Microb Cell Fact. 2024 May 24;23(1):152. doi: 10.1186/s12934-024-02410-4.

ABSTRACT

BACKGROUND: A novel plasmid-mediated resistance-nodulation-division (RND) efflux pump gene cluster tmexCD1-toprJ1 in Klebsiella pneumoniae tremendously threatens the use of convenient therapeutic options in the post-antibiotic era, including the "last-resort" antibiotic tigecycline.

RESULTS: In this work, the natural alkaloid harmaline was found to potentiate tigecycline efficacy (4- to 32-fold) against tmexCD1-toprJ1-positive K. pneumoniae, which also thwarted the evolution of tigecycline resistance. Galleria mellonella and mouse infection models in vivo further revealed that harmaline is a promising candidate to reverse tigecycline resistance. Inspiringly, harmaline works synergistically with tigecycline by undermining tmexCD1-toprJ1-mediated multidrug resistance efflux pump function via interactions with TMexCD1-TOprJ1 active residues and dissipation of the proton motive force (PMF), and triggers a vicious cycle of disrupting cell membrane integrity and metabolic homeostasis imbalance.

CONCLUSION: These results reveal the potential of harmaline as a novel tigecycline adjuvant to combat hypervirulent K. pneumoniae infections.

PMID:38790017 | DOI:10.1186/s12934-024-02410-4

Prog Mol Biol Transl Sci. 2024;205:247-257. doi: 10.1016/bs.pmbts.2024.03.013. Epub 2024 Apr 16.

ABSTRACT

High-throughput screening (HTS) is a simple, rapid and cost-effective solution to determine active candidates from large library of compounds. HTS is gaining attention from Pharmaceuticals and Biotechnology companies for accelerating their drug discovery programs. Conventional drug discovery program is time consuming and expensive. In contrast drug repurposing approach is cost-effective and increases speed of drug discovery as toxicity profile is already known. The present chapter highlight HTS technology including microplate, microfluidics, lab-on-chip, organ-on-chip for drug repurposing. The current chapter also highlights the application of HTS for bacterial infections and cancer.

PMID:38789182 | DOI:10.1016/bs.pmbts.2024.03.013

Prog Mol Biol Transl Sci. 2024;205:221-245. doi: 10.1016/bs.pmbts.2024.03.027. Epub 2024 Apr 4.

ABSTRACT

Drug repurposing, or drug repositioning, refers to the identification of alternative therapeutic applications for established medications that go beyond their initial indications. This strategy has becoming increasingly popular since it has the potential to significantly reduce the overall costs of drug development by around $300 million. System biology methodologies have been employed to facilitate medication repurposing, encompassing computational techniques such as signature matching and network-based strategies. These techniques utilize pre-existing drug-related data types and databases to find prospective repurposed medications that have minimal or acceptable harmful effects on patients. The primary benefit of medication repurposing in comparison to drug development lies in the fact that approved pharmaceuticals have already undergone multiple phases of clinical studies, thereby possessing well-established safety and pharmacokinetic properties. Utilizing system biology methodologies in medication repurposing offers the capacity to expedite the discovery of viable candidates for drug repurposing and offer novel perspectives for structure-based drug design.

PMID:38789180 | DOI:10.1016/bs.pmbts.2024.03.027

Prog Mol Biol Transl Sci. 2024;205:171-211. doi: 10.1016/bs.pmbts.2024.03.030. Epub 2024 Mar 31.

ABSTRACT

The purpose of drug repurposing is to leverage previously approved drugs for a particular disease indication and apply them to another disease. It can be seen as a faster and more cost-effective approach to drug discovery and a powerful tool for achieving precision medicine. In addition, drug repurposing can be used to identify therapeutic candidates for rare diseases and phenotypic conditions with limited information on disease biology. Machine learning and artificial intelligence (AI) methodologies have enabled the construction of effective, data-driven repurposing pipelines by integrating and analyzing large-scale biomedical data. Recent technological advances, especially in heterogeneous network mining and natural language processing, have opened up exciting new opportunities and analytical strategies for drug repurposing. In this review, we first introduce the challenges in repurposing approaches and highlight some success stories, including those during the COVID-19 pandemic. Next, we review some existing computational frameworks in the literature, organized on the basis of the type of biomedical input data analyzed and the computational algorithms involved. In conclusion, we outline some exciting new directions that drug repurposing research may take, as pioneered by the generative AI revolution.

PMID:38789178 | DOI:10.1016/bs.pmbts.2024.03.030

Braz J Microbiol. 2024 May 24. doi: 10.1007/s42770-024-01344-8. Online ahead of print.

ABSTRACT

Candida albicans is a polymorphic human fungal pathogen and the prime etiological agent responsible for candidiasis. The main two aspects of C. albicans virulence that have been suggested are yeast-to-hyphal (Y-H) morphological transitions and biofilm development. Anti-fungal agents targeting these virulence attributes enhances the antifungal drug development process. Repositioning with other non-fungal drugs offered a one of the new strategies and a potential alternative option to counter the urgent need for antifungal drug development. In the current study, an antiviral drug ganciclovir was screened as an antifungal agent against ATCC 90028, 10231 and clinical isolate (C1). Ganciclovir at 0.5 mg/ml concentration reduced 50% hyphal development on a silicon-based urinary catheter and was visualized using scanning electron microscopy. Ganciclovir reduced ergosterol biosynthesis in both strains and C1 isolate of C. albicans in a concentration-dependent manner. Additionally, a gene expression profile study showed that ganciclovir treatment resulted in upregulation of hyphal-specific repressors MIG1, TUP1, and NRG1 in C. albicans. Additionally, an in vivo study on the Bombyx mori silkworm model further evidenced the virulence inhibitory ability of ganciclovir (0.5 mg/ml) against C. albicans. This is the first report that explore the novel anti-morphogenic activities of ganciclovir against the pathogenic C. albicans strains, along with clinical isolates. Further, ganciclovir may be considered for therapeutic purpose after combinations with standard antifungal agents.

PMID:38789908 | DOI:10.1007/s42770-024-01344-8

EMBO Mol Med. 2024 May 24. doi: 10.1038/s44321-024-00073-7. Online ahead of print.

ABSTRACT

In the injured brain, new neurons produced from endogenous neural stem cells form chains and migrate to injured areas and contribute to the regeneration of lost neurons. However, this endogenous regenerative capacity of the brain has not yet been leveraged for the treatment of brain injury. Here, we show that in healthy brain chains of migrating new neurons maintain unexpectedly large non-adherent areas between neighboring cells, allowing for efficient migration. In instances of brain injury, neuraminidase reduces polysialic acid levels, which negatively regulates adhesion, leading to increased cell-cell adhesion and reduced migration efficiency. The administration of zanamivir, a neuraminidase inhibitor used for influenza treatment, promotes neuronal migration toward damaged regions, fosters neuronal regeneration, and facilitates functional recovery. Together, these findings shed light on a new mechanism governing efficient neuronal migration in the adult brain under physiological conditions, pinpoint the disruption of this mechanism during brain injury, and propose a promising therapeutic avenue for brain injury through drug repositioning.

PMID:38789599 | DOI:10.1038/s44321-024-00073-7

Sci Rep. 2024 May 24;14(1):11890. doi: 10.1038/s41598-024-62684-x.

ABSTRACT

Biofilm-associated candidiasis poses a significant challenge in clinical settings due to the limited effectiveness of existing antifungal treatments. The challenges include increased pathogen virulence, multi-drug resistance, and inadequate penetration of antimicrobials into biofilm structures. One potential solution to this problem involves the development of novel drugs that can modulate fungal virulence and biofilm formation, which is essential for pathogenesis. Resistance in Candida albicans is initiated by morphological changes from yeast to hyphal form. This transition triggers a series of events such as cell wall elongation, increased adhesion, invasion of host tissues, pathogenicity, biofilm formation, and the initiation of an immune response. The cell wall is a critical interface for interactions with host cells, primarily through various cell wall proteins, particularly mannoproteins. Thus, cell wall proteins and enzymes are considered potential antifungal targets. In this regard, we explored α-glucosidase as our potential target which plays a crucial role in processing mannoproteins. Previous studies have shown that inhibition of α-glucosidase leads to defects in cell wall integrity, reduced adhesion, diminished secretion of hydrolytic enzymes, alterations in immune recognition, and reduced pathogenicity. Since α-glucosidase, primarily converts carbohydrates, our study focuses on FDA-approved carbohydrate mimic drugs (Glycomimetics) with well-documented applications in various biological contexts. Through virtual screening of 114 FDA-approved carbohydrate-based drugs, a pseudo-sugar Acarbose, emerged as a top hit. Acarbose is known for its pharmacological potential in managing type 2 diabetes mellitus by targeting α-glucosidase. Our preliminary investigations indicate that Acarbose effectively inhibits C. albicans biofilm formation, reduces virulence, impairs morphological switching, and hinders the adhesion and invasion of host cells, all at very low concentrations in the nanomolar range. Furthermore, transcriptomic analysis reveals the mechanism of action of Acarbose, highlighting its role in targeting α-glucosidase.

PMID:38789465 | DOI:10.1038/s41598-024-62684-x

Prog Mol Biol Transl Sci. 2024;205:91-109. doi: 10.1016/bs.pmbts.2024.03.018. Epub 2024 Apr 4.

ABSTRACT

The drug discovery and development (DDD) process greatly relies on the data available in various forms to generate hypotheses for novel drug design. The complex and heterogeneous nature of biological data makes it difficult to utilize or gather meaningful information as such. Computational biology techniques have provided us with opportunities to better understand biological systems through refining and organizing large amounts of data into actionable and systematic purviews. The drug repurposing approach has been utilized to overcome the expansive time periods and costs associated with traditional drug development. It deals with discovering new uses of already approved drugs that have an established safety and efficacy profile, thereby, requiring them to go through fewer development phases. Thus, drug repurposing through computational biology provides a systematic approach to drug development and overcomes the constraints of traditional processes. The current chapter covers the basics, approaches and tools of computational biology that can be employed to effectively develop repurposing profile of already approved drug molecules.

PMID:38789189 | DOI:10.1016/bs.pmbts.2024.03.018

Prog Mol Biol Transl Sci. 2024;205:9-21. doi: 10.1016/bs.pmbts.2024.03.021. Epub 2024 Mar 22.

ABSTRACT

Synthetic biology, precision medicine, and nanobiotechnology are the three main emerging areas that drive translational innovation toward commercialization. There are several strategies used in precision medicine and drug repurposing is one of the key approaches as it addresses the challenges in drug discovery (high cost and time). Here, we provide a perspective on various new approaches to drug repurposing for cancer precision medicine. We report here our optimized wound healing methodology that can be used to validate drug sensitivity and drug repurposing. Using HeLa as our benchmark, we demonstrated that the assay can be applied to identify drugs that limit cell proliferation. From a future perspective, this assay can be expanded to ex vivo culturing of solid tumors in 2D culture and leukemia in 3D culture.

PMID:38789188 | DOI:10.1016/bs.pmbts.2024.03.021

Prog Mol Biol Transl Sci. 2024;205:71-90. doi: 10.1016/bs.pmbts.2024.03.022. Epub 2024 Apr 4.

ABSTRACT

The lab-on-chip technique broadly comprises of microfluidics and aims to progress multidimensionally by changing the outlook of medicine and pharmaceuticals as it finds it roots in miniaturization. Moreover, microfluidics facilitates precise physiological simulation and possesses biological system-mimicking capabilities for drug development and repurposing. Thus, organs on chip could pave a revolutionary pathway in the field of drug development and repurposing by reducing animal testing and improving drug repurposing.

PMID:38789187 | DOI:10.1016/bs.pmbts.2024.03.022

Prog Mol Biol Transl Sci. 2024;205:357-375. doi: 10.1016/bs.pmbts.2024.03.019. Epub 2024 Apr 4.

ABSTRACT

Drug repurposing has emerged as a promising approach in the drug discovery and development process as it offers safe and effective therapeutic options in a time effective manner. Though the issues related to pre-clinical and clinical aspects of drug development process are greatly addressed during drug repurposing yet regulatory perspectives gain even more However, like traditional drug development the repurposed drugs face multiple challenges. Such challenges range from the patenting rights, novelty of repurposing, data and market exclusivity to affordability and equitable access to the patient population. In order to optimize the market access of repurposed drugs, regulatory organizations throughout the world have developed accelerated approval procedures. The regulatory bodies have recognized the importance of repurposing approaches and repurposed drugs. Regulatory bodies can encourage the development of repurposed drugs by providing incentives to pharmaceutical companies and more accessible and affordable repurposed agents for the general population. This chapter summarizes the regulatory and ethical considerations pertaining to the repurposed drugs and highlights a few cases of intellectual property rights for repurposed drugs that have helped improve patient's access to safe, efficacious and cost-effective therapeutic options.

PMID:38789186 | DOI:10.1016/bs.pmbts.2024.03.019

Prog Mol Biol Transl Sci. 2024;205:303-355. doi: 10.1016/bs.pmbts.2024.03.025. Epub 2024 Apr 8.

ABSTRACT

The conventional theory linking a single gene with a particular disease and a specific drug contributes to the dwindling success rates of traditional drug discovery. This requires a substantial shift focussing on contemporary drug design or drug repurposing, which entails linking multiple genes to diverse physiological or pathological pathways and drugs. Lately, drug repurposing, the art of discovering new/unlabelled indications for existing drugs or candidates in clinical trials, is gaining attention owing to its success rates. The rate-limiting phase of this strategy lies in target identification, which is generally driven through disease-centric and/or drug-centric approaches. The disease-centric approach is based on exploration of crucial biomolecules such as genes or proteins underlying pathological cascades of the disease of interest. Investigating these pathological interplays aids in the identification of potential drug targets that can be leveraged for novel therapeutic interventions. The drug-centric approach involves various strategies such as exploring the mechanism of adverse drug reactions that can unearth potential targets, as these untoward reactions might be considered desirable therapeutic actions in other disease conditions. Currently, artificial intelligence is an emerging robust tool that can be used to translate the aforementioned intricate biological networks to render interpretable data for extracting precise molecular targets. Integration of multiple approaches, big data analytics, and clinical corroboration are essential for successful target mining. This chapter highlights the contemporary strategies steering target identification and diverse frameworks for drug repurposing. These strategies are illustrated through case studies curated from recent drug repurposing research inclined towards neurodegenerative diseases, cancer, infections, immunological, and cardiovascular disorders.

PMID:38789185 | DOI:10.1016/bs.pmbts.2024.03.025

Prog Mol Biol Transl Sci. 2024;205:277-302. doi: 10.1016/bs.pmbts.2024.03.028. Epub 2024 Apr 2.

ABSTRACT

The field of drug repurposing is gaining attention as a way to introduce pharmaceutical agents with established safety profiles to new patient populations. This approach involves finding new applications for existing drugs through observations or deliberate efforts to understand their mechanisms of action. Recent advancements in bioinformatics and pharmacology, along with the availability of extensive data repositories and analytical techniques, have fueled the demand for novel methodologies in pharmaceutical research and development. To facilitate systematic drug repurposing, various computational methodologies have emerged, combining experimental techniques and in silico approaches. These methods have revolutionized the field of drug discovery by enabling the efficient repurposing of screens. However, establishing an ideal drug repurposing pipeline requires the integration of molecular data accessibility, analytical proficiency, experimental design expertise, and a comprehensive understanding of clinical development processes. This chapter explores the key methodologies used in systematic drug repurposing and discusses the stakeholders involved in this field. It emphasizes the importance of strategic alliances to enhance the success of repurposing existing compounds for new indications. Additionally, the chapter highlights the current benefits, considerations, and challenges faced in the repurposing process, which is pursued by both biotechnology and pharmaceutical companies. Overall, drug repurposing holds great promise in expanding the use of existing drugs and bringing them to new patient populations. With the advancements in computational methodologies and the collaboration of various stakeholders, this approach has the potential to accelerate drug development and improve patient outcomes.

PMID:38789184 | DOI:10.1016/bs.pmbts.2024.03.028

Prog Mol Biol Transl Sci. 2024;205:259-275. doi: 10.1016/bs.pmbts.2024.03.024. Epub 2024 Apr 9.

ABSTRACT

Medications that are currently on the market and have proven therapeutic usage can have new therapeutic indications discovered through a process called drug repurposing, which is also called drug repositioning. This approach presents a viable method for drug developers and pharmaceutical companies to discern novel targets for FDA-approved medications. Drug repurposing presents several advantages, including reduced time consumption, lower costs, and diminished risk of failure. Sildenafil, commonly known as Viagra, serves as a notable illustration of a repurposed pharmaceutical agent, initially developed and introduced to the market as an antianginal medication. However, in the current context, its application has been redirected towards serving as a pharmaceutical intervention for the treatment of erectile dysfunction. Comparably, a multitude of pharmaceutical agents exist that have demonstrated efficacy in repurposing for therapeutic management of various clinical conditions. Focusing on the historical use of repurposed pharmaceuticals and their present state of application in disease therapies, this chapter seeks to offer a thorough review of drug repurposing methodologies. Furthermore, the rules and regulations that control the repurposing of drugs will be covered in detail in this chapter.

PMID:38789183 | DOI:10.1016/bs.pmbts.2024.03.024

Nucleic Acids Res. 2024 May 23:gkae388. doi: 10.1093/nar/gkae388. Online ahead of print.

ABSTRACT

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.

PMID:38783119 | DOI:10.1093/nar/gkae388

J Biomed Inform. 2024 May 21:104658. doi: 10.1016/j.jbi.2024.104658. Online ahead of print.

ABSTRACT

OBJECTIVE: Relation extraction is an essential task in the field of biomedical literature mining and offers significant benefits for various downstream applications, including database curation, drug repurposing, and literature-based discovery. The broad-coverage natural language processing (NLP) tool SemRep has established a solid baseline for extracting subject-predicate-object triples from biomedical text and has served as the backbone of the Semantic MEDLINE Database (SemMedDB), a PubMed-scale repository of semantic triples. While SemRep achieves reasonable precision (0.69), its recall is relatively low (0.42). In this study, we aimed to enhance SemRep using a relation classification approach, in order to eventually increase the size and the utility of SemMedDB.

METHODS: We combined and extended existing SemRep evaluation datasets to generate training data. We leveraged the pre-trained PubMedBERT model, enhancing it through additional contrastive pre-training and fine-tuning. We experimented with three entity representations: mentions, semantic types, and semantic groups. We evaluated the model performance on a portion of the SemRep Gold Standard dataset and compared it to SemRep performance. We also assessed the effect of the model on a larger set of 12K randomly selected PubMed abstracts.

RESULTS: Our results show that the best model yields a precision of 0.62, recall of 0.81, and F1 score of 0.70. Assessment on 12K abstracts shows that the model could double the size of SemMedDB, when applied to entire PubMed. We also manually assessed the quality of 506 triples predicted by the model that SemRep had not previously identified, and found that 67% of these triples were correct.

CONCLUSION: These findings underscore the promise of our model in achieving a more comprehensive coverage of relationships mentioned in biomedical literature, thereby showing its potential in enhancing various downstream applications of biomedical literature mining. Data and code related to this study are available at https://github.com/Michelle-Mings/SemRep_RelationClassification.

PMID:38782169 | DOI:10.1016/j.jbi.2024.104658

PLoS One. 2024 May 23;19(5):e0299685. doi: 10.1371/journal.pone.0299685. eCollection 2024.

ABSTRACT

Nischarin was reported to be a tumor suppressor that plays a critical role in breast cancer initiation and progression, and a positive prognostic marker in breast, ovarian and lung cancers. Our group has found that nischarin had positive prognostic value in female melanoma patients, but negative in males. This opened up a question whether nischarin has tumor type-specific and sex-dependent roles in cancer progression. In this study, we systematically examined in the public databases the prognostic value of nischarin in solid tumors, regulation of its expression and associated signaling pathways. We also tested the effects of a nischarin agonist rilmenidine on cancer cell viability in vitro. Nischarin expression was decreased in tumors compared to the respective healthy tissues, most commonly due to the deletions of the nischarin gene and promoter methylation. Unlike in healthy tissues where it was located in the cytoplasm and at the membrane, in tumor tissues nischarin could also be observed in the nuclei, implying that nuclear translocation may also account for its cancer-specific role. Surprisingly, in several cancer types high nischarin expression was a negative prognostic marker. Gene set enrichment analysis showed that in tumors in which high nischarin expression was a negative prognostic marker, signaling pathways that regulate stemness were enriched. In concordance with the findings that nischarin expression was negatively associated with pathways that control cancer growth and progression, nischarin agonist rilmenidine decreased the viability of cancer cells in vitro. Taken together, our study lays a ground for functional studies of nischarin in a context-dependent manner and, given that nischarin has several clinically approved agonists, provides rationale for their repurposing, at least in tumors in which nischarin is predicted to be a positive prognostic marker.

PMID:38781180 | DOI:10.1371/journal.pone.0299685

Phys Chem Chem Phys. 2024 May 23. doi: 10.1039/d4cp00576g. Online ahead of print.

ABSTRACT

Myeloid cell leukemia 1 (Mcl1), a critical protein that regulates apoptosis, has been considered as a promising target for antitumor drugs. The conventional pharmacophore screening approach has limitations in conformation sampling and data mining. Here, we offered an innovative solution to identify Mcl1 inhibitors with molecular dynamics-refined pharmacophore and machine learning methods. Considering the safety and druggability of FDA-approved drugs, virtual screening of the database was performed to discover Mcl1 inhibitors, and the hit was subsequently validated via TR-FRET, cytotoxicity, and flow cytometry assays. To reveal the binding characteristics shared by the hit and a typical Mcl1 selective inhibitor, we employed quantum mechanics and molecular mechanics (QM/MM) calculations, umbrella sampling, and metadynamics in this work. The combined studies suggested that fluvastatin had promising cell inhibitory potency and was suitable for further investigation. We believe that this research will shed light on the discovery of novel Mcl1 inhibitors that can be used as a supplemental treatment against leukemia and provide a possible method to improve the accuracy of drug repurposing with limited computational resources while balancing the costs of experimentation well.

PMID:38780456 | DOI:10.1039/d4cp00576g

Acta Oncol. 2024 May 23;63:385-391. doi: 10.2340/1651-226X.2024.34791.

ABSTRACT

BACKGROUND: In the two European Union (EU)-funded projects, PCM4EU (Personalized Cancer Medicine for all EU citizens) and PRIME-ROSE (Precision Cancer Medicine Repurposing System Using Pragmatic Clinical Trials), we aim to facilitate implementation of precision cancer medicine (PCM) in Europe by leveraging the experience from ongoing national initiatives that have already been particularly successful.

PATIENTS AND METHODS: PCM4EU and PRIME-ROSE gather 17 and 24 partners, respectively, from 19 European countries. The projects are based on a network of Drug Rediscovery Protocol (DRUP)-like clinical trials that are currently ongoing or soon to start in 11 different countries, and with more trials expected to be established soon. The main aims of both the projects are to improve implementation pathways from molecular diagnostics to treatment, and reimbursement of diagnostics and tumour-tailored therapies to provide examples of best practices for PCM in Europe.

RESULTS: PCM4EU and PRIME-ROSE were launched in January and July 2023, respectively. Educational materials, including a podcast series, are already available from the PCM4EU website (http://www.pcm4eu.eu). The first reports, including an overview of requirements for the reimbursement systems in participating countries and a guide on patient involvement, are expected to be published in 2024.

CONCLUSION: European collaboration can facilitate the implementation of PCM and thereby provide affordable and equitable access to precision diagnostics and matched therapies for more patients. ble from the PCM4EU website (http://www.pcm4eu.eu). The first reports, including an overview of requirements for the reimbursement systems in participating countries and a guide on patient involvement, are expected to be published in 2024.

CONCLUSION: European collaboration can facilitate the implementation of PCM and thereby provide affordable and equitable access to precision diagnostics and matched therapies for more patients.

PMID:38779910 | DOI:10.2340/1651-226X.2024.34791

Front Endocrinol (Lausanne). 2024 May 8;15:1365321. doi: 10.3389/fendo.2024.1365321. eCollection 2024.

ABSTRACT

BACKGROUND: Adrenocortical carcinoma (ACC) is an aggressive endocrine malignancy with limited therapeutic options. Treating advanced ACC with mitotane, the cornerstone therapy, remains challenging, thus underscoring the significance to predict mitotane response prior to treatment and seek other effective therapeutic strategies.

OBJECTIVE: We aimed to determine the efficacy of mitotane via an in vitro assay using patient-derived ACC cells (PDCs), identify molecular biomarkers associated with mitotane response and preliminarily explore potential agents for ACC.

METHODS: In vitro mitotane sensitivity testing was performed in 17 PDCs and high-throughput screening against 40 compounds was conducted in 8 PDCs. Genetic features were evaluated in 9 samples using exomic and transcriptomic sequencing.

RESULTS: PDCs exhibited variable sensitivity to mitotane treatment. The median cell viability inhibition rate was 48.4% (IQR: 39.3-59.3%) and -1.2% (IQR: -26.4-22.1%) in responders (n=8) and non-responders (n=9), respectively. Median IC50 and AUC were remarkably lower in responders (IC50: 53.4 µM vs 74.7 µM, P<0.0001; AUC: 158.0 vs 213.5, P<0.0001). Genomic analysis revealed CTNNB1 somatic alterations were only found in responders (3/5) while ZNRF3 alterations only in non-responders (3/4). Transcriptomic profiling found pathways associated with lipid metabolism were upregulated in responder tumors whilst CYP27A1 and ABCA1 expression were positively correlated to in vitro mitotane sensitivity. Furthermore, pharmacologic analysis identified that compounds including disulfiram, niclosamide and bortezomib exhibited efficacy against PDCs.

CONCLUSION: ACC PDCs could be useful for testing drug response, drug repurposing and guiding personalized therapies. Our results suggested response to mitotane might be associated with the dependency on lipid metabolism. CYP27A1 and ABCA1 expression could be predictive markers for mitotane response, and disulfiram, niclosamide and bortezomib could be potential therapeutics, both warranting further investigation.

PMID:38779454 | PMC:PMC11109426 | DOI:10.3389/fendo.2024.1365321