circ_0000337 Promotes the Progression of Cervical Cancer by miR-155-5p/RAB3B Axis.

Current study aims to investigate the biological function of circular RNA (circRNA, circ_0000337) in cervical cancer (CC). Bioinformatic analyses were used to predict targets for circ_0000337 and miR-155-5p, and analyze the gene expression differences between cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) tissues and normal tissues. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were applied to assess mRNA and protein expressions of circ_0000337, microRNA-155-5p (miR-155-5p) and member RAS oncogene family (RAB3B), respectively. Following the establishment of gain/loss-of-function models, CCK-8 was performed to evaluate cell proliferation. Bioinformatics analysis, dual-luciferase reporter assay and RNA immunoprecipitation (RIP) were used to identify the interaction in circ_0000337, miR-155-5p, and RAB3B. Circ_0000337 and RAB3B were upregulated, while miR-155-5p was downregulated in CC tissues and cell lines. circ_0000337 overexpression promoted cell proliferation, circ_0000337 knock down inhibited cell proliferation by sponging miR-155-5p. RAB3B was a target of miR-155-5p which was positively regulated by circ_0000337. In the collected CC tissues, there was a negative correlation between miR-155-5p and circ_0000337 or RAB3B, and a positive correlation between circ_0000337 and RAB3B. miR-155-5p was positively, while RAB3B was negatively correlated with OS in patients with CC, and they were negatively correlated. In conclusion, circ_0000337 upregulates RAB3B by sponging miR-155-5p to promote CC cell proliferation.

Development of a necroptosis-related gene signature and the immune landscape in ovarian cancer.

BACKGROUND: Necroptosis is a novel type of programmed cell death distinct from apoptosis. However, the role of necroptosis in ovarian cancer (OC) remains unclear. The present study investigated the prognostic value of necroptosis-related genes (NRGs) and the immune landscape in OC. METHODS: The gene expression profiling and clinical information were downloaded from the TCGA and GTEx databases. Differentially expressed NRGs (DE-NRGs) between OC and normal tissueswere identified. The regression analyses were conducted to screen the prognostic NRGs and construct the predictive risk model. Patients were then divided into high- and low-risk groups, and the GO and KEGG analyses were performed to explore bioinformatics functions between the two groups. Subsequently, the risk level and immune status correlations were assessed through the ESTIMATE and CIBERSORT algorithms. The tumor mutation burden (TMB) and the drug sensitivity were also analyzed based on the two-NRG signature in OC. RESULTS: Totally 42 DE-NRGs were identified in OC. The regression analyses screened out two NRGs (MAPK10 and STAT4) with prognostic values for overall survival. The ROC curve showed a better predictive ability in five-year OS using the risk score. Immune-related functions were significantly enriched in the high- and low-risk group. Macrophages M1, T cells CD4 memory activated, T cells CD8, and T cells regulatory infiltration immune cells were associated with the low-risk score. The lower tumor microenvironment score was demonstrated in the high-risk group. Patients with lower TMB in the low-risk group showed a better prognosis, and a lower TIDE score suggested a better immune checkpoint inhibitor response in the high-risk group. Besides, cisplatin and paclitaxel were found to be more sensitive in the low-risk group. CONCLUSIONS: MAPK10 and STAT4 can be important prognosis factors in OC, and the two-gene signature performs well in predicting survival outcomes. Our study provided novel ways of OC prognosis estimation and potential treatment strategy.

ALKBH5-HOXA10 loop-mediated JAK2 m6A demethylation and cisplatin resistance in epithelial ovarian cancer.

BACKGROUND: Chemotherapy resistance remains a barrier to improving the prognosis of epithelial ovarian cancer (EOC). ALKBH5 has recently been shown to be one of the RNA N6-methyladenosine (m6A) demethyltransferases associated with various cancers, but its role in cancer therapeutic resistance remains unclear. This study aimed to investigate the role of AlkB homolog 5 (ALKBH5) in cisplatin-resistant EOC. METHODS: Functional assays were performed both in vitro and in vivo. RNA sequencing (RNA-seq), m6A-modified RNA immunoprecipitation sequencing (MeRIP-seq), chromatin immunoprecipitation, RNA immunoprecipitation, and luciferase reporter and actinomycin-D assays were performed to investigate RNA/RNA interaction and m6A modification of the ALKBH5-HOXA10 loop. RESULTS: ALKBH5 was upregulated in cisplatin-resistant EOC and promoted cancer cell cisplatin resistance both in vivo and in vitro. Notably, HOXA10 formed a loop with ALKBH5 and was found to be the upstream transcription factor of ALKBH5. HOXA10 overexpression also facilitated EOC cell chemoresistance both in vivo and in vitro. Collective results of MeRIP-seq and RNA-seq showed that JAK2 is the m6A-modified gene targeted by ALKBH5. The JAK2/STAT3 signaling pathway was activated by overexpression of the ALKBH5-HOXA10 loop, resulting in EOC chemoresistance. Cell sensitivity to cisplatin was rescued by ALKBH5 and HOXA10 knockdown or inhibition of the JAK2/STAT3 signaling pathway in EOC cells overexpressing ALKBH5-HOXA10. CONCLUSIONS: The ALKBH5-HOXA10 loop jointly activates the JAK2/STAT3 signaling pathway by mediating JAK2 m6A demethylation, promoting EOC resistance to cisplatin. Thus, inhibition of the expression of the ALKBH5-HOXA10 loop may be a potential strategy to overcome cisplatin resistance in EOC.

CXCL2-mediated ATR/CHK1 signaling pathway and platinum resistance in epithelial ovarian cancer.

Tumor microenvironment and chemokines play a significant role in cancer chemoresistance. This study was designed to reveal the important role of CXCL2 in platinum resistance in epithelial ovarian cancer (EOC). Differently expressed (DE) genes were screen out based on analysis of GSE114206 dataset in GEO database. The expression of DE chemokines was further validated in platinum- resistant and sensitive EOC. Cell viability assay and cell apoptosis assay were performed to explore the roles of CXCL2 in EOC. Cell stemness characteristics and the signaling pathway regulated by CXCL2 were also investigated in this study. As the results showed, CXCL2 was identified up-regulated in platinum-resistant EOC. The functional assays showed overexpressing CXCL2 or co-culturing with recombinant human CXCL2 promoted cell resistance to cisplatin. Conversely, knocking down CXCL2 or co-culturing with neutralizing antibody to CXCL2 increased cell response to cisplatin. CXCL2 overexpressing maintained cell stemness and activated ATR/CHK1 signaling pathway in EOC. Moreover, we further demonstrated that CXCL2-mediated resistance to cisplatin could be saved by SB225002, the inhibitor of CXCL2 receptor, as well as be rescued by SAR-020106, the inhibitor of ATR/CHK1 signaling pathway. This study identified a CXCL2-mediated mechanism in EOC platinum resistance. Our findings provided a novel target for chemoresistance prevention in EOC.

Identification of a Novel Immune Landscape Signature for Predicting Prognosis and Response of Endometrial Carcinoma to Immunotherapy and Chemotherapy.

Uterine Corpus Endometrial Carcinoma (UCEC) is the most common gynecological cancer. Here, we have investigated the significance of immune-related genes in predicting the prognosis and response of UCEC patients to immunotherapy and chemotherapy. Based on the Cancer Genome Atlas (TCGA) database, the single-sample gene-set enrichment analysis (ssGSEA) scores was utilized to obtain enrichment of 29 immune signatures. Univariate, multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to generate an immune-related prognostic signature (IRPS). The biological functions of IRPS-associated genes were evaluated using GSEA, Tumor Immune Estimation Resource (TIMER) Database analysis, Mutation analysis, Immunophenoscore (IPS) analysis, Gene Expression Profiling Interactive Analysis (GEPIA), Genomics of Drug Sensitivity in Cancer (GDSC) and Immune Cell Abundance Identifier (ImmuCellAI). Potential small molecule drugs for UCEC were predicted using the connectivity map (Cmap). The mRNA and protein expression levels of IRPS-associated genes were tested via quantitative real-time PCR (qPCR) and immunohistology. Two immune-related genes (CCL13 and KLRC1) were identified to construct the IRPS. Both genes were related to the prognosis of UCEC patients (P < 0.05). The IRPS could distinguish patients with different prognosis and was closely associated with the infiltration of several types of immune cells. Our findings showed that patients with low IRPS benefited more from immunotherapy and developed stronger response to several chemotherapies, which was also confirmed by the results of ImmuCellAI. Finally, we identified three small molecular drugs that might improve the prognosis of patients with high IRPS. IRPS can be utilized to predict the prognosis of UCEC patients and provide valuable information about their therapeutic response to immunotherapy and chemotherapy.

Construction of miRNA-mRNA Regulatory Network and Prognostic Signature in Endometrial Cancer.

INTRODUCTION: This bioinformatic study confirmed a new miRNA-mRNA regulatory network and a prognostic signature in endometrial cancer (EC). MATERIALS AND METHODS: We downloaded RNA-seq and miRNA-seq data of EC from the TCGA database, then used EdegR package to screen differentially expressed miRNAs and mRNAs (DE-miRNAs and DE-mRNAs). Then, we constructed a regulatory network of EC-associated miRNAs and hub genes by Cytoscape, and determined the expression of unexplored miRNAs in EC tissues and normal adjacent tissues by quantitative Real-Time PCR (qRT-PCR). A prognostic signature model and a predictive nomogram were constructed. Finally, we explored the association between the prognostic model and the immune cell infiltration. RESULTS: A total of 11,531 DE-mRNAs and 236 DE-miRNAs, as well as 275 and 118 candidate DEGs for upregulated and downregulated DE-miRNAs were screened out. The miRNA-mRNA network included 5 downregulated and 13 upregulated DE-miRNAs. qRT-PCR proved that the expression levels of miRNA-18a-5p, miRNA-18b-5p, miRNA-449c-5p and miRNA-1224-5p and their target genes (NR3C1, CTGF, MYC, and TNS1) were consistent with our predictions. Univariate and multivariate Cox proportional hazards regression analyses of the hub genes revealed a significant prognostic value of NR3C1, EZH2, AND GATA4, and these genes were closely related to eight types of immune infiltration cells. CONCLUSION: We identified three genes as candidate biomarkers for EC, which may provide a theoretical basis for targeted therapy.

IGF2BP1 overexpression stabilizes PEG10 mRNA in an m6A-dependent manner and promotes endometrial cancer progression.

Rationale: N6-methyladenosine (m6A) mRNA methylation is the most abundant chemical posttranscriptional modification in mRNA and is involved in the regulation of a number of biological processes. Insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1) has recently been reported as having the capacity to recognize m6A sites in mRNA and plays a role in regulating mRNA metabolization. However, it is unclear which genes IGF2BP1 targets to identify m6A sites and what are their respective functions in endometrial cancer (EC). Methods: Quantitative PCR, western blot and immunohistochemistry were used to measure IGF2BP1 expression in EC cell lines and tissues. Xenograft experiments were performed to examine the in vivo role of IGF2BP1 in EC cell growth. RNA-binding protein immunoprecipitation sequencing, methylated RNA-binding protein immunoprecipitation sequencing and RNA-sequencing were also conducted to identify potential IGF2BP1 targets involved in EC regulation. Co-immunoprecipitation and mass spectrometry were used to identify IGF2BP1-interacting proteins. Results: IGF2BP1 expression increased in EC, and high expression of this protein correlated with poor prognosis. IGF2BP1 overexpression/knockdown can promote (and inhibit) cell proliferation and regulate the tumor cell cycle and cancer progression, both in vivo and in vitro. Mechanistically, IGF2BP1 can recognize m6A sites in the 3' untranslated region (3'UTR) of Paternally Expressed Gene 10 (PEG10) mRNA and recruits polyadenylate-binding protein 1 (PABPC1) to enhance PEG10 mRNA stability, which consequently promotes PEG10 protein expression. Additionally, it would appear that a large number of PEG10 proteins bind p16 and p18 gene promoter sequences, thereby repressing expression and accelerating the cell cycle. Conclusion: This investigation found that IGF2BP1 has a crucial role in the m6A-dependent regulatory mechanism for endometrial cancer. This study provides new insights into our understanding of disease progression and provides another potential route for understanding biological functions.

Identification of a prognostic signature of epithelial ovarian cancer based on tumor immune microenvironment exploration.

This study aims to develop an immune-related genes (IRGs) prognostic signature to stratify the epithelial ovarian cancer (EOC) patients. We identified 332 up- and 154 down-regulated EOC-specific IRGs. As a result, candidate IRGs were idendified to construct prognostic models respectivy for overall survial and progression-free survival. The risk score was validated as a risk factor for prognosis and was used to built a combined nomogram. According to the IRG-related prognostic model, EOC patients were divided into high- and low- risk group and were further explored their association with tumor immune microenvironment (TME). CIBERSORT algorithm showed higher macrophages M1 cell, T cells follicular helper cell and plasma cells infiltrating levels in the low-risk group. In addition, the low-risk group was found with higher immunophenoscore and distinct mutation signatures compared with the high-risk group. These findings may shed light on the development of novel immune biomarkers and target therapy of EOC.

Methylation-driven genes and their prognostic value in cervical squamous cell carcinoma.

BACKGROUND: Abnormal gene methylation is crucial for tumor progression. This study explored a cluster of methylation-driven genes involved in cervical squamous cell carcinoma (CESC). METHODS: The data on RNA expression, methylation and clinical outcomes of CESC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Protein-protein interaction (PPI) network was constructed. Gene Ontology (GO) and KEGG analyses were performed to identify the biological functions of methylation-driven genes, and univariable and multivariate Cox analyses to screen out the key prognostic genes. A risk signature was established and its predictive value was evaluated with Kaplan-Meier and ROC curves. The key genes were further investigated by Cox regression analyses, gene set enrichment analysis (GSEA), and methylation site analysis. Additionally, "rms" package was used for establishing nomogram and calibrate curve. RESULTS: We found 144 differentially expressed methylation-driven genes. A risk model was constructed with three key prognostic genes (ITGA5, HHEX and S1PR4). The risk score was an independent risk factor for CESC prognosis. Lowly-expressed and hypermethylated ITGA5, highly-expressed and hypomethylated HHEX and S1PR4 were associated with better CESC prognosis. The methylation sites and biological functions enriched in ITGA5, HHEX and S1PR4 were uncovered. Additionally, the nomogram also validated the performance of risk model. CONCLUSIONS: Methylation-driven ITGA5, HHEX and S1PR4 are associated with CESC development. The three genes might serve as potential targets in the treatment of CESC.

Using mRNAsi to identify prognostic-related genes in endometrial carcinoma based on WGCNA.

AIMS: Cancer Stem Cells (CSCs) refers to heterogeneous tumor cells retaining the abilities of self-renewal and differentiation. This study used mRNAsi, which is an index to describe the similarity between tumor cells and CSCs, to define genes involved in endometrial carcinoma. MATERIALS AND METHODS: The mRNA expression profiles of 552 tumor samples and 23 non-tumor samples were calculated for differentially expressed genes. WGCNA was utilized to construct gene co-expression networks and classify screened genes into different modules. Univariate and multivariate Cox regression models were performed to identify and construct the prognostic model. Time-dependent receiver operating characteristic (ROC), Kaplan-Meier curve, multivariate Cox regression analysis, and nomogram were used to assess the prognostic capacity of the six-gene signature. The screened genes were further validated by GEO (GSE17025) and qRT-PCR in EC tissues. KEY FINDINGS: 2573 upregulated and 1890 downregulated genes were identified. A total of 35 genes in the turquoise module were identified as key genes. With multivariate analysis, six genes (DEPDC1, FAM83D, NCAPH, SPC25, TPX2, and TTK) up-regulated in endometrial carcinoma were identified, and their higher expression was associated with a higher stage/age/grade. Moreover, ROC and Kaplan-Meier plots indicated these genes had a high prognostic value for EC. A nomogram was constructed for clinical use. In addition, we explored the pathogenesis involving six genes. The results showed that these genes may become pathogenic as their copy numbers changes and methylation level reduces. Finally, GSEA revealed these genes had a close association with cell cycle, etc. SIGNIFICANCE: These findings may provide new insights into the treatment of diseases.

A prognostic signature based on immune-related genes for cervical squamous cell carcinoma and endocervical adenocarcinoma.

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is the fourth commonest female malignancy worldwide. CESC progresses in immune-microenvironment mainly composed of infiltrating immune and stromal cells. Here, we performed an integrated analysis incorporating the expression profiles from the Cancer Genome Atlas (TCGA) database and scores of immune and stromal cells calculated by Estimation of Stromal and Immune cells in Malignant Tumours using Expression data (ESTIMATE) algorithm. A two-gene signature (CD1C and CD6 genes) was established to predict the prognosis of CESC. Based on this signature, patients were divided into the high- and low-risk groups, and this signature showed good prognostic performance according to the results of Kaplan-Meier analysis and receiver operating characteristic (ROC) analysis in train set and two validation sets. A nomogram was built for evaluating the clinical applicability of this signature. In addition, based on Tumor Immune Estimation Resource (TIMER) database, 2 hub genes showed negative correlations with tumor purity and positive correlations with infiltrating levels of immune filtrating cells. What's more, we propose new treatment strategies for the two prognostic subtypes. Low- risk patients were found presenting with a higher level of immune checkpoint molecules and showing higher immunogenicity in immunophenoscore (IPS) analysis, which indicated a better response for immunotherapy. Meanwhile, estimated by Genomics of Drug Sensitivity in Cancer (GDSC) database, the high-risk patients showed sensitive responses to five chemotherapy drugs. Finally, 10 candidate small-molecule drugs for CESC were defined. In summary, the CD1C-CD6 signature can accurately predict the prognosis of CESC.

Exploration of a novel prognostic risk signatures and immune checkpoint molecules in endometrial carcinoma microenvironment.

In this study, we devoted to investigate immune-related genes and tumor microenvironment (TME) in EC based on The Cancer Genome Atlas (TCGA) database. In total 799 up-regulated and 139 down-regulated immune-related and differentially expressed genes in EC were investigated for functional annotations and prognosis. By a conjoint Cox regression analysis, we built two risk models for OS and DFS, as well as the consistent nomograms. Immune-related pathways were revealed mostly enriched in the low-risk group. By further analyzing TME based on the risk signatures, the higher immune cell infiltration and activation, lower tumor purity and higher tumor mutational burden were found in low-risk group, which presented a better prognosis. Both the expression and immunophenoscore of immune checkpoints PD-1, CTLA4, PD-L1 and PD-L2 increased significantly in low-risk group. These findings may provide new ideas for novel biomarkers and immunotherapy targets in EC.

Nine glycolysis-related gene signature predicting the survival of patients with endometrial adenocarcinoma.

BACKGROUND: Endometrial cancer is the fourth most common cancer in women. The death rate for endometrial cancer has increased. Glycolysis of cellular respiration is a complex reaction and is the first step in most carbohydrate catabolism, which was proved to participate in tumors. METHODS: We analyzed the sample data of over 500 patients from TCGA database. The bioinformatic analysis included GSEA, cox and lasso regression analysis to select prognostic genes, as well as construction of a prognostic model and a nomogram for OS evaluation. The immunohistochemistry staining, survival analysis and expression level validation were also performed. Maftools package was for mutation analysis. GSEA identified Glycolysis was the most related pathway to EC. qRT-PCR verified the expression level of hub gene in clinical samples. RESULTS: According to the prognostic model using the train set, 9 glycolysis-related genes including B3GALT6, PAM, LCT, GMPPB, GLCE, DCN, CAPN5, GYS2 and FBP2 were identified as prognosis-related genes. Based on nine gene signature, the EC patients could be classified into high and low risk subgroups, and patients with high risk score showed shorter survival time. Time-dependent ROC analysis and Cox regression suggested that the risk score predicted EC prognosis accurately and independently. Analysis of test and train sets yielded consistent results A nomogram which incorporated the 9-mRNA signature and clinical features was also built for prognostic prediction. Immunohistochemistry staining and TCGA validation showed that expression levels of these genes do differ between EC and normal tissue samples. GSEA revealed that the samples of the low-risk group were mainly concentrated on Bile Acid Metabolism. Patients in the low-risk group displayed obvious mutation signatures compared with those in the high-risk group. The expression levels of B3GALT6, DCN, FBP2 and GYS2 are lower in tumor samples and higher in normal tissue samples. The expression of CAPN5 and LCT in clinical sample tissues is just the opposite. CONCLUSION: This study found that the Glycolysis pathway is associated with EC and screened for hub genes on the Glycolysis pathway, which may serve as new target for the treatment of EC.

A microRNA-Messenger RNA Regulatory Network and Its Prognostic Value in Cervical Cancer.

Cervical cancer (CC) is the fourth commonest cancer in women worldwide. Increasing evidence proves that microRNA (miRNA)-messenger RNA (mRNA) network is involved in CC. In this study, miRNA and mRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Differently expressed miRNAs (DE-miRNAs) and mRNAs (DE-mRNAs) were obtained by "Empirical Analysis of Digital Gene Expression Data in R (EdgeR)" package. Then, functional analyses were conducted. With Cytoscape software, a protein-protein interaction (PPI) network was established to identify hub genes that were used for building an miRNA-hub gene network. Next, a prognostic signature based on hub genes was constructed by Cox regression analysis, and its prognostic value was assessed by a nomogram. Finally, the relationship between immune cell infiltration and the three genes in the prognostic model was investigated by using the CIBERSORT algorithm. We screened out 5096 DE-mRNAs and 114 DE-miRNAs between healthy cervical and CC tissues. Then, 102 target DE-mRNAs of upregulated DE-miRNAs and 150 target DE-mRNAs of downregulated DE-miRNAs were obtained. PPI network demonstrated 20 hub nodes with higher connectivity. DE-mRNAs were mostly enriched in pathways in cancer, cell cycle, and proteoglycans in cancer. The miRNA-hub gene network showed that most hub genes could be potentially modulated by miR-200c-3p, miR-23b-3p, and miR-106b-5p. Quantitative real-time PCR proved that 10 miRNAs were downregulated and 6 mRNAs were upregulated markedly in CC tissues. Furthermore, a prognostic signature was established based on enhancer of zeste homolog 2 (EZH2), Fms-related tyrosine kinase 1 (FLT1), and glyceraldehyde 3-phosphate dehydrogenase (GAPDH). The area under the curve value of the 5-year receiver operating characteristic curve was 0.609. The three genes were also found to be related to the infiltration of six types of immune cells, including dendritic cells, macrophages M0 and M1, mast cells, and monocytes. In conclusion, the development of CC is regulated by the miRNA-mRNA network we proposed in this study.

Identification of Key Genes in Association with Progression and Prognosis in Cervical Squamous Cell Carcinoma.

Cervical cancer remains a primary cause of female death in developing countries, but its prognosis can be greatly improved if patients are diagnosed earlier. In the present study, we screened the common differentially expressed genes (DEGs) of cervical squamous cell carcinoma (CESC) from dataset GSE7803, Gene Expression Omnibus, and The Cancer Genome Atlas databases. An integrated bioinformatics analysis was performed based on these DEGs for their enrichment in functions and pathways, interaction network, prognostic signature, and candidate molecular drugs. As a result, 164 (114 upregulated and 47 downregulated) DEGs of CESC were identified for further investigation. We then conducted the gene ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes Pathway analyses to reveal the underlying functions and pathways of these DEGs. In the protein-protein interaction network, hub module and hub genes were identified. Five genes of significant prognostic value-DSG2, ITM2A, CENPM, RIBC2, and MEIS2-were identified by prognostic signature analysis and used to construct a risk linear model. Further validation and investigation suggested DSG2 might be a key gene in CESC prognosis. We then identified two candidate small molecules (trichostatin A and tanespimycin) against CESC. Further validation and exploration of these hub genes are warranted for future prospect in clinical applications.

Identification of molecular markers associated with the progression and prognosis of endometrial cancer: a bioinformatic study.

BACKGROUND: Endometrial cancer (EC) is one kind of women cancers. Bioinformatic technology could screen out relative genes which made targeted therapy becoming conventionalized. METHODS: GSE17025 were downloaded from GEO. The genomic data and clinical data were obtained from TCGA. R software and bioconductor packages were used to identify the DEGs. Clusterprofiler was used for functional analysis. STRING was used to assess PPI information and plug-in MCODE to screen hub modules in Cytoscape. The selected genes were coped with functional analysis. CMap could find EC-related drugs that might have potential effect. Univariate and multivariate Cox proportional hazards regression analyses were performed to predict the risk of each patient. Kaplan-Meier curve analysis could compare the survival time. ROC curve analysis was performed to predict value of the genes. Mutation and survival analysis in TCGA database and UALCAN validation were completed. Immunohistochemistry staining from Human Protein Atlas database. GSEA, ROC curve analysis, Oncomine and qRT-PCR were also performed. RESULTS: Functional analysis showed that the upregulated DEGs were strikingly enriched in chemokine activity, and the down-regulated DEGs in glycosaminoglycan binding. PPI network suggested that NCAPG was the most relevant protein. CMap identified 10 small molecules as possible drugs to treat EC. Cox analysis showed that BCHE, MAL and ASPM were correlated with EC prognosis. TCGA dataset analysis showed significantly mutated BHCE positively related to EC prognosis. MAL and ASPM were further validated in UALCAN. All the results demonstrated that the two genes might promote EC progression. The profile of ASPM was confirmed by the results from immunohistochemistry. ROC curve demonstrated that the mRNA levels of two genes exhibited difference between normal and tumor tissues, indicating their diagnostic efficiency. qRT-PCR results supported the above results. Oncomine results showed that DNA copy number variation of MAL was significantly higher in different EC subtypes than in healthy tissues. GSEA suggested that the two genes played crucial roles in cell cycle. CONCLUSION: BCHE, MAL and ASPM are tumor-related genes and can be used as potential biomarkers in EC treatment.

Upregulated LINC00565 Accelerates Ovarian Cancer Progression By Targeting GAS6.

BACKGROUND: Long noncoding RNAs (lncRNAs) have been identified to participate in tumorigenesis. However, the underlying mechanisms of differentially expressed lncRNAs engaged in diseases remain indistinct and need further exploration. METHODS: Raw data files downloaded from TCGA and GEO dataset were used to analyze the differentially expressed lncRNAs and LINC00565 was picked out as the potential oncogene. qRT-PCR was used to analyze the LINC00565 level in ovarian tissues and cell lines. Subsequently, the selected ovarian tumor cells were then transfected with LINC00565 siRNA by Lipofectamine 2000 and the cell cycle was detected by flow cytometry. Effect of LINC00565 on tumor growth and cell cycle was verified by tumor formation assay in nude mice. The mechanism of LINC00565 involving in cell cycle regulation was further explored by Western blot. RESULTS: In this research, we discovered that LINC00565, a novel lncRNA, was highly expressed in ovarian cancer (OC). LINC00565 expression level was negatively associated with outcomes of OC patients. Further analysis showed that LINC00565 expression was closely correlated to tumor size, FIGO stage, but not related to other clinical features. In vitro experiments indicated that knockdown of LINC00565 significantly inhibited proliferative, invasive and migratory abilities of ovarian cancer cells. Besides, knockdown of LINC00565 can induce cell cycle arrest in G0/G1 phase. In addition, in vivo assay showed that low expression of LINC00565 inhibited the growth of OC. Further study found that LINC00565 knockdown markedly downregulated the protein expressions of CyclinD1, CyclinE1 and CDK4, but upregulated the expression of P16 and P21. Subsequently, we confirmed that LINC00565 promoted the progression of OC via upregulating GAS6, which has been confirmed to promote tumor progression. CONCLUSION: In summary, our study firstly reported that the LINC00565 functioned as an oncogene to promote the progression of OC by interacting with GAS6.

Identification of EPHX2 and RMI2 as two novel key genes in cervical squamous cell carcinoma by an integrated bioinformatic analysis.

Cervical cancer is the fourth most common malignancy in women worldwide and cervical squamous cell carcinoma (CESC) is the most common histological type of cervical cancer. The dysregulation of genes plays a significant role in cancer. In the present study, we screened out differentially expressed genes (DEGs) of CESC in the GSE63514 data set from the Gene Expression Omnibus database. An integrated bioinformatics analysis was used to select hub genes, as well as to investigate their related prognostic signature, functional annotation, methylation mechanism, and candidate molecular drugs. As a result, a total of 1907 DEGs were identified (944 were upregulated and 963 were downregulated). In the protein-protein interaction network, three hub modules and 30 hub genes were identified. And two hub modules and 116 hub genes were screened out from four CESC-related modules by the weighted gene coexpression network analysis. The gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to better understand functions and pathways. Genes with a significant prognostic value were found by prognostic signature analysis. And there were five genes (EPHX2, CHAF1B, KIAA1524, CDC45, and RMI2) identified as significant CESC-associated genes after expression validation and survival analysis. Among them, EPHX2 and RMI2 were noted as two novel key genes for the CESC-associated methylation and expression. In addition, four candidate small molecule drugs for CESC (camptothecin, resveratrol, vorinostat, and trichostatin A) were defined. Further studies are required to explore these significant CESC-associated genes for their potentiality in diagnosis, prognosis, and targeted therapy.

Competing endogenous RNA network of endometrial carcinoma: A comprehensive analysis.

Competing endogenous RNA (ceRNA) network is dysregulated in the initiation and progression of tumors. In the present study, we explored the regulatory mechanism of ceRNA in endometrial carcinoma (EC) and the potential key molecules with potential value in the diagnosis, treatment, and prognosis of EC. The long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) expression profiles (552 EC tissues and 35 nontumor tissues) and microRNAs (miRNAs) expression profiles (546 EC tissues and 33 nontumor tissues) were downloaded from The Cancer Genome Atlas database to identify differentially expressed RNAs (DERNAs) in EC. An integrated bioinformatics analysis was used to construct an EC-specific ceRNA network and select key molecules. As a result, 96 differentially expressed lncRNAs (DElncRNAs), 29 differentially expressed miRNAs (DEmiRNAs), and 77 differentially expressed mRNAs (DEmRNAs) were identified. An EC-specific ceRNA network was built based on nine DElncRNAs significantly associated with overall survival. CCNB1 was found as a key gene in EC through the weighted gene coexpression network analysis and protein-protein interaction network analysis. Our ceRNA network showed C2orf48 and LINC00483 might upregulate CCNB1 via competing with miR-183. In addition, we found a subnetwork which contained survival-associated DERNAs (AC110491.1, LINC00483-miR-192-GRHL1). The results of reverse transcription quantitative polymerase chain reaction supported the relative expressions of C2orf48, LINC00483 were upregulated and that of AC110491.1 was downregulated in EC. We further found C2orf48 was upregulated in serous EC, endometrioid EC, and mixed serous and endometrioid EC. LINC00483 was upregulated in mixed serous and endometrioid EC compared with that in the normal tissues according to UALCAN database. In addition, candidate small molecular drugs were screened out by ConnectivityMap based on the 77 DEmRNAs in the ceRNA network. Eventually, C2orf48, LINC00483, and AC110491.1 were identified as three key lncRNAs in EC.

Characterization of AD-like phenotype in aged APPSwe/PS1dE9 mice.

Transgenic APPSwe/PS1dE9 (APP/PS1) mice that overproduce amyloid beta (Aß) are extensively used in the studies of pathogenesis and experimental therapeutics and new drug screening for Alzheimer's disease (AD). However, most of the current literature uses young or adult APP/PS1 mice. In order to provide a broader view of AD-like phenotype of this animal model, in this study, we systematically analyzed behavioral and pathological profiles of 24-month-old male APP/PS1 mice. Aged APP/PS1 mice had reference memory deficits as well as anxiety, hyperactivity, and social interaction impairment. Consistently, there was obvious deposition of amyloid plaques in the dorsal hippocampus with decreased expression of insulin-degrading enzyme, a proteolytic enzyme responsible for degradation of intracellular Aß. Furthermore, decreases in hippocampal volume, neuronal number and synaptophysin expression, and astrocyte atrophy were also observed in aged APP/PS1 mice. This finding suggests that aged APP/PS1 mice can well replicate cognitive and noncognitive behavioral abnormalities, hippocampal atrophy, and neuronal and astrocyte degeneration in AD patients, to enable more objective and refined preclinical evaluation of therapeutic drugs and strategies for AD treatment.