increased exponentially in the past decade. Those terms relate to a drug discovery strategy, where the ultimate goal is finding new uses for existing drugs (Pushpakom et al., 2018). Although several factors could be attributed to this phenomenon, the economic benefit remains the driving force. This approach grants pharmaceutical companies extended patents as a mean to overcome the difficulties arising from the so-called productivity problem. Additionally, the worldwide pressure on prices, the challenges from generics and the ever-increasing regulatory hurdles make drug repositioning an attractive stratagem. Drug reprofiling represents a cost-effective subterfuge over de novo drug discovery and development for diverse reasons, since it offers one of the best risk-versus-reward trade-offs of the available drug development strategies (Ashburn and Thor, 2004; Pushpakom et al., 2018). This occurs because repositioning candidates have often been through several stages of development, including efficacy, pharmacokinetics, pharmacodynamics and toxicity, and may even be marketed entities (Fig. 1).

The repurposing of drugs has been applied in several chemotherapeutic strategies to treat human health disorders such as cancer (Antoszczak et al., 2020; Armando et al., 2020; Masuda et al., 2020; Mudduluru et al., 2016; Nowak-Sliwinska et al., 2019; Serafin et al., 2019), neurodegenerative diseases (Corbett et al., 2015; De Castro et al., 2018), neglected tropical diseases (Andrade et al., 2019; Sbaraglini et al., 2016), autoimmune diseases (Grammer and Lipsky, 2017), asthma (Huo and Zhang, 2018), psoriasis (Xu and Zhang, 2017), cystic fibrosis (Valeria et al., 2019), and systemic lupus erythematosus (Grammer et al., 2016), to mention a few. With the development of computational methods and the increasing availability of novel types of big data (Kwon et al., 2019), the major limitation to find a new indication of a known drug lays in the identification of the molecular target of the disease of interest. In this particular context, dedicated computational tools have been developed to identify novel drug–disease connections (Yosipof et al., 2018; Zhang and Gant, 2009). Among the experimental approaches to unveil new drug-target interactions, binding assays using drug libraries and high-throughput phenotypic screening of compounds using in vitro or in vivo disease models can facilitate the identification of new potential drug candidates for clinical evaluation (Fig. 2).

As a matter of fact, drug repositioning arises from the exploitation of the promiscuity of small molecule drugs, i.e., the ability to disturb two or more independent proteins causing undesired side effects. The growing appreciation of network pharmacology as the next drug-discovery paradigm encourages scientists to better understand and make use of such polypharmacological effects of promiscuous compounds (Chaudhari et al., 2017). Polypharmacological effects offer significant advantages for finding novel therapeutics particularly for the treatment of complex and multifactorial diseases such as cancer. In this context, the antiparasitic drug niclosamide has emerged as a relevant multitarget drug against both cancer cells and cancer stem cells (CSCs). Niclosamide inhibits the Wnt/β-catenin, mTORC1, STAT3, NF-κB, NFAT and Notch signaling pathways, and targets mitochondria in cancer cells and glutathione biosynthesis, thereby inducing cell cycle arrest, growth inhibition and apoptosis (Hamdoun et al., 2017; Li et al., 2014b). The unexplored off-target potencies of the approved drugs axitinib and tivantinib led to novel drug repurposing opportunities for cancer treatment (Kuenzi et al., 2019; Pemovska et al., 2015). More importantly, polypharmacology represents a promising strategy to overcome multidrug resistant (MDR) diseases (Stelitano et al., 2020).

In the past decades, several drugs that were originally approved for indications other than cancer treatment have shown cytostatic effect on cancer cells (Hanusova et al., 2015; Yang et al., 2016). Notable examples of drug repositioning can be found in anthelmintics, antibiotics, antifungal, antiviral, antihypertensive drugs, psychopharmaceuticals and antidiabetic drugs due to their extensive immunomodulatory, antiproliferative, pro-apoptotic, and antimetastatic potential. These drugs have the potential to be used in combinations with existing anticancer chemotherapeutics as a mean to prevent or to overcome drug resistance.

In this review, we highlight the attempts to repurpose selected drugs commonly used for other medical indications, with a particular focus on the outcomes and future perspectives of drug repositioning for the treatment of MDR tumors. We present a brief outline of the computational methods that are relevant for drug reprofiling. In the subsequent sections, different classes of clinically used drugs (Fig. 3, Fig. 4) will be outlined and discussed for their anti-tumor properties and, for some of them, the most relevant repositioning studies (Table 1) that have been reported. Our aim is not to summarize all the reported studies but to provide an overview of the current possibilities and limitations.

Section snippets

Pharmacophores and drug repurposing

Overexpression of ATP-binding cassette (ABC) transporters in cancer cells, particularly ABCB1 (P-glycoprotein, P-gp), ABCC1 (MDR protein 1, MRP1) and ABCG2 (breast cancer related protein, BCRP), has been identified as a key player in the development of MDR to multiple chemotherapeutic agents (Assaraf et al., 2019; Cui et al., 2018; Gacche and Assaraf, 2018; Gonen and Assaraf, 2012; Kopecka et al., 2020; Li et al., 2016; Livney and Assaraf, 2013; Milman et al., 2019; Niewerth et al., 2015;

Immunomodulatory imide drugs (IMiDs)

Immunomodulatory imide drugs (IMiDs) are chemotherapeutic drugs capable of controlling molecular pathways, relevant in the context of tumor development and secondary spread. The most common known drug of the family is thalidomide. Thalidomide was approved in 1953 for preventing morning sickness in pregnancy and as a sedative, but it was retracted from the market in 1963, because babies exposed to the drug in utero showed severe teratogenic effects. Studies aimed at elucidating the mechanism of

Immunomodulatory imide drugs (IMiDs)

Thalidomide induced marked and durable responses in some patients with MM, including those who relapsed after high-dose chemotherapy (Singhal et al., 1999). In 2006, the FDA approved thalidomide for MM therapy in combination with dexamethasone. In 2005, the FDA approved the use of lenalidomide in the treatment of myelodysplastic syndrome (MDS) with 5q deletion, of MM in 2006, of either relapsed or refractory mantle cell lymphoma in 2013, as well as of adult patients with previously treated

Conclusions and future perspectives

As there are currently no clinically approved cancer MDR chemosensitizing agents, drug repurposing provides a practical therapeutic strategy to resensitize MDR cancers to conventional chemotherapeutic agents. Drug repositioning offers the possibility of high rewards because of shorter times to market and higher possibility of differentiation as compared with in-licensing and reformulation strategies. An additional commercial incentive of drug repurposing is the possibility to prolong patents

Declaration of Competing Interest

The authors declare no potential conflict of interest.

Acknowledgments

This article is based upon work from COST Action CA17104 STRATAGEM - “New diagnostic and therapeutic tools against multidrug resistant tumors”, supported by COST (European Cooperation in Science and Technology). JD acknowledges the financial support from The Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007). TE acknowledges the grants from the German Research Foundation (Deutsche Forschungsgemeinschaft) and Germany Cancer Aid (

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