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Turkish Journal of Medical Sciences 2023Cysteine and glycine-rich protein 1 (CSRP1) is involved in the cysteine-rich protein family and is a marker of smooth muscle lineages. In colon cancer, the expression of...
BACKGROUND/AIM
Cysteine and glycine-rich protein 1 (CSRP1) is involved in the cysteine-rich protein family and is a marker of smooth muscle lineages. In colon cancer, the expression of this gene is associated with poor prognosis. In this study, the aim was to reevaluate its prognostic relationship in independent cohorts and explore potential underlying biological processes that are linked to aggressive behavior in tumors with high CSRP1 expression, such as epithelial-to-mesenchymal transition (EMT), stromal fractions in the tumor microenvironment, and consensus molecular subtypes (CMSs).
MATERIALS AND METHODS
RNA sequencing (RNAseq)-, microarray-, and single-cell RNAseq (scRNAseq)-based transcriptomic data were obtained from public databases. The EMT score was calculated based on the expression of E-cadherin and vimentin genes using a previously published method. The stromal score generated by the ESTIMATE method was utilized for the analysis of correlation with the CSRP1 expression. The scRNAseq data were analyzed via the Seurat R package. The immunohistochemistry-based protein level expression of CSRP1 was evaluated using the Human Protein Atlas database.
RESULTS
Lower CSRP1 expression was noted in colon tumors compared to normal colon tissue. Patients with a high CSRP1 expression had shorter recurrence-free, overall, and disease-specific survivals in the GSE39582 and GSE17536 datasets (p < 0.05). The methylation level of the CSRP1 gene was negatively correlated (r = -0.57, p < 0.0001) with CSRP1 expression in The Cancer Genome Atlas colon adenocarcinoma dataset. CSRP1 expression was positively correlated with the expression of mesenchymal markers, EMT score, and stromal score obtained via the ESTIMATE method. CMS4 colon tumors had a significantly higher CSRP1 expression compared to other CMSs. Analysis of the scRNAseq data revealed that CSRP1 was expressed by epithelial cells and cancer-associated fibroblasts in the colorectal tumor microenvironment, which was also confirmed by the protein expression data from the Human Protein Atlas database.
CONCLUSION
CSRP1 expression is associated with CMS4, a more mesenchymal stroma-rich molecular profile, and poor prognosis in colon cancer.
Topics: Humans; Colonic Neoplasms; Prognosis; Epithelial-Mesenchymal Transition; Male; Biomarkers, Tumor; Female; Tumor Microenvironment; Middle Aged; Repressor Proteins; Aged
PubMed: 38813484
DOI: 10.55730/1300-0144.5736 -
International Journal of General... 2024The role of aldehyde dehydrogenase 2 (ALDH2) in cardiovascular diseases has been gradually studied. However, it is unclear whether polymorphism is associated with the...
BACKGROUND
The role of aldehyde dehydrogenase 2 (ALDH2) in cardiovascular diseases has been gradually studied. However, it is unclear whether polymorphism is associated with the risk of early onset (onset age ≤55 years old in men and ≤65 years old in women) coronary artery stenosis (CAS). The association between single nucleotide polymorphism (SNP) rs671 and risk in patients with early onset CAS was investigated in this study.
METHODS
The study included 213 early onset CAS patients and 352 individuals without CAS were set as controls. The rs671 polymorphism was genotyped by polymerase chain reaction (PCR) - microarray. Differences in rs671 genotypes and alleles between patients and controls were compared. Multiple logistic regression analysis was performed after adjusting for gender, body mass index (BMI), smoking history, drinking history, and diabetes mellitus to assess the relationship between rs671 genotypes and early onset CAS risk.
RESULTS
The frequency of the rs671 G/G genotype was lower in the early onset CAS patients (43.7% vs 55.3%, =0.007) than that in the controls. The frequency of the rs671 A allele was higher (32.9% vs 25.0%) than that in the controls (=0.005). After adjusting for other confounding factors, multivariate logistic regression showed that rs671 A/A genotype (A/A vs G/G: odds ratio (OR) 2.508, 95% confidence interval (CI): 1.130-5.569, =0.024), overweight (BMI≥24.0 vs 18.5-23.9: OR 5.047, 95% CI: 3.275-7.777, <0.001), history of smoking (yes vs no: OR 2.813, 95% CI: 1.595-4.961, <0.001), and diabetes mellitus (yes vs no: OR 2.191, 95% CI: 1.397-3.437, =0.001) were the independent risk factors of early onset CAS.
CONCLUSION
In men ≤55 years old and women ≤65 years old, individuals with rs671 A/A genotype, overweight (BMI ≥24.0 kg/m), smoking history, and diabetes mellitus increased risk of developing CAS.
PubMed: 38813240
DOI: 10.2147/IJGM.S461004 -
PloS One 2024The association between Alzheimer's disease and metabolic disorders as significant risk factors is widely acknowledged. However, the intricate molecular mechanism...
The association between Alzheimer's disease and metabolic disorders as significant risk factors is widely acknowledged. However, the intricate molecular mechanism intertwining these conditions remains elusive. To address this knowledge gap, we conducted a thorough investigation using a bioinformatics method to illuminate the molecular connections and pathways that provide novel perspectives on these disorders' pathological and clinical features. Microarray datasets (GSE5281, GSE122063) from the Gene Expression Omnibus (GEO) database facilitated the way to identify genes with differential expression in Alzheimer's disease (141 genes). Leveraging CoreMine, CTD, and Gene Card databases, we extracted genes associated with metabolic conditions, including hypertension, non-alcoholic fatty liver disease, and diabetes. Subsequent analysis uncovered overlapping genes implicated in metabolic conditions and Alzheimer's disease, revealing shared molecular links. We utilized String and HIPPIE databases to visualize these shared genes' protein-protein interactions (PPI) and constructed a PPI network using Cytoscape and MCODE plugin. SPP1, CD44, IGF1, and FLT1 were identified as crucial molecules in the main cluster of Alzheimer's disease and metabolic syndrome. Enrichment analysis by the DAVID dataset was employed and highlighted the SPP1 as a novel target, with its receptor CD44 playing a significant role in the inflammatory cascade and disruption of insulin signaling, contributing to the neurodegenerative aspects of Alzheimer's disease. ECM-receptor interactions, focal adhesion, and the PI3K/Akt pathways may all mediate these effects. Additionally, we investigated potential medications by repurposing the molecular links using the DGIdb database, revealing Tacrolimus and Calcitonin as promising candidates, particularly since they possess binding sites on the SPP1 molecule. In conclusion, our study unveils crucial molecular bridges between metabolic syndrome and AD, providing insights into their pathophysiology for therapeutic interventions.
Topics: Alzheimer Disease; Humans; Metabolic Syndrome; Drug Repositioning; Protein Interaction Maps; Systems Biology; Gene Regulatory Networks; Computational Biology; Signal Transduction; Databases, Genetic; Gene Expression Profiling
PubMed: 38809924
DOI: 10.1371/journal.pone.0304410 -
The Importance of Nutrigenetics and Microbiota in Personalized Medicine: From Phenotype to Genotype.Cureus May 2024Background After the completion of the Human Genome Project in 2003, the impact of genetic variations among people on human health was better understood. Precision...
Background After the completion of the Human Genome Project in 2003, the impact of genetic variations among people on human health was better understood. Precision medicine, also called 4P (Predictive, Preventive, Personalized, Participatory) medicine, is used to determine personal health risks, prevent, diagnose, and treat chronic diseases, and aims to identify the phenotypic, genotypic, and environmental factors that affect individual health risks instead of applying the same approach to everyone. Methods The study was conducted with 24 patients aged between 7 and 57. The patient group was selected from individuals who had undergone genetic and microbiota testing at Epigenetic Coaching Company. The patients' age, gender, and health status were documented. Genomic analysis of buccal samples was subsequently conducted using a custom Infinium HTS iSelect microarray on an Illumina iScan instrument, and microbiota metagenome analysis was performed using an Illumina NextSeq 500 platform. This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Biruni University Molecular Biology and Genetics Ethics Committee, with the decision number 2023/78-03. Results The genotypes of 19 cases carrying genetic variants involved in the metabolism of Vitamin D, Folate, B12, and Choline were analyzed. Eight of the cases were included in our study as autism patients, eight as allergy patients, and three as autoimmune thyroiditis patients. The Vitamin D receptor (VDR) genetic variants and microbiota diversity (using the Firmicutes/Bacteroides ratio, an indicator of dysbiosis) of 11 cases (9 allergy and two autism patients) participating in the study were evaluated together. Conclusions Translating nutrigenetic and nutrigenomic research into multidisciplinary clinical practice is the most challenging aspect. It is now evident that integrating data regarding phenotype and genotype, and using nutrition, lifestyle, and supplements tailored to an individual's genetics can increase clinical success. Importantly, if we wish to adopt an epigenomic approach, we must incorporate analyses of nutrigenetics, microbiota, and personalized risk based on test results.
PubMed: 38807972
DOI: 10.7759/cureus.61256 -
Biotechnology For Biofuels and... May 2024Aspergillus tubingensis is a citric acid-producing fungus that can utilize sugars in hydrolysate of lignocellulosic biomass such as sugarcane bagasse and, unlike A....
BACKGROUND
Aspergillus tubingensis is a citric acid-producing fungus that can utilize sugars in hydrolysate of lignocellulosic biomass such as sugarcane bagasse and, unlike A. niger, does not produce mycotoxins. To date, no attempt has been made to model its metabolism at genome scale.
RESULTS
Here, we utilized the whole-genome sequence (34.96 Mb length) and the measured biomass composition to reconstruct a genome-scale metabolic model (GSMM) of A. tubingensis DJU120 strain. The model, named iMK1652, consists of 1652 genes, 1657 metabolites and 2039 reactions distributed over four cellular compartments. The model has been extensively curated manually. This included removal of dead-end metabolites and generic reactions, addition of secondary metabolite pathways and several transporters. Several mycotoxin synthesis pathways were either absent or incomplete in the genome, providing a genomic basis for the non-toxinogenic nature of this species. The model was further refined based on the experimental phenotypic microarray (Biolog) data. The model closely captured DJU120 fermentative data on glucose, xylose, and phosphate consumption, as well as citric acid and biomass production, showing its applicability to capture citric acid fermentation of lignocellulosic biomass hydrolysate.
CONCLUSIONS
The model offers a framework to conduct metabolic systems biology investigations and can act as a scaffold for integrative modelling of A. tubingensis.
PubMed: 38807234
DOI: 10.1186/s13068-024-02506-4 -
Database : the Journal of Biological... May 2024In the field of complex autoimmune diseases such as systemic lupus erythematosus (SLE), systems immunology approaches have proven invaluable in translational research...
In the field of complex autoimmune diseases such as systemic lupus erythematosus (SLE), systems immunology approaches have proven invaluable in translational research settings. Large-scale datasets of transcriptome profiling have been collected and made available to the research community in public repositories, but remain poorly accessible and usable by mainstream researchers. Enabling tools and technologies facilitating investigators' interaction with large-scale datasets such as user-friendly web applications could promote data reuse and foster knowledge discovery. Microarray blood transcriptomic data from the LUPUCE cohort (publicly available on Gene Expression Omnibus, GSE49454), which comprised 157 samples from 62 adult SLE patients, were analyzed with the third-generation (BloodGen3) module repertoire framework, which comprises modules and module aggregates. These well-characterized samples corresponded to different levels of disease activity, different types of flares (including biopsy-proven lupus nephritis), different auto-antibody profiles and different levels of interferon signatures. A web application was deployed to present the aggregate-level, module-level and gene-level analysis results from LUPUCE dataset. Users can explore the similarities and heterogeneity of SLE samples, navigate through different levels of analysis, test hypotheses and generate custom fingerprint grids and heatmaps, which may be used in reports or manuscripts. This resource is available via this link: https://immunology-research.shinyapps.io/LUPUCE/. This web application can be employed as a stand-alone resource to explore changes in blood transcript profiles in SLE, and their relation to clinical and immunological parameters, to generate new research hypotheses.
Topics: Lupus Erythematosus, Systemic; Humans; Transcriptome; Internet; Databases, Genetic; Gene Expression Profiling; Software
PubMed: 38805754
DOI: 10.1093/database/baae045 -
Heliyon May 2024Esophageal adenocarcinoma (EAC) is a common cancer with a poor prognosis in advanced stages. Therefore, early EAC diagnosis and treatment have gained attention in recent...
BACKGROUND
Esophageal adenocarcinoma (EAC) is a common cancer with a poor prognosis in advanced stages. Therefore, early EAC diagnosis and treatment have gained attention in recent decades. It has been found that various pathological changes, particularly Barrett's Esophagus (BE), can occur in the esophageal tissue before the development of EAC. In this study, we aimed to identify the molecular contributor in BE to EAC progression by detecting the essential regulatory genes that are differentially expressed in both BE and EAC.
MATERIALS AND METHODS
We conducted a comprehensive bioinformatics analysis to detect BE and EAC-associated genes. The common differentially expressed genes (DEGs) and common single nucleotide polymorphisms (SNPs) were detected using the GEO and DisGeNET databases, respectively. Then, hub genes and the top modules within the protein-protein interaction network were identified. Moreover, the co-expression network of the top module by the HIPPIE database was constructed. Additionally, the gene regulatory network was constructed based on miRNAs and circRNAs. Lastly, we inspected the DGIdb database for possible interacted drugs.
RESULTS
Our microarray dataset analysis identified 92 common DEGs between BE and EAC with significant enrichment in skin and epidermis development genes. The study also identified 22 common SNPs between BE and EAC. The top module of PPI network analysis included and . We constructed a ceRNA network involving three specific mRNAs, 23 miRNAs, and 101 selected circRNAs. According to the results from the DGIdb database, TD101 was found to interact with the gene.
CONCLUSION
The present study provides novel potential candidate genes that may be involved in the molecular association between Esophageal adenocarcinoma and Barrett's Esophagus, resulting in developing the diagnostic tools and therapeutic targets to prevent progression of BE to EAC.
PubMed: 38803922
DOI: 10.1016/j.heliyon.2024.e31194 -
Heliyon May 2024The initiator of cytokine storm in Coronavirus disease (COVID-19) is still unknown. We recently suggested a complex interaction of matrix metalloproteinases (MMPs), Fas...
BACKGROUND
The initiator of cytokine storm in Coronavirus disease (COVID-19) is still unknown. We recently suggested a complex interaction of matrix metalloproteinases (MMPs), Fas ligand (FasL), and viral entry factors could be responsible for the cytokine outrage In COVID-19. We explored the molecular dynamics of FasL/MMP7-9 in COVID-19 conditions and provide neuroimmune insights for future.
METHODS
We enrolled and analyzed a clinical cohort of COVID-19 patients, and recorded their blood Na + levels and temperature at admission. A blood-like molecular dynamics simulation (MDS) box was then built. Four conditions were studied; MMP7/FasL (healthy), MMP7/FasL (COVID-19), MMP9-FasL (healthy), and MMP9/FasL (COVID-19). MDS was performed by GROningen MAchine for Chemical Simulation (GROMACS). We analyzed bonds, short-range energies, and free binding energies to draw conclusions on the interaction of MMP7/MMP9 and FasL to gain insights into COVID-19 immunopathology. Genevestigator was used study RNA-seq/microarray expression data of MMPs in the cells of immune and nervous systems. Finally, epitopes of MMP/FasL complexes were identified as drug targets by machine learning (ML) tools.
RESULTS
MMP7-FasL (Healthy), MMP7-FasL (COVID-19), MMP9-FasL (Healthy), and MMP9-FasL (COVID-19) systems showed 0, 1, 4, and 2 salt bridges, indicating MMP9 had more salt bridges. Moreover, in both COVID-19 and normal conditions, the number of interacting residues and surface area was higher for MMP9 compared to MMP7 group. The COVID-19 MMP9-FasL group had more H-bonds compared to MMP7-FasL group (12 vs. 7). 15 epitopes for FasL-MMP9 and 10 epitopes for FasL-MMP7 were detected. Extended MD simulation for 100 ns confirmed stronger binding of MMP9 based on Molecular Mechanics Generalized Borne Surface analysis (MM-GBSA) and Coul and Leonard-Jones (LJ) short-range energies.
CONCLUSIONS
MMP9 interacts stronger than MMP7 with FasL, however, both molecules maintained strong interaction through the MDS. We suggested epitopes for MMP-FasL complexes as valuable therapeutic targets in COVID-19. These data could be utilized in future immune drug and protein design and repurposing efforts.
PubMed: 38803919
DOI: 10.1016/j.heliyon.2024.e30898 -
Analytical Cellular Pathology... 2024Premature rupture of membrane (PROM) refers to the rupture of membranes before the onset of labor which increases the risk of perinatal morbidity and mortality....
Premature rupture of membrane (PROM) refers to the rupture of membranes before the onset of labor which increases the risk of perinatal morbidity and mortality. Recently, circular RNAs (circRNAs) have emerged as promising regulators of diverse diseases. However, the circRNA expression profiles and potential circRNA-miRNA-mRNA regulatory mechanisms in PROM remain enigmatic. In this study, we displayed the expression profiles of circRNAs and mRNAs in plasma and fetal membranes of PROM and normal control (NC) groups based on circRNA microarray, the Gene Expression Omnibus database, and NCBI's Sequence Read Archive. A total of 1,459 differentially expressed circRNAs (DECs) in PROM were identified, with 406 upregulated and 1,053 downregulated. Then, we constructed the circRNA-miRNA-mRNA network in PROM, encompassing 22 circRNA-miRNA pairs and 128 miRNA-mRNA pairs. Based on the analysis of gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene set enrichment analysis (GSEA), DECs were implicated in immune-related pathways, with certain alterations persisting even postpartum. Notably, 11 host genes shared by DECs of fetal membrane tissue and prenatal plasma in PROM were significantly implicated in inflammatory processes and extracellular matrix regulation. Our results suggest that structurally stable circRNAs may predispose to PROM by mediating systemic immune imbalances, including peripheral leukocyte disorganization, local immune imbalance at the maternal-fetal interface, and local collagen disruption. This is the first time to decipher a landscape on circRNAs of PROM, reveals the pathogenic cause of PROM from the perspective of circRNA, and opens up a new direction for the diagnosis and treatment of PROM.
Topics: RNA, Circular; Humans; Pregnancy; Fetal Membranes, Premature Rupture; Female; RNA, Messenger; Gene Expression Profiling; Gene Regulatory Networks; MicroRNAs; Gene Ontology; Adult; Gene Expression Regulation; Transcriptome
PubMed: 38803428
DOI: 10.1155/2024/6724914 -
BMC Oral Health May 2024This study aims to elucidate the biological functions of ferroptosis-related genes in periodontitis, along with their correlation to tumor microenvironment (TME)...
PURPOSE
This study aims to elucidate the biological functions of ferroptosis-related genes in periodontitis, along with their correlation to tumor microenvironment (TME) features such as immune infiltration. It aims to provide potential diagnostic markers of ferroptosis for clinical management of periodontitis.
METHODS
Utilizing the periodontitis-related microarray dataset GSE16134 from the Gene Expression Omnibus (GEO) and a set of 528 ferroptosis-related genes identified in prior studies, this research unveils differentially expressed ferroptosis-related genes in periodontitis. Subsequently, a protein-protein interaction network was constructed. Subtyping of periodontitis was explored, followed by validation through immune cell infiltration and gene set enrichment analyses. Two algorithms, randomForest and SVM(Support Vector Machine), were employed to reveal potential ferroptosis diagnostic markers for periodontitis. The diagnostic efficacy, immune correlation, and potential transcriptional regulatory networks of these markers were further assessed. Finally, potential targeted drugs for differentially expressed ferroptosis markers in periodontitis were predicted.
RESULTS
A total of 36 ferroptosis-related genes (30 upregulated, 6 downregulated) were identified from 829 differentially expressed genes between 9 periodontitis samples and the control group. Subsequent machine learning algorithm screening highlighted 4 key genes: SLC1A5(Solute Carrier Family 1 Member 5), SLC2A14(Solute Carrier Family 1 Member 14), LURAP1L(Leucine Rich Adaptor Protein 1 Like), and HERPUD1(Homocysteine Inducible ER Protein With Ubiquitin Like Domain 1). Exploration of these 4 key genes, supported by time-correlated ROC analysis, demonstrated reliability, while immune infiltration results indicated a strong correlation between key genes and immune factors. Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted for the four key genes, revealing enrichment in GO/KEGG pathways that have a significant impact on periodontitis. Finally, the study predicted potential transcriptional regulatory networks and targeted drugs associated with these key genes in periodontitis.
CONCLUSIONS
The ferroptosis-related genes identified in this study, including SLC1A5, SLC2A14, LURAP1L, and HERPUD1, may serve as novel diagnostic and therapeutic targets for periodontitis. They are likely involved in the occurrence and development of periodontitis through mechanisms such as immune infiltration, cellular metabolism, and inflammatory chemotaxis, potentially linking the ferroptosis pathway to the progression of periodontitis. Targeted drugs such as flurofamide, L-733060, memantine, tetrabenazine, and WAY-213613 hold promise for potential therapeutic interventions in periodontitis associated with these ferroptosis-related genes.
Topics: Ferroptosis; Humans; Periodontitis; Protein Interaction Maps; Gene Regulatory Networks; Biomarkers
PubMed: 38802844
DOI: 10.1186/s12903-024-04342-2