Drug repurposing using high-throughput screening identifies a promising drug combination to treat adrenocortical carcinoma

Antonio M. Lerario; Gary D. Hammer

doi:10.18632/oncotarget.26091

Unbiased High-Throughput Drug Combination Pilot Screening Identifies Synergistic Drug Combinations Effective against Patient-Derived and Drug-Resistant Melanoma Cell Lines

SLAS DISCOVERY Advancing Life Sciences ◽

10.1177/2472555220970917 ◽

2020 ◽

pp. 247255522097091

Author(s):

David A. Close ◽

John M. Kirkwood ◽

Ronald J. Fecek ◽

Walter J. Storkus ◽

Paul A. Johnston

Keyword(s):

Growth Inhibition ◽

Cell Lines ◽

Melanoma Cell ◽

High Throughput ◽

Drug Combination ◽

High Throughput Screening ◽

Dna Methyltransferase ◽

Cross Resistance ◽

Braf Mutations ◽

Melanoma Cell Lines

We describe the development, optimization, and validation of 384-well growth inhibition assays for six patient-derived melanoma cell lines (PDMCLs), three wild type (WT) for BRAF and three with V600E- BRAF mutations. We conducted a pilot drug combination (DC) high-throughput screening (HTS) of 45 pairwise 4×4 DC matrices prepared from 10 drugs in the PDMCL assays: two B-Raf inhibitors (BRAFi), a MEK inhibitor (MEKi), and a methylation agent approved for melanoma; cytotoxic topoisomerase II and DNA methyltransferase chemotherapies; and drugs targeting the base excision DNA repair enzyme APE1 (apurinic/apyrimidinic endonuclease-1/redox effector factor-1), SRC family tyrosine kinases, the heat shock protein 90 (HSP90) molecular chaperone, and histone deacetylases. Pairwise DCs between dasatinib and three drugs approved for melanoma therapy—dabrafenib, vemurafenib, or trametinib—were flagged as synergistic in PDMCLs. Exposure to fixed DC ratios of the SRC inhibitor dasatinib with the BRAFis or MEKis interacted synergistically to increase PDMCL sensitivity to growth inhibition and enhance cytotoxicity independently of PDMCL BRAF status. These DCs synergistically inhibited the growth of mouse melanoma cell lines that either were dabrafenib-sensitive or had acquired resistance to dabrafenib with cross resistance to vemurafenib, trametinib, and dasatinib. Dasatinib DCs with dabrafenib, vemurafenib, or trametinib activated apoptosis and increased cell death in melanoma cells independently of their BRAF status or their drug resistance phenotypes. These preclinical in vitro studies provide a data-driven rationale for the further investigation of DCs between dasatinib and BRAFis or MEKis as candidates for melanoma combination therapies with the potential to improve outcomes and/or prevent or delay the emergence of disease resistance.

Phenotypic assays in yeast and zebrafish reveal drugs that rescue ATP13A2 deficiency

Brain Communications ◽

10.1093/braincomms/fcz019 ◽

2019 ◽

Vol 1 (1) ◽

Cited By ~ 1

Author(s):

Ursula Heins-Marroquin ◽

Paul P Jung ◽

Maria Lorena Cordero-Maldonado ◽

Alexander D Crawford ◽

Carole L Linster

Keyword(s):

Heavy Metal ◽

High Throughput ◽

High Throughput Screening ◽

Drug Testing ◽

Neuronal Ceroid Lipofuscinosis ◽

Drug Repurposing ◽

In Vivo Model ◽

Inherited Disorders ◽

Zebrafish Model

Abstract Mutations in ATP13A2 (PARK9) are causally linked to the rare neurodegenerative disorders Kufor-Rakeb syndrome, hereditary spastic paraplegia and neuronal ceroid lipofuscinosis. This suggests that ATP13A2, a lysosomal cation-transporting ATPase, plays a crucial role in neuronal cells. The heterogeneity of the clinical spectrum of ATP13A2-associated disorders is not yet well understood and currently, these diseases remain without effective treatment. Interestingly, ATP13A2 is widely conserved among eukaryotes, and the yeast model for ATP13A2 deficiency was the first to indicate a role in heavy metal homeostasis, which was later confirmed in human cells. In this study, we show that the deletion of YPK9 (the yeast orthologue of ATP13A2) in Saccharomyces cerevisiae leads to growth impairment in the presence of Zn2+, Mn2+, Co2+ and Ni2+, with the strongest phenotype being observed in the presence of zinc. Using the ypk9Δ mutant, we developed a high-throughput growth rescue screen based on the Zn2+ sensitivity phenotype. Screening of two libraries of Food and Drug Administration-approved drugs identified 11 compounds that rescued growth. Subsequently, we generated a zebrafish model for ATP13A2 deficiency and found that both partial and complete loss of atp13a2 function led to increased sensitivity to Mn2+. Based on this phenotype, we confirmed two of the drugs found in the yeast screen to also exert a rescue effect in zebrafish—N-acetylcysteine, a potent antioxidant, and furaltadone, a nitrofuran antibiotic. This study further supports that combining the high-throughput screening capacity of yeast with rapid in vivo drug testing in zebrafish can represent an efficient drug repurposing strategy in the context of rare inherited disorders involving conserved genes. This work also deepens the understanding of the role of ATP13A2 in heavy metal detoxification and provides a new in vivo model for investigating ATP13A2 deficiency.

DrugCombDB: a comprehensive database of drug combinations toward network medicine and combination therapy

10.1101/477547 ◽

2018 ◽

Author(s):

Lei Deng ◽

Bo Zou ◽

Wenhao Zhang ◽

Hui Liu

Keyword(s):

High Throughput ◽

Drug Combination ◽

High Throughput Screening ◽

Prediction Models ◽

Human Cancer ◽

Drug Combinations ◽

Data Sources ◽

Supporting Evidence ◽

Comprehensive Database ◽

Computational Screening

AbstractDrug combinations have demonstrated high efficacy and low adverse side effects compared to single drug administrations in cancer therapies, and thus draw intensive attentions from researchers and pharmaceutical enterprises. Thanks to the fast development of high-throughput screening (HTS) methods, the amount of available drug combination datasets has tremendously increased. However, existing drug combination databases are lack of indications of the drug combinations and quantitative dose-responses. Therefore, there is an urgent need for a comprehensive database that is crucial to both experimental and computational screening of drug combinations. In this paper, we present DrugCombDB, a comprehensive database dedicated to integrating drug combinations from various data sources. Concretely, the data sources include 1) high-throughput screening assays of drug combinations, 2) external databases, and 3) manual curations from PubMed literature. In total, DrugCombDB includes 1,127,969 experimental data points with quantitative dose response and concentrations of drug combinations covering 561 unique drugs and 104 human cancer cell lines, and 1,875 FDA approved or literature-supported drug combinations. In particular, we adopted the zero interaction potency (ZIP) model [2] to compute the scores determining the synergy or antagonism of two drugs. To facilitate the downstream usage of our data resource, we prepared multiple datasets that are ready for building prediction models of classification and regression analysis. A website with user-friendly data visualization is provided to help users access the wealth of data. Users can input a drug of interest to retrieve associated drug combinations, together with the supporting evidence sources and drug targets. Our database is available at http://drugcombdb.denglab.org/.

Identification of Antifungal Compounds against Multidrug Resistant Candida auris Utilizing a High Throughput Drug Repurposing Screen

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.01305-20 ◽

2021 ◽

Author(s):

Yu-Shan Cheng ◽

Jose Santinni Roma ◽

Min Shen ◽

Caroline Mota Fernandes ◽

Patricia S. Tsang ◽

...

Keyword(s):

High Throughput ◽

High Throughput Screening ◽

Treatment Options ◽

Drug Repurposing ◽

Multidrug Resistant ◽

Current Treatment ◽

Drug Combinations ◽

Serine Palmitoyltransferase ◽

Candida Auris ◽

Pharmacologically Active

Candida auris is an emerging fatal fungal infection that has resulted in several outbreaks in hospitals and care facilities. Current treatment options are limited by the development of drug resistance. Identifying new pharmaceuticals to combat these drug-resistant infections will thus be required to overcome this unmet medical need. We have established a bioluminescent ATP-based assay to identify new compounds and potential drug combinations showing effective growth inhibition against multiple strains of multidrug resistant Candida auris. The assay is robust and suitable for assessing large compound collections by high throughput screening. Utilizing this assay, we conducted a screen of 4,314 approved drugs and pharmacologically active compounds which yielded 25 compounds including 6 novel anti-Candida auris compounds and 13 sets of potential two drug combinations. Among the drug combinations, the serine palmitoyltransferase inhibitor myriocin demonstrated a combinational effect with flucytosine against all tested isolates during screening. This combinational effect was confirmed in 13 clinical isolates of Candida auris.

High-Throughput Identification of Antibacterials Against Pseudomonas aeruginosa

Frontiers in Microbiology ◽

10.3389/fmicb.2020.591426 ◽

2020 ◽

Vol 11 ◽

Author(s):

Shijia Li ◽

Pengfei She ◽

Linying Zhou ◽

Xianghai Zeng ◽

Lanlan Xu ◽

...

Keyword(s):

Pseudomonas Aeruginosa ◽

High Throughput ◽

High Throughput Screening ◽

Combined Therapy ◽

Drug Repurposing ◽

Antimicrobial Activities ◽

Health Concern ◽

Phenotypic Analysis ◽

Screening Assay ◽

High Throughput Screening Assay

Antibiotic resistance is a growing public health concern, though the constant development of new antibiotics. The combination of high-throughput screening and drug repurposing is an effective way to develop new therapeutic uses of drugs. In this study, we screened a drug library consisting of 1,573 drugs already approved by the Food and Drug Administration and 903 drugs from the natural product library, to identify antimicrobials against Pseudomonas aeruginosa. A high-throughput screening assay based on microtiter plate was used to screen 39 drugs that inhibit the planktonic or biofilm formation of P. aeruginosa while most of them are antibiotics. The antimicrobial activities of these drugs were evaluated by phenotypic analysis. Further studies showed the combined therapy of tetracycline antibiotics demeclocycline hydrochloride (DMCT) and the novel antimicrobial peptide SAAP-148 has an effective synergistic antibacterial effect on P. aeruginosa PAO1 and P. aeruginosa ATCC27853. Moreover, the time-kill curve assay and murine model of cutaneous abscesses further confirmed the synergistic effect. In addition, the combination of DMCT and SAAP-148 has the potential to combat clinically isolated multidrug-resistant (MDR) P. aeruginosa strains. Our results clearly indicate that DMCT and SAAP-148 combined therapy could be an effective method to combat MDR P. aeruginosa-related infections.

High-throughput screening of the ReFRAME, Pandemic Box, and COVID Box drug repurposing libraries against SARS-CoV2 nsp15 endoribonuclease to identify small-molecule inhibitors of viral activity

10.1101/2021.01.21.427657 ◽

2021 ◽

Author(s):

Ryan Choi ◽

Mowei Zhou ◽

Roger Shek ◽

Jesse W. Wilson ◽

Logan Tillery ◽

...

Keyword(s):

High Throughput ◽

High Throughput Screening ◽

Nonstructural Protein ◽

Unmet Need ◽

Drug Repurposing ◽

Great Promise ◽

Compound Libraries ◽

Global Pandemic ◽

Essential Enzyme

AbstractSARS-CoV-2 has caused a global pandemic, and has taken over 1.7 million lives as of mid-December, 2020. Although great progress has been made in the development of effective countermeasures, with several pharmaceutical companies approved or poised to deliver vaccines to market, there is still an unmet need of essential antiviral drugs with therapeutic impact for the treatment of moderate-to-severe COVID-19. Towards this goal, a high-throughput assay was used to screen SARS-CoV-2 nsp15 uracil-dependent endonuclease (endoU) function against 13 thousand compounds from drug and lead repurposing compound libraries. While over 80% of initial hit compounds were pan-assay inhibitory compounds, three hits were confirmed as nsp15 endoU inhibitors in the 1-20 μM range in vitro. Furthermore, Exebryl-1, a β-amyloid anti-aggregation molecule for Alzheimer’s therapy, was shown to have antiviral activity between 10 to 66 μM, in VERO, Caco-2, and Calu-3 cells. Although the inhibitory concentrations determined for Exebryl-1 exceed those recommended for therapeutic intervention, our findings show great promise for further optimization of Exebryl-1 as an nsp15 endoU inhibitor and as a SARS-CoV-2 antiviral.Author summaryDrugs to treat COVID-19 are urgently needed. To address this, we searched libraries of drugs and drug-like molecules for inhibitors of an essential enzyme of the virus that causes COVID-19, SARS-CoV-2 nonstructural protein (nsp)15. We found several molecules that inhibited the nsp15 enzyme function and one was shown to be active in inhibiting the SARS-CoV-2 virus. This demonstrates that searching for SARS-CoV-2 nsp15 inhibitors can lead inhibitors of SARS-CoV-2, and thus therapeutics for COVID-19. We are currently working to see if these inhibitors could be turned into a drug to treat COVID-19.

Automatic end-to-end analysis of high-throughput in vitro cell culture screening by HTSplotter

10.1101/2021.09.06.459128 ◽

2021 ◽

Author(s):

Carolina Nunes ◽

Jasper Anckaert ◽

Fanny De Vloed ◽

Jolien De Wyn ◽

Kaat Durinck ◽

...

Keyword(s):

Cell Culture ◽

Data Analysis ◽

Data Processing ◽

Real Time ◽

High Throughput ◽

Drug Combination ◽

High Throughput Screening ◽

Screening Experiments ◽

Over Time

Biomedical researchers are moving towards high-throughput screening, as this allows for automatization, better reproducibility and more and faster results. High-throughput screening experiments encompass drug, drug combination, genetic perturbagen or a combination of genetic and chemical perturbagen screens. These experiments are conducted in real-time assays over time or in an endpoint assay. The data analysis consists of data cleaning and structuring, as well as further data processing and visualisation, which, due to the amount of data, can easily become laborious, time consuming, and error-prone. Therefore, several tools have been developed to aid researchers in this data analysis, but they focus on specific experimental set-ups and are unable to process data of several time points and genetic-chemical perturbagen screens together. To meet these needs, we developed HTSplotter, available as web tool and Python module, that performs automatic data analysis and visualisation of either endpoint or real-time assays from different high-throughput screening experiments: drug, drug combination, genetic perturbagen and genetic-chemical perturbagen screens. HTSplotter implements an algorithm based on conditional statements in order to identify experiment type and controls. After appropriate data normalization, HTSplotter executes downstream analyses such as dose-response relationship and drug synergism by the Bliss independence method. All results are exported as a text file and plots are saved in a PDF file. The main advantage of HTSplotter over other available tools is the automatic analysis of genetic-chemical perturbagen screens and real-time assays where results are plotted over time. In conclusion, HTSplotter allows for the automatic end-to-end data processing, analysis and visualisation of various high-throughput in vitro cell culture screens, offering major improvements in terms of versatility, convenience and time over existing tools.

Methods for High-Throughput Drug Combination Screening and Synergy Scoring

10.1101/051698 ◽

2016 ◽

Cited By ~ 4

Author(s):

Liye He ◽

Evgeny Kulesskiy ◽

Jani Saarela ◽

Laura Turunen ◽

Krister Wennerberg ◽

...

Keyword(s):

Cancer Cells ◽

High Throughput ◽

Drug Combination ◽

High Throughput Screening ◽

Treatment Options ◽

Drug Combinations ◽

Molecular Medicine ◽

Targeted Drugs ◽

Functional Profiling ◽

Automated Screening

AbstractGene products or pathways that are aberrantly activated in cancer but not in normal tissue hold great promises for being effective and safe anticancer therapeutic targets. Many targeted drugs have entered clinical trials but so far showed limited efficacy mostly due to variability in treatment responses and often rapidly emerging resistance. Towards more effective treatment options, we will critically need multi-targeted drugs or drug combinations, which selectively inhibit the cancer cells and block distinct escape mechanisms for the cells to become resistant. Functional profiling of drug combinations requires careful experimental design and robust data analysis approaches. At the Institute for Molecular Medicine Finland (FIMM), we have developed an experimental-computational pipeline for high-throughput screening of drug combination effects in cancer cells. The integration of automated screening techniques with advanced synergy scoring tools allows for efficient and reliable detection of synergistic drug interactions within a specific window of concentrations, hence accelerating the identification of potential drug combinations for further confirmatory studies.

Virtual High Throughput Screening Based Prediction of Potential Drugs for COVID-19

10.20944/preprints202002.0418.v1 ◽

2020 ◽

Cited By ~ 3

Author(s):

Sekhar Talluri

Keyword(s):

High Throughput ◽

High Throughput Screening ◽

Viral Infections ◽

Genomic Sequence ◽

Reproduction Number ◽

Three Dimensional ◽

Drug Repurposing ◽

Dimensional Structure ◽

Main Protease ◽

Approved Drugs

SARS-CoV-2 is a betacoronavirus that was first identified during the Wuhan COVID-19 epidemic in 2019. It was listed as a potential global health threat by WHO due to high mortality, high basic reproduction number and lack of clinically approved drugs and vaccines for COVID-19. The genomic sequence of the virus responsible for COVID-19, as well as the experimentally determined three dimensional structure of the Main protease (Mpro) are available. The reported structure of the target Mpro was utilized in this study to identify potential drugs for COVID-19 using virtual high throughput screening. The results of this study confirm earlier preliminary reports based on studies of homologs that some of the drugs approved for treatment of other viral infections also have the potential for treatment of COVID-19. Approved anti-viral drugs that target proteases were ranked for potential effectiveness against COVID-19 and novel candidates for drug repurposing were identified.

OR28-03 Drug Repurposing Identifies Inhibitors of the Proteostasis Network to Augment Radioiodine Uptake in Combinatorial Approaches Targeting Thyroid Cancer

Journal of the Endocrine Society ◽

10.1210/jendso/bvaa046.2135 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

Author(s):

Martin L Read ◽

Katie Brookes ◽

Alice Fletcher ◽

Caitlin E M Thornton ◽

Mohammed Alshahrani ◽

...

Keyword(s):

Thyroid Cancer ◽

Cancer Cells ◽

High Throughput ◽

High Throughput Screening ◽

Drug Repurposing ◽

Iodide Uptake ◽

Thyroid Cells ◽

Radioiodine Uptake ◽

Repurposed Drugs ◽

Thyroid Cancer Cells

Abstract New combinatorial drug strategies are urgently needed to improve radioiodine (RAI) uptake and efficiently ablate thyroid cancer cells, thereby reducing the risk of recurrent disease. Drug repurposing offers the promise of identifying already approved compounds capable of inducing sodium iodide symporter (NIS) function to enhance iodide uptake. However, a lack of thyroid cell-based assays amenable to high-throughput screening has limited progress. We utilised the mutated yellow fluorescent protein (YFP) as a surrogate biosensor of intracellular iodide and screened the Prestwick Chemical Library (1200 drugs; 95% approved) for quenching of YFP fluorescence. This allowed us to identify putative candidate drugs which increased iodide uptake >2 SD above mean. Categorisation of these revealed a high proportion of drugs that modulate the proteostasis network (19/48; ~40%), including key processes in protein homeostasis such as endoplasmic reticulum-associated protein degradation (ERAD) and autophagy. Secondary screening validated the activity of proteostasis modulators in enhancing iodide uptake after ranking 73 leading compounds based on their pharmacologic (AUC, EMAX and EC50) and specificity of response (NIS+ve vs NIS-ve YFP-thyroid cells) at ten different drug doses (0.1 to 50 μM). Of importance, several repurposed drugs (e.g. ebastine, Prestwick N, Prestwick C and clotrimazole) in combination with the HDAC inhibitor vorinostat induced a robust enhancement in RAI uptake in thyroid cancer cells (TPC-1 and 8505C NIS+ve cells, up to 11-fold vs DMSO, P<0.001), which was significantly greater than using vorinostat alone (up to 3-fold, P<0.01). For clotrimazole, we designed 7 new chemical derivatives, 3 of which showed enhanced aqueous solubility and retained the ability to significantly enhance RAI uptake. TaqMan RT-PCR revealed that, in contrast to vorinostat, our repurposed drugs failed to alter NIS mRNA expression, highlighting post-transcriptional mechanisms. Critically, 11 repurposed drugs induced significant gains in RAI uptake in human primary thyroid cells (up to 4.1-fold; P<0.05), the most physiological setting for NIS function. In conclusion, we performed high-throughput screening and identified proteostasis modulators, as well as other repurposed drugs, that markedly enhance radioiodine uptake. Further clinical investigation of these drugs might offer new combinatorial approaches, especially with existing therapies, to improve the treatment of thyroid cancer.