Drug repurposing in oncology: Compounds, pathways, phenotypes and computational approaches for colorectal cancer

Alternative Cancer Therapeutics: Unpatentable Compounds and Their Potential in Oncology

Cancer remains a leading cause of death globally. Cancer patients often seek alternative therapies in addition to, or instead of, conventional treatments like chemotherapy, radiation, and surgery. The progress in medical advancements and early detection provides more treatment options; however, the development of cancer drugs requires a significant amount of time, demands substantial investments, and results in an overall low percent of regulatory approval. The complex relationship between patent protection and pharmaceutical innovation complicates cancer drug development and contributes to high mortality rates. Adjusting patent criteria for alternative cancer therapeutics could stimulate innovation, enhance treatment options, and ultimately improve outcomes for cancer patients. This article explores the potential of alternative cancer therapeutics, chemopreventive agents, natural products, off-patent drugs, generic unpatentable chemicals, and repurposed drugs in cancer treatment, emphasizing the mechanisms and therapeutic potential of these unconventional compounds as combinatorial cancer therapies. The biological pathways, therapeutic effects, and potential to enhance existing therapies are reviewed, demonstrating their cost-effective and accessible options as adjuvant cancer therapies.

Preliminary study on cytotoxicity of selegiline on different cancer cell lines: exploration of the induction of ROS-independent apoptosis in breast cancer cells

The concept of drug repurposing is now widely utilized by biomedical scientists for drug discovery. An example of this is the use of selegiline (SEL), a monoamine oxidase inhibitor that was initially used for the management of depression but is now being considered for another purpose. This study compares the cytotoxic effects of SEL on different cancer cells. Further, the study explores the molecular mechanism of cell death, validating the possibility of its repurposing for cancer. Preliminary analysis of network pharmacological data was conducted in silico, followed by in vitro cytotoxicity tests on PC12, G361, MDA-MB231, MCF7, THP-1, and Hela cells under normoxic and hypoxic conditions, using the MTT assay. The mechanism of cell death was then confirmed by performing DAPI and FITC-conjugated Annexin V and Propidium Iodide (PI) staining assays. Additionally, ROS levels and PKC phosphorylation were also evaluated. In silico analysis has revealed that SEL is associated with ten genes linked to different cancer types. Specifically, SEL was most cytotoxic to neuronal pheochromocytoma, triple-negative human epithelial breast cancer cells, and ER+ and PR+ breast cancer cells. Furthermore, it was observed that this cell death occurred through ROS-independent apoptosis pathways. In addition, SEL was found to inhibit the phosphorylation of PKC, which may contribute to cell death. SEL induces apoptosis in breast cancer cells independently of reactive oxygen species and inhibits the phosphorylation of protein kinase C, which merits further exploration.

A BERT-GNN Approach for Metastatic Breast Cancer Prediction Using Histopathology Reports

Metastatic breast cancer (MBC) continues to be a leading cause of cancer-related deaths among women. This work introduces an innovative non-invasive breast cancer classification model designed to improve the identification of cancer metastases. While this study marks the initial exploration into predicting MBC, additional investigations are essential to validate the occurrence of MBC. Our approach combines the strengths of large language models (LLMs), specifically the bidirectional encoder representations from transformers (BERT) model, with the powerful capabilities of graph neural networks (GNNs) to predict MBC patients based on their histopathology reports. This paper introduces a BERT-GNN approach for metastatic breast cancer prediction (BG-MBC) that integrates graph information derived from the BERT model. In this model, nodes are constructed from patient medical records, while BERT embeddings are employed to vectorise representations of the words in histopathology reports, thereby capturing semantic information crucial for classification by employing three distinct approaches (namely univariate selection, extra trees classifier for feature importance, and Shapley values to identify the features that have the most significant impact). Identifying the most crucial 30 features out of 676 generated as embeddings during model training, our model further enhances its predictive capabilities. The BG-MBC model achieves outstanding accuracy, with a detection rate of 0.98 and an area under curve (AUC) of 0.98, in identifying MBC patients. This remarkable performance is credited to the model's utilisation of attention scores generated by the LLM from histopathology reports, effectively capturing pertinent features for classification.

The Potential of Integrative Cancer Treatment Using Melatonin and the Challenge of Heterogeneity in Population-Based Studies: A Case Report of Colon Cancer and a Literature Review

Melatonin is a multifunctional hormone regulator that maintains homeostasis through circadian rhythms, and desynchronization of these rhythms can lead to gastrointestinal disorders and increase the risk of cancer. Preliminary clinical studies have shown that exogenous melatonin alleviates the harmful effects of anticancer therapy and improves quality of life, but the results are still inconclusive due to the heterogeneity of the studies. A personalized approach to testing clinical parameters and response to integrative treatment with nontoxic and bioavailable melatonin in patient-centered N-of-1 studies deserves greater attention. This clinical case of colon cancer analyzes and discusses the tumor pathology, the adverse effects of chemotherapy, and the dynamics of markers of inflammation (NLR, LMR, and PLR ratios), tumors (CEA, CA 19-9, and PSA), and hemostasis (D-dimer and activated partial thromboplastin time). The patient took melatonin during and after chemotherapy, nutrients (zinc, selenium, vitamin D, green tea, and taxifolin), and aspirin after chemotherapy. The patient's PSA levels decreased during CT combined with melatonin (19 mg/day), and melatonin normalized inflammatory markers and alleviated symptoms of polyneuropathy but did not help with thrombocytopenia. The results are analyzed and discussed in the context of the literature on oncostatic and systemic effects, alleviating therapy-mediated adverse effects, association with survival, and N-of-1 studies.

Computational drug repurposing for primary hyperparathyroidism

In hyperparathyroidism (hyperPTH), excessive amounts of PTH are secreted, interfering with calcium regulation in the body. Several drugs can control the disease's side effects, but none of them is an alternative treatment to surgery. Therefore, new drug candidates are necessary. In this study, three computationally repositioned drugs, DG 041, IMD 0354, and cucurbitacin I, are evaluated in an in vitro model of hyperPTH. First, we integrated publicly available transcriptomics datasets to propose drug candidates. Using 3D spheroids derived from a single primary hyperPTH patient, we assessed their in vitro efficacy. None of the proposed drugs affected the viability of healthy cell control (HEK293) or overactive parathyroid cells at the level of toxicity. This behavior was attributed to the non-cancerous nature of the parathyroid cells, establishing the hyperPTH disease model. Cucurbitacin I and IMD 0354 exhibited a slight inverse relationship between increased drug concentrations and cell viability, whereas DG 041 increased viability. Based on these results, further studies are needed on the mechanism of action of the repurposed drugs, including determining the effects of these drugs on cellular PTH synthesis and secretion and on the metabolic pathways that regulate PTH secretion.

An anti-depressant drug vortioxetine suppresses malignant glioblastoma cell growth

Glioblastoma (GBM) stands as the predominant primary malignant brain tumor in adults, characterized by an exceedingly grim prognosis. Urgent efforts are essential to pioneer effective therapeutics capable of addressing both the intrinsic and acquired resistance exhibited by GBM towards existing treatments. This study employs a drug repurposing strategy to explore the anti-cancer potential of vortioxetine in malignant U251 and T98G glioblastoma cells. Findings from the WST-8 cell counting assay and clonogenic assays indicated that vortioxetine effectively suppressed the short-term viability and long-term survival of glioblastoma cells. We also showed that vortioxetine inhibited the migration of glioblastoma cells as compared to the control. Our findings encourage further exploration and validation of the use of vortioxetine in the treatment of glioblastoma.

Unlocking hidden potential: advancements, approaches, and obstacles in repurposing drugs for cancer therapy

High rates of failure, exorbitant costs, and the sluggish pace of new drug discovery and development have led to a growing interest in repurposing "old" drugs to treat both common and rare diseases, particularly cancer. Cancer, a complex and heterogeneous disease, often necessitates a combination of different treatment modalities to achieve optimal outcomes. The intrinsic polygenicity of cancer, intricate biological signalling networks, and feedback loops make the inhibition of a single target frequently insufficient for achieving the desired therapeutic impact. As a result, addressing these complex or "smart" malignancies demands equally sophisticated treatment strategies. Combinatory treatments that target the multifaceted oncogenic signalling network hold immense promise. Repurposed drugs offer a potential solution to this challenge, harnessing known compounds for new indications. By avoiding the prohibitive costs and long development timelines associated with novel cancer drugs, this approach holds the potential to usher in more effective, efficient, and cost-effective cancer treatments. The pursuit of combinatory therapies through drug repurposing may hold the key to achieving superior outcomes for cancer patients. However, drug repurposing faces significant commercial, technological and regulatory challenges that need to be addressed. This review explores the diverse approaches employed in drug repurposing, delves into the challenges faced by the drug repurposing community, and presents innovative solutions to overcome these obstacles. By emphasising the significance of combinatory treatments within the context of drug repurposing, we aim to unlock the full potential of this approach for enhancing cancer therapy. The positive aspects of drug repurposing in oncology are underscored here; encompassing personalized treatment, accelerated development, market opportunities for shelved drugs, cancer prevention, expanded patient reach, improved patient access, multi-partner collaborations, increased likelihood of approval, reduced costs, and enhanced combination therapy.

Mechanistic QSAR modeling derived virtual screening, drug repurposing, ADMET and in-vitro evaluation to identify anticancer lead as lysine-specific demethylase 5a inhibitor

A lysine-specific demethylase is an enzyme that selectively eliminates methyl groups from lysine residues. KDM5A, also known as JARID1A or RBP2, belongs to the KDM5 Jumonji histone demethylase subfamily. To identify novel molecules that interact with the LSD5A receptor, we created a quantitative structure-activity relationship (QSAR) model. A group of 435 compounds was used in a study of the quantitative relationship between structure and activity to guess the IC50 values for blocking LASD5A. We used a genetic algorithm-multilinear regression-based quantitative structure-activity connection model to forecast the bioactivity (PIC50) of 1615 food and drug administration pharmaceuticals from the zinc database with the goal of repurposing clinically used medications. We used molecular docking, molecular dynamic simulation modelling, and molecular mechanics generalised surface area analysis to investigate the molecule's binding mechanism. A genetic algorithm and multi-linear regression method were used to make six variable-based quantitative structure-activity relationship models that worked well (R2 = 0.8521, Q2LOO = 0.8438, and Q2LMO = 0.8414). ZINC000000538621 was found to be a new hit against LSD5A after a quantitative structure-activity relationship-based virtual screening of 1615 zinc food and drug administration compounds. The docking analysis revealed that the hit molecule 11 in the KDM5A binding pocket adopted a conformation similar to the pdb-6bh1 ligand (docking score: -8.61 kcal/mol). The results from molecular docking and the quantitative structure-activity relationship were complementary and consistent. The most active lead molecule 11, which has shown encouraging results, has good absorption, distribution, metabolism, and excretion (ADME) properties, and its toxicity has been shown to be minimal. In addition, the MTT assay of ZINC000000538621 with MCF-7 cell lines backs up the in silico studies. We used molecular mechanics generalise borne surface area analysis and a 200-ns molecular dynamics simulation to find structural motifs for KDM5A enzyme interactions. Thus, our strategy will likely expand food and drug administration molecule repurposing research to find better anticancer drugs and therapies.Communicated by Ramaswamy H. Sarma.

Recent Advancements in Refashioning of NSAIDs and their Derivatives as Anticancer Candidates

Inflammation is critical to the formation and development of tumors and is closely associated with cancer. Therefore, addressing inflammation and the mediators that contribute to the inflammatory process may be a useful strategy for both cancer prevention and treatment. Tumor predisposition can be attributed to inflammation. It has been demonstrated that NSAIDs can modify the tumor microenvironment by enhancing apoptosis and chemosensitivity and reducing cell migration. There has been a recent rise in interest in drug repositioning or repurposing because the development of innovative medications is expensive, timeconsuming, and presents a considerable obstacle to drug discovery. Repurposing drugs is crucial for the quicker and less expensive development of anticancer medicines, according to an increasing amount of research. This review summarizes the antiproliferative activity of derivatives of NSAIDs such as Diclofenac, Etodolac, Celecoxib, Ibuprofen, Tolmetin, and Sulindac, published between 2017 and 2023. Their mechanism of action and structural activity relationships (SARs) were also discussed to set the path for potential future repositioning of NSAIDs for clinical deployment in the treatment of cancer.

Canagliflozin reduces thyroid cancer cells migration in vitro by inhibiting CXCL8 and CCL2: An additional anti-tumor effect of the drug

PURPOSE

Canagliflozin exert anti-cancer effects in several types of cancer including thyroid cancer (TC). However, whether it could modulate chemokines secreted in TC microenvironment is still unknown. The aim of the present study is to evaluate whether Canagliflozin could inhibit pro-tumorigenic chemokines CXCL8 and CCL2 and/or the TC cell migration induced by them.

EXPERIMENTAL DESIGN

TC cell lines, TPC-1 and 8505C, HUVEC and normal thyroid cells NHT were treated with increasing concentrations of Canagliflozin. Viability was assessed by WST-1 and colony formation/proliferation by cristal violet. Chemokines were measured in cell supernatants by ELISA. mRNAs were evaluated by RT-PCR. TC migration (trans-well) and HUVEC proliferation (cristal violet) were assessed by treating cells with Canagliflozin alone or in combination with CXCL8 or CCL2.

RESULTS

Canagliflozin reduced TC, HUVEC and NHT cells viability. The ability to form colonies of TC and the HUVEC proliferation (basal and CXCL8 or CCL2-induced) was also inhibited. mRNA and the secretion of CXCL8 was reduced in all cell types. The secretion of CCL2 was reduced by Canagliflozin in all cell types whereas its mRNA levels were reduced only in TPC-1. IL-6 was reduced in all cell types, while CXCL10 increased. More interestingly the CXCL8 and CCL2-induced TC cell migration as well as HUVEC proliferation was inhibited by Canagliflozin in both cell types.

CONCLUSION

Canagliflozin exerts anti-cancer effects not only by reducing TC viability or colonies formation, but also by modulating two pro-tumorigenic chemokines resulting in reduced TC cells migration. These results expand the spectrum of canagliflozin-promoted anti-cancer effects.

Current implications and challenges of artificial intelligence technologies in therapeutic intervention of colorectal cancer

Irrespective of men and women, colorectal cancer (CRC), is the third most common cancer in the population with more than 1.85 million cases annually. Fewer than 20% of patients only survive beyond five years from diagnosis. CRC is a highly preventable disease if diagnosed at the early stage of malignancy. Several screening methods like endoscopy (like colonoscopy; gold standard), imaging examination [computed tomographic colonography (CTC)], guaiac-based fecal occult blood (gFOBT), immunochemical test from faeces, and stool DNA test are available with different levels of sensitivity and specificity. The available screening methods are associated with certain drawbacks like invasiveness, cost, or sensitivity. In recent years, computer-aided systems-based screening, diagnosis, and treatment have been very promising in the early-stage detection and diagnosis of CRC cases. Artificial intelligence (AI) is an enormously in-demand, cost-effective technology, that uses various tools machine learning (ML), and deep learning (DL) to screen, diagnose, and stage, and has great potential to treat CRC. Moreover, different ML algorithms and neural networks [artificial neural network (ANN), k-nearest neighbors (KNN), and support vector machines (SVMs)] have been deployed to predict precise and personalized treatment options. This review examines and summarizes different ML and DL models used for therapeutic intervention in CRC cancer along with the gap and challenges for AI.

Drug repositioning in thyroid cancer treatment: the intriguing case of anti-diabetic drugs

Cancer represents the main cause of death worldwide. Thyroid cancer (TC) shows an overall good rate of survival, however there is a percentage of patients that do not respond or are refractory to common therapies. Thus new therapeutics strategies are required. In the past decade, drug repositioning become very important in the field of cancer therapy. This approach shows several advantages including the saving of: i) time, ii) costs, iii) de novo studies regarding the safety (just characterized) of a drug. Regarding TC, few studies considered the potential repositioning of drugs. On the other hand, certain anti-diabetic drugs, were the focus of interesting studies on TC therapy, in view of the fact that they exhibited potential anti-tumor effects. Among these anti-diabetic compounds, not all were judjed as appropriate for repositioning, in view of well documented side effects. However, just to give few examples biguanides, DPP-4-inhibitors and Thiazolidinediones were found to exert strong anti-cancer effects in TC. Indeed, their effects spaced from induction of citotoxicity and inhibition of metastatic spread, to induction of de-differentiation of TC cells and modulation of TC microenvironment. Thus, the multifacial anti-cancer effect of these compounds would make the basis also for combinatory strategies. The present review is aimed at discuss data from studies regarding the anti-cancer effects of several anti-diabetic drugs recently showed in TC in view of their potential repositioning. Specific examples of anti-diabetic repositionable drugs for TC treatment will also be provided.

The evidence for repurposing anti-epileptic drugs to target cancer

Antiepileptic drugs are versatile drugs with the potential to be used in functional drug formulations with drug repurposing approaches. In the present review, we investigated the anticancer properties of antiepileptic drugs and interlinked cancer and epileptic pathways. Our focus was primarily on those drugs that have entered clinical trials with positive results and those that provided good results in preclinical studies. Many contributing factors make cancer therapy fail, like drug resistance, tumor heterogeneity, and cost; exploring all alternatives for efficient treatment is important. It is crucial to find new drug targets to find out new antitumor molecules from the already clinically validated and approved drugs utilizing drug repurposing methods. The advancements in genomics, proteomics, and other computational approaches speed up drug repurposing. This review summarizes the potential of antiepileptic drugs in different cancers and tumor progression in the brain. Valproic acid, oxcarbazepine, lacosamide, lamotrigine, and levetiracetam are the drugs that showed potential beneficial outcomes against different cancers. Antiepileptic drugs might be a good option for adjuvant cancer therapy, but there is a need to investigate further their efficacy in cancer therapy clinical trials.

Unlocking therapeutic potential: integration of drug repurposing and immunotherapy for various disease targeting

Drug repurposing, also known as drug repositioning, entails the application of pre-approved or formerly assessed drugs having potentially functional therapeutic amalgams for curing various disorders or disease conditions distinctive from their original remedial indication. It has surfaced as a substitute for the development of drugs for treating cancer, cardiovascular diseases, neurodegenerative disorders, and various infectious diseases like Covid-19. Although the earlier lines of findings in this area were serendipitous, recent advancements are based on patient centered approaches following systematic, translational, drug targeting practices that explore pathophysiological ailment mechanisms. The presence of definite information and numerous records with respect to beneficial properties, harmfulness, and pharmacologic characteristics of repurposed drugs increase the chances of approval in the clinical trial stages. The last few years have showcased the successful emergence of repurposed drug immunotherapy in treating various diseases. In this light, the present review emphasises on incorporation of drug repositioning with Immunotherapy targeted for several disorders.

Molecular Mechanisms of the Antitumor Effects of Mesalazine and Its Preventive Potential in Colorectal Cancer

Chemoprevention is one of the ways to fight colorectal cancer, which is a huge challenge in oncology. Numerous pieces of evidence indicate that chronic inflammation in the course of Crohn's disease or ulcerative colitis (UC) is a significant cancer risk factor. Epidemiologic studies suggest that long-term use of non-steroidal anti-inflammatory drugs (NSAIDs), including mesalazine, has beneficial effects on colitis-associated colorectal cancer. Mesalazine is a first-line therapy for UC and is also widely used for maintaining remission in UC. Data showed that mesalazine has antiproliferative properties associated with cyclooxygenase (COX) inhibition but can also act through COX-independent pathways. This review summarizes knowledge about mesalazine's molecular mechanisms of action and chemopreventive effect by which it could interfere with colorectal cancer cell proliferation and survival.

Repurposing of neprilysin inhibitor 'sacubitrilat' as an anti-cancer drug by modulating epigenetic and apoptotic regulators

Modifications in the epigenetic landscape have been considered a hallmark of cancer. Histone deacetylation is one of the crucial epigenetic modulations associated with the aggressive progression of various cancer subtypes. Herein, we have repurposed the neprilysin inhibitor sacubitrilat as a potent anticancer agent using in-silico protein-ligand interaction profiler (PLIP) analysis, molecular docking, and in vitro studies. The screening of PLIP profiles between vorinostat/panobinostat and HDACs/LTA4H followed by molecular docking resulted in five (Sacubitrilat, B65, BDS, BIR, and NPV) FDA-approved, experimental and investigational drugs. Sacubitrilat has demonstrated promising anticancer activity against colorectal cancer (SW-480) and triple-negative breast cancer (MDA-MB-231) cells, with IC₅₀ values of 14.07 μg/mL and 23.02 μg/mL, respectively. FACS analysis revealed that sacubitrilat arrests the cell cycle at the G0/G1 phase and induces apoptotic-mediated cell death in SW-480 cells. In addition, sacubitrilat inhibited HDAC isoforms at the transcriptomic level by 0.7-0.9 fold and at the proteomic level by 0.5-0.6 fold as compared to the control. Sacubitrilat increased the protein expression of tumor-suppressor (p53) and pro-apoptotic makers (Bax and Bid) by 0.2-2.5 fold while decreasing the expression of anti-apoptotic Bcl2 and Nrf2 proteins by 0.2-0.5 fold with respect to control. The observed cleaved PARP product indicates that sacubitrilat induces apoptotic-mediated cell death. This study may pave the way to identify the anticancer potential of sacubitrilat and can be explored in human clinical trials.

A systematic review of computational approaches to understand cancer biology for informed drug repurposing

Cancer is the second leading cause of death globally, trailing only heart disease. In the United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, the success rate for new cancer drug development remains less than 10%, making the disease particularly challenging. This low success rate is largely attributed to the complex and poorly understood nature of cancer etiology. Therefore, it is critical to find alternative approaches to understanding cancer biology and developing effective treatments. One such approach is drug repurposing, which offers a shorter drug development timeline and lower costs while increasing the likelihood of success. In this review, we provide a comprehensive analysis of computational approaches for understanding cancer biology, including systems biology, multi-omics, and pathway analysis. Additionally, we examine the use of these methods for drug repurposing in cancer, including the databases and tools that are used for cancer research. Finally, we present case studies of drug repurposing, discussing their limitations and offering recommendations for future research in this area.

Inclusion of Nitrofurantoin into the Realm of Cancer Chemotherapy via Biology-Oriented Synthesis and Drug Repurposing

Structural modifications of the antibacterial drug nitrofurantoin were envisioned, employing drug repurposing and biology-oriented drug synthesis, to serve as possible anticancer agents. Eleven compounds showed superior safety in non-cancerous human cells. Their antitumor efficacy was assessed on colorectal, breast, cervical, and liver cancer cells. Three compounds induced oxidative DNA damage in cancer cells with subsequent cellular apoptosis. They also upregulated the expression of Bax while downregulated that of Bcl-2 along with activating caspase 3/7. The DNA damage induced by these compounds, demonstrated by pATM nuclear shuttling, was comparable in both MCF7 and MDA-MB-231 (p53 mutant) cell lines. Mechanistic studies confirmed the dependence of these compounds on p53-mediated pathways as they suppressed the p53-MDM2 interaction. Indeed, exposure of radiosensitive prostatic cancer cells to low non-cytotoxic concentrations of compound 1 enhanced the cytotoxic response to radiation indicating a possible synergistic effect. In vivo antitumor activity was verified in an MCF7-xenograft animal model.

Potential target identification for osteosarcoma treatment: Gene expression re-analysis and drug repurposing

Survival rate of osteosarcoma has remained plateaued for the past three decades. New treatment is needed to improve survival rate. Drug repurposing, a method to identify new indications of previous drugs, which saves time and cost compared to the de novo drug discovery. Data mining from gene expression profile was carried out and new potential targets were identified by using drug repurposing strategy. Selected data were newly categorized as pathophysiology and metastasis groups. Data were normalized and calculated the differential gene expression. Genes with log fold change ≥ 2 and adjusted p-value ≤ 0.05 were selected as primary candidate genes (PCGs). PCGs were further enriched to determine the secondary candidate genes (SCGs) by protein interaction analysis, upstream transcription factor and related-protein kinase identification. PCGs and SCGs were further matched with gene targeted of corresponding drugs from the Drug Repurposing Hub. A total of 778 targets were identified (360 from PCGs, and 418 from SCGs). This newly identified KLHL13 is a new candidate target based on its molecular function. KLHL13 was upregulated in clinical samples. We found 256 drugs from matching processes (50anti-cancerand206non-anticancerdrugs). Clinical trials of anti-cancer drugs from 5 targets (CDK4, BCL-2, JUN, SRC, PIK3CA) are being performed for osteosarcoma treatment. Niclosamide and synthetic PPARɣ ligands are candidates for repurposing due to the possibility based on their mechanism and pharmacology properties. Re-analysis of gene expression profile could identify new potential targets, confirm a current implication, and expand the chance of repurposing drugs for osteosarcoma treatment.

New frontier radioiodinated probe based on in silico resveratrol repositioning for microtubules dynamic targeting

PURPOSE

As the 'de novo' drug discovery faces a highly attrition rates, drug repositioning procures a heighten concern in identifying novel uses for existing medications. This study aimed to fabricate radioiodinated resveratrol as a potent microtubules interfering agent for cancer theragnosis.

METHODS

Resveratrol was radiolabeled with radioactive iodine where the radioiodination efficiency was enlightened and the computational approaches were employed to investigate the affinity and specificity with tubulins. Furthermore, the in-vivo distribution and pharmacokinetic studies in normal and tumor induced mice were investigated.

RESULTS

The maximum radioiodination yield (94.6 ± 1.66) was achieved at optimum preparation parameters stated as 100 μg/mL of oxidizing agent, 100 μg/ml of resveratrol, reaction time of 30 min and reaction pH 5. The in silico studies showed that di-iodinated resveratrol (compound 6) exhibited the best binding score (-34.46) and interaction with the β-tubulin binding site. The in vivo distribution in tumor models revealed a significant accumulation (4.02% ID/g) in tumor lesion at 60 min p.i. The rate of drug elimination demonstrated a mono-exponential decline of radioactivity versus time in the blood.

CONCLUSION

Radioiodinated resveratrol revealed good microtubules targeting which render it as a novel theranostic probe for cancer management.

Drug Repurposing in Non-Small Cell Lung Carcinoma: Old Solutions for New Problems

Lung cancer is the second most common cancer and the leading cause of cancer-related deaths in 2022. The majority (80%) of lung cancer cases belong to the non-small cell lung carcinoma (NSCLC) subtype. Despite the increased screening efforts, the median five-year survival of metastatic NSCLC remains low at approximately 3%. Common treatment approaches for NSCLC include surgery, multimodal chemotherapy, and concurrent radio and chemotherapy. NSCLC exhibits high rates of resistance to treatment, driven by its heterogeneity and the plasticity of cancer stem cells (CSCs). Drug repurposing offers a faster and cheaper way to develop new antineoplastic purposes for existing drugs, to help overcome therapy resistance. The decrease in time and funds needed stems from the availability of the pharmacokinetic and pharmacodynamic profiles of the Food and Drug Administration (FDA)-approved drugs to be repurposed. This review provides a synopsis of the drug-repurposing approaches and mechanisms of action of potential candidate drugs used in treating NSCLC, including but not limited to antihypertensives, anti-hyperlipidemics, anti-inflammatory drugs, anti-diabetics, and anti-microbials.

In silico drug screen reveals potential competitive MTHFR inhibitors for clinical repurposing

MTHFR (Methylenetetrahydrofolate reductase) is a pivotal enzyme involved in one-carbon metabolism, which is critical for the proliferation of cancer cells. In line with this, published literature showed that MTHFR knockdown caused impaired growth of multiple types of cancer cells. Moreover, higher MTHFR expression levels were linked to shorter overall survival in hepatocellular carcinoma, adrenocortical carcinoma, and low-grade glioma, bringing the need to design MTHFR inhibitors as a possible treatment option. No competitive inhibitors of MTHFR have been reported as of today. This study aimed to identify potential competitive MTHFR inhibitor candidates using an in silico drug screen. A total of 30470 molecules containing biogenic compounds, FDA-approved drugs, and those in clinical trials were screened against the catalytic pocket of MTHFR in the presence and absence of cofactors. Binding energy and ADMET analysis revealed that Vilanterol (β2-adrenergic agonist), Selexipag (prostacyclin receptor agonist), and Ramipril Diketopiperazine (ACE inhibitor) are potential competitive inhibitors of MTHFR. Molecular dynamics analyses and MM-PBSA calculations with these compounds particularly revealed the amino acids between 285-290 for ligand binding and highlighted Vilanterol as the strongest candidate for MTHFR inhibition. Our results could guide the development of novel MTHFR inhibitor compounds, which could be inspired by the drugs brought into the spotlight here. More importantly, these potential candidates could be quhickly tested as a repurposing strategy in pre-clinical and clinical studies of the cancers mentioned above.Communicated by Ramaswamy H. Sarma.

Screening of GPCR drugs for repurposing in breast cancer

Drug repurposing can overcome both substantial costs and the lengthy process of new drug discovery and development in cancer treatment. Some Food and Drug Administration (FDA)-approved drugs have been found to have the potential to be repurposed as anti-cancer drugs. However, the progress is slow due to only a handful of strategies employed to identify drugs with repurposing potential. In this study, we evaluated GPCR-targeting drugs by high throughput screening (HTS) for their repurposing potential in triple-negative breast cancer (TNBC) and drug-resistant human epidermal growth factor receptor-2-positive (HER2+) breast cancer (BC), due to the dire need to discover novel targets and drugs in these subtypes. We assessed the efficacy and potency of drugs/compounds targeting different GPCRs for the growth rate inhibition in the following models: two TNBC cell lines (MDA-MB-231 and MDA-MB-468) and two HER2+ BC cell lines (BT474 and SKBR3), sensitive or resistant to lapatinib + trastuzumab, an effective combination of HER2-targeting therapies. We identified six drugs/compounds as potential hits, of which 4 were FDA-approved drugs. We focused on β-adrenergic receptor-targeting nebivolol as a candidate, primarily because of the potential role of these receptors in BC and its excellent long-term safety profile. The effects of nebivolol were validated in an independent assay in all the cell line models. The effects of nebivolol were independent of its activation of β3 receptors and nitric oxide production. Nebivolol reduced invasion and migration potentials which also suggests its inhibitory role in metastasis. Analysis of the Surveillance, Epidemiology and End Results (SEER)-Medicare dataset found numerically but not statistically significant reduced risk of all-cause mortality in the nebivolol group. In-depth future analyses, including detailed in vivo studies and real-world data analysis with more patients, are needed to further investigate the potential of nebivolol as a repurposed therapy for BC.

Photothermal therapy (PTT) is an effective treatment measure against solid tumors which fails to respond conventional chemo/radiation therapies in clinic

Photothermal therapy (PTT) has emerged as a fast, precisive, and cost-effective anticancer therapy protocol. Here we applied our previously designed nanomaterial (Tocophotoxil) for prospective PTT application to manage radiation- and chemo-resistant cancers in a preclinical model. A PTT dose vs. efficacy relationship was established for radioresistant breast (ZR-75-1 50Gy, 4T1 20Gy) and chemo-resistant ovarian (A2780LR) cancer cells and tumors in mice models. Compared to the sensitive cases, resistant cells treated with PTT for a shorter duration show higher endurance. However, preclinical tumor xenografts treated with optimal PTT dose show 2-3 fold higher longevity (P ≤ 0.05) of treated mice monitored by non-invasive imaging methods. Elevated ERK and AKT activation in radioresistant or only AKT activation in chemo-resistant cells were contributory to higher cell survival in sub-optimal PTT dose. A comprehensive single-cell Raman map of PTT treated ZR-75-1 cell reveals broad-spectrum macromolecular deformities, including protein damage features. Marked induction of pJNK, unfolded protein response (UPR) pathway, increased reactive oxygen species (ROS), and lipid peroxidation in PTT-treated cells disrupted the intracellular homeostasis. Analyzing cellular ultrastructure, the coexistence of swollen endoplasmic reticulum, and autophagic bodies after PTT indicate possible coordination between UPR and autophagy pathways. Therefore, this comprehensive study provides new evidence on the potential impact of PTT as a standalone therapy for ablation of failed conventional therapy-resistant cancers in vivo, the success of which is intricately linked to the PTT dose optimization. The study, for the first time, also illustrates that under PTT treatment, concerted action of novel molecular switches such as JNK activation and UPR activation plays a vital role in triggering autophagy and cancer cell death.

A comprehensive review on recent approaches for cancer drug discovery associated with artificial intelligence

Through the revolutionization of artificial intelligence (AI) technologies in clinical research, significant improvement is observed in diagnosis of cancer. Utilization of these AI technologies, such as machine and deep learning, is imperative for the discovery of novel anticancer drugs and improves existing/ongoing cancer therapeutics. However, building a model for complicated cancers and their types remains a challenge due to lack of effective therapeutics that hinder the establishment of effective computational tools. In this review, we exploit recent approaches and state-of-the-art in implementing AI methods for anticancer drug discovery, and discussed how advances in these applications need to be considered in the current cancer therapeutics. Considering the immense potential of AI, we explore molecular docking and their interactions to recognize metabolic activities that support drug design. Finally, we highlight corresponding strategies in applying machine and deep learning methods to various types of cancer with their pros and cons.

Combination Therapy of Curcumin and Disulfiram Synergistically Inhibits the Growth of B16-F10 Melanoma Cells by Inducing Oxidative Stress

Oxidative stress plays a central role in the pathophysiology of melanoma. Curcumin (CUR) is a polyphenolic phytochemical that stimulates reactive oxygen species (ROS) production, while disulfiram (DSS) is a US FDA-approved drug for the treatment of alcoholism that can act by inhibiting the intracellular antioxidant system. Therefore, we hypothesized that they act synergistically against melanoma cells. Herein, we aimed to study the antitumor potential of the combination of CUR with DSS in B16-F10 melanoma cells using in vitro and in vivo models. The cytotoxic effects of different combination ratios of CUR and DSS were evaluated using the Alamar Blue method, allowing the production of isobolograms. Apoptosis detection, DNA fragmentation, cell cycle distribution, and mitochondrial superoxide levels were quantified by flow cytometry. Tumor development in vivo was evaluated using C57BL/6 mice bearing B16-F10 cells. The combinations ratios of 1:2, 1:3, and 2:3 showed synergic effects. B16-F10 cells treated with these combinations showed improved apoptotic cell death and DNA fragmentation. Enhanced mitochondrial superoxide levels were observed at combination ratios of 1:2 and 1:3, indicating increased oxidative stress. In vivo tumor growth inhibition for CUR (20 mg/kg), DSS (60 mg/kg), and their combination were 17.0%, 19.8%, and 28.8%, respectively. This study provided data on the potential cytotoxic activity of the combination of CUR with DSS and may provide a useful tool for the development of a therapeutic combination against melanoma.

Repurposed Effect of 177Lu-DOTATATE in the Treatment of Mantle Cell Lymphoma

Mantle cell lymphoma (MCL) is an uncommon subcategory of non-Hodgkin lymphoma (NHL). Pathogenesis primarily includes overexpression of CCND1 and SOX11 along with other molecular aberrations. Lutetium ¹⁷⁷Lu-DOTATATE is a radiolabeled somatostatin analogue used for the treatment of gastrointestinal neuroendocrine tumors. There are no clinical data supporting the use of Lutetium ¹⁷⁷Lu-DOTATATE in the treatment of lymphoma. We describe the case of an 84-year-old man with a history of MCL and carcinoid tumor of the lung. Following progression of the carcinoid malignancy, the patient was treated with Lutetium ¹⁷⁷Lu-DOTATATE. After treatment, there was an overall improvement of the patient's MCL that was demonstrated by stable lymphadenopathy on serial CT scans and down-trend of the absolute lymphocyte count. Therefore, we hypothesize that ¹⁷⁷Lu-DOTATATE might have a role and can be repurposed for treating MCL.

Drug repurposing-an emerging strategy in cancer therapeutics

Cancer is a complex disease affecting millions of people around the world. Despite advances in surgical and radiation therapy, chemotherapy continues to be an important therapeutic option for the treatment of cancer. The current treatment is expensive and has several side effects. Also, over time, cancer cells develop resistance to chemotherapy, due to which there is a demand for new drugs. Drug repurposing is a novel approach that focuses on finding new applications for the old clinically approved drugs. Current advances in the high-dimensional multiomics landscape, especially proteomics, genomics, and computational omics-data analysis, have facilitated drug repurposing. The drug repurposing approach provides cheaper, effective, and safe drugs with fewer side effects and fastens the process of drug development. The review further delineates each repurposed drug's original indication and mechanism of action in cancer. Along with this, the article also provides insight upon artificial intelligence and its application in drug repurposing. Clinical trials are vital for determining medication safety and effectiveness, and hence the clinical studies for each repurposed medicine in cancer, including their stages, status, and National Clinical Trial (NCT) identification, are reported in this review article. Various emerging evidences imply that repurposing drugs is critical for the faster and more affordable discovery of anti-cancerous drugs, and the advent of artificial intelligence-based computational tools can accelerate the translational cancer-targeting pipeline.

Drug Repurposing to Enhance Antitumor Response to PD-1/PD-L1 Immune Checkpoint Inhibitors

Monoclonal antibodies targeting the PD-1/PD-L1 immune checkpoint have considerably improved the treatment of some cancers, but novel drugs, new combinations, and treatment modalities are needed to reinvigorate immunosurveillance in immune-refractory tumors. An option to elicit antitumor immunity against cancer consists of using approved and marketed drugs known for their capacity to modulate the expression and functioning of the PD-1/PD-L1 checkpoint. Here, we have reviewed several types of drugs known to alter the checkpoint, either directly via the blockade of PD-L1 or indirectly via an action on upstream effectors (such as STAT3) to suppress PD-L1 transcription or to induce its proteasomal degradation. Specifically, the repositioning of the approved drugs liothyronine, azelnidipine (and related dihydropyridine calcium channel blockers), niclosamide, albendazole/flubendazole, and a few other modulators of the PD-1/PD-L1 checkpoint (repaglinide, pimozide, fenofibrate, lonazolac, propranolol) is presented. Their capacity to bind to PD-L1 or to repress its expression and function offer novel perspectives for combination with PD-1 targeted biotherapeutics. These known and affordable drugs could be useful to improve the therapy of cancer.

Repurposing of ingenol mebutate for treating human colorectal cancer by targeting S100 calcium-binding protein A4 (S100A4)

Colorectal cancer (CRC) is the world's second most common cause of cancer-related death. Novel treatments are still urgently needed. S100 calcium-binding protein A4 (S100A4) was demonstrated to be an anticancer therapeutic target. Herein, we found that higher S100A4 expression was associated with a poorer prognosis in publicly available cohorts and a Taiwanese CRC patient cohort. To identify repurposed S100A4 inhibitors, we mined the Connectivity Map (CMap) database for clinical drugs mimicking the S100A4-knockdown gene signature. Ingenol mebutate, derived from the sap of the plant Euphorbia peplus, is approved as a topical treatment for actinic keratosis. The CMap analysis predicted ingenol mebutate as a potent S100A4 inhibitor. Indeed, both messenger RNA and protein levels of S100A4 were attenuated by ingenol mebutate in human CRC cells. In addition, CRC cells with higher S100A4 expressions and/or the wild-type p53 gene were more sensitive to ingenol mebutate, and their migration and invasion were inhibited by ingenol mebutate. Therefore, our results suggest the repurposing of ingenol mebutate for treating CRC by targeting S100A4.

A knowledge graph to interpret clinical proteomics data

Implementing precision medicine hinges on the integration of omics data, such as proteomics, into the clinical decision-making process, but the quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across multiple biomedical databases and publications, pose a challenge to data integration. Here we present the Clinical Knowledge Graph (CKG), an open-source platform currently comprising close to 20 million nodes and 220 million relationships that represent relevant experimental data, public databases and literature. The graph structure provides a flexible data model that is easily extendable to new nodes and relationships as new databases become available. The CKG incorporates statistical and machine learning algorithms that accelerate the analysis and interpretation of typical proteomics workflows. Using a set of proof-of-concept biomarker studies, we show how the CKG might augment and enrich proteomics data and help inform clinical decision-making.

Overcoming Therapy Resistance in Colon Cancer by Drug Repurposing

Simple Summary

Despite improvements in standardized screening methods and the development of promising therapies for colorectal cancer (CRC), survival rates are still low. Drug repurposing offers an affordable solution to achieve new indications for previously approved drugs that could play a protagonist or adjuvant role in the treatment of CRC. In this review, we summarize the current data supporting drug repurposing as a feasible option for patients with CRC.

Abstract

Colorectal cancer (CRC) is the third most common cancer in the world. Despite improvement in standardized screening methods and the development of promising therapies, the 5-year survival rates are as low as 10% in the metastatic setting. The increasing life expectancy of the general population, higher rates of obesity, poor diet, and comorbidities contribute to the increasing trends in incidence. Drug repurposing offers an affordable solution to achieve new indications for previously approved drugs that could play a protagonist or adjuvant role in the treatment of CRC with the advantage of treating underlying comorbidities and decreasing chemotherapy toxicity. This review elaborates on the current data that supports drug repurposing as a feasible option for patients with CRC with a focus on the evidence and mechanism of action promising repurposed candidates that are widely used, including but not limited to anti-malarial, anti-helminthic, anti-inflammatory, anti-hypertensive, anti-hyperlipidemic, and anti-diabetic agents.

Drug repositioning: Progress and challenges in drug discovery for various diseases

Compared with traditional de novo drug discovery, drug repurposing has become an attractive drug discovery strategy due to its low-cost and high efficiency. Through a comprehensive analysis of the candidates that have been identified with drug repositioning potentials, it is found that although some drugs do not show obvious advantages in the original indications, they may exert more obvious effects in other diseases. In addition, some drugs have a synergistic effect to exert better clinical efficacy if used in combination. Particularly, it has been confirmed that drug repositioning has benefits and values on the current public health emergency such as the COVID-19 pandemic, which proved the great potential of drug repositioning. In this review, we systematically reviewed a series of representative drugs that have been repositioned for different diseases and illustrated successful cases in each disease. Especially, the mechanism of action for the representative drugs in new indications were explicitly explored for each disease, we hope this review can provide important insights for follow-up research.

Use of "Repurposed" Drugs in the Treatment of Epithelial Ovarian Cancer: A Systematic Review

Epithelial ovarian cancer has poor outcomes with standard therapy and limited options for treatment of recurrent disease. This systematic review summarizes the data on the clinical use of repurposed drugs. We searched for clinical studies using "repurposed" agents for the treatment of ovarian cancer in the following databases: PubMed, clinicaltrials.gov, Clinical Trial Registry of India, European Clinical Trials Registry, and Chinese Clinical Trial Registry. We excluded reviews, preclinical studies, and non-English language studies. We assessed the quality of included studies. The following agents/class of agents were included: statins, hydroxychloroquine, metformin, itraconazole, nonsteroidal anti-inflammatory drugs, vitamin D, proton pump inhibitors, beta-blockers, and sodium valproate. Only one randomized controlled trial investigated metformin, which found no benefit of metformin. However, this had a high risk of bias (no details of randomization). Among the observational studies, 70% were of high quality (Newcastle-Ottawa scale ≥7). Clinical benefit was seen for itraconazole, beta-blockers, metformin, statins, and proton pump inhibitors. Though multiple studies aim to repurpose agents in epithelial ovarian cancer, the most published literature is observational, and none are practice-changing. Given the solid preclinical data regarding the anticancer efficacy of these agents, well-designed clinical trials are urgently required.

Drug repurposing for cancer therapy in the era of precision medicine

Drug repurposing refers to the identification of clinically approved drugs, with the known safety profiles and defined pharmacokinetic properties, to new indications. Despite the advances in oncology research, cancers are still associated with the most unmet medical needs. Drug repurposing has emerged as a useful approach for the search for effective and durable cancer treatment. It may also represent a promising strategy to facilitate precision cancer treatment and to overcome drug resistance. The repurposing of non-cancer drugs for precision oncology effectively extends the inventory of actionable molecular targets and thus increases the number of patients who may benefit from precision cancer treatment. In cancer types where genetic heterogeneity is so high that it is not feasible to identify strong repurposed drug candidates for standard treatment, the precision oncology approach offers individual patients access to novel treatment options. For repurposed candidates with low potency, a combination of multiple repurposed drugs may produce a synergistic therapeutic effect. Precautions should be taken when combining repurposed drugs with anticancer agents to avoid detrimental drug-drug interactions and unwanted side effects. New multifactorial data analysis and artificial intelligence methods are needed to untangle the complex association of molecular signatures influencing specific cancer subtypes to facilitate drug repurposing in precision oncology.

Repurposing non-oncology small-molecule drugs to improve cancer therapy: Current situation and future directions

Drug repurposing or repositioning has been well-known to refer to the therapeutic applications of a drug for another indication other than it was originally approved for. Repurposing non-oncology small-molecule drugs has been increasingly becoming an attractive approach to improve cancer therapy, with potentially lower overall costs and shorter timelines. Several non-oncology drugs approved by FDA have been recently reported to treat different types of human cancers, with the aid of some new emerging technologies, such as omics sequencing and artificial intelligence to overcome the bottleneck of drug repurposing. Therefore, in this review, we focus on summarizing the therapeutic potential of non-oncology drugs, including cardiovascular drugs, microbiological drugs, small-molecule antibiotics, anti-viral drugs, anti-inflammatory drugs, anti-neurodegenerative drugs, antipsychotic drugs, antidepressants, and other drugs in human cancers. We also discuss their novel potential targets and relevant signaling pathways of these old non-oncology drugs in cancer therapies. Taken together, these inspiring findings will shed new light on repurposing more non-oncology small-molecule drugs with their intricate molecular mechanisms for future cancer drug discovery.

Screening of Clinically Approved and Investigation Drugs as Potential Inhibitors of SARS-CoV-2: A Combined in silico and in vitro Study

In the current study, we used 7922 FDA approved small molecule drugs as well as compounds in clinical investigation from NIH's NPC database in our drug repurposing study. SARS-CoV-2 main protease as well as Spike protein/ACE2 targets were used in virtual screening and top-100 compounds from each docking simulations were considered initially in short molecular dynamics (MD) simulations and their average binding energies were calculated by MM/GBSA method. Promising hit compounds selected based on average MM/GBSA scores were then used in long MD simulations. Based on these numerical calculations following compounds were found as hit inhibitors for the SARS-CoV-2 main protease: Pinokalant, terlakiren, ritonavir, cefotiam, telinavir, rotigaptide, and cefpiramide. In addition, following 3 compounds were identified as inhibitors for Spike/ACE2: Denopamine, bometolol, and rotigaptide. In order to verify the predictions of in silico analyses, 4 compounds (ritonavir, rotigaptide, cefotiam, and cefpiramide) for the main protease and 2 compounds (rotigaptide and denopamine) for the Spike/ACE2 interactions were tested by in vitro experiments. While the concentration-dependent inhibition of the ritonavir, rotigaptide, and cefotiam was observed for the main protease; denopamine was effective at the inhibition of Spike/ACE2 binding.

Two Possible Strategies for Drug Modification of Gemcitabine and Future Contributions to Personalized Medicine

Drug repurposing is an emerging strategy, which uses already approved drugs for new medical indications. One such drug is gemcitabine, an anticancer drug that only works at high doses since a portion is deactivated in the serum, which causes toxicity. In this review, two methods were discussed that could improve the anticancer effect of gemcitabine. The first is a chemical modification by conjugation with cell-penetrating peptides, namely penetratin, pVEC, and different kinds of CPP6, which mostly all showed an increased anticancer effect. The other method is combining gemcitabine with repurposed drugs, namely itraconazole, which also showed great cancer cell inhibition growth. Besides these two strategies, physiologically based pharmacokinetic models (PBPK models) are also the key for predicting drug distribution based on physiological data, which is very important for personalized medicine, so that the correct drug and dosage regimen can be administered according to each patient’s physiology. Taking all of this into consideration, it is believed that gemcitabine can be repurposed to have better anticancer effects.

Artificial intelligence in colorectal cancer management

Artificial intelligence (AI) is a new branch of computer science involving many disciplines and technologies. Since its application in the medical field, it has been constantly studied and developed. AI includes machine learning and neural networks to create new technologies or to improve existing ones. Various AI supporting systems are available for a personalized and novel strategy for the management of colorectal cancer (CRC). This mini-review aims to summarize the progress of research and possible clinical applications of AI in the investigation, early diagnosis, treatment, and management of CRC, to offer elements of knowledge as a starting point for new studies and future applications.

Drug Repurposing for Glioblastoma and Current Advances in Drug Delivery-A Comprehensive Review of the Literature

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults with an extremely poor prognosis. There is a dire need to develop effective therapeutics to overcome the intrinsic and acquired resistance of GBM to current therapies. The process of developing novel anti-neoplastic drugs from bench to bedside can incur significant time and cost implications. Drug repurposing may help overcome that obstacle. A wide range of drugs that are already approved for clinical use for the treatment of other diseases have been found to target GBM-associated signaling pathways and are being repurposed for the treatment of GBM. While many of these drugs are undergoing pre-clinical testing, others are in the clinical trial phase. Since GBM stem cells (GSCs) have been found to be a main source of tumor recurrence after surgery, recent studies have also investigated whether repurposed drugs that target these pathways can be used to counteract tumor recurrence. While several repurposed drugs have shown significant efficacy against GBM cell lines, the blood–brain barrier (BBB) can limit the ability of many of these drugs to reach intratumoral therapeutic concentrations. Localized intracranial delivery may help to achieve therapeutic drug concentration at the site of tumor resection while simultaneously minimizing toxicity and side effects. These strategies can be considered while repurposing drugs for GBM.

Application of Reverse Docking in the Research of Small Molecule Drugs and Traditional Chinese Medicine

With the development of structural biology and data mining, computer-aided drug design (CADD) has been playing an important role in all aspects of new drug development. Reverse docking, a method of virtual screening based on molecular docking in CADD, is widely used in drug repositioning, drug rescue, and traditional Chinese medicine (TCM) research, for it can search for macromolecular targets that can bind to a given ligand molecule. This review revealed the principle of reverse docking, summarized common target protein databases and docking procedures, and enumerated the applications of reverse docking in drug repositioning, adverse drug reactions, traditional Chinese medicine, and COVID-19 treatment. Hope our work can give some inspiration to researchers engaged in drug development.

Towards Drug Repurposing in Cancer Cachexia: Potential Targets and Candidates

As a multifactorial and multiorgan syndrome, cancer cachexia is associated with decreased tolerance to antitumor treatments and increased morbidity and mortality rates. The current approaches for the treatment of this syndrome are not always effective and well established. Drug repurposing or repositioning consists of the investigation of pharmacological components that are already available or in clinical trials for certain diseases and explores if they can be used for new indications. Its advantages comparing to de novo drugs development are the reduced amount of time spent and costs. In this paper, we selected drugs already available or in clinical trials for non-cachexia indications and that are related to the pathways and molecular components involved in the different phenotypes of cancer cachexia syndrome. Thus, we introduce known drugs as possible candidates for drug repurposing in the treatment of cancer-induced cachexia.

Pharmacological strategies for improving the prognosis of glioblastoma

Introduction: Treatments for brain cancer have radically evolved in the past decade due to a better understanding of the interplay between the immune system and tumors of the central nervous system (CNS). However, glioblastoma multiforme (GBM) remains the most common and lethal CNS malignancy affecting adults.Areas covered: The authors review the literature on glioblastoma pharmacologic therapies with a focus on trials of combination chemo-/immunotherapies and drug delivery platforms from 2015 to 2021.Expert opinion: Few therapeutic advances in GBM treatment have been made since the Food and Drug Administration (FDA) approval of the BCNU-eluting wafer, Gliadel, in 1996 and oral temozolomide (TMZ) in 2005. Recent advances in our understanding of GBM have promoted a wide assortment of new therapeutic approaches including combination therapy, immunotherapy, vaccines, and Car T-cell therapy along with developments in drug delivery. Given promising preclinical data, these novel pharmacotherapies for the treatment of GBM are currently being evaluated in various stages of clinical trials.

Combining repurposed drugs to treat colorectal cancer

The drug development process, especially of antineoplastic agents, has become increasingly costly and ineffective. Drug repurposing and drug combination are alternatives to de novo drug development, being low cost, rapid, and easy to apply. These strategies allow higher efficacy, decreased toxicity, and overcoming of drug resistance. The combination of antineoplastic agents is already being applied in cancer therapy, but the combination of repurposed drugs is still under-explored in pre- and clinical development. In this review, we provide a set of pharmacological concepts focusing on drug repurposing for treating colorectal cancer (CRC) and that are relevant for the application of new drug combinations against this disease.

Differential Interactome Based Drug Repositioning Unraveled Abacavir, Exemestane, Nortriptyline Hydrochloride, and Tolcapone as Potential Therapeutics for Colorectal Cancers

There is a critical requirement for alternative strategies to provide the better treatment in colorectal cancer (CRC). Hence, our goal was to propose novel biomarkers as well as drug candidates for its treatment through differential interactome based drug repositioning. Differentially interacting proteins and their modules were identified, and their prognostic power were estimated through survival analyses. Drug repositioning was carried out for significant target proteins, and candidate drugs were analyzed via in silico molecular docking prior to in vitro cell viability assays in CRC cell lines. Six modules (mAPEX1, mCCT7, mHSD17B10, mMYC, mPSMB5, mRAN) were highlighted considering their prognostic performance. Drug repositioning resulted in eight drugs (abacavir, ribociclib, exemestane, voriconazole, nortriptyline hydrochloride, theophylline, bromocriptine mesylate, and tolcapone). Moreover, significant in vitro inhibition profiles were obtained in abacavir, nortriptyline hydrochloride, exemestane, tolcapone, and theophylline (positive control). Our findings may provide new and complementary strategies for the treatment of CRC.

Recent Updates on Mechanisms of Resistance to 5-Fluorouracil and Reversal Strategies in Colon Cancer Treatment

5-Fluorouracil (5-FU) plus leucovorin (LV) remain as the mainstay standard adjuvant chemotherapy treatment for early stage colon cancer, and the preferred first-line option for metastatic colon cancer patients in combination with oxaliplatin in FOLFOX, or irinotecan in FOLFIRI regimens. Despite treatment success to a certain extent, the incidence of chemotherapy failure attributed to chemotherapy resistance is still reported in many patients. This resistance, which can be defined by tumor tolerance against chemotherapy, either intrinsic or acquired, is primarily driven by the dysregulation of various components in distinct pathways. In recent years, it has been established that the incidence of 5-FU resistance, akin to multidrug resistance, can be attributed to the alterations in drug transport, evasion of apoptosis, changes in the cell cycle and DNA-damage repair machinery, regulation of autophagy, epithelial-to-mesenchymal transition, cancer stem cell involvement, tumor microenvironment interactions, miRNA dysregulations, epigenetic alterations, as well as redox imbalances. Certain resistance mechanisms that are 5-FU-specific have also been ascertained to include the upregulation of thymidylate synthase, dihydropyrimidine dehydrogenase, methylenetetrahydrofolate reductase, and the downregulation of thymidine phosphorylase. Indeed, the successful modulation of these mechanisms have been the game plan of numerous studies that had employed small molecule inhibitors, plant-based small molecules, and non-coding RNA regulators to effectively reverse 5-FU resistance in colon cancer cells. It is hoped that these studies would provide fundamental knowledge to further our understanding prior developing novel drugs in the near future that would synergistically work with 5-FU to potentiate its antitumor effects and improve the patient's overall survival.

Dickkopf Proteins and Their Role in Cancer: A Family of Wnt Antagonists with a Dual Role

The Wnt signaling pathway regulates crucial aspects such as cell fate determination, cell polarity and organogenesis during embryonic development. Wnt pathway deregulation is a hallmark of several cancers such as lung, gastric and liver cancer, and has been reported to be altered in others. Despite the general agreement reached by the scientific community on the oncogenic potential of the central components of the pathway, the role of the antagonist proteins remains less clear. Deregulation of the pathway may be caused by overexpression or downregulation of a wide range of antagonist proteins. Although there is growing information related to function and regulation of Dickkopf (DKK) proteins, their pharmacological potential as cancer therapeutics still has not been fully developed. This review provides an update on the role of DKK proteins in cancer and possible potential as therapeutic targets for the treatment of cancer; available compounds in pre-clinical or clinical trials are also reviewed.

Drug Repurposing to Identify a Synergistic High-Order Drug Combination to Treat Sunitinib-Resistant Renal Cell Carcinoma

Simple Summary

In this study, drug combination screening was used to design a multidrug combination consisting of repurposed drugs to treat sunitinib-resistant clear cell renal cell carcinoma. In the frame of this project, the multidrug combination has been optimized and validated and an insight into the mechanism of action is given. The multidrug combinations significantly altered the transcription of genes related to apoptosis and metabolic pathways. Further analysis of the metabolism revealed strong upregulation of the presence of sphingolipids after multidrug combination treatment. Final evaluation for translation of the multidrug combination in ex vivo organoid-like cultures demonstrated significant anti-cancer efficacy.

Abstract

Repurposed drugs have been evaluated for the management of clear cell renal cell carcinoma (ccRCC), but only a few have influenced the overall survival of patients with advanced disease. To combine repurposed non-oncology with oncological drugs, we applied our validated phenotypic method, which consisted of a reduced experimental part and data modeling. A synergistic optimized multidrug combination (ODC) was identified to significantly reduce the energy levels in cancer remaining inactive in non-cancerous cells. The ODC consisted of Rapta-C, erlotinib, metformin and parthenolide and low doses. Molecular and functional analysis of ODC revealed a loss of adhesiveness and induction of apoptosis. Gene-expression network analysis displayed significant alterations in the cellular metabolism, confirmed by LC-MS based metabolomic analysis, highlighting significant changes in the lipid classes. We used heterotypic in vitro 3D co-cultures and ex vivo organoids to validate the activity of the ODC, maintaining an efficacy of over 70%. Our results show that repurposed drugs can be combined to target cancer cells selectively with prominent activity. The strong impact on cell adherence and metabolism indicates a favorable mechanism of action of the ODC to treat ccRCC.

Modern computational intelligence based drug repurposing for diabetes epidemic

BACKGROUND AND AIM

Objectives are to explore recent advances in discovery of new antidiabetic agents using repurposing strategies and to discuss modern technologies used for drug repurposing highlighting diabetic specific web portal.

METHODS

Recent literature were studied and analyzed from various sources such as Scopus, PubMed, and IEEE Xplore databases.

RESULTS

Drugs like Niclosamideethanolamine, Methazolamide, Diacerein, Berberine, Clobetasol, etc. with possibility of repurposing to curb diabetes can be potential late-stage clinical candidates, providing access to information on pharmacology, formulation, and probable toxicity if any.

CONCLUSIONS

With collaboration of artificial intelligence (AI) with pharmacology, the efficiency of drug repurposing can improve significantly.