Decoding the Role of Astrocytes in the Entorhinal Cortex in Alzheimer’s Disease Using High-Dimensional Single-Nucleus RNA Sequencing Data and Next-Generation Knowledge Discovery Methodologies: Focus on Drugs and Natural Product Remedies for Dementia

Computational identification of natural senotherapeutic compounds that mimic dasatinib based on gene expression data

The major risk factor for chronic disease is chronological age, and age-related chronic diseases account for the majority of deaths worldwide. Targeting senescent cells that accumulate in disease-related tissues presents a strategy to reduce disease burden and to increase healthspan. The senolytic combination of the tyrosine-kinase inhibitor dasatinib and the flavonol quercetin is frequently used in clinical trials aiming to eliminate senescent cells. Here, our goal was to computationally identify natural senotherapeutic repurposing candidates that may substitute dasatinib based on their similarity in gene expression effects. The natural senolytic piperlongumine (a compound found in long pepper), and the natural senomorphics parthenolide, phloretin and curcumin (found in various edible plants) were identified as potential substitutes of dasatinib. The gene expression changes underlying the repositioning highlight apoptosis-related genes and pathways. The four compounds, and in particular the top-runner piperlongumine, may be combined with quercetin to obtain natural formulas emulating the dasatinib + quercetin formula.

Deciphering aging-associated molecular mechanisms in bone marrow derived hematopoietic stem cells in the elderly using NGS data

Aging is a complex process that is not yet fully understood. Despite advancements in research, a deeper understanding of the underlying biological mechanisms is necessary to develop interventions that promote healthy longevity. The aim of this study was to elucidate the complex mechanisms associated with healthy aging and longevity in healthy elderly individuals. The RNA sequencing (RNA-seq) data used in this study was obtained from the Gene Expression Omnibus (GEO) database (accession number GSE104406), which was collected from Fluorescent Activated Cell Sorting (FACS) of human bone marrow derived human hematopoietic stem cells (BM-HSCs) (Lineage-, CD34+, CD38-) young (18-30 years old) and aged (65-75 years old) donors who had no known hematological malignancy, with 10 biological replicates per group. The GEO RNA-seq Experiments Interactive Navigator (GREIN) software was used to obtain raw gene-level counts and filtered metadata for this dataset. Next generation knowledge discovery (NGKD) tools provided by BioJupies were used to obtain differentially regulated pathways, gene ontologies (GO), and gene signatures in the BM-HSCs. Finally, the L1000 Characteristic Direction Signature Search Engine (L1000CDS2) tool was used to identify specific drugs that reverse aging-associated gene signatures in old but healthy individuals. The down-regulation of signaling pathways such as longevity regulation, proteasome, Notch, apoptosis, nuclear factor kappa B (NFkB), and peroxisome proliferator-activated receptors (PPAR) signaling pathways in the BM-HSCs of healthy elderly. GO functions related to negative regulation of bone morphogenetic protein (BMP), telomeric DNA binding, nucleoside binding, calcium -dependent protein binding, chromatin-DNA binding, SMAD binding, and demethylase activity were significantly downregulated in the BM-HSCs of the elderly compared to the healthy young group. Importantly, potential drugs such as salermide, celestrol, cercosporin, dorsomorphin dihydrochloride, and LDN-193189 monohydrochloride that can reverse the aging-associated signatures in HSCs from healthy elderly were identified. The analysis of RNA-seq data based on NGKD techniques revealed a plethora of differentially regulated pathways, gene ontologies, and drugs with anti-aging potential to promote healthspan in the elderly.

Alterations of mRNAs and Non-coding RNAs Associated with Neuroinflammation in Alzheimer's Disease

Alzheimer's disease is a neurodegenerative pathology whose pathognomonic hallmarks are increased generation of β-amyloid (Aβ) peptide, production of hyperphosphorylated (pTau), and neuroinflammation. The last is an alteration closely related to the progression of AD and although it is present in multiple neurodegenerative diseases, the pathophysiological events that characterize neuroinflammatory processes vary depending on the disease. In this article, we focus on mRNA and non-coding RNA alterations as part of the pathophysiological events characteristic of neuroinflammation in AD and the influence of these alterations on the course of the disease through interaction with multiple RNAs related to the generation of Aβ, pTau, and neuroinflammation itself.

Diverse signaling mechanisms and heterogeneity of astrocyte reactivity in Alzheimer's disease

Alzheimer's disease (AD) affects various brain cell types, including astrocytes, which are the most abundant cell types in the central nervous system (CNS). Astrocytes not only provide homeostatic support to neurons but also actively regulate synaptic signaling and functions and become reactive in response to CNS insults through diverse signaling pathways including the JAK/STAT, NF-κB, and GPCR-elicited pathways. The advent of new technology for transcriptomic profiling at the single-cell level has led to increasing recognition of the highly versatile nature of reactive astrocytes and the context-dependent specificity of astrocyte reactivity. In AD, reactive astrocytes have long been observed in senile plaques and have recently been suggested to play a role in AD pathogenesis and progression. However, the precise contributions of reactive astrocytes to AD remain elusive, and targeting this complex cell population for AD treatment poses significant challenges. In this review, we summarize the current understanding of astrocyte reactivity and its role in AD, with a particular focus on the signaling pathways that promote astrocyte reactivity and the heterogeneity of reactive astrocytes. Furthermore, we explore potential implications for the development of therapeutics for AD. Our objective is to shed light on the complex involvement of astrocytes in AD and offer insights into potential therapeutic targets and strategies for treating and managing this devastating neurodegenerative disorder.

Expression pattern, prognostic value and potential microRNA silencing of FZD8 in breast cancer

Breast cancer (BC) is one of the most widespread types of cancer affecting females, and therefore, early diagnosis is critical. BC is a complex heterogeneous disease affected by several key pathways. Among these, WNT proteins and their frizzled receptors (FZD) have been demonstrated to be crucial in regulating a number of cellular and molecular events in BC tumorigenesis. The role of the WNT receptor, FZD8, in BC has received minimal attention; for that reason, the present study examined the prognostic value of its protein expression pattern in a BC cohort. FZD8 cytoplasmic expression pattern analysis revealed that ~38% of the primary samples presented with a high expression profile, whereas ~63% of the samples had a low expression profile. Overall, ~46% of the malignant tissues in the lymph node-positive samples exhibited an increased FZD8 cytoplasmic expression, whereas 54% exhibited low expression levels. An increased expression of FZD8 was associated with several clinicopathological characteristics of the patients, including a low survival rate, tumor vascular invasion, tumor size and grade, and molecular subtypes. Affymetrix microarray triple-negative BC datasets were analyzed and compared with healthy breast tissues in order to predict the potential interfering microRNAs (miRNAs) in the WNT/FZD8 signaling pathway. A total of 29 miRNAs with the potential to interact with the WNT/FZD8 signaling pathway were identified, eight of which exhibited a significant prediction score. The target genes for each predicted miRNA were identified. On the whole, the findings of the present study suggest that FZD8 is a potential prognostic marker for BC, shedding some light onto the silencing mechanisms involved in the complex BC signaling.

Identification of Artemisia Argyi (AA) Therapy in Alzheimer's Disease (AD) Using Network Pharmacology and Molecular Docking

This study aims to investigate the molecular mechanism of Artemisia argyi (AA) in the treatment of cognitive impairment of Alzheimer's disease (AD) and the docking activity of AA on potential therapeutic targets using network pharmacology and molecular docking techniques. Bioinformatic analysis showed that neuroactive ligand-receptor interaction, the pathway of cancer, calcium signaling, neurodegeneration-multiple disease, and chemical carcinogenesis-receptor activation might be the related signal pathway in AA-AD. Moreover, the binding energy of AA active compounds to potential targets are ≦-4.16 kJ mol-1 with 10 patterns ≦-10 kJ mol-1 . The results of molecular docking showed that there would be a stable binding ability between the active components of AA and potential target genes. Among them, 24-methylenecyloartanone, beta-sitosterol, and Stigmasterol are active components with potential oral bioavailability (OB), drug-likeness (DL), and blood-brain-barrier(BBB) are screened out with the stable binding ability to target genes, which may be potential components of AA treatment for AD. This study laid an important foundation for further study of the molecular mechanism of AA treatment for AD.

Characterization of human umbilical cord blood-derived mast cells using high-throughput expression profiling and next-generation knowledge discovery platforms

Mast cells (MCs) are tissue-resident innate immune cells that express the high-affinity receptor for immunoglobulin E and are responsible for host defense and an array of diseases related to immune system. We aimed in this study to characterize the pathways and gene signatures of human cord blood-derived MCs (hCBMCs) in comparison to cells originating from CD34- progenitors using next-generation knowledge discovery methods. CD34+ cells were isolated from human umbilical cord blood using magnetic activated cell sorting and differentiated into MCs with rhIL-6 and rhSCF supplementation for 6-8 weeks. The purity of hCBMCs was analyzed by flow cytometry exhibiting the surface markers CD117+CD34-CD45-CD23-FcεR1αdim. Total RNA from hCBMCs and CD34- cells were isolated and hybridized using microarray. Differentially expressed genes were analyzed using iPathway Guide and Pre-Ranked Gene Set Enrichment Analysis. Next-generation knowledge discovery platforms revealed MC-specific gene signatures and molecular pathways enriched in hCBMCs and pertain the immunological response repertoire.

Exploration of potential molecular mechanisms and genotoxicity of anti-cancer drugs using next generation knowledge discovery methods

Background & Objectives

Accurate identification of molecular and toxicological functions of potential drug candidates is crucial for drug discovery and development. This may aid in the evaluation of the risks of genotoxicity and carcinogenesis. In addition, in silico characterization of existing and new drugs might offer clues for future investigations and aid in the development of anticancer treatments. Using next-generation knowledge discovery (NGKD) methodology, we endeavored to establish a risk assessment of anticancer drugs for their molecular mechanism(s) and genotoxicity.

Methods

This study was performed at the Faculty of Applied Medical Sciences, King Abdulaziz University (KAU), Jeddah, Saudi Arabia, in November 2022. Using innovative in silico model systems, we assessed the molecular mechanism of action and toxicity of around 20 distinct substances such as Deguelin, Etoposide, Camptothecin, Cytarabine (Ara-C), Cisplatin, Hydroxyurea, Trichostain A, Antimycin, Colchicine, 2-deoxyglucose, Tunicamycin, Thapsigargin, Vinblastin, Docetaxel, Oxaliplatin, Methotrexate, 5-flurouracil, Bleomycin, Taxol (Paclitaxel), and Apicidin. Using the Ingenuity Pathway Analysis (IPA) knowledge base, the number of targets for each compound was determined in silico. Subsequently, they were examined using Fisher's exact test and Benjamini Hochberg Multiple Testing Correction (P<0.05) and submitted to core analysis with IPA to decode the biological and toxicological activities differently controlled by these drugs. In addition, a multiple comparison module in IPA was used to compare the core analyses of each molecule. In addition, we obtained the top 100 protein targets of Etoposide, Camptothecin, and Ara-C using SwissTargetPrediction, as well as the key pathways and gene ontologies affected by these drugs and disease associations using the WebGestalt tool.

Results

We identified distinct toxicological signatures and canonical signaling pathways in tumor cell lines regulated by these 20 anticancer drugs. These signaling pathways included cell death and apoptosis in addition to molecular processes, p53 signaling, and aryl hydrocarbon receptor signaling. The TP53 signaling pathway is utilized by these agents to effectively trigger cell death and apoptosis, and p53 functions as a master regulator in a variety of cellular stress responses, including genotoxic stress.

Conclusion

Our research has laid the groundwork for the discovery of additional biomarkers that assess both the safety and effectiveness of treatment. Our mechanism based "NGKD" tools have more relevance for the identification of safer therapies and has the potential to lead to the rational screening of drug candidates targeting specific molecular networks and canonical pathways implicated in cancer and genotoxicity. In addition, the combination of protein, microRNA and metabolome profiles may be essential for the development of translatable biomarkers for the safety and efficacy of pharmacotherapeutic agents.Our research has laid the groundwork for the discovery of additional biomarkers that assess both the safety and the effectiveness of a treatment.

Role of the antineoplastic drug bleomycin based on toxicogenomic-DNA damage inducing (TGx-DDI) genomic biomarkers data: A meta-analysis

Objectives

Accurately identifying the cellular, biomolecular, and toxicological functions of anticancer drugs help to decipher the potential risk of genotoxicity and other side effects. Here, we examined bleomycin for cellular, molecular and toxicological mechanisms using next-generation knowledge discovery (NGKD) tools.

Methods

This study was conducted at the Faculty of Applied Medical Sciences, King Abdulaziz University (KAU), Jeddah, Saudi Arabia in October 2022. We first analyzed the raw Toxicogenomic and DNA damage-inducing (TGx-DDI) gene expression data from Gene Expression Omnibus (GEO) (GSE196373) of TK6 cells treated with 10 µM bleomycin and TK6 cells treated with DMSO for four hours using the GEO2R tool based on the Linear Models for Microarray Analysis (limma) R packages to derive the differentially expressed genes (DEGs). Then, iPathwayGuide was used to determine differentially regulated signaling pathways, biological processes, cellular, molecular functions and upstream regulators (genes and miRNAs).

Results

Bleomycin differently regulates the p53 pathway, transcriptional dysregulation in cancer, FOXO pathway, viral carcinogenesis, and cancer pathways. The biological processes such as p53 class mediator signaling, intrinsic apoptotic signaling, DNA damage response, and DNA damage-induced intrinsic apoptotic signaling and molecular functions like ubiquitin protein transferase and p53 binding were differentially regulated by bleomycin. iPathwayGuide analysis showed that the p53 and its regulatory gene and microRNA networks induced by bleomycin.

Conclusion

Analysis of TGx-DDI data of bleomycin using NGKD tools provided information about toxicogenomics and other mechanisms. Integration of all "omics" based approaches is crucial for the development of translatable biomarkers for evaluating anticancer drugs for safety and efficacy.

Deciphering SARS CoV-2-associated pathways from RNA sequencing data of COVID-19-infected A549 cells and potential therapeutics using in silico methods

BACKGROUND

Coronavirus (CoV) disease (COVID-19) identified in Wuhan, China, in 2019, is mainly characterized by atypical pneumonia and severe acute respiratory syndrome (SARS) and is caused by SARS CoV-2, which belongs to the Coronaviridae family. Determining the underlying disease mechanisms is central to the identification and development of COVID-19-specific drugs for effective treatment and prevention of human-to-human transmission, disease complications, and deaths.

METHODS

Here, next-generation RNA sequencing (RNA Seq) data were obtained using Illumina Next Seq 500 from SARS CoV-infected A549 cells and mock-treated A549 cells from the Gene Expression Omnibus (GEO) (GSE147507), and quality control (QC) was assessed before RNA Seq analysis using CLC Genomics Workbench 20.0. Differentially expressed genes (DEGs) were imported into BioJupies to decipher COVID-19 induced signaling pathways and small molecules derived from chemical synthesis or natural sources to mimic or reverse COVID -19 specific gene signatures. In addition, iPathwayGuide was used to identify COVID-19-specific signaling pathways, as well as drugs and natural products with anti-COVID-19 potential.

RESULTS

Here, we identified the potential activation of upstream regulators such as signal transducer and activator of transcription 2 (STAT2), interferon regulatory factor 9 (IRF9), and interferon beta (IFNβ), interleukin-1 beta (IL-1β), and interferon regulatory factor 3 (IRF3). COVID-19 infection activated key infectious disease-specific immune-related signaling pathways such as influenza A, viral protein interaction with cytokine and cytokine receptors, measles, Epstein-Barr virus infection, and IL-17 signaling pathway. Besides, we identified drugs such as prednisolone, methylprednisolone, diclofenac, compound JQ1, and natural products such as Withaferin-A and JinFuKang as candidates for further experimental validation of COVID-19 therapy.

CONCLUSIONS

In conclusion, we have used the in silico next-generation knowledge discovery (NGKD) methods to discover COVID-19-associated pathways and specific therapeutics that have the potential to ameliorate the disease pathologies associated with COVID-19.