Identification of novel N7-methylguanine-related gene signatures associated with ulcerative colitis and the association with biological therapy.

OBJECTIVE: Ulcerative colitis (UC) is an inflammatory disease characterized by recurrent episodes of chronic intestinal inflammation. It is closely associated with immune dysregulation in the intestines. However, the mechanisms underlying the role of immune-related N7-methylguanosine (m7G) internal modification in UC remain unclear. METHODS: We conducted a screening of differentially expressed genes (DEGs) associated with m7G and performed immune infiltration analysis. We then investigated the correlation between m7G-related DEGs and immune cells or pathways. To further explore the functional implications, we conducted functional enrichment analysis to identify gene modules that strongly correlated with hub gene expression. In addition, we constructed a miRNA regulatory network for the hub genes in UC. Furthermore, we examined the association between hub genes and disease remission in UC patients undergoing biologic therapy. RESULTS: We obtained 13 m7G-related DEGs and conducted an in-depth analysis of immune infiltration. Among them, we identified five hub genes (NUDT7, NUDT12, POLR2H, QKI, and PRKCB) that showed diagnostic potential for UC. Through WGCNA and KEGG analysis, we found that gene modules strongly correlated with m7G hub gene expression were enriched in inflammation-related pathways. Furthermore, Kaplan-Meier survival analysis revealed a significant association between changes in hub gene expression levels and disease remission in UC patients undergoing biologic therapy. CONCLUSION: The findings of this study demonstrate that five m7G-related DEGs, including the m7G-modified recognition protein QKI, play a key role in the occurrence and progression of UC intestinal inflammation, which is closely related to intestinal immunity. These results provide valuable insights into the mechanisms of m7G modification in UC development and offer new perspectives for exploring novel therapeutic targets for UC.

Prediction and Verification of Potential Therapeutic Targets for Non-Responders to Infliximab in Ulcerative Colitis.

Background: Infliximab (IFX) has been widely used in ulcerative colitis (UC) patients. However, the subsequent effective treatment of IFX non-response in UC patients remains a challenge. This study aims to predict potential therapeutic targets for non-responders by performing a bioinformatic analysis of the data in the Gene Expression Omnibus (GEO) database and validation by biopsies. Methods: Colonic mucosal biopsies expression profiles of IFX-treated UC patients (GSE73661, GSE16879) were utilized to predict potential therapeutic targets. Bioinformatics analyses were used to explore potential biological mechanisms. CytoHubba was performed to screen hub genes. We used a validation dataset and colonic mucosal biopsies of UC patients to validate hub genes. Results: A total of 147 DEGs were identified (119 upregulated genes and 28 downregulated genes). GSEA showed that DEGs in GSE73661 were enriched in the pathways of the cytokine-cytokine receptor, the chemokine, and the adhesion molecules system. Based on the PPI network analysis, we identified four hub genes (and the transcription factor NF-κB). Then, we validate the expression of hub genes by reverse transcription-polymerase chain reaction (RT-PCR). We found higher expression of IL-6, IL1B, CXCL8, and CCL2 in non-responders compared to responders. Conclusion: In summary, four potential targets (IL-6, IL1B, CXCL8, and CCL2) were finally identified by performing a bioinformatics analysis of the datasets in the GEO database. Their expression was confirmed in colonic mucosal biopsies of patients with UC. These results can help to further explore the mechanism of non-responders to IFX in UC and to provide potential targets for their subsequent treatment.

Identification of gene signatures associated with ulcerative colitis and the association with immune infiltrates in colon cancer.

Background: Inflammatory bowel diseases, including ulcerative colitis (UC) and Crohn's disease, are some of the most common inflammatory disorders of the gastrointestinal tract. The dysfunction of the immune system in the intestines is suggested to be the underlying cause of the pathogenesis of UC. However, the mechanisms regulating these dysfunctional immune cells and inflammatory phenotypes are still unclear. Methods: The differential expression analysis on microarray datasets were performed including GSE24287, GSE87466, GSE102133, and GSE107499, including 376 samples. "Gene Ontology" and "Kyoto Encyclopedia of Genes and Genomes" pathway enrichment analyses were conducted to identify the common differentially expressed genes (DEGs) in these datasets and explore their underlying biological mechanisms. Further algorithms like "Cell-type Identification by Estimating Relative Subsets of RNA Transcripts" were used to determine the infiltration status of immune cells in patients with UC. "Cytoscape" and "Gene Set Enrichment Analysis" were used to screen for hub genes and to investigate their biological mechanisms. The Tumor Immune Estimation Resource database was used to study the correlation between hub genes and infiltrating immune cells in patients with UC. A total of three hub genes, CCL3, MMP3, and TIMP1, were identified using Cytoscape. Results: A positive correlation was observed between these hub genes and patients with active UC. These genes served as a biomarker for active UC. Moreover, a decrease in CCL3, MMP3, and TIMP1 expression was observed in the mucosa of the intestine of patients with active UC who responded to Golimumab therapy. In addition, results show a significant positive correlation between CCL3, MMP3, and TIMP1 expression and different immune cell types including dendritic cells, macrophages, CD8+ T cells, and neutrophils in patients with colon cancer. Moreover, CCL3, MMP3, and TIMP1 expression were strongly correlated with different immune cell markers. Conclusion: Study results show the involvement of hub genes like CCL3, MMP3, and TIMP1 in the pathogenesis of UC. These genes could serve as a novel pharmacological regulator of UC. These could be used as a therapeutic target for treating patients with UC and may serve as biomarkers for immune cell infiltration in colon cancer.

LCK, FOXC1 and hsa-miR-146a-5p as potential immune effector molecules associated with rheumatoid arthritis.

Rheumatoid arthritis (RA) is a type of systemic immune disease characterized by chronic inflammatory disease of the joints. However, the aetiology and underlying molecular events of RA are unclear. Here, we applied bioinformatics analysis to identify potential immune effector molecules involved in RA. The three microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. We used the R software screen 115 overlapping differentially expressed genes (DEGs). Subsequently, we constructed a protein-protein interaction (PPI) network encoded by these DEGs and identified 10 genes closely associated with RA - LCK, GZMA, GZMB, CD2, LAG3, IL-15, TNFRSF4, CD247, CCR5 and CCR7. Furthermore, in the miRNA-hub gene networks, we screened out hsa-miR-146a-5p, which is the miRNA controlling the largest number of hub genes. Finally, we found some transcription factors that closely interact with hub genes, such as FOXC1, GATA2, YY1, RUNX2, SREBF1, CEBPB and NFIC. This study successfully predicted that LCK, FOXC1 and hsa-miR-146a-5p can be used as potential immune effector molecules of RA. Our study may have potential implications for future prediction of disease progression in patients with symptomatic RA, and has important significance for the pathogenesis and targeted therapy of RA.

The importance of regulatory pathway mediated by Circ0001955 in colorectal cancer.

INTRODUCTION: Colorectal cancer (CRC) has become one of the most common cancers in recent years. Given the importance that non-coding RNAs have recently acquired in various diseases including cancers, we decided to design this study to evaluate the expression levels of circ0001955/miR-145-5p/ONECUT2 axis in CRC. METHODS: After bioinformatics analysis of GEO datasets related to CRC, a putative circ0001955/ miR-145-5p/ ONECUT2 pathway was assumed. Then, the expression levels of these genes were measured in 50 CRC samples and adjacent tissues by qRT- PCR. Also, correlation coefficients, receiver operating characteristic (ROC) curves, and correlation between circ0001955 levels with clinicopathological parameters of patients were analyzed. RESULTS: Circ0001955 and ONECUT2 were considerably up-regulated, while the expression level of miR-145-5p was decreased in CRC samples compared with adjacent tissues (p < 0.05). Moreover, statistically significant correlations were observed between expression levels of circ0001955, miR-145-5p, and ONECUT2. We did not find any significant correlation between circ0001955 expression and clinicopathological parameters. CONCLUSION: Our study showed that circ0001955 is dysregulated in CRC. This finding can open a new window for researchers for a better understanding of the potential pathways involved in CRC pathogenesis and, consequently, to find new treatment pathways.

Computational Analysis of the Immune Infiltration Pattern and Candidate Diagnostic Biomarkers in Lumbar Disc Herniation.

Objectives: Lumbar disc herniation (LDH) is a musculoskeletal disease that contributes to low back pain, sciatica, and movement disorder. Existing studies have suggested that the immune environment factors are the primary contributions to LDH. However, its etiology remains unknown. We sought to identify the potential diagnostic biomarkers and analyze the immune infiltration pattern in LDH. Methods: The whole-blood gene expression level profiles of GSE124272 and GSE150408 were downloaded from the Gene Expression Omnibus (GEO) database, including that of 25 patients with LDH and 25 healthy volunteers. After merging the two microarray datasets, Differentially Expressed Genes (DEGs) were screened, and a functional correlation analysis was performed. The Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithm and support vector machine recursive feature elimination (SVM-RFE) were applied to identify diagnostic biomarkers by a cross-validation method. Then, the GSE42611 dataset was used as a validation dataset to detect the expression level of these diagnostic biomarkers in the nucleus pulposus and evaluate their accuracy. The hub genes in the network were identified by the CIBERSORT tool and the Weighted Gene Coexpression Network Analysis (WGCNA). A Spearman correlation analysis between diagnostic markers and infiltrating immune cells was conducted to further illustrate the molecular immune mechanism of LDH. Results: The azurophil granule and the systemic lupus erythematosus pathway were significantly different between the healthy group and the LDH group after gene enrichment analysis. The XLOC_l2_012836, lnc-FGD3-1, and scavenger receptor class A member 5 were correlated with the immune cell infiltration in various degrees. In addition, five hub genes that correlated with LDH were identified, including AQP9, SIRPB2, SLC16A3, LILRB3, and HSPA6. Conclusion: The XLOC_l2_012836, lnc-FGD3-1, and SCARA5 might be adopted for the early diagnosis of LDH. The five identified hub genes might have similar pathological mechanisms that contribute to the degeneration of the lumbar disc. The identified hub genes and immune infiltrating pattern extend the knowledge on the potential functioning mechanisms, which offer guidance for the development of therapeutic targets of LDH.

Weighted gene co-expression network analysis reveals prognostic and diagnostic significance of PAQR4 in patients with early and late hepatocellular carcinoma.

Background: This study aimed to reveal novel markers for prognostic and diagnostic prediction of hepatocellular carcinoma (HCC). Methods: We applied The Cancer Genome Atlas (TCGA) data to screen differentially expressed genes (DEGs). We identified hub modules and genes using weighted gene co-expression network analysis (WGCNA). After verification with the GSE36376 dataset, hub genes were further identified. The expression of progestin and adipoQ receptor 4 (PAQR4) was confirmed in HCC by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The diagnostic and prognosis value of PAQR4 was assessed. The expression of PAQR4 was verified using the GSE76427 dataset. Results: A total of 803 DEGs were obtained between HCC and normal tissue. Through WGCNA, 7 hub modules were screened, among which the blue module was selected to identify the hub genes associated with the HCC. After overlapping all the DEGs with 837 genes of the blue module, we obtained 466 DEGs that were defined as hub genes. Among the hub genes, 239 were related to staging. After verifying with the GSE36376 dataset, PAQR4 was identified as the real hub gene of HCC. The results of qRT-PCR revealed that PAQR4 was upregulated between HCC and normal tissue. Furthermore, PAQR4 was related to the diagnosis and prognosis of patients with HCC. Moreover, the GSE76427 verification results of PAQR4 were consistent with our integration and qRT-PCR results. Ultimately, high expression of PAQR4 was significantly related to cell cycle, DNA replication, and the p53 signaling pathway. Conclusions: The PAQR4 gene may be associated with the prognosis and diagnosis of HCC.

Identification of Immune-Related Gene Signature and Prediction of CeRNA Network in Active Ulcerative Colitis.

Background: Ulcerative colitis (UC) is an inflammatory disease of the intestinal mucosa, and its incidence is steadily increasing worldwide. Intestinal immune dysfunction has been identified as a central event in UC pathogenesis. However, the underlying mechanisms that regulate dysfunctional immune cells and inflammatory phenotype remain to be fully elucidated. Methods: Transcriptome profiling of intestinal mucosa biopsies were downloaded from the GEO database. Robust Rank Aggregation (RRA) analysis was performed to identify statistically changed genes and differentially expressed genes (DEGs). Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to explore potential biological mechanisms. CIBERSORT was used to evaluate the proportion of 22 immune cells in biopsies. Weighted co-expression network analysis (WGCNA) was used to determine key module-related clinical traits. Protein-Protein Interaction (PPI) network and Cytoscape were performed to explore protein interaction network and screen hub genes. We used a validation cohort and colitis mouse model to validate hub genes. Several online websites were used to predict competing endogenous RNA (ceRNA) network. Results: RRA integrated analysis revealed 1838 statistically changed genes from four training cohorts (adj. p-value < 0.05). GSEA showed that statistically changed genes were enriched in the innate immune system. CIBERSORT analysis uncovered an increase in activated dendritic cells (DCs) and M1 macrophages. The red module of WGCNA was considered the most critical module related to active UC. Based on the results of the PPI network and Cytoscape analyses, we identified six critical genes and transcription factor NF-κB. RT-PCR revealed that andrographolide (AGP) significantly inhibited the expression of hub genes. Finally, we identified XIST and three miRNAs (miR-9-5p, miR-129-5p, and miR-340-5p) as therapeutic targets. Conclusions: Our integrated analysis identified four hub genes (CXCL1, IL1B, MMP1, and MMP10) regulated by NF-κB. We further revealed that AGP decreased the expression of hub genes by inhibiting NF-κB activation. Lastly, we predicted the involvement of ceRNA network in the regulation of NF-κB expression. Collectively, our results provide valuable information in understanding the molecular mechanisms of active UC. Furthermore, we predict the use of AGP and small RNA combination for the treatment of UC.

Integrating SWATH-MS proteomics and transcriptome analysis to preliminarily identify three DEGs as biomarkers for proliferative diabetic retinopathy.

PURPOSE: We intended to preliminarily find differentially expressed proteins that play crucial roles in proliferative diabetic retinopathy (PDR), and lay the foundation for subsequent further research on the mechanism. EXPERIMENTAL DESIGN: Here, we developed a new strategy integrated the sequential windowed acquisition of all theoretical fragment ion (SWATH) mass spectra (MS) with multi-dataset joint analysis to screen for the PDR plasma biomarker. The annotation of the given gene list was performed with ClueGO function analysis. Additionally, the protein-protein interaction relationship was also revealed by the STRING database. RESULTS: In SWATH-MS assays, we identified 23 upregulated and 13 downregulated proteins in PDR plasma. In the mRNA database analysis, 375 genes were identified as differentially expressed genes in GSE102485. Only three genes (FCGR3A, DPEP2, and ADGRF5) were characterized as upregulated in both the dataset and the SWATH-MS list. The area under the ROC curve (AUC) of FCGR3A, DPEP2, and ADGRF5 in distinguishing PDR from others was 0.739, 0.770, and 0.739. CONCLUSIONS AND CLINICAL RELEVANCE: We provide a novel strategy for biomarker screening and identified plasma FCGR3A, DPEP2, and ADGRF5 as potential biomarkers for patients with PDR. Identifying the key molecules of the disease is essential for the development of new therapeutic molecules and new uses of existing drugs.

Development and Validation of a Prognostic Index Based on Genes Participating in Autophagy in Patients With Lung Adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is a deadly respiratory system malignancy with poor prognosis. Autophagy is essential for the beginning, development, and therapy resistance of cancer. However, the expression of genes participating in autophagy in LUAD and their associations with prognosis remain unclear. METHODS: Predictive genes participating in autophagy in LUAD samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were investigated. TCGA and GEO cohorts were divided into two risk groups, while the low-risk group having a longer overall survival (OS) time. This article aims to point out the interaction between genes participating in autophagy and immune function, immune checkpoints, and m6a in LUAD. The prediction model was designed for exploring least absolute shrinkage and selection operator (LASSO) regression. It has been revealed that gene expression and autophagy are inextricably connected. RESULTS: Genes participating in autophagy were shown to be somewhat overexpressed in the high-risk group even though no different clinical symptoms were present, indicating that they might be used in a model to predict LUAD prognosis. The majority of genes participating in autophagy prognostic signatures controlled immunological and tumor-related pathways, according to gene set enrichment analysis (GSEA). KRT6A, KYNU, IGFBP1, DKK1, PKP2, PLEK2, GAPDH, FLNC, and NTSR1 might be related to the oncology process for LUAD patients. CERS4, CMAHP, and PLEKHB1 have been identified as being associated with low risk in patients with LUAD. Furthermore, the immune function and m6a gene expression differed significantly between the two groups. CONCLUSIONS: Genes participating in autophagy are connected to the development and progression of LUAD. LUAD patients' prognoses are often foreseen utilizing matched prognostic models. Genes participating in autophagy in LUAD may be therapeutic targets that ought to be investigated more.

The two-way regulation molecular network mechanism of Taohechengqi decoction in prevention and treatment of stroke based on vascular endothelial growth factor signaling pathway/tumor necrosis factor signaling pathway / 药学学报

Stroke has been harmful to human health for a long time, and there is no satisfactory treatment strategy because of its complex pathogenesis. Taohechengqi decoction has been effective in the treatment of stroke. In this study, the components were collected by TCMSP, TCMIP, BATMAN-TCM and TCMID databases, the targets were predicted and screened by PharmMapper and BATMAN-TCM databases, and the functional enrichment analysis of the targets was carried out by using R language package clusterProfiler. Finally, the key targets are verified by GEO database and molecular docking. The results showed that 51 active components of Taohechengqi decoction may regulate 15 key targets such as nitric oxide synthase, endothelial (NOS3), prostaglandin G/H synthase 2 (PTGS2), matrix metalloproteinase-9 (MMP9), affecting vascular endothelial growth factor signaling pathway and other pathways to play a role in the prevention of stroke, affecting tumor necrosis factor signaling pathway and other pathways to play a role in the treatment of stroke. GEO data analysis showed that androgen receptor (AR), caspase-8 (CASP8), intercellular adhesion molecule 1 (ICAM1), interleukin-1 beta (IL1B), mitogen-activated protein kinase 14 (MAPK14), MMP9, myeloperoxidase (MPO), peroxisome proliferator-activated receptor gamma (PPARG), PTGS2 and cellular tumor antigen p53 (TP53) were up-regulated genes, while serum albumin (ALB), estrogen receptor 1 (ESR1), NOS3, transcription factor p65 (RELA) and proto-oncogene tyrosine-protein kinase Src (SRC) were down-regulated genes. GEO analysis explained that Taohechengqi decoction may prevent stroke by down-regulating ESR1, NOS3, and treat stroke by up-regulating ICAM1, IL1B, MAPK14, MMP9, PPARG, PTGS2, TP53, and down-regulating RELA and SRC. The study found that in the process of prevention and treatment of stroke, Taohechengqi decoction played a two-way regulation role through multi-genes and multiple ways, which provided a new strategy for the treatment of stroke.

Mitotic checkpoint kinase Mps1/TTK predicts prognosis of colon cancer patients and regulates tumor proliferation and differentiation via PKCα/ERK1/2 and PI3K/Akt pathway.

Mps1/TTK plays an important role in development of many tumors. The purpose of the present study was designed to investigate the role of TTK in colon cancer. We analyzed TTK and colon cancer in the GEO database, colon cancer tissues and normal tissues were collected to verify the results by immunohistochemistry. We detected the TTK expression in the colon cancer cell lines, and overexpressed or silenced TTK expression in colon cancer cell lines. GEO database showed that the expression of TTK was higher in the colon cancer tissues than normal tissues, higher level of TTK shows unfavourable prognosis in colon patients. Furthermore, high differentiation of colon shows the lower expression of TTK. The higher expression of TTK links with the high microsatellite status. However, the expression of TTK has no significant difference among the different stages of colon cancer patients, and has no significant relationship with recurrence or relapse. Here, we also report that the differential expression of TTK in colon cancer cells alters the intrinsic negative regulation of cell proliferation and differentiation, resulting in the difference of proliferation and differentiation capacity. TTK could activate the PKCα/ERK1/2 to influence the proliferation and inactivate the PI3K/AKT pathway to inhibition the expression of MUC2 and TFF3 that related to the differentiation of colon cells. In conclusions, TTK promote the colon cancer cell proliferation via activation of PKCα/ERK1/2 and inhibit the differentiation via inactivation of PI3K/Akt pathway. TTK inhibition may be the potential therapeutic pathway for the treatment of colon cancer.

Analysis of methylation datasets identified significantly changed genes and functional pathways in osteoarthritis.

BACKGROUND: Researches indicate that epigenetics was involved in osteoarthritis (OA). The purpose of this study was to describe the alterations of DNA methylation in hip and knee OA by comparing DNA methylome of OA cartilage and non-OA samples and to identify novel genes and pathways associated with OA. METHODS: We gained two expression profiling datasets (GSE73626 and GSE63695) from the GEO dataset. The RnBeads in R package was used to identify differentially methylated CpG sites. Genes that showed significant differences in DNA methylation between OA and normal control groups underwent functional annotation analysis using the online tool of GeneCodis. Furthermore, we used the Sequenom MassARRAY platform (CapitalBio, Beijing, China) to perform the quantitative methylation analysis. RESULTS: A total of 249 hypermethylated sites and 96 hypomethylated sites were obtained from OA samples compared with normal control samples. Functional analysis of differentially methylated genes obtained that embryonic skeletal system morphogenesis, cartilage development, and skeletal system development may be involved in the pathogenesis of OA. Eight genes including HOXB3, HOXB4, HOXB6, HOXC4, HOXC10, HOXD3, TBX3, and TBX5 were identified as potential novel biomarkers for OA. CONCLUSION: Taken together, our study found different molecular characteristics between OA patients and normal controls. This may provide new clues to elucidate the pathogenesis of OA.Key Points• Embryonic skeletal system morphogenesis, cartilage development, skeletal system development may be involved in the pathogenesis of OA.• Eight genes are identified as potential novel markers for OA.• Our future in vivo molecular intervention experiments will extend our current findings.

Cytokine and molecular networks in sepsis cases: a network biology approach.

Sepsis is a life-threatening condition of organ dysfunction caused by a dysregulated host immune response to infection. We performed network analysis of cytokine molecules and compared network structures between a systematic inflammatory response syndrome (SIRS) or normal control (NC) group and a sepsis group. We recruited SIRS (n = 33) and sepsis (n = 89) patients from electronic medical records (EMR) according to whether data on PCT, CRP, interleukin (IL)-1ß, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12p70, IL-13, IL-17, IL-22, TNF-α, and IFN-γ levels were available. From the public GEO dataset, GSE66099, GSE9960, GSE95233, GSE57065 were downloaded. Genes corresponding to 15 molecules were extracted from an expression array. A correlation matrix was formed for the 15 molecules and statistically significant molecular pairs were used as pairs for network analysis of coexpression. The number of molecular or gene expression pairs significantly correlated among the SIRS or control and sepsis groups are as follows for datasets: EMR, 15 and 15; GEO66099-1, 13 and 15; GEO9960, 13 and 11; GSE95233, 13 and 8; GSE66099-2, 15 and 14; GSE57065, 14 and 13, respectively. Network analysis revealed that network diameter, number of nodes and shortest path were equal to or lower in the sepsis group. The coexpression network in sepsis patients was relatively small sized and had lower shortest paths compared with the SIRS group or healthy control group. Cytokines with one degree (k = 1) are increased in sepsis group compared with SIRS or healthy control group. IL-9 and IL-2 were not included in network of sepsis group indicating that these cytokines showed no correlation with other cytokines. These data might imply that cytokines tend to be dysregulated in the sepsis group compared to that of SIRS or normal control groups.

[Investigation on the role and mechanism of prostagland in D2 synthase in non-small cell lung cancer].

Objective: To investigate prostaglandin D2 synthase (PTGDS) expression in non-small cell lung carcinoma (NSCLC) and clarify whether PTGDS could be a biomarke. Methods: Firstly, the protein expression level of PTGDS in adenocarcinoma (ADC) and squamous cell carcinoma (SCC) were analyzed respectively through Gene Expression Omnibus (GEO)dataset. Then, the results were verified by using tissue microarray (TMA). At last, in order to explore the inner mechanism, lung adenocarcinoma cell lines A549 and Calu-3 were selected to over-express PTGDS, and then transwell chamber assay and Western blotting were used to detect associated changes. Results: PTGDS expression is down-regulated in both ADC and SCC, however, no statistical difference has been found between the two groups, and PTGDS was only related to the progression of ADC. Furthermore, After over-expression of PTGDS, the invasiveness of ADC cells was significantly decreased. Western blotting showed that the inner mechanisms may be related to mitogen-activated protein kinase (MAPK) signal pathway. Conclusions: This study revealed that PTGDS was down-regulated in NSCLC and only related to the development of ADC. It may be a potential biomarker for the diagnosis and prognosis of NSCLC. However, whether it could be used for the treatment of NSCLC still needs more research.

Identified key genes related to carotid atheroma plaque from gene expression chip.

As one of the leading reason in morbidity and death in the world, atherosclerosis is usually associated with vessel stenosis, ulceration, and inflammatory cell infiltration. However, the formation mechanism of atheroma plaque is unknown. In this research, we have used bioinformatics tools to identify 118 differential expression genes from a GEO dataset. Besides, we also revealed KYNU as a crucial gene in atheroma plaque development.

Lower DSC1 expression is related to the poor differentiation and prognosis of head and neck squamous cell carcinoma (HNSCC).

PURPOSE: Although desmocollins have an important position in cancer-related research, there are little reports about the relations between cancers and desmocollin 1 (DSC1). The present study was designed to investigate the correlations between DSC1 and head and neck squamous cell carcinoma (HNSCC). METHODS: First we analyzed the GEO database; then, HNSCC and pericarcinous tissues were collected to verify the results. DSC1 expression was detected by western blot and real-time PCR. The co-expression genes of DSC1 were extracted from Cancer Cell Line Encyclopedia database (CCLE database), and their correlation was analyzed in The Cancer Genome Atlas HNSCC database (TCGA HNSCC database). Next the gene ontology analysis (GO) was carried out. Moreover, we suppressed DSC1 in FaDu cell to investigate the internal mechanism. RESULTS: GEO database showed that DSC1 was higher in HNSCC and patients with higher DSC1 had unfavorable prognosis. The results of the samples showed that DSC1 was significantly higher in HNSCC than in normal tissue, which was consistent with the results of GEO database. The co-expression genes of DSC1 were extracted from CCLE database and verified in TCGA HNSCC database. It revealed that DSC1 was related to cell signal transduction. In FaDu/siDSC1 cells, the proliferation and migration were decreased compared to FaDu cells, and the expression levels of ß-catenin, c-myc and cyclin D1 down-regulated significantly. CONCLUSIONS: The increased expression of DSC1 can promote the occurrence of HNSCC and is associated with tumor. The increased expression of DSC1 also indicates a poor prognosis of the patients with HNSCC.

Down-regulation of neutrophil gelatinase-associated lipocalin in head and neck squamous cell carcinoma correlated with tumorigenesis, not with metastasis.

To examine the significance of the Neutrophil gelatinase-associated lipocalin (NGAL) in diagnosing head and neck squamous cell carcinoma (HNSCC) and predicting regional metastasis. We first used GEO dataset to analyze the NGAL gene expression in HNSCC. Then, we summarized the characteristics of patients retrospectively selected in clinic. Expression of NGAL protein in human HNSCC tumor, lymph node and normal samples were analyzed using immunohistochemistry. Next, we further investigated the NGAL expression in a tissue microassay to analyze the relationship between NGAL protein expression and TNM stage. Finally, we tested the NGAL protein expression in head and neck cancer cell lines. Analysis of GEO dataset concluded that NGAL gene expression in HNSCC was lower than that in normal tissue (P<0.01). There was no statistically significant difference of NGAL gene expression between T-stage and N-stage (P>0.05). NGAL protein expression in tumor was lower than that in normal tissue (P<0.01). There was no statistically significant difference of NGAL protein expression between metastasis group and non-metastasis group (P>0.05). Expression of NGAL protein was not correlated with TNM stage of HNSCC. Aggressive HNSCC cell lines have lower NGAL protein expression. Our data demonstrated that the expression of NGAL protein was correlated with tumorigenesis of HNSCC, but not with regional metastasis. It may serve as a novel biomarker for prognostic evaluation of patients with HNSCC.