Microarray Expression Profiling Research Articles

Mecp2 promotes the anti-inflammatory effect of alpinetin via epigenetic modification crosstalk.

In recent years, inflammatory disorders have emerged as a significant concern for human health. Through ongoing research on anti-inflammatory agents, alpinetin has shown promising anti-inflammatory properties, including involvement in epigenetic modification pathways. As a crucial regulator of epigenetic modifications, Mecp2 may play a role in modulating the epigenetic effects of alpinetin, potentially impacting its anti-inflammatory properties. To test this hypothesis, two key components, p65 (a member of NF-KB family) and p300 (a type of co-activator), were screened by the expression profiling microarray, which exhibited a strong correlation with the intensity of LPS stimulation in mouse macrophages. Meanwhile, alpinetin demonstrates the anti-inflammatory properties through its ability to disrupt the synthesis of p65 and its interaction with promoters of inflammatory genes, yet it did not exhibit similar effects on p300. Additionally, Mecp2 can inhibit the binding of p300 by attaching to the methylated inflammatory gene promoter induced by alpinetin, leading to obstacles in promoter acetylation and subsequently impacting the binding of p65, ultimately enhancing the anti-inflammatory capabilities of alpinetin. Similarly, in a sepsis mouse model, it was observed that homozygotes overexpressing Mecp2 showed a greater reduction in organ damage and improved survival rates compared to heterozygotes when administered by alpinetin. However, blocking the expression of DNA methyltransferase 3A (DNMT3A) resulted in the loss of Mecp2's anti-inflammatory assistance. In conclusion, Mecp2 may augment the anti-inflammatory effects of alpinetin through epigenetic 'crosstalk', highlighting the potential efficacy of a combined therapeutic strategy involving Mecp2 and alpinetin for anti-inflammatory intervention.

A recursive framework for improving the performance of multi-objective differential evolution algorithms for gene selection

Gene selection is a pivotal process in machine-learning-driven medical diagnostics, where the goal is to identify a subset of genes from microarray expression profiles that can enhance the predictive accuracy of classifiers for disease diagnosis. The two key objectives of gene selection are to reduce the dimensionality of the data and to improve the accuracy of disease diagnosis, which is typically a multi-objective optimization problem. In recent years, multi-objective evolutionary algorithms (MOEAs) have gained wide attention in feature selection research, and several related algorithms have been produced. However, most algorithms tend to get stuck in local optimality when searching for solutions from a high-dimensional space. To solve the gene selection problem effectively, this study introduces a recursive multi-objective differential evolution algorithm with elite recursive strategy (RMODE-E) and a recursive multi-objective differential evolution algorithm with Pareto front recursive strategy (RMODE-P). RMODE-E amalgamates the features selected by the top E elite individuals, RMODE-P consolidates the features selected by the Pareto front set, and the combined features then serve as the foundation for subsequent recursive rounds of searching. The proposed feature subspace combination strategy not only reduces the recursive search space but also improves the capacity to find globally optimal feature subsets. Extensive experiments were conducted to compare our proposed algorithms with eight state-of-the-art evolutionary algorithms to validate their effectiveness. Experimental results demonstrate that RMODE-P has better global search capability as it achieves better best classification accuracy, mean classification accuracy, and minimal gene subset size.

Bioinformatics integration reveals key genes associated with mitophagy in myocardial ischemia-reperfusion injury

BackgroundMyocardial ischemia is a prevalent cardiovascular disorder associated with significant morbidity and mortality. While prompt restoration of blood flow is essential for improving patient outcomes, the subsequent reperfusion process can result in myocardial ischemia–reperfusion injury (MIRI). Mitophagy, a specialized autophagic mechanism, has consistently been implicated in various cardiovascular disorders. However, the specific connection between ischemia–reperfusion and mitophagy remains elusive. This study aims to elucidate and validate central mitophagy-related genes associated with MIRI through comprehensive bioinformatics analysis.MethodsWe acquired the microarray expression profile dataset (GSE108940) from the Gene Expression Omnibus (GEO) and identified differentially expressed genes (DEGs) using GEO2R. Subsequently, these DEGs were cross-referenced with the mitophagy database, and differential nucleotide sequence analysis was performed through enrichment analysis. Protein–protein interaction (PPI) network analysis was employed to identify hub genes, followed by clustering of these hub genes using cytoHubba and MCODE within Cytoscape software. Gene set enrichment analysis (GSEA) was conducted on central genes. Additionally, Western blotting, immunofluorescence, and quantitative polymerase chain reaction (qPCR) analyses were conducted to validate the expression patterns of pivotal genes in MIRI rat model and H9C2 cardiomyocytes.ResultsA total of 2719 DEGs and 61 mitophagy-DEGs were identified, followed by enrichment analyses and the construction of a PPI network. HSP90AA1, RPS27A, EEF2, EIF4A1, EIF2S1, HIF-1α, and BNIP3 emerged as the seven hub genes identified by cytoHubba and MCODE of Cytoscape software. Functional clustering analysis of HIF-1α and BNIP3 yielded a score of 9.647, as determined by Cytoscape (MCODE). In our MIRI rat model, Western blot and immunofluorescence analyses confirmed a significant elevation in the expression of HIF-1α and BNIP3, accompanied by a notable increase in the ratio of LC3II to LC3I. Subsequently, qPCR confirmed a significant upregulation of HIF-1α, BNIP3, and LC3 mRNA in the MIRI group. Activation of the HIF-1α/BNIP3 pathway mediates the regulation of the degree of Mitophagy, thereby effectively reducing apoptosis in rat H9C2 cardiomyocytes.ConclusionsThis study has identified seven central genes among mitophagy-related DEGs that may play a pivotal role in MIRI, suggesting a correlation between the HIF-1α/BNIP3 pathway of mitophagy and the pathogenesis of MIRI. The findings highlight the potential importance of mitophagy in MIRI and provide valuable insights into underlying mechanisms and potential therapeutic targets for further exploration in future studies.

Determination of target genes for classified molecular subtypes of triple-negative breast cancer form microarray gene expression profiling: An integrative in silico approach.

Highly heterogeneous triple-negative breast cancer (TNBC) has tough clinical features, which were gradually solving and improving in diagnosis by the molecular subtyping of TNBC. Presently, this study was focused on analyzing the genetic makeup of TNBC subtypes. This study explored the MicroArray expression profiling of differentially expressed genes in molecular subtypes BL1, BL2, IM, luminal androgen receptor, M, and mesenchymal stem-like of TNBC by analyzing the Gene Expression Omnibus dataset GSE167213. Various gene ontologies-based protein-protein interaction (PPI) networks were subtyped TNBC genes. The effect of genetic alteration on TNBC cases was also interpreted. The MicroArray gene expression profiling was done through R programming and subjected to functional annotation through the database for annotation, visualization, and integrated discovery. The PPI networking of functionally associated genes was interpreted by STRING. The survival analysis was done through cBioPortal. The t-test was used through R programming to generate the P values for a test of the significance of expressed genes. A total of 54,613 significant probes were analyzed in the TNBC MicroArray dataset. The functional PPI networks of BL1, BL2, and IM upregulated genes showed significant associations. The survival analysis of differentially expressed genes showed the significant prognostic effect of 32 upregulated genes of different subtypes on TNBC cases with genetic alterations, whereas the remaining genes showed no significant effects. The output of the present study provided significant target gene panels for different TNBC subtypes, which would add an informative genetic value to TNBC diagnosis.

SH3GL2 and MMP17 as lung adenocarcinoma biomarkers: a machine-learning based approach

ObjectiveUsing bioinformatics machine learning methods, our research aims to identify the potential key genes associated with Lung adenocarcinoma (LUAD). MethodsWe obtained two gene expression profiling microarrays (GSE68571 and GSE74706) from the public Gene Expression Omnibus (GEO) database at the National Centre for Biotechnology Information (NCBI). The purpose was to identify Differentially Expressed Genes (DEGs) between the lung adenocarcinoma group and the healthy control group. The limma R package in R was utilized for this analysis. For the differential gene diagnosis of lung adenocarcinoma, we employed the least absolute shrinkage and selection operator (LASSO) regression and SVM-RFE screening crossover. To evaluate the performance, ROC curves were plotted. We performed immuno-infiltration analysis using CIBERSORT. Finally, we validated the key genes through qRT-PCR and Western-blot verification, then downregulated MMP17 gene expression, upregulated SH3GL2 gene expression, and performed CCK8 experiments. ResultsA total of 32 Differentially Expressed Genes (DEGs) were identified. Two diagnostic marker genes, SH3GL2 and MMP17, were selected by employing LASSO and SVM-RFE machine learning methods. In Lung adenocarcinoma cells, the expression of MMP17 was observed to be elevated compared to normal lung epithelial cells in the control group (P < 0.05). In contrast, a down-regulation of SH3GL2 was found in Lung adenocarcinoma cells (P < 0.05). Finally, we downregulated MMP17 and upregulated SH3GL2 gene expression, then the CCK8 showed that the proliferation of both lung cancer cells was inhibited. ConclusionSH3GL2 and MMP17 are expected to be potential biomarkers for Lung adenocarcinoma.

DNA methylation profiling identifies epigenetic signatures of early gastric cancer.

Research on the DNA methylation status of gastric cancer (GC) has primarily focused on identifying invasive GC to develop biomarkers for diagnostic. However, DNA methylation in noninvasive GC remains unclear. We conducted a comprehensive DNA methylation profiling study of differentiated-type intramucosal GCs (IMCs). Illumina 850K microarrays were utilized to assess the DNA methylation profiles of formalin-fixed paraffin-embedded tissues from eight patients who were Epstein-Barr virus-negative and DNA mismatch repair proficient, including IMCs and paired adjacent nontumor mucosa. Gene expression profiling microarray data from the GEO database were analyzed via bioinformatics to identify candidate methylation genes. The final validation was conducted using quantitative real-time PCR, the TCGA methylation database, and single-sample gene set enrichment analysis (GSEA). Genome-wide DNA methylation profiling revealed a global decrease in methylation in IMCs compared with nontumor tissues. Differential methylation analysis between IMCs and nontumor tissues identified 449 differentially methylated probes, with a majority of sites showing hypomethylation in IMCs compared with nontumor tissues (66.1% vs 33.9%). Integrating two RNA-seq microarray datasets, we found one hypomethylation-upregulated gene: eEF1A2, overlapped with our DNA methylation data. The mRNA expression of eEF1A2 was higher in twenty-four IMC tissues than in their paired adjacent nontumor tissues. GSEA indicated that the functions of eEF1A2 were associated with the development of IMCs. Furthermore, TCGA data indicated that eEF1A2 is hypomethylated in advanced GC. Our study illustrates the implications of DNA methylation alterations in IMCs and suggests that aberrant hypomethylation and high mRNA expression of eEF1A2 might play a role in IMCs development.

MicroRNA expression profiling of cutaneous squamous cell carcinomas and precursor lesions

AbstractBackgroundActinic keratoses (AK) are pre‐malignant skin lesions caused by chronic sun exposure. Progression from an AK to intraepidermal carcinoma (IEC) and a cutaneous squamous cell carcinoma (SCC) is well known but the rate of transformation to an invasive SCC is highly variable. Since no definitive biomarkers are available, treatment decisions are made ad hoc.ObjectivesTo fully characterise our AK to SCC progression series, we performed microRNA (miRNA) microarray expression profiling of normal and photodamaged skin, as well as AKs, IEC, and invasive SCCs.MethodsThe study recruited 27 patients who donated fresh biopsies of normal skin, photodamaged skin, AK, IEC, and SCC (n = 67 specimens). All miRbase (v.21) miRNAs were profiled to identify miRNAs related to SCC progression. miRNAs were validated using qRT‐PCR and in vitro phenotypic assays.ResultsThere were 234 robustly expressed miRNAs across the tissue collection, which resulted in 20 miRNA that were differentially expressed ((cor)p ≤ 0.05 and ≥ 10 fold) between normal skin and SCC. Hierarchical clustering all samples illustrated that AKs, IEC, and SCCs were largely indistinguishable, which confirms the premalignant status of an AK. A panel of miRNAs showed significant dysregulation between normal and photodamaged skin and AK. Importantly, we found miR‐34a‐5p and miR‐31‐5p had significant differential expression between AKs and IEC and IEC and SCC respectively. Phenotypic assays determined that the miR‐31 duplex had opposing effects on SCC cell lines which suggests that dysregulation of this duplex may be related to the dynamic control of progression of transformed keratinocytes.ConclusionsThis study confirmed the continuum of AK with IEC and SCC highlighting that miRNA expression plays a role in keratinocyte transformation. Development of our putative miRNA biomarker candidates is warranted to aid in clinical management of patients experiencing high AK load to determine the most appropriate treatment.

Modeling of new markers for the diagnosis and prognosis of pancreatic cancer based on the transition from inflammation to cancer.

Pancreatic adenocarcinoma (PAAD) is a lethal disease with a poor prognosis. Genes involved in acute pancreatitis (AP) or chronic pancreatitis (CP) might be important for PAAD development. This study sought to identify potential PAAD diagnosis markers and to establish a PAAD prognosis prediction model based on AP- and CP-related genes. The significantly differentially expressed genes in both AP or CP and PAAD were obtained by a bioinformatics analysis. A risk-score model for predicting survival was constructed based on The Cancer Genome Atlas (TCGA) data and validated using an International Cancer Genome Consortium (ICGC) cohort. Protein expression and the effects of the genes in the risk models were validated by immunohistochemistry, or Cell Counting Kit-8 (CCK-8) and transwell assays. The study sample data included six AP tissue samples and five normal pancreatic tissue samples, six CP tissue samples and six normal pancreatic tissue samples from the Gene Expression Omnibus (GEO) expression profiling microarrays GSE109227 and GSE41418 data sets, respectively, and fragments per kilobase per million mapped fragments (FPKM) data from four normal controls and 150 PAAD cases from TCGA database, and 182 cancer patient samples with complete survival prognostic data from the ICGC database. In total, 508 significantly differentially expressed genes were found in both AP or CP and PAAD. Trefoil factor 2 (TFF2), tubulointerstitial nephritis antigen (TINAG), trefoil factor 1 (TFF1), aquaporin 5 (AQP5), SAM pointed domain containing ETS transcription factor (SPDEF), anterior gradient protein 2 (AGR2), apolipoprotein B messenger RNA editing enzyme catalytic subunit 1 (APOBEC1), kallikrein-related peptidase 6 (KLK6), dopa decarboxylase (DDC), mucin 13 (MUC13), claudin 18 (CLDN18), annexin A10 (ANXA10), and tetraspanin 1 (TSPAN1) were found to be present in PAAD and had the largest fold change. A risk-score model, comprising 19 genes, was constructed for prognostic prediction. A high-risk score indicated a poor prognosis. TINAG, DDC, SPDEF, and APOBEC1 proteins were increased in PAAD, while TINAG and DDC were correlated with the pathologic grade. Decreased TINAG, APOBEC1, transmembrane protein 94 (TMEM94), and kelch like family member 36 (KLHL36) expression inhibited PAAD cell proliferation, while decreased SPDEF, TMEM94, and KLHL36 expression significantly inhibited PAAD cell migration. The AP and CP co-related genes were significantly correlated with PAAD. TINAG, DDC, SPDEF, and APOBEC1 could serve as new PAAD predictors. The risk model developed in this study could be used to predict the prognosis of PAAD patients.

Identification and validation of ferroptosis-related genes for diabetic retinopathy.

Diabetic retinopathy (DR) is a leading cause of blindness, and ferroptosis may be an essential component of the pathological process of DR. In this study, we aimed to screen five hub genes (TLR4, CAV1, HMOX1, TP53, and IL-1B) using bioinformatics analysis and experimentally verify their expression and effects on ferroptosis and cell function. The online Gene Expression Omnibus microarray expression profiling datasets GSE60436 and GSE1025485 were selected for investigation. Ferroptosis-related genes that might be differentially expressed in DR were identified. Then, Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein interaction (PPI) network analyses were conducted to characterize the differentially-expressed ferroptosis-related genes. After tissue-specific analyses and external dataset validation of hub genes, the mRNA and protein levels of hub genes in retinal microvascular endothelial cells (HRMECs) symbiotic with high glucose were verified using real-time quantitative PCR (qRT-PCR) and immunocytochemistry (ICC). Finally, hub genes were knocked down using siRNA, and changes in ferroptosis and cell function were observed. Based on the differential expression analysis, 19 ferroptosis-related genes were identified. GO and KEGG enrichment analyses showed that ferroptosis-related genes were significantly enriched in reactive oxygen species metabolic processes, necrotic cell death, hypoxia responses, iron ion responses, positive regulation of cell migration involved in sprouting angiogenesis, NF-kappa B signaling pathway, ferroptosis, fluid shear stress, and atherosclerosis. Subsequently, PPI network analysis and critical module construction were used to identify five hub genes. Based on bioinformatics analysis of mRNA microarrays, qRT-PCR confirmed higher mRNA expression of five genes in the DR model, and immunocytochemistry confirmed their higher protein expression. Finally, siRNA interference was used to verify the effects of five genes on ferroptosis and cell function. Based on bioinformatics analysis, five potential genes related to ferroptosis were identified, and their upregulation may affect the onset or progression of DR. This study sheds new light on the pathogenesis of DR.

Meta-analysis of Arabidopsis thaliana microarray data in relation to heat stress response.

Increasing global warming has made heat stress a serious threat to crop productivity and global food security in recent years. One of the most promising solutions to address this issue is developing heat-stress-tolerant plants. Hence, a thorough understanding of heat stress response mechanisms, particularly molecular ones, is crucial. Although numerous studies have used microarray expression profiling technology to explore this area, these experiments often face limitations, leading to inconsistent results. To overcome these limitations, a random effects meta-analysis was employed using advanced statistical methods. A meta-analysis of 16 microarray datasets related to heat stress response in Arabidopsis thaliana was conducted. The analysis revealed 1,972 significant differentially expressed genes between control and heat-stressed plants (826 over-expressed and 1,146 down-expressed), including 128 differentially expressed transcription factors from different families. The most significantly enriched biological processes, molecular functions, and KEGG pathways for over-expressed genes included heat response, mRNA splicing via spliceosome pathways, unfolded protein binding, and heat shock protein binding. Conversely, for down-expressed genes, the most significantly enriched categories included cell wall organization or biogenesis, protein phosphorylation, transmembrane transporter activity, ion transmembrane transporter, biosynthesis of secondary metabolites, and metabolic pathways. Through our comprehensive meta-analysis of heat stress transcriptomics, we have identified pivotal genes integral to the heat stress response, offering profound insights into the molecular mechanisms by which plants counteract such stressors. Our findings elucidate that heat stress influences gene expression both at the transcriptional phase and post-transcriptionally, thereby substantially augmenting our comprehension of plant adaptive strategies to heat stress.

Transcriptome Changes and Metabolic Outcomes After Bariatric Surgery in Adults With Obesity and Type 2 Diabetes.

Bariatric surgery has been shown to be effective in inducing complete remission of type 2 diabetes in adults with obesity. However, its efficacy in achieving complete diabetes remission remains variable and difficult to predict before surgery. We aimed to characterize bariatric surgery-induced transcriptome changes associated with diabetes remission and the predictive role of the baseline transcriptome. We performed a whole-genome microarray in peripheral mononuclear cells at baseline (before surgery) and 2 and 12 months after bariatric surgery in a prospective cohort of 26 adults with obesity and type 2 diabetes. We applied machine learning to the baseline transcriptome to identify genes that predict metabolic outcomes. We validated the microarray expression profile using a real-time polymerase chain reaction. Sixteen patients entered diabetes remission at 12 months and 10 did not. The gene-expression analysis showed similarities and differences between responders and nonresponders. The difference included the expression of critical genes (SKT4, SIRT1, and TNF superfamily), metabolic and signaling pathways (Hippo, Sirtuin, ARE-mediated messenger RNA degradation, MSP-RON, and Huntington), and predicted biological functions (β-cell growth and proliferation, insulin and glucose metabolism, energy balance, inflammation, and neurodegeneration). Modeling the baseline transcriptome identified 10 genes that could hypothetically predict the metabolic outcome before bariatric surgery. The changes in the transcriptome after bariatric surgery distinguish patients in whom diabetes enters complete remission from those who do not. The baseline transcriptome can contribute to the prediction of bariatric surgery-induced diabetes remission preoperatively.

Microarray Expression Profile of Exosomal circRNAs from High Glucose Stimulated Human Renal Tubular Epithelial Cells

Microarray Expression Profile of Exosomal circRNAs from High Glucose Stimulated Human Renal Tubular Epithelial Cells

A multitasking multi-objective differential evolution gene selection algorithm enhanced with new elite and guidance strategies for tumor identification

A key preprocessing step in tumor recognition based on microarray expression profile data and machine learning is to identify tumor marker genes. Gene selection aims to select the most relevant gene subset from the original ultra-high dimensional microarray expression profile data to improve tumor identification performance. Inspired by evolutionary multitasking (EMT) and multi-objective optimization, this paper puts forward a novel multitasking multi-objective differential evolution gene selection algorithm (MMODE) which uses new elite and guidance strategies to select the best gene subsets. MMODE initializes two different populations according to different filtering criteria to increase the diversity of the search. These two populations guide their respective populations to search in the optimal direction through knowledge transfer in the evolutionary process. In addition, MMODE employs new elite and guidance strategies that enables individuals to narrow the search range and jump out of local optima. The proposed algorithm is validated on 13 publicly available microarray expression datasets in comparison with state-of-the-art gene selection algorithms. The experimental results show that MMODE can find smaller gene subsets and achieve higher classification accuracy compared with other algorithms.

The Novel Prognostic Biomarker MAPK12 Promotes Migration, Proliferation, and Invasion in Head and Neck Squamous Cell Carcinoma

Background:: The prognosis and survival rate of patients with head and neck squamous cell carcinoma (HNSCC) remain a serious public health concern. Therefore, elucidation of the underlying mechanisms responsible for the biological behavior of HNSCC is crucial for the development of effective treatment strategies. Methods and Materials: In this study, we analyzed the TCGA database and found that MAPK12 was overexpressed in tumor samples compared to normal samples, which was confirmed by microarray expression profiles, quantitative real-time polymerase chain reaction, and immunohistochemistry. Results:: Cell functional experiments, including the cell counting kit-8 assay, wound healing test, and Transwell assay, revealed that MAPK12 overexpression increased the proliferation, invasion, and migration of HNSCC cells. A correlation was observed between MAPK12 expression and patient survival in HNSCC across several clinicopathological variables, including disease grade and stage. Analysis of immune-related functions demonstrated that HNSCC patients with low MAPK12 expression had a more favorable tumor immune microenvironment and better immunological functions. Conclusion:: Collectively, our study identified for the first time that MAPK12 is upregulated in HNSCC, functioning as an oncogene, indicating a suppressive tumor immune microenvironment and poor prognosis since it could promote cancer cell proliferation, invasion, and migration. However, further studies are needed to gain a more comprehensive understanding of the role of MAPK12 in HNSCC and other tumor types.

Synergy of the microRNA Ratio as a Promising Diagnosis Biomarker for Mucinous Borderline and Malignant Ovarian Tumors.

Epithelial ovarian cancers (EOCs) are a heterogeneous collection of malignancies, each with their own developmental origin, clinical behavior and molecular profile. With less than 5% of EOC cases, mucinous ovarian carcinoma is a rare form with a poor prognosis and a 5-year survival of 11% for advanced stages (III/IV). At the early stages, these malignant forms are clinically difficult to distinguish from borderline (15%) and benign (80%) forms with a better prognosis due to the large size and heterogeneity of mucinous tumors. Improving their diagnosis is therefore a challenge with regard to the risk of under-treating a malignant form or of unnecessarily undertaking radical surgical excision. The involvement of microRNAs (miRNAs) in tumor progression and their potential as biomarkers of diagnosis are becoming increasingly recognized. In this study, the comparison of miRNA microarray expression profiles between malignant and borderline tumor FFPE samples identified 10 down-regulated and 5 up-regulated malignant miRNAs, which were validated by individual RT-qPCR. To overcome normalization issues and to improve the accuracy of the results, a ratio analysis combining paired up-regulated and down-regulated miRNAs was performed. Although 21/50 miRNA expression ratios were significantly different between malignant and borderline tumor samples, any ratio could perfectly discriminate the two groups. However, a combination of 14 pairs of miRNA ratios (double ratio) showed high discriminatory potential, with 100% of accuracy in distinguishing malignant and borderline ovarian tumors, which suggests that miRNAs may hold significant clinical potential as a diagnostic tool. In summary, these ratio miRNA-based signatures may help to improve the precision of histological diagnosis, likely to provide a preoperative diagnosis in order to adapt surgical procedures.

Identification of novel potential genes in testicular germ cell tumors: A transcriptome analysis.

Testicular germ cell tumors (TGCTs), containing pure seminoma and non-seminoma, occupy the most majority of testicular cancers in adolescents and young men, which has increased dramatically in recent decades. Therefore, it is important to find crucial genes for improving diagnosis and prognosis in TGCTs. However, the diagnostic and prognostic markers of TGCTs are limited. In this study, our main objective is to explore novel potential genes that can be used as diagnostic and prognostic biomarkers in TGCTs. Our study detected 732 differentially expressed genes (DEGs) using three microarray expression profiling datasets from Gene Expression Omnibus (GEO). Multiple analysis was performed to identify the roles of DEGs, including pathway and functional enrichment analysis, protein-protein interaction (PPI) network analysis, module analysis, and survival analysis. In total, 322 upregulated genes and 406 downregulated genes were identified as DEGs The functional and pathway enrichment analysis shows that DEGs were highly enriched in multiple biological attributes such as T cell activation, reproduction in multicellular organism, sperm flagellum, antigen processing and presentation Then, seven potential crucial genes were identified via PPI network analysis, module analysis, and survival analysis. Furthermore, 7 potential crucial genes had shown to play a key role in regulating immune cell infiltration level in patients with TGCTs. We identified seven potential crucial genes (LAPTM5, NCF2, PECAM1, CD14, COL4A2, ANPEP and RGS1), which may be molecular markers in improving the way of diagnosis and prognosis in TGCTs.

Molecular mechanism of a novel root-end filling material containing zirconium oxide on the osteogenic/odontogenic differentiation of human osteosarcoma MG-63 cells.

Although the novel root-end filling material containing zirconium oxide (NRFM-Zr) which is hydroxyapatite-based may promote osteoblast differentiation, the molecular mechanism remains unclear. The aim of this study is to investigate it underlying the osteogenic/odontogenic differentiation of human osteosarcoma MG-63 cells induced by NRFM-Zr, compared with calcium silicate-based mineral trioxide aggregate (MTA), and glass ionomer cement (GIC). Firstly, three different types of root filling materials were co-cultured with MG-63 cells, and their cell toxicity, alkaline phosphatase (ALP) activity, and calcium ion concentration were evaluated. Next, gene expression profiling microarray was employed to analyze the impact of the materials on the gene expression profile of MG-63 cells. The results of cell viability revealed that NRFM-Zr group had no significant difference compared to the negative control group. After 5 and 7days of cultivation, both the NRFM-Zr and MTA groups exhibited significantly higher ALP activity compared to the negative control (p < 0.05). Moreover, the NRFM-Zr group had the highest calcium ion concentration, while the GIC group was the lowest (p < 0.05). Gene expression profiling microarray analysis identified 2915 (NRFM-Zr), 2254 (MTA) and 392 (GIC) differentially expressed genes, respectively. GO functional and KEGG pathway analysis revealed that differentially expressed genes of NRFM-Zr, MTA and GIC participated in 8, 6 and 0 differentiation-related pathways, respectively. Comparing the molecular mechanisms of osteogenic/odontogenic differentiation induced by hydroxyapatite-based NRFM-Zr and calcium silicate-based MTA, it was found that they shared similarities in their molecular mechanisms of promoting osteogenic differentiation. NRFM-Zr primarily promotes differentiation and inhibits cell apoptosis, thereby enhancing osteogenic/odontogenic differentiation of MG-63 cells. Furthermore, the inducing efficacy of NRFM-Zr was found to be superior to MTA.

The p65-LOC727924-miR-26a/KPNA3-p65 regulatory loop mediates vasoactive intestinal peptide effects on osteoarthritis chondrocytes.

Loss and dysfunction of articular chondrocytes, which disrupt the homeostasis of extracellular matrix formation and breakdown, promote the onset of osteoarthritis (OA). Targeting inflammatory pathways is an important therapeutic strategy for OA. Vasoactive intestinal peptide (VIP) is an immunosuppressive neuropeptide with potent anti-inflammatory effects; however, its role and mechanism in OA remain unclear. In this study, microarray expression profiling from the Gene Expression Omnibus database and integrative bioinformatics analyses were performed to identify differentially expressed lncRNAs in OA samples. qRT-PCR validation of the top ten different expressed lncRNAs indicated that the expression level of intergenic non-protein coding RNA 2203 (LINC02203, also named LOC727924) was the highest in OA cartilage compared to normal cartilage. Hence, the LOC727924 function was further investigated. LOC727924 was upregulated in OA chondrocytes, with a dominant sub-localization in the cytoplasm. In OA chondrocytes, LOC727924 knockdown boosted cell viability, suppressed cell apoptosis, reactive oxygen species (ROS) accumulation, increased aggrecan and collagen II, decreased matrix metallopeptidase (MMP)-3/13 and ADAM metallopeptidase with thrombospondin type 1 motif (ADAMTS)-4/5 levels, and reduced the levels of tumor necrosis factor alpha (TNF-α), interleukin 1 beta (IL-1β), and interleukin 6 (IL-6). LOC727924 could interact with the microRNA 26a (miR-26a)/ karyopherin subunit alpha 3 (KPNA3) axis by competitively targeting miR-26a for KPNA3 binding, therefore down-regulating miR-26a and upregulating KPNA3; in OA chondrocytes, miR-26a inhibition partially abolished LOC727924 knockdown effects on chondrocytes. miR-26a inhibited the nuclear translocation of p65 through targeting KPNA3 and p65 transcriptionally activated LOC727924, forming a p65-LOC727924-miR-26a/KPNA3-p65 regulatory loop to modulate OA chondrocyte phenotypes. In vitro, VIP improved OA chondrocyte proliferation and functions, down-regulated LOC727924, KPNA3, and p65 expression, and upregulated miR-26a expression; in vivo, VIP ameliorated destabilization of the medial meniscus (DMM)-induced damages on the mouse knee joint, down-regulated KPNA3, inhibited the nuclear translocation of p65. In conclusion, the p65-LOC727924-miR-26a/KPNA3-p65 regulatory loop modulates OA chondrocyte apoptosis, ROS accumulation, extracellular matrix (ECM) deposition, and inflammatory response in vitro and OA development in vivo, being one of the mechanisms mediating VIP ameliorating OA.

Integrated molecular-network analysis reveals infertility-associated key genes and transcription factors in the non-obstructive azoospermia

BackgroundMale infertility is a multifactorial reproductive health problem with complex causes. Non-obstructive azoospermia (NOA) is characterized by failure of spermatogenesis, leading to the absence of spermatozoa in ejaculates. The molecular mechanism underlying the NOA is still not well understood. ObjectivesThis study aims to identify the key genes involved in male infertility that could be a potential biomarker in the diagnosis and prognosis of azoospermia. Study designThe microarray expression profiles dataset GSE45885 and GSE45887 were downloaded from the NCBI's Gene Expression Omnibus (GEO) database and analyzed for male infertility-associated differentially expressed genes (DEGs) using the GEO2R tool. The common DEGs between the two datasets were combined and their protein–protein interaction (PPI) network was constructed using Cytoscape to reveal the hub genes by topology and module analysis. In addition, transcription factors (TFs) and protein kinases regulating the hub genes were identified using the X2K tool. Then, the expression of the hub genes was validated by analyzing the GSE190752 microarray dataset. Further, the PPI network was screened for biological roles and enriched pathways using DAVID software. ResultsAbout 256 DEGs associated with NOA were identified and constructed the PPI network to find the infertility-associated proteins. The biological processes linked with these proteins were spermatogenesis, cell differentiation, flagellated sperm motility, and spermatid development. The topology and module analysis of the infertility-associated protein network identified the hub genes TEX38, FAM71F, PRR30, FAM166A, LYZL6, TPPP2, ARMC12, SPACA4, and FAM205A, which were found to be upregulated in the non-obstructive azoospermia. In addition, a total of 23 transcription factors and 3 protein kinases that are regulating these key hub genes were identified. Further these hub genes expression was validated using the microarray data and found that their expression was increased in the testicular biopsies obtained from NOA subjects, compared to healthy individuals. ConclusionThe identified key genes and its associated transcription factors are known to regulate the infertility-related processes in the non-obstructive azoospermia. Also, the clinical sample-based microarray data validation for the expression of these key hub genes indicates their potentiality to develop them as diagnostic or prognostic biomarkers for NOA.

Influence of GO-Antisense miRNA-21 on the Expression of Selected Cytokines at Glioblastoma Cell Lines.

Graphene oxide (GO) is a single layer of carbon atoms with unique properties, which are beneficial due to its surface functionalisation by miRNA. miRNAs are a non-coding small form of RNA that suppress the expression of protein-coding genes by translational repression or degradation of messenger RNA. Antisense miRNA-21 is very promising for future investigation in cancer therapy. This study aimed to detect cytokine expression levels after the administration of GO-antisense miRNA-21 into U87, U118, U251 and T98 glioma cell lines. U87, U118, U251 and T98 glioma cell line were investigated in term of viability, human cytokine expression level at protein and genes after treatment with GO, GO-antisense miRNA-21 and antisense miRNA-21. The delivery of antisense miRNA-21 into the glioma cell at in vitro investigation were conducted by GO based transfection and electroporation. The results of the protein microarray and gene expression profile showed that complexes of GO-antisense miRNA-21 modified the metallopeptidase inhibitor 2 (TIMP-2), interleukin-6 (IL-6), interleukin 8 (IL-8), intercellular adhesion molecule 1 (ICAM-1), and monocyte chemoattractant protein-1 (MCP-1) expression level compared to transfection by electroporation of antisense miRNA-21 at investigated glioblastoma cell lines. The TIMP-2 protein and gene expression level was upregulated after antisense miRNA-21 delivery by GO complex into U87, U251 and T98 glioblastoma cell lines comparing to the non-treated control group. The downregulation at protein expression level of ICAM - 1 was observed at U87, U118, U251 and T98 glioma cell lines. Moreover, the IL-8 expression level at mRNA for genes and protein was decreased significantly after delivery the antisense-miRNA-21 by GO compared to electroporation as a transfection method. This work demonstrated that the graphene oxide complexes with antisense miRNA-21 can effectively modulate the cytokine mRNA and protein expression level at U87, U118, U251 and T98 glioma cell lines.