-
Toxics May 2024Cadmium (Cd), a prevalent environmental contaminant, exerts widespread toxic effects on human health through various biochemical and molecular mechanisms. This review... (Review)
Review
Cadmium (Cd), a prevalent environmental contaminant, exerts widespread toxic effects on human health through various biochemical and molecular mechanisms. This review encapsulates the primary pathways through which Cd inflicts damage, including oxidative stress induction, disruption of Ca signaling, interference with cellular signaling pathways, and epigenetic modifications. By detailing the absorption, distribution, metabolism, and excretion (ADME) of Cd, alongside its interactions with cellular components such as mitochondria and DNA, this paper highlights the extensive damage caused by Cd at the cellular and tissue levels. The role of Cd in inducing oxidative stress-a pivotal mechanism behind its toxicity-is discussed with emphasis on how it disrupts the balance between oxidants and antioxidants, leading to cellular damage and apoptosis. Additionally, the review covers Cd's impact on signaling pathways like Mitogen-Activated Protein Kinase (MAPK), Nuclear Factor kappa-light-chain-enhancer of activated B cells (NF-κB), and Tumor Protein 53 (p53) pathways, illustrating how its interference with these pathways contributes to pathological conditions and carcinogenesis. The epigenetic effects of Cd, including DNA methylation and histone modifications, are also explored to explain its long-term impact on gene expression and disease manifestation. This comprehensive analysis not only elucidates the mechanisms of Cd toxicity but also underscores the critical need for enhanced strategies to mitigate its public health implications.
PubMed: 38922068
DOI: 10.3390/toxics12060388 -
Cells Jun 2024Neuroplasticity in the amygdala and its central nucleus (CeA) is linked to pain modulation and pain behaviors, but cellular mechanisms are not well understood. Here, we...
Dysfunction of Small-Conductance Ca-Activated Potassium (SK) Channels Drives Amygdala Hyperexcitability and Neuropathic Pain Behaviors: Involvement of Epigenetic Mechanisms.
Neuroplasticity in the amygdala and its central nucleus (CeA) is linked to pain modulation and pain behaviors, but cellular mechanisms are not well understood. Here, we addressed the role of small-conductance Ca-activated potassium (SK) channels in pain-related amygdala plasticity. The facilitatory effects of the intra-CeA application of an SK channel blocker (apamin) on the pain behaviors of control rats were lost in a neuropathic pain model, whereas an SK channel activator (NS309) inhibited pain behaviors in neuropathic rats but not in sham controls, suggesting the loss of the inhibitory behavioral effects of amygdala SK channels. Brain slice electrophysiology found hyperexcitability of CeA neurons in the neuropathic pain condition due to the loss of SK channel-mediated medium afterhyperpolarization (mAHP), which was accompanied by decreased SK2 channel protein and mRNA expression, consistent with a pretranscriptional mechanisms. The underlying mechanisms involved the epigenetic silencing of the SK2 gene due to the increased DNA methylation of the CpG island of the SK2 promoter region and the change in methylated CpG sites in the CeA in neuropathic pain. This study identified the epigenetic dysregulation of SK channels in the amygdala (CeA) as a novel mechanism of neuropathic pain-related plasticity and behavior that could be targeted to control abnormally enhanced amygdala activity and chronic neuropathic pain.
Topics: Animals; Male; Rats; Amygdala; Behavior, Animal; DNA Methylation; Epigenesis, Genetic; Neuralgia; Neurons; Rats, Sprague-Dawley; Small-Conductance Calcium-Activated Potassium Channels
PubMed: 38920682
DOI: 10.3390/cells13121055 -
Cells Jun 2024Hepatocellular carcinoma (HCC) development is associated with altered modifications in DNA methylation, changing transcriptional regulation. Emerging evidence indicates...
Hepatocellular carcinoma (HCC) development is associated with altered modifications in DNA methylation, changing transcriptional regulation. Emerging evidence indicates that DNA methyltransferase 1 (DNMT1) plays a key role in the carcinogenesis process. This study aimed to investigate how pirfenidone (PFD) modifies this pathway and the effect generated by the association between c-Myc expression and DNMT1 activation. Rats F344 were used for HCC development using 50 mg/kg of diethylnitrosamine (DEN) and 25 mg/kg of 2-Acetylaminofluorene (2-AAF). The HCC/PFD group received simultaneous doses of 300 mg/kg of PFD. All treatments lasted 12 weeks. On the other hand, HepG2 cells were used to evaluate the effects of PFD in restoring DNA methylation in the presence of the inhibitor 5-Aza. Histopathological, biochemical, immunohistochemical, and western blot analysis were carried out and our findings showed that PFD treatment reduced the amount and size of tumors along with decreased Glipican-3, β-catenin, and c-Myc expression in nuclear fractions. Also, this treatment improved lipid metabolism by modulating PPARγ and SREBP1 signaling. Interestingly, PFD augmented DNMT1 and DNMT3a protein expression, which restores global methylation, both in our in vivo and in vitro models. In conclusion, our results suggest that PFD could slow down HCC development by controlling DNA methylation.
Topics: Animals; DNA (Cytosine-5-)-Methyltransferase 1; DNA Methylation; Pyridones; Rats; Carcinoma, Hepatocellular; Humans; Hep G2 Cells; Proliferating Cell Nuclear Antigen; Male; Rats, Inbred F344; Liver Neoplasms; Gene Expression Regulation, Neoplastic; Diethylnitrosamine; Liver Neoplasms, Experimental
PubMed: 38920644
DOI: 10.3390/cells13121013 -
Cells Jun 2024Non-coding RNAs (ncRNAs) have emerged as pivotal regulators in cellular biology, dispelling their former perception as 'junk transcripts'. Notably, the DLK1-DIO3 region...
Non-coding RNAs (ncRNAs) have emerged as pivotal regulators in cellular biology, dispelling their former perception as 'junk transcripts'. Notably, the DLK1-DIO3 region harbors numerous ncRNAs, including long non-coding RNAs (lncRNAs) and over 50 microRNA genes. While papillary thyroid cancer showcases a pervasive decrease in DLK1-DIO3-derived ncRNA expression, the precise mechanisms driving this alteration remain elusive. We hypothesized that epigenetic alterations underlie shifts in ncRNA expression during thyroid cancer initiation and progression. This study aimed to elucidate the epigenetic mechanisms governing DLK1-DIO3 region expression in this malignancy. We have combined the analysis of DNA methylation by bisulfite sequencing together with that of histone modifications through ChIP-qPCR to gain insights into the epigenetic contribution to thyroid cancer in cell lines representing malignancies with different genetic backgrounds. Our findings characterize the region's epigenetic signature in thyroid cancer, uncovering distinctive DNA methylation patterns, particularly within CpG islands on the lncRNA MEG3-DMR, which potentially account for its downregulation in tumors. Pharmacological intervention targeting DNA methylation combined with histone deacetylation restored ncRNA expression. These results contribute to the understanding of the epigenetic mechanisms controlling the DLK1-DIO3 region in thyroid cancer, highlighting the combined role of DNA methylation and histone marks in regulating the locus' expression.
Topics: Humans; Epigenesis, Genetic; DNA Methylation; Thyroid Neoplasms; Gene Expression Regulation, Neoplastic; Cell Line, Tumor; Calcium-Binding Proteins; Iodide Peroxidase; RNA, Long Noncoding; CpG Islands; Intercellular Signaling Peptides and Proteins; Histones; Membrane Proteins
PubMed: 38920632
DOI: 10.3390/cells13121001 -
Epigenomes Jun 2024The post-genomic era has ushered in the extensive application of epigenetic editing tools, allowing for precise alterations of gene expression. The use of reprogrammable...
The post-genomic era has ushered in the extensive application of epigenetic editing tools, allowing for precise alterations of gene expression. The use of reprogrammable editors that carry transcriptional corepressors has significant potential for long-term epigenetic silencing for the treatment of human diseases. The ideal scenario involves precise targeting of a specific genomic location by a DNA-binding domain, ensuring there are no off-target effects and that the process yields no genetic remnants aside from specific epigenetic modifications (i.e., DNA methylation). A notable example is a recent study on the mouse gene, crucial for cholesterol regulation and expressed in hepatocytes, which identified synthetic zinc-finger (ZF) proteins as the most effective DNA-binding editors for silencing efficiently, specifically, and persistently. This discussion focuses on enhancing the specificity of ZF-array DNA binding by optimizing interactions between specific amino acids and DNA bases across three promoters containing CpG islands.
PubMed: 38920624
DOI: 10.3390/epigenomes8020023 -
Frontiers in Immunology 2024The global impact of the SARS-CoV-2 pandemic has been unprecedented, posing a significant public health challenge. Chronological age has been identified as a key... (Review)
Review
The global impact of the SARS-CoV-2 pandemic has been unprecedented, posing a significant public health challenge. Chronological age has been identified as a key determinant for severe outcomes associated with SARS-CoV-2 infection. Epigenetic age acceleration has previously been observed in various diseases including human immunodeficiency virus (HIV), Cytomegalovirus (CMV), cardiovascular diseases, and cancer. However, a comprehensive review of this topic is still missing in the field. In this review, we explore and summarize the research work focusing on biological aging markers, i.e., epigenetic age and telomere attrition in COVID-19 patients. From the reviewed articles, we identified a consistent pattern of epigenetic age dysregulation and shortened telomere length, revealing the impact of COVID-19 on epigenetic aging and telomere attrition.
Topics: Humans; COVID-19; Aging; SARS-CoV-2; Epigenesis, Genetic; Telomere; Telomere Shortening
PubMed: 38919619
DOI: 10.3389/fimmu.2024.1399676 -
Biology Direct Jun 2024Prostate cancer (PCa) is the second leading cause of tumor-related mortality in men. Metastasis from advanced tumors is the primary cause of death among patients....
BACKGROUND
Prostate cancer (PCa) is the second leading cause of tumor-related mortality in men. Metastasis from advanced tumors is the primary cause of death among patients. Identifying novel and effective biomarkers is essential for understanding the mechanisms of metastasis in PCa patients and developing successful interventions.
METHODS
Using the GSE8511 and GSE27616 data sets, 21 metastasis-related genes were identified through the weighted gene co-expression network analysis (WGCNA) method. Subsequent functional analysis of these genes was conducted on the gene set cancer analysis (GSCA) website. Cluster analysis was utilized to explore the relationship between these genes, immune infiltration in PCa, and the efficacy of targeted drug IC50 scores. Machine learning algorithms were then employed to construct diagnostic and prognostic models, assessing their predictive accuracy. Additionally, multivariate COX regression analysis highlighted the significant role of POLD1 and examined its association with DNA methylation. Finally, molecular docking and immunohistochemistry experiments were carried out to assess the binding affinity of POLD1 to PCa drugs and its impact on PCa prognosis.
RESULTS
The study identified 21 metastasis-related genes using the WGCNA method, which were found to be associated with DNA damage, hormone AR activation, and inhibition of the RTK pathway. Cluster analysis confirmed a significant correlation between these genes and PCa metastasis, particularly in the context of immunotherapy and targeted therapy drugs. A diagnostic model combining multiple machine learning algorithms showed strong predictive capabilities for PCa diagnosis, while a transfer model using the LASSO algorithm also yielded promising results. POLD1 emerged as a key prognostic gene among the metastatic genes, showing associations with DNA methylation. Molecular docking experiments supported its high affinity with PCa-targeted drugs. Immunohistochemistry experiments further validated that increased POLD1 expression is linked to poor prognosis in PCa patients.
CONCLUSIONS
The developed diagnostic and metastasis models provide substantial value for patients with prostate cancer. The discovery of POLD1 as a novel biomarker related to prostate cancer metastasis offers a promising avenue for enhancing treatment of prostate cancer metastasis.
Topics: Humans; Male; Prostatic Neoplasms; Machine Learning; Immunotherapy; Neoplasm Metastasis; Biomarkers, Tumor; Prognosis; Molecular Docking Simulation; Gene Expression Regulation, Neoplastic
PubMed: 38918844
DOI: 10.1186/s13062-024-00494-x -
Scientific Reports Jun 2024The benefits of breastfeeding for the health and wellbeing of both infants and mothers are well documented, yet global breastfeeding rates are low. One factor associated...
The benefits of breastfeeding for the health and wellbeing of both infants and mothers are well documented, yet global breastfeeding rates are low. One factor associated with low breast feeding is maternal body mass index (BMI), which is used as a measure of obesity. The negative relationship between maternal obesity and breastfeeding is likely caused by a variety of social, psychological, and physiological factors. Maternal obesity may also have a direct biological association with breastfeeding through changes in maternal DNA methylation. Here, we investigate this potential biological association using data from a UK-based cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC). We find that pre-pregnancy body mass index (BMI) is associated with lower initiation to breastfeed and shorter breastfeeding duration. We conduct epigenome-wide association studies (EWAS) of pre-pregnancy BMI and breastfeeding outcomes, and run candidate-gene analysis of methylation sites associated with BMI identified via previous meta-EWAS. We find that DNA methylation at cg11453712, annotated to PHTP1, is associated with pre-pregnancy BMI. From our results, neither this association nor those at candidate-gene sites are likely to mediate the link between pre-pregnancy BMI and breastfeeding.
Topics: Humans; DNA Methylation; Breast Feeding; Body Mass Index; Female; Pregnancy; Adult; Longitudinal Studies; Genome-Wide Association Study; United Kingdom; Obesity; Epigenesis, Genetic
PubMed: 38918574
DOI: 10.1038/s41598-024-65605-0 -
Scientific Reports Jun 2024PTBP1 is an oncogene that regulates the splicing of precursor mRNA. However, the relationship between PTBP1 expression and gene methylation, cancer prognosis, and tumor...
PTBP1 is an oncogene that regulates the splicing of precursor mRNA. However, the relationship between PTBP1 expression and gene methylation, cancer prognosis, and tumor microenvironment remains unclear. The expression profiles of PTBP1 across various cancers were derived from the TCGA, as well as the GTEx and CGGA databases. The CGGA mRNA_325, CGGA mRNA_301, and CGGA mRNA_693 datasets were utilized as validation cohorts. Immune cell infiltration scores were approximated using the TIMER 2.0 tool. Functional enrichment analysis for groups with high and low PTBP1 expression was conducted using Gene Set Enrichment Analysis (GSEA). Methylation data were predominantly sourced from the SMART and Mexpress databases. Linked-omics analysis was employed to perform functional enrichment analysis of genes related to PTBP1 methylation, as well as to conduct protein functional enrichment analysis. Single-cell transcriptome analysis and spatial transcriptome analysis were carried out using Seurat version 4.10. Compared to normal tissues, PTBP1 is significantly overexpressed and hypomethylated in various cancers. It is implicated in prognosis, immune cell infiltration, immune checkpoint expression, genomic variation, tumor neoantigen load, and tumor mutational burden across a spectrum of cancers, with particularly notable effects in low-grade gliomas. In the context of gliomas, PTBP1 expression correlates with WHO grade and IDH1 mutation status. PTBP1 expression and methylation play an important role in a variety of cancers. PTBP1 can be used as a marker of inflammation, progression and prognosis in gliomas.
Topics: Humans; Polypyrimidine Tract-Binding Protein; Heterogeneous-Nuclear Ribonucleoproteins; Prognosis; Biomarkers, Tumor; Glioma; Gene Expression Regulation, Neoplastic; Tumor Microenvironment; DNA Methylation; Gene Expression Profiling; Inflammation; Transcriptome; Brain Neoplasms; Disease Progression; Multiomics
PubMed: 38918441
DOI: 10.1038/s41598-024-64979-5 -
Scientific Reports Jun 2024Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the...
Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the mechanisms behind this defect are insufficiently characterized. Integrating multiple layers of biomedical information, such as different Omics, may allow more accurate understanding of complex diseases such as T2D. Our aim was to explore and use Machine Learning to integrate multiple sources of biological/molecular information (multiOmics), in our case RNA-sequening, DNA methylation, SNP and phenotypic data from islet donors with T2D and non-diabetic controls. We exploited Machine Learning to perform multiOmics integration of DNA methylation, expression, SNPs, and phenotypes from pancreatic islets of 110 individuals, with ~ 30% being T2D cases. DNA methylation was analyzed using Infinium MethylationEPIC array, expression was analyzed using RNA-sequencing, and SNPs were analyzed using HumanOmniExpress arrays. Supervised linear multiOmics integration via DIABLO based on Partial Least Squares (PLS) achieved an accuracy of 91 ± 15% of T2D prediction with an area under the curve of 0.96 ± 0.08 on the test dataset after cross-validation. Biomarkers identified by this multiOmics integration, including SACS and TXNIP DNA methylation, OPRD1 and RHOT1 expression and a SNP annotated to ANO1, provide novel insights into the interplay between different biological mechanisms contributing to T2D. This Machine Learning approach of multiOmics cross-sectional data from human pancreatic islets achieved a promising accuracy of T2D prediction, which may potentially find broad applications in clinical diagnostics. In addition, it delivered novel candidate biomarkers for T2D and links between them across the different Omics.
Topics: Humans; Diabetes Mellitus, Type 2; Machine Learning; DNA Methylation; Islets of Langerhans; Polymorphism, Single Nucleotide; Male; Female; Middle Aged; Biomarkers; Adult; Aged
PubMed: 38918439
DOI: 10.1038/s41598-024-64846-3