Integrated Transcriptomics and Network Analysis Identified Altered Neural Mechanisms in Frontal Aging Brain-Associated Alzheimer's Disease.

Alzheimer's disease (AD) is the most common neurodegenerative disease. The late stage of AD typically develops after 60 years of age and AD pathogenesis can be detected predominately in the frontal lobe, which is responsible for memory. Multiple alterations in cellular mechanisms have been associated with AD, but there is no clear information on AD pathogenesis during brain aging. This study aimed to explore the differentially expressed genes (DEGs) in the frontal lobe of aging brains and to identify shared crucial mechanisms in the aging brain linked to AD pathogenesis. Three datasets were downloaded from the Gene Expression Omnibus (GEO). Biological function analysis was performed by DAVID and KEGG databases. An AD patient's cohort (GSE150696) was collected for verification of the enriched pathway. The results demonstrated that multiple neurochemical synapsis and regulation of the cytoskeleton are linked to AD pathogenesis during aging. Taken together, this study contributes to our further understanding of neural alterations during aging in AD that could be used to develop therapeutics for early intervention to prevent or slow progression.

Integrative In Silico and In Vitro Transcriptomics Analysis Revealed Gene Expression Changes and Oncogenic Features of Normal Cholangiocytes after Chronic Alcohol Exposure.

Cholangiocarcinoma (CCA) is a malignant tumor originating from cholangiocyte. Prolonged alcohol consumption has been suggested as a possible risk factor for CCA, but there is no information about alcohol's mechanisms in cholangiocyte. This study was designed to investigate global transcriptional alterations through RNA-sequencing by using chronic alcohol exposure (20 mM for 2 months) in normal human cholangiocyte MMNK-1 cells. To observe the association of alcohol induced CCA pathogenesis, we combined differentially expressed genes (DEGs) with computational bioinformatics of CCA by using publicly gene expression omnibus (GEO) datasets. For biological function analysis, Gene ontology (GO) analysis showed biological process and molecular function related to regulation of transcription from RNA polymerase II promoter, while cellular component linked to the nucleoplasm. KEGG pathway presented pathways in cancer that were significantly enriched. From KEGG result, we further examined the oncogenic features resulting in chronic alcohol exposure, enhanced proliferation, and migration through CCND-1 and MMP-2 up-regulation, respectively. Finally, combined DEGs were validated in clinical data including TCGA and immunohistochemistry from HPA database, demonstrating that FOS up-regulation was related to CCA pathogenesis. This study is the first providing more information and molecular mechanisms about global transcriptome alterations and oncogenic enhancement of chronic alcohol exposure in normal cholangiocytes.

Identification of Molecular Mechanisms of Ameloblastoma and Drug Repositioning by Integration of Bioinformatics Analysis and Molecular Docking Simulation.

Background: Ameloblastoma (AM) is a benign tumor locally originated from odontogenic epithelium that is commonly found in the jaw. This tumor makes aggressive invasions and has a high recurrence rate. This study aimed to investigate the differentially expressed genes (DEGs), biological function alterations, disease targets, and existing drugs for AM using bioinformatics analysis. Methods: The data set of AM was retrieved from the GEO database (GSE132474) and identified the DEGs using bioinformatics analysis. The biological alteration analysis was applied to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Protein-protein interaction (PPI) network analysis and hub gene identification were screened through NetworkAnalyst. The transcription factor-protein network was constructed via OmicsNet. We also identified candidate compounds from L1000CDS2 database. The target of AM and candidate compounds were verified using docking simulation. Results: Totally, 611 DEGs were identified. The biological function enrichment analysis revealed glycosaminoglycan and GABA (γ-aminobutyric acid) signaling were most significantly up-regulated and down-regulated in AM, respectively. Subsequently, hub genes and transcription factors were screened via the network and showed FOS protein was found in both networks. Furthermore, we evaluated FOS protein to be a therapeutic target in AMs. Candidate compounds were screened and verified using docking simulation. Tanespimycin showed the greatest affinity binding value to bind FOS protein. Conclusions: This study presented the underlying molecular mechanisms of disease pathogenesis, biological alteration, and important pathways of AMs and provided a candidate compound, Tanespimycin, targeting FOS protein for the treatment of AMs.

Exploring protein profiles and hub genes in ameloblastoma.

Ameloblastoma (AM) is a prominent benign odontogenic tumor characterized by aggressiveness, likely originating from tooth-generating tissue or the dental follicle (DF). However, proteomic distinctions between AM and DF remain unclear. In the present study, the aim was to identify the distinction between AM and DF in terms of their proteome and to determine the associated hub genes. Shotgun proteomics was used to compare the proteomes of seven fresh-frozen AM tissues and five DF tissues. Differentially expressed proteins (DEPs) were quantified and subsequently analyzed through Gene Ontology-based functional analysis, protein-protein interaction (PPI) analysis and hub gene identification. Among 7,550 DEPs, 520 and 216 were exclusive to AM and DF, respectively. Significant biological pathways included histone H2A monoubiquitination and actin filament-based movement in AM, as well as pro-B cell differentiation in DF. According to PPI analysis, the top-ranked upregulated hub genes were ubiquitin C (UBC), breast cancer gene 1 (BRCA1), lymphocyte cell-specific protein-tyrosine kinase (LCK), Janus kinase 1 and ATR serine/threonine kinase, whereas the top-ranked downregulated hub genes were UBC, protein kinase, DNA-activated, catalytic subunit (PRKDC), V-Myc avian myelocytomatosis viral oncogene homolog (MYC), tumor protein P53 and P21 (RAC1) activated kinase 1. When combining upregulated and downregulated genes, UBC exhibited the highest degree and betweenness values, followed by MYC, BRCA1, PRKDC, embryonic lethal, abnormal vision, Drosophila, homolog-like 1, myosin heavy chain 9, amyloid beta precursor protein, telomeric repeat binding factor 2, LCK and filamin A. In summary, these findings contributed to the knowledge on AM protein profiles, potentially aiding future research regarding AM etiopathogenesis and leading to AM prevention and treatment.

Identification of Potential Molecular Mechanisms and Prognostic Markers for Oral Squamous Cell Carcinoma: A Bioinformatics Analysis.

Aims and Objectives: The goal of this study was to uncover crucial biochemical pathways, prognostic indicators, and therapeutic targets in patients with oral cancer in order to enhance therapy strategies. Materials and Methods: Five gene expression omnibus datasets were analyzed by using bioinformatics approaches to identify differentially expressed genes (DEGs). To determine biological alterations, gene ontology (GO) and KEGG pathway analyses were implied using the identified DEGs. Hub genes were determined using protein-protein interaction (PPI) network analysis and an interactome was constructed using NetworkAnalyst. Furthermore, five hub genes were evaluated for use as prognostic markers by using the human protein atlas (HPA) and the GEPIA2.0 database. In addition, the correlations between hub-gene expression and immune cell infiltration of oral squamous cell carcinoma (OSCC) tumors were analyzed using the tWumor immune estimation resource (TIMER) database. Results: A total of 2071 upregulated genes and 1893 downregulated genes were identified. GO and pathway analysis showed DEGs were enriched in multiple immune response terms and interaction of inflammatory cytokines. From the PPI network, five hub genes were identified that have a crucial role in OSCC. These included interferon regulatory factor 4 (IRF4), chemokine receptor 7 (CCR7), TNF receptor superfamily member 17 (TNFRSF17), CD27, and sphingosine-1-phosphate receptor 4 (S1PR4), which were predicted to be favorable prognostic markers for OSCC using HPA. Overall survival analysis revealed that low expression of the five hub genes was significantly associated with worse overall survival. Our analysis of tumor-associated immune infiltration revealed that increased IRF4 expression was positively correlated with the gene expression profiles suggestive of infiltration of all immune cell types, whereas increased CCR7 expression was negatively correlated with neutrophil infiltration. Increased expression of CD27, S1PR4, and TNFRSF17 was found to be negatively correlated with dendritic cell, M0 macrophage, and neutrophil infiltration. Conclusion: In summary, inflammation, and the immune response play an important role in OSCC. All five hub genes were good predictors of OSCC prognosis, suggesting that they could be used as potential therapeutic targets and tumor markers.

Integrated Transcriptomics and Network Analysis of Potential Mechanisms and Health Effects of Convalescent COVID-19 Patients.

Coronaviral disease 2019 (COVID-19) is a recent pandemic disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, there are still cases of COVID-19 around the world that can develop into persistent symptoms after discharge. The constellation of symptoms, termed long COVID, persists for months and can lead to various diseases such as lung inflammation and cardiovascular disease, which may lead to considerable financial burden and possible risk to human health. Moreover, the molecular mechanisms underlying the post-pandemic syndrome of COVID-19 remain unclear. In this study, we aimed to explore the molecular mechanism, disease association, and possible health risks in convalescent COVID-19 patients. Gene expression data from a human convalescent COVID-19 data set was compared with a data set from healthy normal individuals in order to identify differentially expressed genes (DEGs). To determine biological function and potential pathway alterations, the GO and KEGG databases were used to analyze the DEGs. Disease association, tissue, and organ-specific analyses were used to identify possible health effects. A total of 250 DEGs were identified between healthy and convalescent COVID-19 subjects. The biological function alterations identified revealed cytokine interactions and increased inflammation through NF-κB1, RELA, JUN, STAT3, and SP1. Interestingly, the most significant pathways were cytokine-cytokine receptor interaction, altered lipid metabolism, and atherosclerosis that play a crucial role in convalescent COVID-19. In addition, we also found pneumonitis, dermatitis, and autoimmune diseases. Based on our study, convalescent COVID-19 is associated with inflammation in a variety of organs that could lead to autoimmune and inflammatory diseases, as well as atherosclerosis. These findings are a first step toward fully exploring the disease mechanisms in depth to understand the relationship between post-COVID-19 infection and potential health risks. This is necessary for the development of appropriate strategies for the prevention and treatment of long COVID.

LINE-1 and Alu Methylation in hrHPV-Associated Precancerous Cervical Samples.

OBJECTIVE: This study was conducted to determine global DNA methylation patterns in cervical cells cytologically identified as atypical squamous cells of unknown significance (ASCUS) with a normal, LSIL, or HSIL histopathological result. METHODS: Methylation patterns of long interspersed nuclear elements (LINE-1) and short interspersed element (Alu) sequences were assessed using the combined bisulfite restriction analysis (COBRA) method in cervical samples with cytology-diagnosed cervical lesions. RESULTS: In cervical precancerous lesions with hrHPV positive, the percentage of overall (mC) and mCmC LINE-1 methylation levels showed a stepwise increase from hrHPV positive normal to HSIL with significant differences (p<0.001). However, both methylation levels were significantly higher in hrHPV negative normal than in hrHPV positive normal (p<0.001). The overall (mC) Alu methylation in hrHPV positive LSIL and HSIL was lower than in hrHPV positive normal, with a significant difference (p<0.05). Remarkably, the percentage of uCmC and mCuC of LINE-1 and Alu in three different hrHPV positive cervical lesions showed a stepwise decrease from hrHPV positive normal, LSIL and HSIL, respectively. Furthermore, receiver operating characteristic (ROC) curve analyses revealed that the LINE-1 mC and mCmC patterns have high sensitivity and specificity for distinguishing HSIL from normal/LSIL in hrHPV positive cases at the appropriate cutoff levels. CONCLUSION: We have demonstrated the LINE-1 and Alu methylation data in normal and premalignant cervical epithelia. LINE-1 hypomethylation was found in hrHPV positive normal cells, with lower methylation levels associated with cancer features. In cytologically diagnosed Atypical Squamous Cells of Unknown Significance (ASCUS), the levels of mC and the mCmC pattern could be utilized in concert with hrHPV detection to classify the ASCUS sample prior to colposcopy.

Potential candidate treatment agents for targeting of cholangiocarcinoma identified by gene expression profile analysis.

Cholangiocarcinoma (CCA) remains to be a major health problem in several Asian countries including Thailand. The molecular mechanism of CCA is poorly understood. Early diagnosis is difficult, and at present, no effective therapeutic drug is available. The present study aimed to identify the molecular mechanism of CCA by gene expression profile analysis and to search for current approved drugs which may interact with the upregulated genes in CCA. Gene Expression Omnibus (GEO) was used to analyze the gene expression profiles of CCA patients and normal subjects. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG), gene ontology enrichment analysis was also performed, with the KEGG pathway analysis indicating that pancreatic secretion, protein digestion and absorption, fat digestion and absorption, and glycerolipid metabolism may serve important roles in CCA oncogenesis. The drug signature database (DsigDB) was used to search for US Food and Drug Administration (FDA)-approved drugs potentially capable of reversing the effects of the upregulated gene expression in CCA. A total of 61 antineoplastic and 86 non-antineoplastic drugs were identified. Checkpoint kinase 1 was the most interacting with drug signatures. Many of the targeted protein inhibitors that were identified have been approved by the US-FDA as therapeutic agents for non-antineoplastic diseases, including cimetidine, valproic acid and lovastatin. The current study demonstrated an application for bioinformatics analysis in assessing the potential efficacy of currently approved drugs for novel use. The present results suggest novel indications regarding existing drugs useful for CCA treatment. However, further in vitro and in vivo studies are required to support the current predictions.

CCNA1 promoter methylation: a potential marker for grading Papanicolaou smear cervical squamous intraepithelial lesions.

BACKGROUND: From our previous study, we established that cyclin A1 (CCNA1) promoter methylation is strongly correlated with multistep progression of HPV-associated cervical cancer, suggesting potential use as a diagnostic maker of disease. OBJECTIVES: The purpose of the present study was to assess the prevalence of CCNA1 promoter methylation in residual cervical cells isolated from liquid-based cytology that underwent hrHPV DNA screening for cervical cancer, and then to evaluate this marker for diagnostic accuracy using parameters like sensitivity, specificity, predictive values and likelihood ratio. METHODS: In this retrospective study, histopathology was used as the gold standard method with specimens separated into the following groups: negative (n=31), low- grade squamous intraepithelial lesions (LSIL, n=34) and high-grade squamous intraepithelial lesions or worse (HSIL+, n=32). The hrHPV was detected by Hybrid Capture 2 (HC2) and CCNA1 promoter methylation was examined by CCNA1 duplex methylation specific PCR. RESULTS: The results showed the frequencies of CCNA1 promoter methylation were 0%, 5.88% and 83.33%, while the percentages of hrHPV were 66.67%, 82.35% and 100% in the negative, LSIL and HSIL+ groups, respectively. Although hrHPV infection showed high frequency in all three groups, it could not differentiate between the different groups and grades of precancerous lesions. In contrast, CCNA1 promoter methylation clearly distinguished between negative/LSIL and HSIL+, with high levels of all statistic parameters. CONCLUSION: CCNA1 promoter methylation is a potential marker for distinguishing between histologic negative/LSIL and HSIL+using cervical cytology samples.