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Life (Basel, Switzerland) Mar 2024We are exposed to a mixture of environmental man-made and natural xenobiotics. We experience a wide spectrum of environmental exposure in our lifetime, including the... (Review)
Review
We are exposed to a mixture of environmental man-made and natural xenobiotics. We experience a wide spectrum of environmental exposure in our lifetime, including the effects of xenobiotics on gametogenesis and gametes that undergo fertilization as the starting point of individual development and, moreover, in utero exposure, which can itself cause the first somatic or germline mutation necessary for breast cancer (BC) initiation. Most xenobiotics are metabolized or/and bioaccumulate and biomagnify in our tissues and cells, including breast tissues, so the xenobiotic metabolism plays an important role in BC initiation and progression. Many considerations necessitate a more valuable explanation regarding the molecular mechanisms of action of xenobiotics which act as genotoxic and epigenetic carcinogens. Thus, exposomics and the exposome concept are based on the diversity and range of exposures to physical factors, synthetic chemicals, dietary components, and psychosocial stressors, as well as their associated biologic processes and molecular pathways. Existing evidence for BC risk (BCR) suggests that food-borne chemical carcinogens, air pollution, ionizing radiation, and socioeconomic status are closely related to breast carcinogenesis. The aim of this review was to depict the dynamics and kinetics of several xenobiotics involved in BC development, emphasizing the role of new omics fields related to BC exposomics, such as environmental toxicogenomics, epigenomics and interactomics, metagenomics, nutrigenomics, nutriproteomics, and nutrimiRomics. We are mainly focused on food and nutrition, as well as endocrine-disrupting chemicals (EDCs), involved in BC development. Overall, cell and tissue accumulation and xenobiotic metabolism or biotransformation can lead to modifications in breast tissue composition and breast cell morphology, DNA damage and genomic instability, epimutations, RNA-mediated and extracellular vesicle effects, aberrant blood methylation, stimulation of epithelial-mesenchymal transition (EMT), disruption of cell-cell junctions, reorganization of the actin cytoskeleton, metabolic reprogramming, and overexpression of mesenchymal genes. Moreover, the metabolism of xenobiotics into BC cells impacts almost all known carcinogenic pathways. Conversely, in our food, there are many bioactive compounds with anti-cancer potential, exerting pro-apoptotic roles, inhibiting cell cycle progression and proliferation, migration, invasion, DNA damage, and cell stress conditions. We can conclude that exposomics has a high potential to demonstrate how environmental exposure to xenobiotics acts as a double-edged sword, promoting or suppressing tumorigenesis in BC.
PubMed: 38541726
DOI: 10.3390/life14030402 -
Biomedicine & Pharmacotherapy =... Jul 2023More information about a person's genetic makeup, drug response, multi-omics response, and genomic response is now available leading to a gradual shift towards... (Review)
Review
More information about a person's genetic makeup, drug response, multi-omics response, and genomic response is now available leading to a gradual shift towards personalized treatment. Additionally, the promotion of non-animal testing has fueled the computational toxicogenomics as a pivotal part of the next-gen risk assessment paradigm. Artificial Intelligence (AI) has the potential to provid new ways analyzing the patient data and making predictions about treatment outcomes or toxicity. As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. AI can process and integrate a multitude of data including genome data, patient records, clinical data and identify patterns to derive predictive models anticipating clinical outcomes and assessing the risk of any personalized medicine approaches. In this article, we have studied the current trends and future perspectives in personalized medicine & toxicology, the role of toxicogenomics in connecting the two fields, and the impact of AI on personalized medicine & toxicology. In this work, we also study the key challenges and limitations in personalized medicine, toxicogenomics, and AI in order to fully realize their potential.
Topics: Humans; Artificial Intelligence; Precision Medicine; Toxicogenetics; Algorithms; Technology
PubMed: 37121152
DOI: 10.1016/j.biopha.2023.114784 -
Biomedicines Sep 2023Neuropathic pain (NP) is a typical symptom of peripheral nerve disorders, including painful neuropathy. The biological mechanisms that control ion channels are important... (Review)
Review
Neuropathic pain (NP) is a typical symptom of peripheral nerve disorders, including painful neuropathy. The biological mechanisms that control ion channels are important for many cell activities and are also therapeutic targets. Disruption of the cellular mechanisms that govern ion channel activity can contribute to pain pathophysiology. The voltage-gated sodium channel (VGSC) is the most researched ion channel in terms of NP; however, VGSC impairment is detected in only <20% of painful neuropathy patients. Here, we discuss the potential role of the other peripheral ion channels involved in sensory signaling (transient receptor potential cation channels), neuronal excitation regulation (potassium channels), involuntary action potential generation (hyperpolarization-activated cyclic nucleotide-gated channels), thermal pain (anoctamins), pH modulation (acid sensing ion channels), and neurotransmitter release (calcium channels) related to pain and their prospective role as therapeutic targets for painful neuropathy.
PubMed: 37893054
DOI: 10.3390/biomedicines11102680 -
Advances in Clinical and Experimental... Aug 2023The majority of Americans, accounting for 51% of the population, take 2 or more drugs daily. Unfortunately, nearly 100,000 people die annually as a result of adverse...
The majority of Americans, accounting for 51% of the population, take 2 or more drugs daily. Unfortunately, nearly 100,000 people die annually as a result of adverse drug reactions (ADRs), making it the 4th most common cause of mortality in the USA. Drug-drug interactions (DDls) and their impact on patients represent critical challenges for the healthcare system. To reduce the incidence of ADRs, this study focuses on identifying DDls using a machine-learning approach. Drug-related information was obtained from various free databases, including DrugBank, BioGRID and Comparative Toxicogenomics Database. Eight similarity matrices between drugs were created as covariates in the model in order to assess their infiuence on DDls. Three distinct machine learning algorithms were considered, namely, logistic regression (LR), extreme Gradient Boosting (XGBoost) and neural network (NN). Our study examined 22 notable drugs and their interactions with 841 other drugs from DrugBank. The accuracy of the machine learning approaches ranged from 68% to 78%, while the F1 scores ranged from 78% to 83%. Our study indicates that enzyme and target similarity are the most significant parameters in identifying DDls. Finally, our data-driven approach reveals that machine learning methods can accurately predict DDls and provide additional insights in a timely and cost-effective manner.
Topics: Humans; Drug Interactions; Drug-Related Side Effects and Adverse Reactions; Algorithms; Databases, Factual; Machine Learning
PubMed: 37589227
DOI: 10.17219/acem/169852 -
European Journal of Medical Genetics Jun 2023Phelan-McDermid syndrome (PMS) is a 22q13.3 deletion syndrome that presents with a disturbed development, neurological and psychiatric characteristics, and sometimes... (Review)
Review
Phelan-McDermid syndrome (PMS) is a 22q13.3 deletion syndrome that presents with a disturbed development, neurological and psychiatric characteristics, and sometimes other comorbidities like seizures. The epilepsy manifests itself in a variety of seizure semiologies. Further diagnostics using electroencephalogram (EEG) and brain magnetic resonance imaging (MRI) are important in conjunction with the clinical picture of the seizures to decide whether anticonvulsant therapy is necessary. As part of the development of European consensus guidelines we focussed on the prevalence and semiology of epileptic seizures in PMS associated with a pathogenic variant in the SHANK3 gene or the 22q13 deletion involving SHANK3, in order to then be able to make recommendations regarding diagnosis and therapy.
Topics: Humans; Chromosome Disorders; Chromosome Deletion; Epilepsy; Seizures; Chromosomes, Human, Pair 22
PubMed: 36967043
DOI: 10.1016/j.ejmg.2023.104746 -
Frontiers in Toxicology 2023
PubMed: 37736263
DOI: 10.3389/ftox.2023.1284932 -
Scientific Reports Sep 2023To explore the clinical role of QPRT in breast cancer. The gene expression, methylation levels and prognostic value of QPRT in breast cancer was analyzed using TCGA... (Meta-Analysis)
Meta-Analysis
To explore the clinical role of QPRT in breast cancer. The gene expression, methylation levels and prognostic value of QPRT in breast cancer was analyzed using TCGA data. Validation was performed using the data from GEO dataset and TNMPLOT database. Meta analysis method was used to pool the survival data for QPRT. The predictive values of QPRT for different drugs were retrieved from the ROC plot. The expression differences of QPRT in acquired drug-resistant and sensitive cell lines were analyzed using GEO datasets. GO and KEGG enrichment analysis were conducted for those genes which were highly co-expressed with QPRT in tissue based on TCGA data and which changed after QPRT knockdown. Timer2.0 was utilized to explore the correlation between QPRT and immune cells infiltration, and the Human Protein Atlas was used to analyse QPRT's single-cell sequencing data across different human tissues. The expression of QPRT in different types of macrophages, and the expression of QPRT were analysed after coculturing HER2+ breast cancer cells with macrophages. Additionally, TargetScan, Comparative Toxicogenomics and the connectivity map were used to research miRNAs and drugs that could regulate QPRT expression. Cytoscape was used to map the interaction networks between QPRT and other proteins. QPRT was highly expressed in breast cancer tissue and highly expressed in HER2+ breast cancer patients (P < 0.01). High QPRT expression levels were associated with worse OS, DMFS, and RFS (P < 0.01). Two sites (cg02640602 and cg06453916) were found to be potential regulators of breast cancer (P < 0.01). QPRT might predict survival benefits in breast cancer patients who received taxane or anthracycline. QPRT was associated with tumour immunity, especially in macrophages. QPRT may influence the occurrence and progression of breast cancer through the PI3K-AKT signalling pathway, Wnt signalling pathway, and cell cycle-related molecules.
Topics: Female; Humans; Anthracyclines; Breast Neoplasms; MicroRNAs; Phosphatidylinositol 3-Kinases; Pentosyltransferases
PubMed: 37723185
DOI: 10.1038/s41598-023-42566-4 -
International Journal of Clinical and... 2023Osteoarthritis (OA) is a non-inflammatory degenerative joint disease that mainly involves articular cartilage damage and involves the whole joint tissue. However, the...
OBJECTIVE
Osteoarthritis (OA) is a non-inflammatory degenerative joint disease that mainly involves articular cartilage damage and involves the whole joint tissue. However, the relationship between CD14 and CSF1R and osteoarthritis remains unclear. The aim of this study was to explore the important role of CD14 and CSF1R in osteoarthritis and provide a new direction for its prevention and treatment.
METHOD
The osteoarthritis datasets GSE46750 and GSE82107 were downloaded from gene expression omnibus (GEO) database generated by GPL10558 and GPL570. R package limma was used to screen differentially expressed genes (DEDs). Weighted gene co-expression network analysis (WGCNA) was performed. The construction and analysis of a protein-protein interaction (PPI) network, functional enrichment analysis, gene set enrichment analysis (GSEA), and comparative toxicogenomics database (CTD) analysis were performed. TargetScan screened miRNAs that regulated central DEGs.
RESULTS
687 DEGs were identified. According to gene ontology (GO), they were mainly concentrated in inflammatory response, IL-17 signaling pathway, rheumatoid arthritis, exercise, and regulation of response to external stimuli. The enrichment items are similar to the GO Kyoto Encyclopedia of Gene and Genome (KEGG) enrichment items of DEGs. These were mainly concentrated in exercise, inflammatory response, defense response, collagen containing extracellular matrix, and receptor regulator activity. In an enrichment project of Metascape, GO had inflammatory response, SARS-CoV-2 signal pathway network map, PIDIL8CXCR1 pathway, regulation of bone remodeling and endochondral ossification. 20 core genes were obtained by PPI network construction and analysis. Gene expression heat map showed that core genes (C1QC, CSF1R, CD14, TYROBP, HLA-DRA, C1QB, FCER1G, S100A9, HCLS1, WAS, BTK, TREM1) were highly expressed in osteoarthritis synovial tissues and were low in normal synovial tissues. CTD analysis showed that twelve genes (C1QC, CSF1R, CD14, TYROBP, HLA-DRA, C1QB, FCER1G, S100A9, HCLS1, WAS, BTK, TREM1) were found to be associated with inflammation, necrosis, gout, acute myeloid leukemia and thrombocytopenia.
CONCLUSION
CD14 and CSF1R are highly expressed in osteoarthritis and may be therapeutic targets for osteoarthritis.
PubMed: 37693684
DOI: No ID Found -
IScience Feb 2024Pancreatic cancer is a severe malignancy with increasing incidence and high mortality due to late diagnosis and low sensitivity to treatments. Search for the most...
Pancreatic cancer is a severe malignancy with increasing incidence and high mortality due to late diagnosis and low sensitivity to treatments. Search for the most appropriate drugs and therapeutic regimens is the most promising way to improve the treatment outcomes of the patients. This study aimed to compare (1) efficacy and (2) antitumor effects of conventional paclitaxel and the newly synthesized second (SB-T-1216) and third (SB-T-121605 and SB-T-121606) generation taxanes in wild type BxPC-3 and more aggressive G12V mutated Paca-44 pancreatic cancer cell line models. , paclitaxel efficacy was 27.6 ± 1.7 nM, while SB-Ts showed 1.7-7.4 times higher efficacy. Incorporation of SB-T-121605 and SB-T-121606 into therapeutic regimens containing paclitaxel was effective in suppressing tumor growth in Paca-44 tumor-bearing mice at small doses (≤3 mg/kg). SB-T-121605 and SB-T-121606 in combination with paclitaxel are promising candidates for the next phase of preclinical testing.
PubMed: 38357661
DOI: 10.1016/j.isci.2024.109044 -
Medicine Oct 2023Osteoarthritis (OA) is a non-inflammatory degenerative joint disease that mainly involves articular cartilage damage and involves the whole joint tissue. Gastritis is a...
Osteoarthritis (OA) is a non-inflammatory degenerative joint disease that mainly involves articular cartilage damage and involves the whole joint tissue. Gastritis is a common stomach disorder, typically referring to inflammation or lesions of the gastric mucosa. However, the relationship between CD14 and colony stimulating factor-1 receptor (CSF1R) and these 2 diseases is not yet clear. OA datasets GSE46750, GSE82107 and gastritis datasets GSE54043 profiles were downloaded from gene expression omnibus databases generated by GPL10558 and GPL570.The R package limma was used to screen differentially expressed genes (DEGs). Weighted gene co-expression network analysis was performed. The construction and analysis of protein-protein interaction network, functional enrichment analysis, gene set enrichment analysis and comparative toxicogenomics database analysis were performed. TargetScan was used to screen miRNAs regulating central DEGs. A total of 568 DEGs were identified. According to the gene ontology (GO) and biological processes analysis, they were mainly enriched in ATP metabolism negative regulation, toll-like receptor TLR1:TLR2 signaling pathway, and intracellular transport. The enrichment terms for OA and gastritis were similar to the GO and Kyoto encyclopedia of gene and genome enrichment terms of DEGs, mainly enriched in ATP metabolism negative regulation, secretion granules, transmembrane receptor protein kinase activity, cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, MAPK signaling pathway, and TGF-β signaling pathway. In the Metascape enrichment projects, GO enrichment projects showed functions related to cell-cell receptor interaction, cell secretion, and growth. Two core genes were identified through the construction and analysis of the protein-protein interaction network. The core genes (CD14 and CSF1R) exhibited high expression in OA and gastritis samples and low expression in normal samples. Comparative toxicogenomics database analysis revealed associations between core genes (CD14 and CSF1R) and diseases such as OA, osteoporosis, gastritis, juvenile arthritis, diarrhea, and inflammation. CD14 and CSF1R are highly expressed in OA and gastritis, making them potential therapeutic targets for both diseases.
Topics: Humans; Adenosine Triphosphate; Computational Biology; Databases, Genetic; Gastritis; Gene Expression Profiling; Gene Regulatory Networks; Inflammation; Osteoarthritis; Receptor Protein-Tyrosine Kinases; Toll-Like Receptors; Lipopolysaccharide Receptors
PubMed: 37904379
DOI: 10.1097/MD.0000000000035567