Drug Target Pathways Research Articles

A novel hypothesis-generating computational workflow utilizing reverse pharmacophore mapping-A drug repurposing perspective of istradefylline towards major depressive disorder.

Drug repurposing (DR) offers a compelling alternative to traditional drug discovery's lengthy, resource-intensive process. DR is the process of identifying alternative clinical applications for pre-approved drugs as a low-risk and low-cost strategy. Computational approaches are crucial during the early hypothesis-generating stage of DR. However, 'large-scale' data retrieval remains a significant challenge. A computational workflow addressing such limitations might improve hypothesis generation, ultimately benefit patients and advance DR research. We introduce a novel computational workflow (combining free-accessible computational platforms) to provide 'proof-of-concept' of the pre-approved drug's suitability for repurposing. Three key phases are included: target fishing (via reverse pharmacophore mapping), target identification (via disease- and drug-target pathway identification) and retrospective literature and drug-like analysis (via in silico ADMET properties determination). Istradefylline is a Parkinson's disease-approved drug with literature-attributed antidepressant properties remaining unclear. Practically applied, istradefylline's antidepressant activity was assessed in the context of major depressive disorder (MDD). Data mining aided by target identification resulted in istradefylline potentially representing a novel antidepressant drug class. Retrieved drug targets (KYNU, MAO-B, ALOX12 and PLCB2) associated with selected MDD pathways (tryptophan metabolism and serotonergic synapse) generated a hypothesis that istradefylline increased extracellular 5-HT levels (MAO-B inhibition) and reduced inflammation (KYNU, ALOX12 and PLCB2 inhibition). The practically applied workflow's generated hypothesis aligns with known experimental data, validating the effectiveness of this novel computational workflow. It is a low-risk and low-cost DR computational tool providing a bird's-eye view for exploring alternative clinical applications of pre-approved drugs.

Investigation of the Lipid-Lowering Activity and Mechanism of Three Extracts from Astragalus membranaceus, Hippophae rhamnoides L., and Taraxacum mongolicum Hand. Mazz Based on Network Pharmacology and In Vitro and In Vivo Experiments.

Hyperlipidemia is a metabolic disorder characterized by abnormal lipid metabolism, resulting in lipid accumulation in the plasma. According to reports, medicinal and edible plants can reduce the risk of metabolic diseases such as hyperlipidemia. This study investigates the effects and mechanisms of Astragalus membranaceus extract (AME), Hippophae rhamnoides L. extract (HRE), and Taraxacum mongolicum Hand. Mazz extract (TME) on hyperlipidemia. Active compounds and potential gene targets of AME, HRE, and TME were screened using LC-MS and TCMSP databases, and hyperlipidemia targets were detected from the OMIM and DisGeNet databases. A drug-target pathway disease network was constructed through protein interactions, GO enrichment, and KEGG pathway analysis. Finally, the lipid-lowering effects of three extracts were validated through in vitro HepG2 cell and in vivo animal experiments. The results show that LC-MS and network pharmacology methodologies identified 41 compounds and 140 targets. KEGG analysis indicated that the PI3K-Akt and MAPK signaling pathways significantly treat hyperlipidemia with AHT. In vitro experiments have shown that AHT is composed of a ratio of AME:HRE:TME = 3:1:2. HepG2 cell and animal experiments revealed that AHT exhibits strong lipid-lowering and antioxidant properties, significantly regulating the levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), superoxide dismutase (SOD), and total antioxidant capacity (T-AOC). It is worth noting that AHT can effectively downregulate the protein expression levels of p-AKT/AKT and p-PI3K/PI3K and upregulate the protein expression levels of p-AMPK/AMPK and SIRT1, verifying the results predicted by network pharmacology. This study presents a novel approach to utilizing these natural plant extracts as safe and effective treatments for hyperlipidemia.

Exploring the mechanisms of Guizhifuling pills in the treatment of coronary spastic angina based on network pharmacology combined with molecular docking.

Coronary spastic angina (CSA) is common, and treatment options for refractory vasospastic angina are sometimes limited. Guizhifuling pills (GFP) have demonstrated efficacy in reducing CSA episodes, but their pharmacological mechanism remains unclear. To explore the mechanism of action of GFP in preventing and treating CSA, we employed network pharmacology and molecular docking to predict targets and analyze networks. We searched GFP chemical composition information and related targets from databases. The drug-target and drug-target pathway networks were constructed using Cytoscape. Then the protein-protein interaction was analyzed using the STRING database. Gene Ontology biological functions and Kyoto Encyclopedia of Genes and Genomes pathways were performed by the Metascape database, and molecular docking validation of vital active ingredients and action targets of GFP was performed using AutoDock Vina software. The 51 active components in GFP are expected to influence CSA by controlling 279 target genes and 151 signaling pathways. Among them, 6 core components, such as quercetin, β-sitosterol, and baicalein, may regulate CSA by affecting 10 key target genes such as STAT3, IL-6, TP53, AKT1, and EGFR. In addition, they are involved in various critical signaling pathways such as apelin, calcium, advanced glycation end product-receptor for advanced glycation end product, and necroptosis. Molecular docking analysis confirms favorable binding interactions between the active components of GFP and the selected target proteins. The effects of GFP in treating CSA involve multiple components, targets, and pathways, offering a theoretical basis for its clinical use and enhancing our understanding of how it works.

Molecular interactions between metformin and D-limonene inhibit proliferation and promote apoptosis in breast and liver cancer cells

BackgroundCancer is a fatal disease that severely affects humans. Designing new anticancer strategies and understanding the mechanism of action of anticancer agents is imperative.Hypothesis/PurposeIn this study, we evaluated the utility of metformin and D-limonene, alone or in combination, as potential anticancer therapeutics using the human liver and breast cancer cell lines HepG2 and MCF-7.Study designAn integrated systems pharmacology approach is presented for illustrating the molecular interactions between metformin and D-limonene.MethodsWe applied a systems-based analysis to introduce a drug–target–pathway network that clarifies different mechanisms of treatment. The combination treatment of metformin and D-limonene induced apoptosis in both cell lines compared with single drug treatments, as indicated by flow cytometric and gene expression analysis.ResultsThe mRNA expression of Bax and P53 genes were significantly upregulated while Bcl-2, iNOS, and Cox-2 were significantly downregulated in all treatment groups compared with normal cells. The percentages of late apoptotic HepG2 and MCF-7 cells were higher in all treatment groups, particularly in the combination treatment group. Calculations for the combination index (CI) revealed a synergistic effect between both drugs for HepG2 cells (CI = 0.14) and MCF-7 cells (CI = 0.22).ConclusionOur data show that metformin, D-limonene, and their combinations exerted significant antitumor effects on the cancer cell lines by inducing apoptosis and modulating the expression of apoptotic genes.

Abstract 4548: Discovering novel ALK-lung carcinoma therapeutic strategies by identifying combinations with Alectinib from ALK-positive lung carcinoma cell lines

Abstract Background: The therapeutic landscape for chromosomally rearranged anaplastic lymphoma kinase (ALK) has focused on the development of Tyrosine-kinase inhibitors (TKI) that specifically target ALK activity. However, as patients progress on first- and second line TKIs, over 50% of resistance is due to non-mutational resistance via compensatory pathways, also known as ALK-non dominant resistance. Alterations in other drivers such as EGFR, KRAS, MET account for some of the resistance mechanisms. Thus, here we explore the therapeutic activity of drug combinations that pair an ALK inhibitor with a drug that targets a "second driver". We describe our high-throughput drug screening platform that combines Alectinib, a selective blocker of ALK, with a panel of hundreds of chemical compounds curated to be active against a diverse array of pathways involved in cellular functions dysregulated in cancer. In this work, we identified several synergistic combinations that further increased the sensitivity of five ALK-positive lung cancer cell lines (DFCI 032, NCI-H3122, NCI-H2228, SNU2535, SNU324) to Alectinib in comparison to single treatment with the final goal of targeting resistance, before it emerges. Methods: ALK-positive cancer cell sensitivity to different compounds was assessed by generating the IC50 curves in the presence and absence of Alectinib. Cells were characterized by bulk-RNAseq, bulk-DNA seq, Reverse-phase protein array, and Mass spectrometry to identify perturbed RNA pathways, DNA mutations, and proteome alterations. Results: In this study, we present for the first time, a group of compounds, such as Gilteritinib, Trametinib, Dinaciclib, WYE-125132, Cenisertib, SN-38 which exhibit the capacity to induce cytotoxic effects in ALK-positive lung cancer cells, when combined with Alectinib. Our findings demonstrate a novel sensitivity of ALK driven by non-conventional parallel signaling, apart from conventional targets previously described, such as phosphoinositol-3kinase (PI3K)/Akt, signal transducer and activator of transcription 3 (STAT3), and extracellular signal-regulated kinases (ERK). Conclusions: Through the integration of different multiomic approaches on five ALK-positive lung cancer cell lines, we have pinpointed a novel role of MAPK, CDK, and mTOR, pathways and their regulators, as a promising avenue for advancing treatment strategies for ALK-positive lung cancer. These findings, along with the identification of several other significant targetable elements illustrate a new approach towards the discovery of new drug combinations and targetable pathways to tackle ALK TKI resistance in ALK-positive patients before it emerges. We have previously generated Alectinib-resistant models and are in the process of screening to identify any resistant pathways that may align with those identified in the sensitive lines. Citation Format: Hamadi Madhi, Habib Serhan, Nathalie M. Vandecan, Zhaoping Qin, Albert Liu, Aaron Udager, Sofia D. Merajver, Matthew B. Soellner, Nathan Merrill. Discovering novel ALK-lung carcinoma therapeutic strategies by identifying combinations with Alectinib from ALK-positive lung carcinoma cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4548.

Abstract 682: Development of novel eIF4E inhibitors to potently and selectively suppress tumor growth across multiple indications

Abstract Despite considerable progress in treating cancer, drug resistance remains the primary hurdle to achieving cures in patients. Tumors often develop resistance through reactivation of the drug-targeted pathway, or activation of alternative parallel pathways, thereby maintaining the original downstream signaling effects. One of the furthest downstream effectors and critical nodes for many oncogenic signaling pathways is eukaryotic translation initiation factor 4E (eIF4E); the main regulator and rate limiting factor for protein synthesis. eIF4E is reactivated by many resistance mechanisms to promote translation of multiple pro-oncogenic factors including Cyclin D1/3, making it an attractive target to potentiate the anti-cancer activity of targeted therapies and to overcome drug resistance. Here, we present the development of novel, potent, and selective eIF4E inhibitors for use in both treatment-naïve and resistance settings across multiple tumor indications. To capitalize on the potential of targeting eIF4E, we developed a series of compounds with unique properties that maintain anti-tumor efficacy while minimizing toxicity. Our novel, selective, and potent oral eIF4E inhibitors (RBX-eIF4Ei) elicit a reversible, dose-dependent cell cycle arrest. Unlike targeting eIF4A, eIF4E inhibition selectively regulates translation of cancer-dependent pathway proteins instead of global protein synthesis, thus reducing on-target toxicity and increasing tolerability. Cellular profiling demonstrates RBX-eIF4Ei are highly selective, nanomolar inhibitors across many tumor types including, NSCLC, CRC, breast, and melanoma. Additionally, RBX-eIF4Ei demonstrate consistent efficacy across both sensitive and resistant cell lines, including intrinsic and acquired resistance models. Combining RBX-eIF4Ei with standard of care targeted therapies produces additive responses in both settings, suggesting its potential anti-neoplastic benefits post progression. In vivo, daily oral monotherapy treatment with RBX-EIF4Ei causes significant tumor growth inhibition across a variety of indications including BRAFmut CRC, BRAFmut melanoma and ER+ breast cancer, with minimal signs of toxicity. Intratumoral concentration of RBX-eIF4Ei correlate with significant tumor cell growth inhibition, as well as reductions in eIF4E target proteins, ODC1 and Cyclin D1. Combination studies with standard of care in both the treatment naïve and resistant settings are ongoing. Collectively, these data support the addition of RBX-eIF4Ei to standard of care in both the naïve and treatment resistance settings across a variety of indications including NSCLC, breast, CRC, and melanoma. IND enabling studies are planned, marking a significant step toward advancing these promising eIF4E inhibitors into clinical development. Citation Format: Matthew B. Friedersdorf, Devon R. Blake, Sarah E. Thompson, Roheeth Pavana, Ramamurty V. Changalvala, Andrew S. Truong, Krista Marran, Abha Bias, Jessica A. Sorrentino. Development of novel eIF4E inhibitors to potently and selectively suppress tumor growth across multiple indications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 682.

Drug target, class level, and PathFX pathway information share utility for machine learning prediction of common drug-induced side effects

Drug target, class level, and PathFX pathway information share utility for machine learning prediction of common drug-induced side effects

A Network Pharmacology Study on the Similarities and Differences in the Mechanisms of Zuo Gui Wan/You Gui Wan for the Treatment of Premature Ovarian Failure.

Premature ovarian failure is a heterogeneous disease that severely affects the quality of life of women in their reproductive years. The ancient classical Chinese medicine compounds Zuo Gui Wan and You Gui Wan have great potential to treat premature ovarian failure, but the similarities and differences in their pharmacological mechanisms for treating POF are not yet clear. In this study, the public database was used to screen the active ingredients and potential targets of Zuo Gui Wan and You Gui Wan. The similarities and differences in the potential targets of both pills for the treatment of POF were analysed using the POF-related genes obtained from OMIM and GeneCards. The protein-protein interaction network was established and collated to form a drug-active ingredient-target gene network using STRING. Finally, the drug-target-pathway network was constructed by enrichment analysis to find the differences in target enrichment on the same pathway. Pharmacological analysis of the network showed that Zuo Gui Wan contains 72 active ingredients, while You Gui Wan has 112. A total of 62 common compositions, such as quercetin and kaempferol, were identified. Amongst them were 10 unique compounds, such as hydroxyproline and cholesterol, in Zuo Gui Wan and 50 exclusive compounds, such as Karanjin and betacarotene, in You Gui Wan. In addition, 14 overlapping targets, including MAPK1, CXCL8, TNF, IL6, and EGFR, were determined amongst the first 20 targets in the treatment of POF by both pills, demonstrating that the core mechanism of POF treatment is similar between the two. Pathway enrichment analysis showed 87 identical and significant pathways between Zuo Gui Wan and You Gui Wan, including IL-17, TNF, PI3K-Akt, oestrogen, VEGF, and other pathways. Zuo Gui Wan has 12 special pathways, such as natural killer cell-mediated cytotoxicity and intestinal immune network for IgA production. You Gui Wan has nine unique pathways, such as insulin secretion and glucagon signalling pathway. Zuo Gui Wan and You Gui Wan could treat POF by inhibiting oxidative stress and inflammation, regulating hormone levels, improving ovarian function, and promoting follicular development. Zuo Gui Wan is inclined to immune regulation, while You Gui Wan prefers insulin regulation. Therefore, similarities and differences clearly exist in the specific mechanisms of Zuo Gui Wan and You Gui Wan in the treatment of POF.

SARM1 promotes the neuroinflammation and demyelination through IGFBP2/NF-κB pathway in experimental autoimmune encephalomyelitis mice.

Multiple sclerosis (MS) is an autoimmune disease, and its typical characteristics are neuroinflammation and the demyelination of neurons in the central nervous system (CNS). Sterile alpha and TIR motif containing 1 (SARM1) is an essential factor mediating axonal degeneration and SARM1 deletion reduces the neuroinflammation in spinal cord injury. This study aimed to explore the roles of SARM1 and its underlying mechanisms in MS. Experimental autoimmune encephalomyelitis (EAE, a model of MS) model was established. Immunostaining, western blot, electron microscope, and HE staining were used to examine the pathological manifestations such as inflammation, demyelination, and neuronal death in SARM1f/f EAE mice and SARM1Nestin -CKO EAE mice. In addition, RNA-seq, real-time PCR and double-immunostaining were used to examine the underlying mechanism of SARM1 in EAE mice. SARM1 was upregulated in neurons of the spinal cords of EAE mice. SARM1 knockout in CNS ameliorated EAE with less neuroinflammation, demyelination, and dead neurons. Mechanically, SARM1 knockout resulted in the reduction of insulin-like growth factor (IGF)-binding protein 2 (IGFBP2) in neurons of EAE mice, which might inhibit the neuroinflammation through inhibiting NF-κB signaling. Finally, activation of NF-κB partially aggravated the neuroinflammation and demyelination deficits of SARM1Nestin -CKO EAE mice. These results identified the unknown role of SARM1 in the promotion of neuroinflammation and demyelination and revealed a novel drug target pathway of SARM1/IGFBP2/NF-κB for MS.

Associating pathways with diseases using single-cell expression profiles and making inferences about potential drugs.

Finding direct dependencies between genetic pathways and diseases has been the target of multiple studies as it has many applications. However, due to cellular heterogeneity and limitations of the number of samples for bulk expression profiles, such studies have faced hurdles in the past. Here, we propose a method to perform single-cell expression-based inference of association between pathway, disease and cell-type (sci-PDC), which can help to understand their cause and effect and guide precision therapy. Our approach highlighted reliable relationships between a few diseases and pathways. Using the example of diabetes, we have demonstrated how sci-PDC helps in tracking variation of association between pathways and diseases with changes in age and species. The variation in pathways-disease associations in mice and humans revealed critical facts about the suitability of the mouse model for a few pathways in the context of diabetes. The coherence between results from our method and previous reports, including information about the drug target pathways, highlights its reliability for multidimensional utility.

Mechanistic Research for the Student or Educator (Part I of II)

Many discoveries in the biological sciences have emerged from observational studies, but student researchers also need to learn how to design experiments that distinguish correlation from causation. For example, identifying the physiological mechanism of action of drugs with therapeutic potential requires the establishment of causal links. Only by specifically interfering with the purported mechanisms of action of a drug can the researcher determine how the drug causes its physiological effects. Typically, pharmacological or genetic approaches are employed to modify the expression and/or activity of the biological drug target or downstream pathways, to test if the salutary properties of the drug are thereby abolished. However, experimental techniques have caveats that tend to be underappreciated, particularly for newer methods. Furthermore, statistical effects are no guarantor of their biological importance or translatability across models and species. In this two-part series, the caveats and strengths of mechanistic preclinical research are briefly described, using the intuitive example of pharmaceutical drug testing in experimental models of human diseases. Part I focuses on technical practicalities and common pitfalls of cellular and animal models designed for drug testing, and Part II describes in simple terms how to leverage a full-factorial ANOVA, to test for causality in the link between drug-induced activation (or inhibition) of a biological target and therapeutic outcomes. Upon completion of this series, students will have forehand knowledge of technical and theoretical caveats in mechanistic research, and comprehend that “a model is just a model.” These insights can help the new student appreciate the strengths and limitations of scientific research.

Novel mitoNEET ligand NL-1 improves therapeutic outcomes in an aged rat model of cerebral ischemia/reperfusion injury

Cerebral ischemic stroke is a leading cause of mortality and disability worldwide. Currently, there are a lack of drugs capable of reducing neuronal cell loss due to ischemia/reperfusion-injury after stroke. Previously, we identified mitoNEET, a [2Fe-2S] redox mitochondrial protein, as a putative drug target for ischemic stroke. In this study, we tested NL-1, a novel mitoNEET ligand, in a preclinical model of ischemic stroke with reperfusion using aged female rats. Using a transient middle cerebral artery occlusion (tMCAO), we induced a 2 h ischemic injury and then evaluated the effects of NL-1 treatment on ischemic/reperfusion brain injury at 24 and 72 h. Test compounds were administered at time of reperfusion via intravenous dosing. Results of the study demonstrated that NL-1 (10 mg/kg) treatment markedly improved survival and reduced infarct volume and hemispheric swelling in the brain as compared aged rats treated with vehicle or a lower dose of NL-1 (0.25 mg/kg). Interestingly, the protective effect of NL-1 was significantly improved when encapsulated in PLGA nanoparticles, where a 40-fold lesser dose (0.25 mg/kg) of NL-1 produced an equivalent effect as the 10 mg/kg dose. Evaluation of changes in blood-brain barrier permeability and lipid peroxidation corroborated the protective actions of NL-1 (10 mg/kg) or NL-1 NP treatment demonstrated a reduced accumulation of parenchymal IgG, decreased levels of 4-hydroxynonenal (4-HNE) and a decreased TUNEL positive cells in the brains of aged female rats at 72 h after tMCAO with reperfusion. Our studies indicate that targeting mitoNEET following ischemia/reperfusion-injury is a novel drug target pathway that warrants further investigation.

Genomic Approaches to Antifungal Drug Target Identification and Validation.

The last several decades have witnessed a surge in drug-resistant fungal infections that pose a serious threat to human health. While there is a limited arsenal of drugs that can be used to treat systemic infections, scientific advances have provided renewed optimism for the discovery of novel antifungals. The development of chemical-genomic assays using Saccharomyces cerevisiae has provided powerful methods to identify the mechanism of action of molecules in a living cell. Advances in molecular biology techniques have enabled complementary assays to be developed in fungal pathogens, including Candida albicans and Cryptococcus neoformans. These approaches enable the identification of target genes for drug candidates, as well as genes involved in buffering drug target pathways. Here, we examine yeast chemical-genomic assays and highlight how such resources can be utilized to predict the mechanisms of action of compounds, to study virulence attributes of diverse fungal pathogens, and to bolster the antifungal pipeline.

Novel mitoNEET ligand NL‐1 improves therapeutic outcomes in an aged rat model of cerebral ischemia/reperfusion injury

Cerebral ischemic stroke is a leading cause of mortality and disability worldwide. Currently, there are a lack of drugs capable of reducing neuronal cell loss after ischemia/reperfusion‐injury after stroke. Previously, we identified mitoNEET, a [2Fe‐2S] redox mitochondrial protein, as a putative drug target for stroke. In this study, we tested the novel mitoNEET ligand, NL‐1, in a preclinical model of ischemic stroke with reperfusion using aged female rats. Using a transient middle cerebral artery occlusion (tMCAO), we induced a 2 h ischemic injury and then evaluated the effects of NL‐1 treatment on ischemic/reperfusion brain injury at 24 and 72 h. Test drugs were administered at time of reperfusion via IV dosing. Results demonstrated that NL‐1 (10 mg/kg) treatment markedly reduced infarct volume and hemispheric swelling in the brain as compared rats treated with vehicle or a lower concentration of NL‐1 (0.25 mg/kg). Surprisingly, the protective effect of NL‐1 was significantly improved when encapsulated in PLGA nanoparticles, where a 40‐fold lesser dose (0.25 mg/kg) of NL‐1 produced an equivalent effect as the 10 mg/kg dose. Evaluation of changes in blood‐brain barrier permeability and oxidative stress using immunohistochemical staining corroborated the protective actions of NL‐1, showing reduced extravasation of IgG and decreased levels of 4‐hydroxynonenal (4‐HNE) in the brains of aged female rats at 72 h after tMCAO with reperfusion. Our studies indicate that targeting mitoNEET following ischemia/reperfusion‐injury is a novel drug target pathway that warrants further investigation.

Potential Targets and Molecular Mechanism of Quercetin Against Knee Osteoarthritis

AbstractObjective The objective of this study was to clarify the potential mechanism of quercetin against knee osteoarthritis (KOA) based on network pharmacology and molecular docking.Methods The targets of quercetin were predicted by PubChem and Swiss Target Prediction databases, and the targets of KOA were obtained by DisGeNET, OMIM, and GeneCards databases. Then, the targets of quercetin and KOA were intersected to find the potential targets of quercetin against KOA. The protein–protein interaction network was constructed through the STRING database, and the core targets were screened. Gene ontology (GO) functions enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using DAVID database. The drug–target–pathway–disease network was constructed by Cytoscape software, and the molecular docking verification was performed by Vina.Results There were 49 potential targets for quercetin against KOA, including 10 core targets. GO functions enrichment analysis showed that the biological process of quercetin against KOA mainly involved the negative regulation of apoptotic process, collagen catabolic process, and extracellular matrix disassembly. KEGG pathway enrichment analysis showed that quercetin against KOA was closely related to PI3K-Akt signaling pathway, Rap 1 signaling pathway, FoxO signaling pathway, Ras signaling pathway, TNF signaling pathway, and ErbB signaling pathway. The results of molecular docking showed that the binding energies between ligand and receptors were less than −5 kcal • mol−1.Conclusions The molecular mechanism of quercetin against KOA involves many targets and pathways, which can regulate the proliferation and apoptosis of chondrocytes, degradation of extracellular matrix, and inflammatory reaction. Quercetin can stably bind to the active pockets of core target proteins, thereby exerting the effect against KOA.

Engineered Human Meniscus in Modeling Sex Differences of Knee Osteoarthritis in Vitro.

Background: Osteoarthritis (OA) primarily affects mechanical load-bearing joints. The knee joint is the most impacted by OA. Knee OA (KOA) occurs in almost all demographic groups, but the prevalence and severity are disproportionately higher in females. The molecular mechanism underlying the pathogenesis and progression of KOA is unknown. The molecular basis of biological sex matters of KOA is not fully understood. Mechanical stimulation plays a vital role in modulating OA-related responses of load-bearing tissues. Mechanical unloading by simulated microgravity (SMG) induced OA-like gene expression in engineered cartilage, while mechanical loading by cyclic hydrostatic pressure (CHP), on the other hand, exerted a pro-chondrogenic effect. This study aimed to evaluate the effects of mechanical loading and unloading via CHP and SMG, respectively, on the OA-related profile changes of engineered meniscus tissues and explore biological sex-related differences. Methods: Tissue-engineered menisci were made from female and male meniscus fibrochondrocytes (MFCs) under static conditions of normal gravity in chondrogenic media and subjected to SMG and CHP culture. Constructs were assayed via histology, immunofluorescence, GAG/DNA assays, RNA sequencing, and testing of mechanical properties. Results: The mRNA expression of ACAN and COL2A1, was upregulated by CHP but downregulated by SMG. COL10A1, a marker for chondrocyte hypertrophy, was downregulated by CHP compared to SMG. Furthermore, CHP increased GAG/DNA levels and wet weight in both female and male donors, but only significantly in females. From the transcriptomics, CHP and SMG significantly modulated genes related to the ossification, regulation of ossification, extracellular matrix, and angiogenesis Gene Ontology (GO) terms. A clear difference in fold-change magnitude and direction was seen between the two treatments for many of the genes. Furthermore, differences in fold-change magnitudes were seen between male and female donors within each treatment. SMG and CHP also significantly modulated genes in OA-related KEGG pathways, such as mineral absorption, Wnt signalling pathway, and HIF-1 signalling pathway. Conclusion: Engineered menisci responded to CHP and SMG in a sex-dependent manner. SMG may induce an OA-like profile, while CHP promotes chondrogenesis. The combination of SMG and CHP could serve as a model to study the early molecular events of KOA and potential drug-targetable pathways.

Unraveling Drug Response from Pharmacogenomic Data to Advance Systems Pharmacology Decisions in Tumor Therapeutics

The availability of systematic drug response registries for hundreds cell lines, coupled with the comprehensive profiling of their genomes/transcriptomes enabled the development of computational methods that investigate the molecular basis of drug responsiveness. Herein, we propose an automated, multi-omics systems pharmacology method that identifies genomic markers of anti-cancer drug response. Given a cancer type and a therapeutic compound, the method builds two cell line groups on the antipodes of the drug response spectrum, based on the outer quartiles of the maximum micromolar screening concentration. The method intersects cell lines that share common features in their mutation status, gene expression levels or copy number variants, and a pool of drug response biomarkers (core genes) is built, using genes with mutually exclusive alterations in the two cell line groups. The relevance with the drug target pathways is then quantified, using the combined interaction score of the core genes and an accessory protein network having strong, physical/functional interactions. We demonstrate the applicability and effectiveness of our methodology in three use cases that end up in known drug-gene interactions. The method steps into explainable bioinformatics approaches for novel anticancer drug-gene interactions, offering high accuracy and increased interpretability of the analysis results. Availability: https://github.com/PGxAUTH/PGxGDSC.

MDrop-Seq: Massively Parallel Single-Cell RNA-Seq of Saccharomyces cerevisiae and Candida albicans.

Advances in high-throughput single-cell RNA sequencing (scRNA-seq) have been limited by technical challenges such as tough cell walls and low RNA quantity that prevent transcriptomic profiling of microbial species at throughput. We present microbial Drop-seq or mDrop-seq, a high-throughput scRNA-seq technique that is demonstrated on two yeast species, Saccharomyces cerevisiae, a popular model organism, and Candida albicans, a common opportunistic pathogen. We benchmarked mDrop-seq for sensitivity and specificity and used it to profile 35,109 S. cerevisiae cells to detect variation in mRNA levels between them. As a proof of concept, we quantified expression differences in heat shock S. cerevisiae using mDrop-seq. We detected differential activation of stress response genes within a seemingly homogenous population of S. cerevisiae under heat shock. We also applied mDrop-seq to C. albicans cells, a polymorphic and clinically relevant species of yeast with a thicker cell wall compared to S. cerevisiae. Single-cell transcriptomes in 39,705 C. albicans cells were characterized using mDrop-seq under different conditions, including exposure to fluconazole, a common anti-fungal drug. We noted differential regulation in stress response and drug target pathways between C. albicans cells, changes in cell cycle patterns and marked increases in histone activity when treated with fluconazole. We demonstrate mDrop-seq to be an affordable and scalable technique that can quantify the variability in gene expression in different yeast species. We hope that mDrop-seq will lead to a better understanding of genetic variation in pathogens in response to stimuli and find immediate applications in investigating drug resistance, infection outcome and developing new drugs and treatment strategies.

Regulation of cell cycle and differentiation markers by pathogenic, non-pathogenic and opportunistic skin bacteria

Skin is the first line of defense against the physical, chemical and the biological environment. It is an ideal organ for studying molecular responses to biological infections through a variety of skin cells that specialize in immune responses. Comparative analysis of skin response to pathogenic, non-pathogenic, and commensal bacteria would help in the identification of disease specific pathways for drug targets. In this study, we investigated human breast reduction skin responses to Cutibacterium acnes (C. acnes), Staphylococcus aureus (S. aureus), Staphylococcus epidermidis (S. epidermidis), and TLR1/2 agonist using Affymetrix microarray chips. The Pam3CSK4 solution and bacterial cultures were prepared and inoculated in steel rings, that were placed on the acetone treated epidermis in a petri dish. After 24 h incubation, 8 mm punch biopsies were taken from the center of the ring, and RNA was extracted. The genome-wide expression was then analyzed using Affymetrix HG-133A gene chip microarray. We found that the C. acnes and S. aureus boosted the production of extracellular matrix components and attenuated the expression of differentiation markers. The above responses were mediated through the TLR2 pathway. Skin also responded to S. aureus and C. acnes by inducing the genes of the cell cycle machinery; this response was not TLR2-dependent. S. aureus induced, whereas C. acnes suppressed the genes associated with apoptosis; this was also not TLR2-dependent. Moreover, S. epidermis apparently did not lead to changes in gene expression. We conclude that the breast reduction skin is a very useful model to study the global gene expression in response to bacterial treatments.

Single-Cell RNA Sequencing in Multiple Pathologic Types of Renal Cell Carcinoma Revealed Novel Potential Tumor-Specific Markers.

BackgroundRenal cell carcinoma (RCC) is the most common type of kidney cancer. Studying the pathogenesis of RCC is particularly important, because it could provide a direct guide for clinical treatment. Given that tumor heterogeneity is probably reflected at the mRNA level, the study of mRNA in RCC may reveal some potential tumor-specific markers, especially single-cell RNA sequencing (scRNA-seq).MethodsWe performed an exploratory study on three pathological types of RCC with a small sample size. This study presented clear-cell RCC (ccRCC), type 2 pRCC, and chRCC in a total of 30,263 high-quality single-cell transcriptome information from three pathological types of RCC. In addition, scRNA-seq was performed on normal kidneys. Tumor characteristics were well identified by the comparison between different pathological types of RCC and normal kidneys at the scRNA level.ResultsSome new tumor-specific markers for different pathologic types of RCC, such as SPOCK1, PTGIS, REG1A, CP and SPAG4 were identified and validated. We also discovered that NDUFA4L2 both highly expressed in tumor cells of ccRCC and type 2 pRCC. The presence of two different types of endothelial cells in ccRCC and type 2 pRCC was also identified and verified. An endothelial cell in ccRCC may be associated with fibroblasts and significantly expressed fibroblast markers, such as POSTN and COL3A1. At last, by applying scRNA-seq results, the activation of drug target pathways and sensitivity to drug responses was predicted in different pathological types of RCC.ConclusionsTaken together, these findings considerably enriched the single-cell transcriptomic information for RCC, thereby providing new insights into the diagnosis and treatment of RCC.