Construction and Analysis of lncRNA-Mediated ceRNA Network in Cervical Squamous Cell Carcinoma by Weighted Gene Co-Expression Network Analysis

Analysis of Correlation Between LncRNA TDRG1 Expression and its Prognosis in Cervical Carcinoma Tissues

To explore and analyze the correlation between LncRNA TDRG1 expression degree and the prognosis of cervical carcinoma tissues. The cervical cancer tissues and para-carcinoma tissues of 106 patients with cervical carcinoma surgically removed in our hospital were chosen as specimens. LncRNA TDRG1 expression in cervical carcinoma tissues and para-carcinoma tissues was inspected by real-time fluorescence quantitative PCR, and the correlation between LncRNA TDRG1 and the clinicopathological parameters and disease prognosis was analyzed. The relative expression of LncRNA TDRG1 in cervical carcinoma tissues was critically gone up (P < 0.05) compared to para-carcinoma tissues. The relative expression of LncRNA TDRG1 in cervical carcinoma was correlated with FIGO staging, lymph node metastasis, infiltrating depth of cervical basal, and the differentiation of cancer cells (P < 0.05). According to the results of the Kaplan-Meier curve and Log-rank test, the overall survival conditions of subjects with low-lncRNA TDRG1 were superior to that of those with high-lncRNA TDRG1 expression (P < 0.05). The expression of LncRNA TDRG1 in cervical carcinoma tissues and the clinicopathological features in predicting the overall survival (OS) in sufferers with cervical carcinoma were investigated by the Cox regression model. LncRNA TDRG1 expression in cervical carcinoma tissues is tightly associated with the progression and prognosis of cervical carcinoma, which may be a latent biological indicator for clinical diagnosis and prognosis of cervical carcinoma.

mRNA and lncRNA expression profiles of liver tissues in children with biliary atresia

Progressive liver fibrosis is the most common phenotype in biliary atresia (BA). A number of pathways contribute to the fibrosis process so comprehensive understanding the mechanisms of liver fibrosis in BA will pave the way to improve patient's outcome after operation. In this study, the differentially expressed profiles of mRNAs and long non-coding RNAs from BA and choledochal cyst (CC) liver tissues were investigated and analyzed, which may provide potential clues to clarify hepatofibrosis mechanism in BA. A total of two BA and two CC liver tissue specimens were collected, the expression level of mRNAs and lncRNAs was detected by RNA sequencing. Differentially expressed mRNAs (DEmRNAs) were functionally annotated and protein-protein interaction networks (PPI) was established to predict the biological roles and interactive relationships. Differentially expressed lncRNAs (DElncRNAs) nearby targeted DEmRNA network and DElncRNA-DEmRNA co-expression network were constructed to further explore the roles of DElncRNAs in BA pathogenesis. The expression profiles of significant DEmRNAs were validated in Gene Expression Omnibus database. A total of 2,086 DEmRNAs and 184 DElncRNAs between BA and CC liver tissues were obtained. DEmRNAs were enriched in 521 Gene Ontology terms and 71 Kyoto Encyclopedia of Genes and Genomes terms which were mainly biological processes and metabolic pathways related to immune response and inflammatory response. A total of five hub proteins (TYRO protein tyrosine kinase binding protein, C-X-C motif chemokine ligand 8, pleckstrin, Toll-like receptor 8 and C-C motif chemokine receptor 5) were found in the PPI networks. A total of 31 DElncRNA-nearby-targeted DEmRNA pairs and 2,337 DElncRNA-DEmRNA co-expression pairs were obtained. The expression of DEmRNAs obtained from RNA sequencing were verified in GSE46960 dataset, generally. The present study identified key genes and lncRNAs participated in BA associated liver fibrosis, which may present a new avenue for understanding the patho-mechanism for hepatic fibrosis in BA.

Construction of a four-mRNA prognostic signature with its ceRNA network in CESC

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) tumorigenesis involves a combination of multiple genetic alteration processes. Constructing a survival-associated competing endogenous RNA (ceRNA) network and a multi-mRNA-based prognostic signature model can help us better understand the complexity and genetic characteristics of CESC. In this study, the RNA-seq data and clinical information of CESC patients were downloaded from The Cancer Genome Atlas. Differentially expressed mRNAs, lncRNAs and miRNAs were identified with the edgeR R package. A four-mRNA prognostic signature was developed by multivariate Cox regression analysis. Kaplan–Meier survival with the log-rank tests was performed to assess survival rates. The relationships between overall survival (OS) and clinical parameters were evaluated by Cox regression analysis. A survival-associated ceRNA network was constructed with the multiMiR package and miRcode database. Kyoto encyclopedia of genes and genomes (KEGG) analysis and gene ontology analyses were used to identify the functional role of the ceRNA network in the prognosis of CESC. A total of 298 differentially expressed mRNAs, 8 miRNAs, and 29 lncRNAs were significantly associated with the prognosis of CESC. A prognostic signature model based on 4 mRNAs (OPN3, DAAM2, HENMT1, and CAVIN3) was developed, and the prognostic ability of this signature was indicated by the AUC of 0.726. Patients in the high-risk group exhibited significantly worse OS. The KEGG pathways, TGF-β and Cell adhesion molecules, were significantly enriched. In this study, a CESC-associated ceRNA network was constructed, and a multi-mRNA-based prognostic model for CESC was developed based on the ceRNA network, providing a new perspective for cancer pathogenesis research.

Identification of prognostic biomarkers for papillary thyroid carcinoma by a weighted gene co‐expression network analysis

Aim

Methods

Results

Conclusions

Comprehensive analysis of ceRNA networks in HPV16- and HPV18-mediated cervical cancers reveals XIST as a pivotal competing endogenous RNA

Cervical cancer (CC) is one of the most common cancers in women worldwide, being closely related to high-risk human papillomavirus (HR-HPVs). After a particular HR-HPV infects a cervical cell, transcriptional changes in the host cell are expected, including the regulation of lncRNAs, miRNAs, and mRNAs. Such transcripts may work independently or integrated in complex molecular networks - as in competing endogenous RNA (ceRNA) networks. In our research, we gathered transcriptome data from samples of HPV16/HPV18 cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), from The Cancer Genome Atlas (TCGA) project. Using GDCRNATools, we identified ceRNA networks that differentiate HPV16- from HPV18-mediated CESC. For HPV16-CESC, three lncRNA-mRNA co-expressed pairs were reported, all led by the X-inactive specific transcript (XIST): XIST | DLG5, XIST | LGR4, and XIST | ZNF81. The XIST | LGR4 and XIST | ZNF81 pairs shared 11 miRNAs, suggesting an increased impact on their final biological effect. XIST also stood out as an important lncRNA in HPV18-CESC, leading 35 of the 42 co-expressed pairs. Some mRNAs, such as ADAM9 and SLC38A2, emerged as important players in the ceRNA regulatory networks due to sharing a considerable amount of miRNAs with XIST. Furthermore, some XIST-associated axes, namely XIST | miR-23a-3p | LGR4 and XIST | miR-30b-5p or miR-30c-5p or miR-30e-5p I ADAM9, had a significant impact on the overall survival of HPV16- and HPV18-CESC patients, respectively. Together, these data suggest that XIST has an important role in HPV-mediated tumorigenesis, which may implicate different molecular signatures between HPV16 and HPV18-associated tumors.

lncRNA MIR155HG Accelerates the Progression of Sepsis via Upregulating MEF2A by Sponging miR-194-5p

Long noncoding RNA MIR155HG exerts important effects in the progression of multiple diseases. This study investigated the functions of MIR155HG in sepsis development. Blood samples were collected from 28 patients with sepsis and 28 without sepsis. The murine cardiac muscle cell line (HL-1) and macrophage cell line (RAW 264.7) treated with lipopolysaccharide (LPS) were used as the in vitro sepsis models. The levels of MIR155HG, miR-194-5p, and MEF2A were determined using real-time-quantitative polymerase chain reaction. Cell counting kit-8 and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assays were used to assess cell viability and apoptosis, respectively. The association between miR-194-5p and MIR155HG or MEF2A was confirmed using a dual-luciferase reporter assay. The levels of inflammatory cytokines were detected using enzyme-linked immunosorbent assay (ELISA). In this study, we demonstrated that MIR155HG expression was significantly increased in sepsis blood samples, RAW 264.7, and HL-1 cells treated with LPS. Silencing of MIR155HG promoted cell viability and obstructed cell apoptosis and inflammation of RAW 264.7 and HL-1 cells treated with LPS. MiR-194-5p depletion abrogated cell viability promotion and suppressive effect on cell apoptosis and inflammation caused by MIR155HG knockdown. In addition, MIR155HG upregulated MEF2A through interaction with miR-194-5p. Finally, rescue assays indicated that MEF2A overexpression abolished the inhibitory effect on sepsis progression induced by MIR155HG deletion. In conclusion, MIR155HG promotes sepsis progression in an in vitro sepsis model by modulating the miR-194-5p/MEF2A axis. This discovery provides a promising biomarker for sepsis therapy.

Long non-coding RNA RP11-284F21.9 functions as a ceRNA regulating PPWD1 by competitively binding to miR-769-3p in cervical carcinoma

Cervical carcinoma is the most common gynecological cancer in women worldwide. Emerging evidence has shown that long non-coding RNAs (lncRNAs) participate in multiple biological processes of cervical carcinoma tumorigenesis. We aimed to investigate the function of a novel lncRNA RP11-284F21.9 in cervical carcinoma. We found that RP11-284F21.9 was down-regulated in cervical carcinoma tissues and cell lines. Overexpression of RP11-284F21.9 inhibits proliferation, invasion and migration of cervical carcinoma cells in vitro. Further, we identified that RP11-284F21.9 directly interacted with miR-769-3p and functioned as the miR-769-3p sponge. Mechanistically, we showed that miR-769-3p regulated peptidylprolyl isomerase domain and WD repeat-containing protein1 (PPWD1) expression by targeting PPWD1 3′-UTR. Furthermore, xenograft tumor model revealed that overexpression of RP11-284F21.9 inhibited tumor growth of cervical carcinoma in vivo. Taken together, our results demonstrate that RP11-284F21.9 functions as tumor suppressor and regulates PPWD1 expression through competitively binding to miR-769-3p in cervical carcinoma, suggesting that RP11-284F21.9/miR-769-3p/PPWD1 axis could serve as a promising prognostic biomarker and therapeutic target for cervical carcinoma.

Integrated Analysis of ceRNA Regulatory Network Associated With Tumor Stage in Cervical Cancer

Objective

To analyze the abnormally expressed genes involved in cervical cancer occurrence and development.

Materials and Methods

Integrated bioinformatics methods were used to analyze differentially expressed (DE) RNAs, including mRNAs, microRNAs (miRNAs), and long non-coding RNAs (lncRNAs), in stage I, II, III, and IV cervical cancer patients from the TCGA database to fully reveal the dynamic changes caused by cervical cancer.

Results

First, DE RNAs in cervical cancer tissues from stage I, II, III, and IV patients and normal cervical tissues were identified and divided into different profiles. Several DE RNA profiles were down-regulated or up-regulated in stage I, III, and IV patients. GO and KEGG analysis of DE mRNA profile 1, 2, 4, 5, 6 and 22 which were significantly down-regulated or up-regulated showed that DE mRNAs are involved in cell division, DNA replication, cell adhesion, the positive and negative regulation of RNA polymerase ll promoter transcription. Besides, DE RNA profiles with significant differences in patient stages were analyzed to perform a competing endogenous RNA (ceRNA) regulatory network of lncRNA, miRNA, and mRNA. The protein-protein interaction (PPI) network of DE mRNAs in the ceRNA regulatory network was also constructed. The network had nine central genes (up-regulated genes: CDKN2A, GSK3B, BIRC5, CYCS, MAD2L1; down-regulated genes: PTEN, FOXO3, CCND2, TGFBR2). Survival analysis found that 5 lncRNAs, 9 mRNAs, and 4 miRNAs can be used as prognostic indicators of cervical cancer. Finally, combined with cluster analysis results, we further screened 2 DE RNAs (AMZ2P1 and HDAC5) using clinical samples, suggesting that AMZ2P1, and HDAC5 may act as diagnostic biomarkers for the development of cervical cancer.

Conclusion

This research provides new effective targets and reliable biological markers for the diagnosis and prognosis of cervical cancer.

lncRNA H19 acts as a ceRNA to regulate the expression of CTGF by targeting miR-19b in polycystic ovary syndrome

The etiology of polycystic ovary syndrome (PCOS) is complex and the pathogenesis is not fully understood. Some studies have shown that dysregulation of ovarian granulosa cells may be related to abnormal follicles and excessive androgen in women with PCOS. Our team has also confirmed the high expression status of H19 in PCOS patients in the early stage. However, the relationship between H19 and miR-19b in the development of PCOS is still unknown. Therefore, we used bioinformatics to predict the binding sites of human H19 and miR-19b, and of miR-19b and CTGF genes. After the silencing and overexpression of H19, real-time polymerase chain reaction (PCR) was used to detect the expressions of H19, miR-19b, and CTGF. Western blotting was used to detect CTGF protein. Proliferation of KGN cells after H19 silencing was detected by CCK8. Flow cytometry was used to detect the apoptosis of KGN cells after H19 silencing. After the overexpression of H19, it was found that the expression of miR-19b gene decreased and the expression of CTGF increased, whereas silencing of H19 did the opposite. In addition, H19 could promote cell proliferation and decrease cell apoptosis. Finally, luciferase reporter assays showed that the 3′-end sequences of lncRNA H19 and CTGF contained the binding site of miR-19b. In conclusion, our study indicated that lncRNA H19 acted as a ceRNA to bind to miR-19b via a “sponge” to regulate the effect of CTGF on KGN cells, which may play a vital role in PCOS.

Network-Based Analysis Reveals Association of FOXE1 Gene Polymorphisms in Thyroid Cancer Patients; A Case-Control Study in Southeast of Iran

Thyroid cancer (TC) is the mainly frequent endocrine cancer by different incidence rate in worldwide. However, early prediction of  this cancer is still challenging due to the unclear pathogenicity. In this study with the aid of systems biology approach, performed a holistic study on GSE65144 dataset containing anaplastic thyroid carcinoma tissues. Co-expression network analysis by WGCNA suggested that highly preserved turquoise module with 1,480 genes was significantly correlated to TC. Most of the top 54 hub-genes of this module are functionality correlated to thyroid hormone generation (GO:0006590). Of these 54 hub-genes, FOXE1 has been reported previously to contain mutation asosiated to TC and chosen for experimental validation step. To this end, we conducted a case-control study including 81 TC patients and 165 controls individuals to evaluate the effects of FOXE1 functional polymorphisms (rs1867277) on the development of TC in Sistan and Balouchestan province of Iran. The polymorphisms of FOXE1 gene (rs1867277) assessed by tetra-ARMS PCR technique. Homozygous (GG) and (AA) variant of rs1867277 polymorphism were detected in 26 (32.1%) and 15 (18.5 %) of TC patients, and 66 (40.0%), and 15 (9.1%) in controls, respectively (p-value= 0.03, OR= 2.53). The A allele frequency was 70 (43.2%) in TC patients and 114 (34.5%) in controls (p-value= 0.06, OR= 1.44). Overall, our results suggested that FOXE1 gene could be used as a prognostic marker in TC and also provides information related to FOXE1 functional polymorphisms (rs1867277) in Sistan and Balouchestan province of Iran.
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LDAI-ISPS: LncRNA-Disease Associations Inference Based on Integrated Space Projection Scores

Long non-coding RNAs (long ncRNAs, lncRNAs) of all kinds have been implicated in a range of cell developmental processes and diseases, while they are not translated into proteins. Inferring diseases associated lncRNAs by computational methods can be helpful to understand the pathogenesis of diseases, but those current computational methods still have not achieved remarkable predictive performance: such as the inaccurate construction of similarity networks and inadequate numbers of known lncRNA-disease associations. In this research, we proposed a lncRNA-disease associations inference based on integrated space projection scores (LDAI-ISPS) composed of the following key steps: changing the Boolean network of known lncRNA-disease associations into the weighted networks via combining all the global information (e.g., disease semantic similarities, lncRNA functional similarities, and known lncRNA-disease associations); obtaining the space projection scores via vector projections of the weighted networks to form the final prediction scores without biases. The leave-one-out cross validation (LOOCV) results showed that, compared with other methods, LDAI-ISPS had a higher accuracy with area-under-the-curve (AUC) value of 0.9154 for inferring diseases, with AUC value of 0.8865 for inferring new lncRNAs (whose associations related to diseases are unknown), with AUC value of 0.7518 for inferring isolated diseases (whose associations related to lncRNAs are unknown). A case study also confirmed the predictive performance of LDAI-ISPS as a helper for traditional biological experiments in inferring the potential LncRNA-disease associations and isolated diseases.