Repurposing of the ALK Inhibitor Crizotinib for Acute Leukemia and Multiple Myeloma Cells

Applying Spatiotemporal Modeling of Cell Dynamics to Accelerate Drug Development

Cells act as physical computational programs that utilize input signals to orchestrate molecule-level protein-protein interactions (PPIs), generating and responding to forces, ultimately shaping all of the physiological and pathophysiological behaviors. Genome editing and molecule drugs targeting PPIs hold great promise for the treatments of diseases. Linking genes and molecular drugs with protein-performed cellular behaviors is a key yet challenging issue due to the wide range of spatial and temporal scales involved. Building predictive spatiotemporal modeling systems that can describe the dynamic behaviors of cells intervened by genome editing and molecular drugs at the intersection of biology, chemistry, physics, and computer science will greatly accelerate pharmaceutical advances. Here, we review the mechanical roles of cytoskeletal proteins in orchestrating cellular behaviors alongside significant advancements in biophysical modeling while also addressing the limitations in these models. Then, by integrating generative artificial intelligence (AI) with spatiotemporal multiscale biophysical modeling, we propose a computational pipeline for developing virtual cells, which can simulate and evaluate the therapeutic effects of drugs and genome editing technologies on various cell dynamic behaviors and could have broad biomedical applications. Such virtual cell modeling systems might revolutionize modern biomedical engineering by moving most of the painstaking wet-laboratory effort to computer simulations, substantially saving time and alleviating the financial burden for pharmaceutical industries.

In silico approaches for drug repurposing in oncology: a scoping review

Introduction: Cancer refers to a group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body. Due to its complexity, it has been hard to find an ideal medicine to treat all cancer types, although there is an urgent need for it. However, the cost of developing a new drug is high and time-consuming. In this sense, drug repurposing (DR) can hasten drug discovery by giving existing drugs new disease indications. Many computational methods have been applied to achieve DR, but just a few have succeeded. Therefore, this review aims to show in silico DR approaches and the gap between these strategies and their ultimate application in oncology. Methods: The scoping review was conducted according to the Arksey and O'Malley framework and the Joanna Briggs Institute recommendations. Relevant studies were identified through electronic searching of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases, as well as the grey literature. We included peer-reviewed research articles involving in silico strategies applied to drug repurposing in oncology, published between 1 January 2003, and 31 December 2021. Results: We identified 238 studies for inclusion in the review. Most studies revealed that the United States, India, China, South Korea, and Italy are top publishers. Regarding cancer types, breast cancer, lymphomas and leukemias, lung, colorectal, and prostate cancer are the top investigated. Additionally, most studies solely used computational methods, and just a few assessed more complex scientific models. Lastly, molecular modeling, which includes molecular docking and molecular dynamics simulations, was the most frequently used method, followed by signature-, Machine Learning-, and network-based strategies. Discussion: DR is a trending opportunity but still demands extensive testing to ensure its safety and efficacy for the new indications. Finally, implementing DR can be challenging due to various factors, including lack of quality data, patient populations, cost, intellectual property issues, market considerations, and regulatory requirements. Despite all the hurdles, DR remains an exciting strategy for identifying new treatments for numerous diseases, including cancer types, and giving patients faster access to new medications.

Network-based identification of key proteins and repositioning of drugs for non-small cell lung cancer

BACKGROUND

NSCLC is a lethal cancer that is highly prevalent and accounts for 85% of cases of lung cancer. Conventional cancer treatments, such as chemotherapy and radiation, frequently exhibit limited efficacy and notable adverse reactions. Therefore, a drug repurposing method is proposed for effective NSCLC treatment.

AIMS

This study aims to evaluate candidate drugs that are effective for NSCLC at the clinical level using a systems biology and network analysis approach.

METHODS

Differentially expressed genes in transcriptomics data were identified using the systems biology and network analysis approaches. A network of gene co-expression was developed with the aim of detecting two modules of gene co-expression. Following that, the Drug-Gene Interaction Database was used to find possible drugs that target important genes within two gene co-expression modules linked to non-small cell lung cancer (NSCLC). The use of Cytoscape facilitated the creation of a drug-gene interaction network. Finally, gene set enrichment analysis was done to validate candidate drugs.

RESULTS

Unlike previous research on repositioning drugs for NSCLC, which uses a gene co-expression network, this project is the first to research both gene co-expression and co-occurrence networks. And the co-occurrence network also accounts for differentially expressed genes in cancer cells and their adjacent normal cells. For effective management of non-small cell lung cancer (NSCLC), drugs that show higher gene regulation and gene affinity within the drug-gene interaction network are thought to be important. According to the discourse, NSCLC genes have a lot of control over medicines like vincristine, fluorouracil, methotrexate, clotrimazole, etoposide, tamoxifen, sorafenib, doxorubicin, and pazopanib.

CONCLUSION

Hence, there is a possibility of repurposing these drugs for the treatment of non-small-cell lung cancer.

SGCLDGA: unveiling drug-gene associations through simple graph contrastive learning

Drug repurposing offers a viable strategy for discovering new drugs and therapeutic targets through the analysis of drug-gene interactions. However, traditional experimental methods are plagued by their costliness and inefficiency. Despite graph convolutional network (GCN)-based models' state-of-the-art performance in prediction, their reliance on supervised learning makes them vulnerable to data sparsity, a common challenge in drug discovery, further complicating model development. In this study, we propose SGCLDGA, a novel computational model leveraging graph neural networks and contrastive learning to predict unknown drug-gene associations. SGCLDGA employs GCNs to extract vector representations of drugs and genes from the original bipartite graph. Subsequently, singular value decomposition (SVD) is employed to enhance the graph and generate multiple views. The model performs contrastive learning across these views, optimizing vector representations through a contrastive loss function to better distinguish positive and negative samples. The final step involves utilizing inner product calculations to determine association scores between drugs and genes. Experimental results on the DGIdb4.0 dataset demonstrate SGCLDGA's superior performance compared with six state-of-the-art methods. Ablation studies and case analyses validate the significance of contrastive learning and SVD, highlighting SGCLDGA's potential in discovering new drug-gene associations. The code and dataset for SGCLDGA are freely available at https://github.com/one-melon/SGCLDGA.

Drug Repositioning: A Monetary Stratagem to Discover a New Application of Drugs

Drug repurposing, also referred to as drug repositioning or drug reprofiling, is a scientific approach to the detection of any new application for an already approved or investigational drug. It is a useful policy for the invention and development of new pharmacological or therapeutic applications of different drugs. The strategy has been known to offer numerous advantages over developing a completely novel drug for certain problems. Drug repurposing has numerous methodologies that can be categorized as target-oriented, drug-oriented, and problem-oriented. The choice of the methodology of drug repurposing relies on the accessible information about the drug molecule and like pharmacokinetic, pharmacological, physicochemical, and toxicological profile of the drug. In addition, molecular docking studies and other computer-aided methods have been known to show application in drug repurposing. The variation in dosage for original target diseases and novel diseases presents a challenge for researchers of drug repurposing in present times. The present review critically discusses the drugs repurposed for cancer, covid-19, Alzheimer's, and other diseases, strategies, and challenges of drug repurposing. Moreover, regulatory perspectives related to different countries like the United States (US), Europe, and India have been delineated in the present review.

The cardiac glycoside ZINC253504760 induces parthanatos-type cell death and G2/M arrest via downregulation of MEK1/2 phosphorylation in leukemia cells

Overcoming multidrug resistance (MDR) represents a major obstacle in cancer chemotherapy. Cardiac glycosides (CGs) are efficient in the treatment of heart failure and recently emerged in a new role in the treatment of cancer. ZINC253504760, a synthetic cardenolide that is structurally similar to well-known GCs, digitoxin and digoxin, has not been investigated yet. This study aims to investigate the cytotoxicity of ZINC253504760 on MDR cell lines and its molecular mode of action for cancer treatment. Four drug-resistant cell lines (P-glycoprotein-, ABCB5-, and EGFR-overexpressing cells, and TP53-knockout cells) did not show cross-resistance to ZINC253504760 except BCRP-overexpressing cells. Transcriptomic profiling indicated that cell death and survival as well as cell cycle (G2/M damage) were the top cellular functions affected by ZINC253504760 in CCRF-CEM cells, while CDK1 was linked with the downregulation of MEK and ERK. With flow cytometry, ZINC253504760 induced G2/M phase arrest. Interestingly, ZINC253504760 induced a novel state-of-the-art mode of cell death (parthanatos) through PARP and PAR overexpression as shown by western blotting, apoptosis-inducing factor (AIF) translocation by immunofluorescence, DNA damage by comet assay, and mitochondrial membrane potential collapse by flow cytometry. These results were ROS-independent. Furthermore, ZINC253504760 is an ATP-competitive MEK inhibitor evidenced by its interaction with the MEK phosphorylation site as shown by molecular docking in silico and binding to recombinant MEK by microscale thermophoresis in vitro. To the best of our knowledge, this is the first time to describe a cardenolide that induces parthanatos in leukemia cells, which may help to improve efforts to overcome drug resistance in cancer. A cardiac glycoside compound ZINC253504760 displayed cytotoxicity against different multidrug-resistant cell lines. ZINC253504760 exhibited cytotoxicity in CCRF-CEM leukemia cells by predominantly inducing a new mode of cell death (parthanatos). ZINC253504760 downregulated MEK1/2 phosphorylation and further affected ERK activation, which induced G2/M phase arrest.

Cynaropicrin disrupts tubulin and c-Myc-related signaling and induces parthanatos-type cell death in multiple myeloma

The majority of blood malignancies is incurable and has unforeseeable remitting-relapsing paths in response to different treatments. Cynaropicrin, a natural sesquiterpene lactone from the edible parts of the artichoke plant, has gained increased attention as a chemotherapeutic agent. In this study, we investigated the effects of cynaropicrin against multiple myeloma (MM) cells in vitro and assessed its in vivo effectiveness in a xenograft tumor zebrafish model. We showed that cynaropicrin exerted potent cytotoxicity against a panel of nine MM cell lines and two leukemia cell lines with AMO1 being the most sensitive cell line (IC50 = 1.8 ± 0.3 µM). Cynaropicrin (0.8, 1.9, 3.6 µM) dose-dependently reduced c-Myc expression and transcriptional activity in AMO1 cells that was associated with significant downregulation of STAT3, AKT, and ERK1/2. Cell cycle analysis showed that cynaropicrin treatment arrested AMO1 cells in the G2M phase along with an increase in the sub-G0G1 phase after 24 h. With prolonged treatment times, cells accumulated more in the sub-G0G1 phase, implying cell death. Using confocal microscopy, we revealed that cynaropicrin disrupted the microtubule network in U2OS cells stably expressing α-tubulin-GFP. Furthermore, we revealed that cynaropicrin promoted DNA damage in AMO1 cells leading to PAR polymer production by PARP1 hyperactivation, resulting in AIF translocation from the mitochondria to the nucleus and subsequently to a novel form of cell death, parthanatos. Finally, we demonstrated that cynaropicrin (5, 10 µM) significantly reduced tumor growth in a T-cell acute lymphoblastic leukemia (T-ALL) xenograft zebrafish model. Taken together, these results demonstrate that cynaropicrin causes potent inhibition of hematopoietic tumor cells in vitro and in vivo.

Identification of mutation gene prognostic biomarker in multiple myeloma through gene panel exome sequencing and transcriptome analysis in Chinese population

BACKGROUND

The 5-year survival rate of multiple myeloma (MM) in China is less than 40%, with considerable individual heterogeneity. Gene mutations are important predictive biomarkers that influence MM treatment decision. The aim of our study was to uncover the clinical significance of mutated genes in MM in the Chinese population.

METHODS

Targeted exon panel sequencing was performed of 400 genes to detect the gene mutation status in plasma cells from 50 patients with MM. DAVID was used to explore the functions and pathways of mutated genes. Detection of mutant gene expression, prognosis and immune cell infiltration with GSE6477. GEO2R was utilized to identify differentially expressed genes (DEGs). Kaplan-Meier and CIBERSORT were applied to compare survival distributions and evaluate the gene expression associated with immune cell infiltration, respectively.

RESULTS

Mutations of 337 genes were identified in MM. The mutation types included SNP, INS, and DEL, but the dominant mutation type was SNP. Function and pathway analysis of mutant genes were performed to elucidate DNA modifications. We identified a total number of 660 downregulated and 587 upregulated genes from the GSE6477 dataset. Thirty-three common genes were present in both the mutant genes and DEGs. The functions and pathways of the mutated genes were enriched in myeloid cell differentiation, regulation of hemopoiesis, etc. Moreover, we found that the low expression of BCL6, BIRC3, HLA-DQA1, and VCAN was correlated with poor prognosis in MM.

CONCLUSIONS

The mutations and low expression of BCL6, BIRC3, HLA-DQA1, and VCAN were correlated with poor prognosis and immune cell infiltration in MM. This study is the first to reveal the spectrum of mutations in the Chinese population by the use of an NGS panel.

In Silico, In Vitro, and In Vivo Investigations on Adapalene as Repurposed Third Generation Retinoid against Multiple Myeloma and Leukemia

The majority of hematopoietic cancers in adults are incurable and exhibit unpredictable remitting-relapsing patterns in response to various therapies. The proto-oncogene c-MYC has been associated with tumorigenesis, especially in hematological neoplasms. Therefore, targeting c-MYC is crucial to find effective, novel treatments for blood malignancies. To date, there are no clinically approved c-MYC inhibitors. In this study, we virtually screened 1578 Food and Drug Administration (FDA)-approved drugs from the ZINC15 database against c-MYC. The top 117 compounds from PyRx-based screening with the best binding affinities to c-MYC were subjected to molecular docking studies with AutoDock 4.2.6. Retinoids consist of synthetic and natural vitamin A derivatives. All-trans-retinoic acid (ATRA) were highly effective in hematological malignancies. In this study, adapalene, a third-generation retinoid usually used to treat acne vulgaris, was selected as a potent c-MYC inhibitor as it robustly bound to c-MYC with a lowest binding energy (LBE) of -7.27 kcal/mol, a predicted inhibition constant (pKi) of 4.69 µM, and a dissociation constant (Kd value) of 3.05 µM. Thus, we examined its impact on multiple myeloma (MM) cells in vitro and evaluated its efficiency in vivo using a xenograft tumor zebrafish model. We demonstrated that adapalene exerted substantial cytotoxicity against a panel of nine MM and two leukemic cell lines, with AMO1 cells being the most susceptible one (IC50 = 1.76 ± 0.39 µM) and, hence, the focus of this work. Adapalene (0.5 × IC50, 1 × IC50, 2 × IC50) decreased c-MYC expression and transcriptional activity in AMO1 cells in a dose-dependent manner. An examination of the cell cycle revealed that adapalene halted the cells in the G2/M phase and increased the portion of cells in the sub-G0/G1 phase after 48 and 72 h, indicating that cells failed to initiate mitosis, and consequently, cell death was triggered. Adapalene also increased the number of p-H3(Ser10) positive AMO1 cells, which is a further proof of its ability to prevent mitotic exit. Confocal imaging demonstrated that adapalene destroyed the tubulin network of U2OS cells stably transfected with a cDNA coding for α-tubulin-GFP, refraining the migration of malignant cells. Furthermore, adapalene induced DNA damage in AMO1 cells. It also induced apoptosis and autophagy, as demonstrated by flow cytometry and western blotting. Finally, adapalene impeded tumor growth in a xenograft tumor zebrafish model. In summary, the discovery of the vitamin A derivative adapalene as a c-MYC inhibitor reveals its potential as an avant-garde treatment for MM.

Molecular Modes of Action of an Aqueous Nerium oleander Extract in Cancer Cells In Vitro and In Vivo

Cancer drug resistance remains a major obstacle in clinical oncology. As most anticancer drugs are of natural origin, we investigated the anticancer potential of a standardized cold-water leaf extract from Nerium oleander L., termed Breastin. The phytochemical characterization by nuclear magnetic resonance spectroscopy (NMR) and low- and high-resolution mass spectrometry revealed several monoglycosidic cardenolides as major constituents (adynerin, neritaloside, odoroside A, odoroside H, oleandrin, and vanderoside). Breastin inhibited the growth of 14 cell lines from hematopoietic tumors and 5 of 6 carcinomas. Remarkably, the cellular responsiveness of odoroside H and neritaloside was not correlated with all other classical drug resistance mechanisms, i.e., ATP-binding cassette transporters (ABCB1, ABCB5, ABCC1, ABCG2), oncogenes (EGFR, RAS), tumor suppressors (TP53, WT1), and others (GSTP1, HSP90, proliferation rate), in 59 tumor cell lines of the National Cancer Institute (NCI, USA), indicating that Breastin may indeed bypass drug resistance. COMPARE analyses with 153 anticancer agents in 74 tumor cell lines of the Oncotest panel revealed frequent correlations of Breastin with mitosis-inhibiting drugs. Using tubulin-GFP-transfected U2OS cells and confocal microscopy, it was found that the microtubule-disturbing effect of Breastin was comparable to that of the tubulin-depolymerizing drug paclitaxel. This result was verified by a tubulin polymerization assay in vitro and molecular docking in silico. Proteome profiling of 3171 proteins in the NCI panel revealed protein subsets whose expression significantly correlated with cellular responsiveness to odoroside H and neritaloside, indicating that protein expression profiles can be identified to predict the sensitivity or resistance of tumor cells to Breastin constituents. Breastin moderately inhibited breast cancer xenograft tumors in vivo. Remarkably, in contrast to what was observed with paclitaxel monotherapy, the combination of paclitaxel and Breastin prevented tumor relapse, indicating Breastin's potential for drug combination regimens.

Xylochemical Synthesis and Biological Evaluation of the Orchidaceous Natural Products Isoarundinin I, Bleochrin F, Blestanol K, and Pleionol

The first total syntheses of the orchid-derived natural products isoarundinin I (1), (±)-bleochrin F ((±)-2), (±)-blestanol K ((±)-3), and (±)-pleionol ((±)-4) from renewable starting materials are reported, along with the evaluation of their biological activities. The total syntheses were based on regioselective aromatic bromination reactions in combination with a key acid-promoted regioselective intramolecular cyclization. The biological results suggest that isoarundinin I (1), (±)-blestanol K ((±)-3), and (±)-pleionol ((±)-4) have the potential to inhibit the growth of both sensitive and multidrug-resistant cancer cells.

Identification of Gedunin from a Phytochemical Depository as a Novel Multidrug Resistance-Bypassing Tubulin Inhibitor of Cancer Cells

The chemotherapy of tumors is frequently limited by the development of resistance and severe side effects. Phytochemicals may offer promising candidates to meet the urgent requirement for new anticancer drugs. We screened 69 phytochemicals, and focused on gedunin to analyze its molecular modes of action. Pearson test-base correlation analyses of the log₁₀IC₅₀ values of 55 tumor cell lines of the National Cancer Institute (NCI), USA, for gedunin with those of 91 standard anticancer agents revealed statistically significant relationships to all 10 tested microtubule inhibitors. Thus, we hypothesized that gedunin may be a novel microtubule inhibitor. Confocal microscopy, cell cycle measurements, and molecular docking in silico substantiated our assumption. Agglomerative cluster analyses and the heat map generation of proteomic data revealed a subset of 40 out of 3171 proteins, the expression of which significantly correlated with sensitivity or resistance for the NCI cell line panel to gedunin. This indicates the complexity of gedunin’s activity against cancer cells, underscoring the value of network pharmacological techniques for the investigation of the molecular modes of drug action. Finally, we correlated the transcriptome-wide mRNA expression of known drug resistance mechanism (ABC transporter, oncogenes, tumor suppressors) log₁₀IC₅₀ values for gedunin. We did not find significant correlations, indicating that gedunin’s anticancer activity might not be hampered by classical drug resistance mechanisms. In conclusion, gedunin is a novel microtubule-inhibiting drug candidate which is not involved in multidrug resistance mechanisms such as other clinically established mitotic spindle poisons.

Network Pharmacology of Adaptogens in the Assessment of Their Pleiotropic Therapeutic Activity

The reductionist concept, based on the ligand–receptor interaction, is not a suitable model for adaptogens, and herbal preparations affect multiple physiological functions, revealing polyvalent pharmacological activities, and are traditionally used in many conditions. This review, for the first time, provides a rationale for the pleiotropic therapeutic efficacy of adaptogens based on evidence from recent gene expression studies in target cells and where the network pharmacology and systems biology approaches were applied. The specific molecular targets and adaptive stress response signaling mechanisms involved in nonspecific modes of action of adaptogens are identified.

Drug repositioning in non-small cell lung cancer (NSCLC) using gene co-expression and drug–gene interaction networks analysis

Lung cancer is the most common cancer in men and women. This cancer is divided into two main types, namely non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Around 85 to 90 percent of lung cancers are NSCLC. Repositioning potent candidate drugs in NSCLC treatment is one of the important topics in cancer studies. Drug repositioning (DR) or drug repurposing is a method for identifying new therapeutic uses of existing drugs. The current study applies a computational drug repositioning method to identify candidate drugs to treat NSCLC patients. To this end, at first, the transcriptomics profile of NSCLC and healthy (control) samples was obtained from the GEO database with the accession number GSE21933. Then, the gene co-expression network was reconstructed for NSCLC samples using the WGCNA, and two significant purple and magenta gene modules were extracted. Next, a list of transcription factor genes that regulate purple and magenta modules' genes was extracted from the TRRUST V2.0 online database, and the TF–TG (transcription factors–target genes) network was drawn. Afterward, a list of drugs targeting TF–TG genes was obtained from the DGIdb V4.0 database, and two drug–gene interaction networks, including drug-TG and drug-TF, were drawn. After analyzing gene co-expression TF–TG, and drug–gene interaction networks, 16 drugs were selected as potent candidates for NSCLC treatment. Out of 16 selected drugs, nine drugs, namely Methotrexate, Olanzapine, Haloperidol, Fluorouracil, Nifedipine, Paclitaxel, Verapamil, Dexamethasone, and Docetaxel, were chosen from the drug-TG sub-network. In addition, nine drugs, including Cisplatin, Daunorubicin, Dexamethasone, Methotrexate, Hydrocortisone, Doxorubicin, Azacitidine, Vorinostat, and Doxorubicin Hydrochloride, were selected from the drug-TF sub-network. Methotrexate and Dexamethasone are common in drug-TG and drug-TF sub-networks. In conclusion, this study proposed 16 drugs as potent candidates for NSCLC treatment through analyzing gene co-expression, TF–TG, and drug–gene interaction networks.

Anaplastic lymphoma kinase inhibitors and their effect on the kidney

Lung cancer is the leading cause of cancer-related mortality and approximately 5% of non–small-cell lung cancer (NSCLC) patients are positive for anaplastic lymphoma kinase (ALK) gene rearrangement or fusion with echinoderm microtubule-associated protein-like 4. ALK inhibitors are the mainstay treatment for patients with NSCLC harboring a rearrangement of the ALK gene or the ROS1 oncogenes. With the recent publication of pivotal trials leading to the approval of these compounds in different indications, their toxicity profile warrants an update. Several ALK-1 inhibitors are used in clinical practice, including crizotinib, ceritinib and alectinib. According to the package insert and published literature, treatment with several ALK-1 inhibitors appears to be associated with the development of peripheral edema and rare electrolyte disorders, kidney failure, proteinuria and an increased risk for the development and progression of renal cysts. This review introduces the different types of ALK inhibitors, focusing on their detailed kidney-related side effects in clinical practice.