A comprehensive study of construction and analysis of competitive endogenous RNA networks in lung adenocarcinoma

Comprehensive analysis of PTEN-related ceRNA network revealing the key pathways WDFY3-AS2 - miR-21-5p/miR-221-3p/miR-222-3p - TIMP3 as potential biomarker in tumorigenesis and prognosis of kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most common malignancies, and there is still a lack of effective biomarkers for early detection and prognostic prediction. In here, we compared the characteristics of RNA sequencing data sets of KIRC samples based on the tumor suppressor gene phosphatase and tensin homolog (PTEN). The 1016 long noncoding RNAs, 48 microRNAs (miRNAs), and 2104 messenger RNAs associated with PTEN were identified and these genes were differentially expressed between tumor and paracancerous tissues. The most relevant pathway was found to be WDFY3-AS2 - miR-21-5p/miR-221-3p/miR-222-3p - TIMP3 according to the rules of competing endogenous RNA (ceRNA) regulation. WDFY3-AS2 and TIMP3 expression were positively correlated and reduced in KIRC samples, while miR-21-5p, miR-221-3p, and miR-222-3p were relatively highly expressed. The relatively low expression of WDFY3-AS2 and TIMP3 in KIRC were associated with poor prognosis in KIRC patients, while higher expression of miR-21-5p, miR-221-3p, and miR-222-3p predicted reduced survival (p < 0.05). Univariate and multivariate Cox regression analysis showed that lower expression of WDFY3-AS2 and TIMP3 was significantly related to tumor grade, tumor size, lymph node metastasis, distant metastasis, and TNM stage. The expression of TIMP3 in KIRC tissues was also verified by immunohistochemistry, and the results were consistent with our analytical data. In summary, this study constructed a new model with clinical predictive value and identified the WDFY3-AS2/TIMP3 pathway that was closely associated with the prognosis of KIRC, which could serve as a promising biomarker for the diagnosis and treatment of KIRC.

The Prognostic Role of m6A-Related Genes in Paediatric Neuroblastoma Patients

Methods

The gene expression data were extracted from the “Therapeutically Applicable Research to Generate Effective Treatments” (TARGET) database. The differentially expressed genes (DEGs) were identified, and the relationships between DEGs and m6A genes were explored. Then, the correlations among the m6A genes in neuroblastoma were investigated. Finally, the prognostic role of the m6A genes was studied, and the risk model was constructed.

Results

81 NB patients were extracted from the TARGET database. After comparing the gene expression between unfavorable and favorable outcome groups, 73 DEGs were identified, including 54 downregulated genes and 19 upregulated genes. In NB patients, we found that IGF2BP3, METTL14, and METTL16 are prognostic factors for disease-free survival (DFS) while IGF2BP3, METTL14, and METTL16 are prognostic factors for overall survival (OS). Besides, after the risk model construction, the OS between the two risk groups was drawn (log-rank p = 1.64e − 08, HR = 3.438, 95% CI 2.24-5.278). The 1-, 3-, and 5-year time-dependent receiving operating characteristic (ROC) curves were also illustrated, and the areas under the receiver operating characteristic curves (AUCs) attained 0.75, 0.798, and 0.768, respectively.

Conclusions

IGF2BP3, METTL14, and METTL16 were identified as the significant factors for DFS and OS in NB patients.

An 11-Gene Signature Risk-Prediction Model Based on Prognosis-Related miRNAs and Their Target Genes in Lung Adenocarcinoma

Aberrant expression of microRNAs may affect tumorigenesis and progression by regulating their target genes. This study aimed to construct a risk model for predicting the prognosis of patients with lung adenocarcinoma (LUAD) based on differentially expressed microRNA-regulated target genes. The miRNA sequencing data, RNA sequencing data, and patients’ LUAD clinical data were downloaded from the The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs and genes were screened out by combining differential analysis with LASSO regression analysis to further screen out miRNAs associated with patients’ prognosis, and target gene prediction was performed for these miRNAs using a target gene database. Overlapping gene screening was performed for target genes and differentially expressed genes. LASSO regression analysis and survival analysis were then used to identify key genes. Risk score equations for prognostic models were established using multifactorial COX regression analysis to construct survival prognostic models, and the accuracy of the models was evaluated using subject working characteristic curves. The groups were divided into high- and low-risk groups according to the median risk score, and the correlation with the clinicopathological characteristics of the patients was observed. A total of 123 up-regulated miRNAs and 22 down-regulated miRNAs were obtained in this study. Five prognosis-related miRNAs were screened using LASSO regression analysis and Kaplan-Meier method validation, and their target genes were screened with the overlap of differentially expressed genes before multifactorial COX analysis finally resulted in an 11-gene risk model for predicting patient prognosis. The area under the ROC curve proved that the model has high accuracy. The 11-gene risk-prediction model constructed in this study may be an effective predictor of prognosis.

Identification of Hub mRNAs and lncRNAs in Atrial Fibrillation Using Weighted Co-expression Network Analysis With RNA-Seq Data

Atrial fibrillation (AF)/paroxysmal AF (PAF) is the main cause of cardiogenic embolism. In recent years, the progression from paroxysmal AF to persistent AF has attracted more and more attention. However, the molecular mechanism of the progression of AF is unclear. In this study, we performed RNA sequencing for normal samples, paroxysmal AF and persistent AF samples to identify differentially expressed gene (DEG) and explore the roles of these DEGs in AF. Totally, 272 differently expressed mRNAs (DEmRNAs) and 286 differentially expressed lncRNAs (DElncRNAs) were identified in paroxysmal AF compared to normal samples; 324 DEmRNAs and 258 DElncRNAs were found in persistent atrial fibrillation compared with normal samples; and 520 DEmRNAs and 414 DElncRNAs were identified in persistent AF compared to paroxysmal AF samples. Interestingly, among the DEGs, approximately 50% were coding genes and around 50% were non-coding RNAs, suggesting that lncRNAs may also have a crucial role in the progression of AF. Bioinformatics analysis demonstrated that these DEGs were significantly related to regulating multiple AF associated pathways, such as the regulation of vascular endothelial growth factor production and binding to the CXCR chemokine receptor. Furthermore, weighted gene co-expression network analysis (WGCNA) was conducted to identify key modules and hub RNAs and lncRNAs to determine their potential associations with AF. Five hub modules were identified in the progression of AF, including blue, brown, gray, turquoise and yellow modules. Interestingly, blue module and turquoise module were significantly negatively and positively correlated to the progression of AF respectively, indicating that they may have a more important role in the AF. Moreover, the hub protein-protein interaction (PPI) networks and lncRNA-mRNA regulatory network were constructed. Bioinformatics analysis on the hub PPI network in turquoise was involved in regulating immune response related signaling, such as leukocyte chemotaxis, macrophage activation, and positive regulation of α-β T cell activation. Our findings could clarify the underlying molecular changes associated fibrillation, and provide a useful resource for identifying AF marker.

The Functionalities and Clinical Significance of Tumor-Infiltrating Immune Cells in Esophageal Squamous Cell Carcinoma

Tumor-infiltrating immune cells have been implicated in the tumorigenesis and progression of esophageal squamous cell carcinoma (ESCC). However, the functionalities and clinical significance of immune cells remain largely unveiled. In this study, the gene expression data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were extracted. The relative infiltrating levels were estimated by single-sample gene set enrichment analysis. Some cytotoxic immune cells were attenuated, and resting cytotoxic immune cells were accumulated in ESCC. Remarkably, we also observed that infiltrating levels of macrophage M2 and resting natural killer (NK) cells were increased in nonresponders of CRT, and T cells that had anticancer activities such as activated memory CD4 and T helper 2 (Th2) cells were significantly reduced in ESCC tissues of the nonresponders. Moreover, the high infiltrations of the resting natural killer (NK) and dendritic cell (DC) were observed to result in a shorter overall survival in ESCC. Consistently, high expression of immune checkpoint genes, CTLA4 and HAVCR2, was associated with poor prognosis. Furthermore, STAT5B, a key transcription factor, as well as its target genes, involved in the regulation of T cells, was significantly downregulated in ESCC, especially subgroup I, indicating that downregulation of STAT5B might be associated with reduced T cell-mediated anticancer activity. In conclusion, the present study significantly improved our understanding of the regulatory roles of immune cells in ESCC.

Upregulation of miR-29c-3p Hinders Melanoma Progression by Inhibiting CDCA4 Expression

OBJECTIVE

To investigate the expression and regulation mechanism of miR-29c-3p and cell division cycle associated 4 (CDCA4) in melanoma (MM). Data and Methods. Fifty-nine patients with MM admitted to our hospital were enrolled as the MM group. They were followed up for 3 years to analyze the prognostic factors; meanwhile, 51 healthy subjects were allocated into a normal group. MM cell lines (M21 and C8161) were transfected with miR-29c-3p-mimics, miR-29c-3p-inhibitor, miR-NC, si-CDCA4, and sh-CDCA4. The expression of miR-29c-3p, CDCA4, Bax, Caspase3, Bcl-2, N-cadherin, vimentin, and E-cadherin was quantified, and cell proliferation, migration, invasion, and apoptosis, as well as epithelial-mesenchymal transition (EMT), were determined.

RESULTS

Serum miR-29c-3p was lowly expressed and CDCA4 was highly expressed in the MM group. The area under the curve (AUC) of both for diagnosing MM was greater than 0.9. miR-29c-3p and CDCA4 were related to regional lymph node staging (N staging), distant metastasis (M staging), tumor diameter, and pathological differentiation. Low miR-29c-3p and high CDCA4 were associated with poor prognosis of MM. Overexpression of miR-29c-3p and suppression of CDCA4 hindered cell proliferation, migration, invasion, and expression of Bax, Caspase3, N-cadherin, and vimentin, but cell apoptosis and expression of Bcl-2 and E-cadherin were enhanced. Dual-luciferase reporter (DLR) assay confirmed the targeted relationship between miR-29c-3p and CDCA4. After miR-29c-3p-mimics+sh-CDCA4 was transfected into M21 and C8161 cells, the proliferation, invasion, and apoptosis were not different from those in the miR-NC group transfected with unrelated sequences.

CONCLUSION

Overexpression of miR-29c-3p suppresses CDCA4 expression and decreases proliferation, migration, invasion, apoptosis, and EMT of MM cells, thus hindering MM progression.

CircITGA7 Suppresses Gastric Cancer Progression Through miR-1471/MTDH Axis

In recent years, there have been reports about the involvement of circular RNAs (circRNAs) in the pathogenesis of gastric cancer (GC), but the molecular mechanism in cell proliferation, invasion, and migration is still unclear. Based on The Cancer Genome Atlas (TCGA) database, we analyzed differentially expressed circRNAs between GC and non-tumor tissues. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were used to clarify the functional role in GC. Here, we showed that circITGA7 was lowly expressed in GC tissues based on the TCGA database. In vitro, silencing the expression of circITGA7 increased cell proliferation and metastasis, whereas overexpression did the opposite. Mechanistically, miR-1471 has circITGA7 as a sponge, and miR-1471 has metadherin (MTDH) as a target gene. Consequently, functional analysis showed that the tumor suppressor effect of circITGA7 was the result of regulating the miR-1471/MTDH axis. Overall, the circITGA7/miR-1471/MTDH signaling pathway may play a crucial role in GC, providing a new potential mechanism involved in GC progression.

miR-339-5p Inhibits Autophagy to Reduce the Resistance of Laryngeal Carcinoma on Cisplatin via Targeting TAK1

Laryngeal carcinoma is a malignant disease with high morbidity and mortality. Several studies have indicated that miRNA dysfunction involves in the development of laryngeal carcinoma. In this study, the connection of miR-339-5p and laryngeal carcinoma was investigated, and qRT-PCR, CCK-8, and flow cytometry assay were used to observe the function of miR-339-5p on laryngeal carcinoma. Besides, the target database, dual-luciferase reporter assay, and western blot were used to explore the regulation mechanism of miR-339-5p on the progression of laryngeal carcinoma. The results showed that miR-339-5p was significantly downregulated in cisplatin-resistant cells of laryngeal carcinoma, and miR-339-5p upregulation could weaken the resistance of laryngeal carcinoma cells on cisplatin. Moreover, miR-339-5p could directly react with 3'-UTR of TAK1, and TAK1 could reverse the effects of miR-339-5p on the progression of autophagy. In conclusion, this study suggests that miR-339-5p can inhibit the autophagy to decrease the cisplatin resistance of laryngeal carcinoma via targeting TAK1.

Integrative Analysis of Differently Expressed Genes Reveals a 17-Gene Prognosis Signature for Endometrial Carcinoma

Endometrial carcinoma (EC) is the fifth widely occurring malignant neoplasm among women all over the world. However, there is still lacking efficacy indicators for EC's prognosis. Here, we analyzed two databases including an RNA-sequencing-based TCGA dataset and a microarray-based GSE106191. After normalizing the raw data, we identified 114 common genes with upregulation and 308 common genes with downregulation in both the TCGA and GSE106191 databases. Bioinformatics analysis showed that the differently expressed genes in EC were related to the IL17 signaling pathway, PI3K-Akt signaling pathway, and cGMP-PKG signaling pathway. Furthermore, we performed the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and generated a signature featuring 17 prognosis-related genes (MAL2, ANKRD22, METTL7B, IL32, ERFE, OAS1, TRPC1, SRPX, RAPGEF4, PSD3, SIMC1, TRPC6, WFS1, PGR, PAMR1, KCNK6, and FAM189A2) and found that it could predict OS in EC patients. The further analysis showed that OAS1, MAL2, ANKRD22, METTL7B, and IL32 were significantly upregulated in EC samples after comparison with normal samples. However, TRPC1, SRPX, RAPGEF4, PSD3, SIMC1, TRPC6, WFS1, PGR, PAMR1, KCNK6, and FAM189A2 were significantly downregulated in EC samples in comparison with normal samples. And correlation analysis showed that our results showed that the expressions of 17 prognosis-related hub genes were significantly correlated based on Pearson correlation. We here offer a newly genetic biomarker for the prediction of EC patients' prognosis.

miR-101-3p Serves as a Tumor Suppressor for Renal Cell Carcinoma and Inhibits Its Invasion and Metastasis by Targeting EZH2

BACKGROUND

The role of miRNAs in renal cell carcinoma (RCC) is not certain. We wanted to study the biological functions and potential mechanisms of miR-101-3p in RCC.

METHODS

miR-101-3p was inhibited in A498 and OSRC-2 (two RCC cell lines). We studied its effect on cell invasion and proliferation. Target EZH2 of miR-101-3p was designated by different methods, including luciferase functional analysis and Western blotting. The expression level of the target gene in treated cells was quantitatively analyzed by quantitative real-time polymerase chain reaction. In addition, induction of miR-101-3p to prevent tumor formation of A498 cells in mice was further studied.

RESULTS

The overexpression of miR-101-3p significantly inhibited the proliferation, migration, and invasion in two RCC cells. Western blotting and luciferase functional analysis indicated that miR-101-3p regulated the expression of EZH2 in two cell lines. Mice inoculated with A498 and OSRC-2 cells transfected with miR-101-3p mimics showed significantly smaller xenografts and weaker EZH2 expression levels than the control group.

CONCLUSIONS

miR-101-3p inhibited RCC cell proliferation, migration, and invasion by targeting EZH2.

Increased Expression of PDK4 Was Displayed in Gastric Cancer and Exhibited an Association With Glucose Metabolism

Previous studies reported that pyruvate dehydrogenase kinase 4 (PDK4) is closely related to diabetes, heart disease, and carcinomas. Nevertheless, the role of PDK4 in gastric cancer (GC) occurrence and development is yet poorly understood. Our experiments were taken to evaluate PDK4's function in GC. The Cancer Genome Atlas tumor genome map database was employed to validate the levels of PDK family in different grades and stages of GC. The survival ratio of PDK families in GC was detected by the Kaplan-Meier plotter database. The links existing in the expression of PDK family and the level of tumor-infiltrating immune cells were investigated by tumor immunity assessment resource (TIMER). PDK4-associated signal pathways in GC were analyzed by the Kyoto Encyclopedia of Genes and Genomes pathway analysis. PDK4 mRNA level in the GC cells was measured by qRT-PCR. Cell counting kit-8 and Transwell assays were separately carried out to evaluate PDK4-induced influence on GC cell proliferation, migration, and invasion. Our data suggested that GC cells highly expressed PDK4, and PDK4 expression presented a significant relation with the staging, grade, and survival rate of GC. PDK4 expression presented a positive correlation with the types of different infiltrating immune cells, comprising B cells, CD4+ T cells, and dendritic cells. Meanwhile, PDK4 expression exhibited a strong association with macrophages. Survival analysis revealed that the expression of PDK4 displayed a relationship with the prognosis of patients. Therefore, PDK4 was liable to be a biomarker for prognosis. Our results further displayed that PDK4 might modulate the glycolysis level in GC cells, and its expression was associated with GC cell proliferation, migration, and invasion. These data may provide insights into designing a new treatment strategy for GC.

Altered Gene Expression in the Testis of Infertile Patients with Nonobstructive Azoospermia

Background

The molecular mechanism of nonobstructive azoospermia (NOA) remains unclear. The aim of this study was to identify gene expression changes in NOA patients and to explore potential biomarkers and therapeutic targets.

Methods

The gene expression profiles of GSE45885 and GSE145467 were collected from the Gene Expression Omnibus (GEO) database, and the differences between NOA and normal spermatogenesis were analyzed. Enrichment analysis was performed to explore biological functions for common differentially expressed genes (DEGs) in GSE45885 and GSE145467. Coexpression analysis of DEGs in GSE45885 was performed, and two modules with the highest correlation with NOA were screened. Key genes were then screened from the intersection genes of the two modules and common DEGs and PPI network. The expression of key genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR) experiments. Finally, through miRTarBase, miRDB, and RAID, the miRNAs were predicted to regulate key genes, respectively.

Results

A total of 345 common DEGs were identified and they were mainly related to spermatogenesis, insulin signaling pathway. Coexpression analysis of DEGs in GSE45885 yielded eight modules; MEblack and MEturquoise had the highest correlation with NOA. Six genes in MEturquoise and RNF141 in MEblack were identified as key genes. qRT-PCR experiments validated the differential expression of key genes between NOA and control. Furthermore, RNF141 was regulated by the largest number of miRNAs.

Conclusion

Our findings suggest that the significant change expression of key genes may be potential markers and therapeutic targets of NOA and may have some impact on the development of NOA.

Long Non-coding RNA FIRRE Acts as a miR-520a-3p Sponge to Promote Gallbladder Cancer Progression via Mediating YOD1 Expression

OBJECTIVES

The role of lncRNAs in gallbladder cancer (GBC) remains poorly understood. In this study, we explored the function of functional intergenic repeating RNA element (FIRRE) in GBC.

MATERIALS AND METHODS

Whole transcriptome resequencing was performed in three pairs of GBC tissues and adjacent non-tumor tissues. lncRNA FIRRE expression was verified by real-time PCR. The function of FIRRE in GBC was evaluated by experiments in vitro and in vivo. The mechanism of FIRRE was investigated via fluorescent in situ hybridization, RNA pull-down, dual luciferase reporter assays, and RNA immunoprecipitation.

RESULTS

FIRRE level was dramatically increased in GBC tissues compared to that in the adjacent non-tumor tissues. High expression of FIRRE was closely related to clinical stage and poor prognosis in GBC patients. Moreover, FIRRE remarkably enhanced proliferation and migration, and inhibited apoptosis of GBC cells. Mechanistically, FIRRE modulated YOD1 expression by sponging miR-520a-3p, thus contributing to the development of GBC.

CONCLUSION

Our data revealed that FIRRE might act as a novel mediator in GBC progression by sponging miR-520a-3p and regulating YOD1. FIRRE might be regarded as a potential diagnostic marker or target for GBC treatment.

Upregulation Mitochondrial Carrier 1 (MTCH1) Is Associated with Cell Proliferation, Invasion, and Migration of Liver Hepatocellular Carcinoma

Among the primary causes of cancer-associated death in the world, liver hepatocellular carcinoma (LIHC) ranks the third. LIHC is defined as the sixth most frequently diagnosed carcinoma. The gene mitochondrial carrier 1 (MTCH1) is a protein-coding gene. Recent research suggests that MTCH1 may be associated with some diseases. Here, our study attempts to explore the role and implication of MTCH1 in LIHC. Kaplan Meier Plotter and GEPIA (Gene Expression Profiling Interactive Analysis) databases were employed to determine the expression of MTCH1 and its correlation with prognostic status in LIHC patients. For the first time, our results suggested that MTCH1 was aberrantly expressed in human pan-cancer and highly expressed in LIHC. Its high expression was closely associated with metastasis of tumor, stage of cancer, and poor survival of patients. Then, through enrichment analysis, MTCH1 was found to be closely related to RNA splicing in LIHC. Subsequently, we conducted a series of functional experiments. PCR data showed that LIHC cell lines and samples are highly expressed MTCH1. CCK-8 (Cell Counting Kit-8) assays and Transwell assays indicated that silencing MTCH1 certainly suppressed cell proliferation, migration, and invasion. These findings shed the clue that MTCH1 could be regarded as the potential prognosis biomarker of LIHC and a promising therapeutic target for LIHC.

Marker Genes Change of Synovial Fibroblasts in Rheumatoid Arthritis Patients

Background

Rheumatoid arthritis (RA) is a chronic condition that manifests as inflammation of synovial joints, leading to joint destruction and deformity.

Methods

We identified single-cell RNA-seq data of synovial fibroblasts from RA and osteoarthritis (OA) patients in GSE109449 dataset. RA- and OA-specific cellular subpopulations were identified, and enrichment analysis was performed. Further, key genes for RA and OA were obtained by combined analysis with differentially expressed genes (DEGs) between RA and OA in GSE56409 dataset. The diagnostic role of key genes for RA was predicted using receiver operating characteristic (ROC) curve. Finally, we identified differences in immune cell infiltration between RA and OA patients, and utilized flow cytometry, qRT-PCR, and Western blot were used to examine the immune cell and key genes in RA patients.

Results

The cluster 0 matched OA and cluster 3 matched RA and significantly enriched for neutrophil-mediated immunity and ECM receptor interaction, respectively. We identified 478 DEGs. In the top 20 degrees of connection in the PPI network, the key genes for RA were obtained by comparing with the gene markers of cluster 0 and cluster 3, respectively. ROC curve showed that CCL2 and MMP13 might be diagnostic markers for RA. We found aberrant levels of CD8+T, neutrophil, and B cells in RA fibroblasts, which were validated in clinical samples. Importantly, we also validated the differential expression of key genes between RA and OA.

Conclusion

High expression of CCL2 and MMP13 in RA may be a diagnostic and therapeutic target.

Comprehensive Analysis and Identification of Key Driver Genes for Distinguishing Between Esophageal Adenocarcinoma and Squamous Cell Carcinoma

Background: Esophageal cancer (EC) is one of the deadliest cancers in the world. However, the mechanism that drives the evolution of EC is still unclear. On this basis, we identified the key genes and molecular pathways that may be related to the progression of esophageal adenocarcinoma and squamous cell carcinoma to find potential markers or therapeutic targets. Methods: GSE26886 were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) among normal samples, EA, and squamous cell carcinoma were determined using R software. Then, potential functions of DEGs were determined using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The STRING software was used to identify the most important modules in the protein-protein interaction (PPI) network. The expression levels of hub genes were confirmed using UALCAN database. Kaplan-Meier plotters were used to confirm the correlation between hub genes and outcomes in EC. Results: In this study, we identified 1,098 genes induced in esophageal adenocarcinoma (EA) and esophageal squamous cell carcinoma (ESCC), and 669 genes were reduced in EA and ESCC, suggesting that these genes may play an important role in the occurrence and development of EC tumors. Bioinformatics analysis showed that these genes were involved in cell cycle regulation and p53 and phosphoinositide 3-kinase (PI3K)/Akt signaling pathway. In addition, we identified 147 induced genes and 130 reduced genes differentially expressed in EA and ESCC. The expression of ESCC in the EA group was different from that in the control group. By PPI network analysis, we identified 10 hub genes, including GNAQ, RGS5, MAPK1, ATP1B1, HADHA, HSDL2, SLC25A20, ACOX1, SCP2, and NLN. TCGA validation showed that these genes were present in the dysfunctional samples between EC and normal samples and between EA and ESCC. Kaplan-Meier analysis showed that MAPK1, ACOX1, SCP2, and NLN were associated with overall survival in patients with ESCC and EA. Conclusions: In this study, we identified a series of DEGs between EC and normal samples and between EA and ESCC samples. We also identified 10 key genes involved in the EC process. We believe that this study may provide a new biomarker for the prognosis of EA and ESCC.

Identification of Molecular Characteristics and New Prognostic Targets for Thymoma by Multiomics Analysis

BACKGROUND

Thymoma is a heterogeneous tumor originated from thymic epithelial cells. The molecular mechanism of thymoma remains unclear.

METHODS

The expression profile, methylation, and mutation data of thymoma were obtained from TCGA database. The coexpression network was constructed using the variance of gene expression through WGCNA. Enrichment analysis using clusterProfiler R package and overall survival (OS) analysis by Kaplan-Meier method were carried out for the intersection of differential expression genes (DEGs) screened by limma R package and important module genes. PPI network was constructed based on STRING database for genes with significant impact on survival. The impact of key genes on the prognosis of thymoma was evaluated by ROC curve and Cox regression model. Finally, the immune cell infiltration, methylation modification, and gene mutation were calculated.

RESULTS

We obtained eleven coexpression modules, and three of them were higher positively correlated with thymoma. DEGs in these three modules mainly involved in MAPK cascade and PPAR pathway. LIPE, MYH6, ACTG2, KLF4, SULT4A1, and TF were identified as key genes through the PPI network. AUC values of LIPE were the highest. Cox regression analysis showed that low expression of LIPE was a prognostic risk factor for thymoma. In addition, there was a high correlation between LIPE and T cells. Importantly, the expression of LIPE was modified by methylation. Among all the mutated genes, GTF2I had the highest mutation frequency.

CONCLUSION

These results suggested that the molecular mechanism of thymoma may be related to immune inflammation. LIPE may be the key genes affecting prognosis of thymoma. Our findings will help to elucidate the pathogenesis and therapeutic targets of thymoma.

Construction of a Nine-MicroRNA-Based Signature to Predict the Overall Survival of Esophageal Cancer Patients

BACKGROUND

Esophageal cancer (EC) is a common malignant tumor. MicroRNAs (miRNAs) play a key role in the occurrence and metastasis and are closely related to the prognosis of EC. Therefore, it will provide a powerful tool to predict the overall survival (OS) of EC patients based on miRNAs expression in EC tissues and blood samples.

METHODS

Five independent databases, TCGA, GSE106817, GSE113486, GSE122497, and GSE112264, were used to construct nine-miRna signature and nomograms for prognosis. The bioinformatics analysis was used to predict the enrichment pathways of targets.

RESULTS

A total of 132 overexpressed miRNAs and 23 suppressed miRNAs showed significant differential expression in both EC serum and tissue samples compared with normal samples. We also showed that nine miRNAs were related to the prognosis of EC. Higher levels of miR-15a-5p, miR-92a-3p, miR-92a-1-5p, miR-590-5p, miR-324-5p, miR-25-3p, miR-181b-5p, miR-421, and miR-93-5p were correlated to the shorter survival time in patients with EC. In addition, we constructed a risk prediction model based on the levels of nine differentially expressed miRNAs (DEMs) and found that the OS time of EC patients with high-risk score was shorter than that of EC patients with low-risk score. Furthermore, our results showed that the risk prediction scores of EC samples were higher than those of normal samples. Finally, the area under the curve (AUC) was used to analyze the risk characteristics of EC and normal controls. By calculating the AUC and the calibration curve, the RNA signature showed a good performance. Bioinformatics analysis showed that nine DEMs were associated with several crucial signaling, including p53, FoxO, PI3K-Akt, HIF-1, and TORC1 signaling. Finally, 14 messenger RNAs (mRNAs) were identified as hub targets of nine miRNAs, including BTRC, SIAH1, RNF138, CDC27, NEDD4L, MKRN1, RLIM, FBXO11, RNF34, MYLIP, FBXW7, RNF4, UBE3C, and RNF111. TCGA dataset validation showed that these hub targets were significantly differently expressed in EC tissues compared with normal samples.

CONCLUSION

We have constructed maps and nomograms of nine-miRna risk signals associated with EC prognosis. Bioinformatics analysis revealed that nine DEMs were associated with several crucial signaling, including p53, FoxO, PI3K-Akt, HIF-1, and TORC1 signaling, in EC. We think that this study will provide clinicians with an effective decision-making tool.

PD-L1 and Immune Infiltration of m6A RNA Methylation Regulators and Its miRNA Regulators in Hepatocellular Carcinoma

BACKGROUND

The aim of this study was to systematically evaluate the relationship between the expression of m6A RNA methylation regulators and prognosis in HCC.

METHODS

We compared the expression of m6A methylation modulators and PD-L1 between HCC and normal in TCGA database. HCC samples were divided into two subtypes by consensus clustering of data from m6A RNA methylation regulators. The differences in PD-L1, immune infiltration, and prognosis between the two subtypes were further compared. The LASSO regression was used to build a risk score for m6A modulators. In addition, we identified miRNAs that regulate m6A regulators.

RESULTS

We found that fourteen m6A regulatory genes were significantly differentially expressed between HCC and normal. HCC samples were divided into two clusters. Of these, there are higher PD-L1 expression and poorer overall survival (OS) in cluster 1. There was a significant difference in immune cell infiltration between cluster 1 and cluster 2. Through the LASSO model, we obtained 12 m6A methylation regulators to construct a prognostic risk score. Compared with patients with a high-risk score, patients with a low-risk score had upregulated PD-L1 expression and worse prognosis. There was a significant correlation between risk score and tumor-infiltrating immune cells. Finally, we found that miR-142 may be the important regulator for m6A RNA methylation in HCC.

CONCLUSION

Our results suggest that m6A RNA methylation modulators may affect the prognosis through PD-L1 and immune cell infiltration in HCC patients. In addition, the two clusters may be beneficial for prognostic stratification and improving immunotherapeutic efficacy.

Circular RNA circitga7 accelerates glioma progression via miR-34a-5p/VEGFA axis

Circular RNAs (circRNAs) are a group of noncoding RNAs derived from back-splicing events. CircRNA is reported to be involved in various tumor progressions, including glioma. Although there are a few reports of circular RNAs participating in gliomas, it is still unclear whether circular RNAs regulate the occurrence of gliomas. In our research, we found that the expression of circITGA7 in glioma tissues and glioma cells increased significantly. Knocking down circITGA7 can significantly inhibit the proliferation of glioma cells and reduce cell metastasis. Through analysis and dual-luciferase report assay, we found that circITGA7 acts as a sponge for miR-34a-5p targeting VEGFA in glioma. Our study showed that circITGA7 regulates the proliferation and metastasis of glioma cell lines (SW1783&U373) by regulating the miR-34a-5p/VEGFA pathway. In conclusion, our study revealed a regulatory loop for the circITGA7/miR-34a-5p/VEGFA axis to regulate glioma development.

Hippo Pathway Core Genes Based Prognostic Signature and Immune Infiltration Patterns in Lung Squamous Cell Carcinoma

BACKGROUND

We investigated the prognostic effects and their patterns of immune infiltration of hippo pathway core genes in lung squamous cell carcinoma, in order to find some clues for underlying mechanisms of LUSC tumorigenesis and help developing new therapeutic methods.

METHODS

The mutational data, transcriptome data and corresponding clinical medical information of LUSC patients were extracted from The Cancer Genome Atlas (TCGA) database. Differential expression genes (DEGs) and Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were explored. Survival analysis for the hippo core genes and the prognostic model were performed. Immune infiltration was estimated by CIBERSORT algorithm and some immune checkpoints-related genes were further investigated.

RESULTS

Overall, 551 LUSC samples were included in our study, consisting of 502 LUSC tumor samples and 49 adjacent normal samples, respectively. There were 1910 up-regulated DEGs and 2253 down-regulated DEGs were finally identified. The top five mutational hippo pathway core genes were LATS1 (4%), WWC1 (2%), TAOK1 (2%), TAOK3 (2%), and TAOK2 (2%), respectively. the mutation of LATS2 was highly associated with co-mutational NF2 (P <0.05) and TAOK1 (P <0.05). In survival analyses, we found only WWC1 (log-rank p = 0.046, HR = 1.32, 95% CI = 1-1.73) and LATS2 (log-rank p = 0.013, HR = 1.41, 95%CI = 1.08-1.86) had significant prognostic roles. After getting the three subgroups according to the subtyping results, we demonstrated that T cell gamma delta (p = 5.78e-6), B cell memory (p = 4.61e-4) and T cell CD4+ memory resting (p = 2.65e-5) had significant differences among the three groups. SIGLEC15 (P <0.01) and CD274 (P <0.05) also had statistical differences among the three subgroups.

CONCLUSIONS

Our study verified the prognostic roles of WWC1 and LATS2 in LUSC patients. Immune checkpoints-related genes SIGLEC15 and CD274 had statistical differences among the three subgroups, which may provide new perceptions on the molecular mechanisms in LUSC and maybe helpful for precisely selecting specific LUSC patients with potential immunotherapy benefits.

Identification of Molecular Regulatory Features and Markers for Acute Type A Aortic Dissection

BACKGROUND

Acute type A aortic dissection (ATAAD) is one of the most lethal cardiovascular diseases, and its molecular mechanism remains unclear.

METHODS

Differentially expressed genes (DEGs) between ATAAD and control were detected by limma R package in GSE52093, GSE153434, GSE98770, and GSE84827, respectively. The coexpression network of DEGs was identified by the WGCNA package. Enrichment analysis was performed for module genes that were positively correlated with ATAAD using clusterProfiler R package. In addition, differentially methylated markers between aortic dissection and control were identified by ChAMP package. After comparing with ATAAD-related genes, a protein-protein interaction (PPI) network was established based on the STRING database. The genes with the highest connectivity were identified as hub genes. Finally, differential immune cell infiltration between ATAAD and control was identified by ssGSEA.

RESULTS

From GSE52093 and GSE153434, 268 module genes were obtained with consistent direction of differential expression and high correlation with ATAAD. They were significantly enriched in T cell activation, HIF-1 signaling pathway, and cell cycle. In addition, 2060 differentially methylated markers were obtained from GSE84827. Among them, 77 methylation markers were ATAAD-related DEGs. Using the PPI network, we identified MYC, ITGA2, RND3, BCL2, and PHLPP2 as hub genes. Finally, we identified significantly differentially infiltrated immune cells in ATAAD.

CONCLUSION

The hub genes we identified may be regulated by methylation and participate in the development of ATAAD through immune inflammation and oxidative stress response. The findings may provide new insights into the molecular mechanisms and therapeutic targets for ATAAD.

Identification of Inflammatory Genes, Pathways, and Immune Cells in Necrotizing Enterocolitis of Preterm Infant by Bioinformatics Approaches

Background

Necrotizing enterocolitis (NEC) is one of the most serious gastrointestinal disease-causing high morbidity and mortality in premature infants. However, the underlying mechanism of the pathogenesis of NEC is still not fully understood.

Methods

RNA sequencing of intestinal specimens from 9 NEC and 5 controls was employed to quantify the gene expression levels. RNA sequencing was employed to quantify the gene expression levels. DESeq2 tool was used to identify the differentially expressed genes. The biological function, pathways, transcription factors, and immune cells dysregulated in NEC were characterized by gene set enrichment analysis.

Results

In the present study, we analyzed RNA sequencing data of NECs and controls and revealed that immune-related pathways were highly activated, while some cellular responses to external stimuli-related pathways were inactivated in NEC. Moreover, B cells, macrophages M1, and plasma cells were identified as the major cell types involved in NEC. Furthermore, we also found that inflammation-related transcription factor genes, such as STAT1, STAT2, and IRF2, were significantly activated in NEC, further suggesting that these TFs might play critical roles in NEC pathogenesis. In addition, NEC samples exhibited heterogeneity to some extent. Interestingly, two subgroups in the NEC samples were identified by hierarchical clustering analysis. Notably, B cells, T cells, Th1, and Tregs involved in adaptive immune were predicted to highly infiltrate into subgroup I, while subgroup II was significantly infiltrated by neutrophils. The heterogeneity of immune cells in NEC indicated that both innate and adaptive immunes might induce NEC-related inflammatory response.

Conclusions

In summary, we systematically analyzed inflammation-related genes, signaling pathways, and immune cells to characterize the NEC pathogenesis and samples, which greatly improved our understanding of the roles of inflammatory responses in NEC.

circSLC8A1 Acts as a Tumor Suppressor in Prostate Cancer via Sponging miR-21

BACKGROUND

There is more and more evidence showed that circRNAs played essentially role in the regulation of various biological processes. The role of circSLC8A1 in prostate cancer (PCa) is yet little known.

METHODS

The CircSLC8A1 expression in human prostate cancer was measured by qRT-PCR. The interplay between the specific circRNA, miRNA, and mRNA was investigated by RT-PCR and luciferase reporter assay. Through transient transfection of siRNA, the impacts of circSLC8A1 on PCa were discussed. Cell cycle evaluation, transwell assay, and CCK-8 assay were employed to determine its biological influences.

RESULTS

In this study, our data revealed that circSLC8A1 was downregulated in PCa tissues and cells. The reduction of circSLC8A1 resulted in the inhibition of cell proliferation and migration. In mechanism, circSLC8A1 exhibited a direct interaction with miR-21 and displayed as a miRNA sponge to inhibit PCa progression. The functional analysis revealed that the circSLC8A1/miR-21 axis may regulate the cell proliferation, angiogenesis, cell migration, epithelial to mesenchymal transition, MAPK signaling pathway, and chemokine signaling pathway.

CONCLUSIONS

CircSLC8A1 functioned as an inhibitor of neoplasm via modulating the miR-21 and might serve as a prospective target for the treatment of PCa.

Gene Expression Signature of Traumatic Brain Injury

Background: Traumatic brain injury (TBI) is a brain function change caused by external forces, which is one of the main causes of death and disability worldwide. The aim of this study was to identify early diagnostic markers and potential therapeutic targets for TBI.

Methods: Differences between TBI and controls in GSE89866 and GSE104687 were analyzed. The two groups of differentially expressed genes (DEGs) were combined for coexpression analysis, and the modules of interest were performed using enrichment analysis. Hub genes were identified by calculating area under curve (AUC) values of module genes, PPI network analysis, and functional similarity. Finally, the difference in immune cell infiltration between TBI and control was calculated by ssGSEA.

Results: A total of 4,817 DEGs were identified in GSE89866 and 1,329 DEGs in GSE104687. They were clustered into nine modules. The genes of modules 1, 4, and 7 had the most crosstalk and were identified as important modules. Enrichment analysis revealed that they were mainly associated with neurodevelopment and immune inflammation. In the PPI network constructed by genes with top 50 AUC values in module genes, we identified the top 10 genes with the greatest connectivity. Among them, down-regulated RPL27, RPS4X, RPL23A, RPS15A, and RPL7A had similar functions and were identified as hub genes. In addition, DC and Tem were significantly up-regulated and down-regulated between TBI and control, respectively.

Conclusion: We found that hub genes may have a diagnostic role for TBI. Molecular dysregulation mechanisms of TBI are associated with neurological and immune inflammation. These results may provide new ideas for the diagnosis and treatment of TBI.

Comprehensive Analysis of the Prognostic Role and Mutational Characteristics of m6A-Related Genes in Lung Squamous Cell Carcinoma

BACKGROUND

There have been limited treatment therapies for lung squamous cell carcinoma (LUSC). M6A-related genes may be the next therapeutic targets for LUSC. In this study, we explored the prognostic role and mutational characteristics of m6A-related genes in LUSC.

METHODS

LUSC gene expression data, mutational data, and corresponding clinical information were extracted from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified, and the mutation characteristics of LUSC patients were explored. Then, m6A-related genes were extracted and the correlations among the genes were detected. Finally, the prognostic roles of the genes were investigated and the nomogram model was developed. Besides, the protein-protein interaction (PPI) network was used to explore the potential interactions among the genes.

RESULTS

In total, there are 551 LUSC samples enrolled in our study, containing 502 LUSC tumor samples and 49 adjacent normal LUSC samples, respectively. There were 2970 upregulated DEGs and 1806 downregulated DEGs were further explored. IGF2BP1 and RBM15 had significant co-occurrence frequency (p < 0.05). Besides, METTL14 and ZC3H13 or YTHDF3 also had significant co-occurrence frequency (p < 0.05). All the m6A-related genes represent the positive correlation. WTAP was identified as a prognostic gene in the TCGA database while YTHDC1 and YTHDF1 were identified as prognostic genes. In multivariate Cox analysis, YTHDF1, age, pN stage, pTNM stage, and smoking were all identified as significant prognostic factors for OS.

CONCLUSION

We investigated the expression patterns and mutational characteristics of LUSC patients and identified three potential independent prognostic m6A-related genes (WTAP, YTHDC1, and YTHDF1) for OS in LUSC patients.

Identification of Potential Therapeutic Targets and Molecular Regulatory Mechanisms for Osteoporosis by Bioinformatics Methods

BACKGROUND

Osteoporosis is characterized by low bone mass, deterioration of bone tissue structure, and susceptibility to fracture. New and more suitable therapeutic targets need to be discovered.

METHODS

We collected osteoporosis-related datasets (GSE56815, GSE99624, and GSE63446). The methylation markers were obtained by differential analysis. Degree, DMNC, MCC, and MNC plug-ins were used to screen the important methylation markers in PPI network, then enrichment analysis was performed. ROC curve was used to evaluate the diagnostic effect of osteoporosis. In addition, we evaluated the difference in immune cell infiltration between osteoporotic patients and control by ssGSEA. Finally, differential miRNAs in osteoporosis were used to predict the regulators of key methylation markers.

RESULTS

A total of 2351 differentially expressed genes and 5246 differentially methylated positions were obtained between osteoporotic patients and controls. We identified 19 methylation markers by PPI network. They were mainly involved in biological functions and signaling pathways such as apoptosis and immune inflammation. HIST1H3G, MAP3K5, NOP2, OXA1L, and ZFPM2 with higher AUC values were considered key methylation markers. There were significant differences in immune cell infiltration between osteoporotic patients and controls, especially dendritic cells and natural killer cells. The correlation between MAP3K5 and immune cells was high, and its differential expression was also validated by other two datasets. In addition, NOP2 was predicted to be regulated by differentially expressed hsa-miR-3130-5p.

CONCLUSION

Our efforts aim to provide new methylation markers as therapeutic targets for osteoporosis to better treat osteoporosis in the future.

m6A Regulators Is Differently Expressed and Correlated With Immune Response of Esophageal Cancer

N6 methyladenosine (m6A) RNA methylation regulators play an important role in the development of tumors. However, their function in esophageal cancer (EC) has not been fully elucidated. Here, we analyzed the gene expression data of 24 major m6A RNA methylation regulators from 775 patients with EC from TCGA dataset. The present study showed the aberrations of m6A regulators in genome were correlated to prognosis in human ECs. Meanwhile, 17 m6A regulators showed increased expression in EC samples, including YTHDC1, IGF2BP2, FTO, METTL14, YTHDF3, RBM15, WTAP, HNRNPA2B1, HNRNPC, ALKBH5, YTHDF2, METTL16, IGF2BP3, VIRMA, RBM15B, YTHDF1, KIAA1429, HAKAI, and ZC3H13. Among them, we found HNRNPC, YTHDC2, WTAP, VIRMA, IGF2BP3, and HNRNPA2B1 were significantly correlated to worse outcomes and advanced stage in EC. Furthermore, we showed levels of m6A regulators is correlated with the expression of Immuno-regulators (Immunoinhibitors, Immunostimulators, and MHC molecules) and immune infiltration levels in EC. Bioinformatics further confirm m6A regulators were involved in regulating RNA splicing, RNA stability, and cell proliferation. Our study showed m6A regulators are promising targets and biomarkers for cancer immunotherapy in EC.

Identification of Common Genes and Pathways in Eight Fibrosis Diseases

Acute and chronic inflammation often leads to fibrosis, which is also the common and final pathological outcome of chronic inflammatory diseases. To explore the common genes and pathogenic pathways among different fibrotic diseases, we collected all the reported genes of the eight fibrotic diseases: eye fibrosis, heart fibrosis, hepatic fibrosis, intestinal fibrosis, lung fibrosis, pancreas fibrosis, renal fibrosis, and skin fibrosis. We calculated the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment scores of all fibrotic disease genes. Each gene was encoded using KEGG and GO enrichment scores, which reflected how much a gene can affect this function. For each fibrotic disease, by comparing the KEGG and GO enrichment scores between reported disease genes and other genes using the Monte Carlo feature selection (MCFS) method, the key KEGG and GO features were identified. We compared the gene overlaps among eight fibrotic diseases and connective tissue growth factor (CTGF) was finally identified as the common key molecule. The key KEGG and GO features of the eight fibrotic diseases were all screened by MCFS method. Moreover, we interestingly found overlaps of pathways between renal fibrosis and skin fibrosis, such as GO:1901890-positive regulation of cell junction assembly, as well as common regulatory genes, such as CTGF, which is the key molecule regulating fibrogenesis. We hope to offer a new insight into the cellular and molecular mechanisms underlying fibrosis and therefore help leading to the development of new drugs, which specifically delay or even improve the symptoms of fibrosis.

Integrated WGCNA and PPI Network to Screen Hub Genes Signatures for Infantile Hemangioma

BACKGROUND

Infantile hemangioma (IH) is characterized by proliferation and regression.

METHODS

Based on the GSE127487 dataset, the differentially expressed genes (DEGs) between 6, 12, or 24 months and normal samples were screened, respectively. STEM software was used to screen the continued up-regulated or down-regulated in common genes. The modules were assessed by weighted gene co-expression network analysis (WGCNA). The enrichment analysis was performed to identified the biological function of important module genes. The area under curve (AUC) value and protein-protein interaction (PPI) network were used to identify hub genes. The differential expression of hub genes in IH and normal tissues was detected by qPCR.

RESULTS

There were 5,785, 4,712, and 2,149 DEGs between 6, 12, and 24 months and normal tissues. We found 1,218 DEGs were up-regulated or down-regulated expression simultaneously in common genes. They were identified as 10 co-expression modules. Module 3 and module 4 were positively or negatively correlated with the development of IH, respectively. These two module genes were significantly involved in immunity, cell cycle arrest and mTOR signaling pathway. The two module genes with AUC greater than 0.8 at different stages of IH were put into PPI network, and five genes with the highest degree were identified as hub genes. The differential expression of these genes was also verified by qRTPCR.

CONCLUSION

Five hub genes may distinguish for proliferative and regressive IH lesions. The WGCNA and PPI network analyses may help to clarify the molecular mechanism of IH at different stages.

Circular PVT1 regulates cell proliferation and invasion via miR-149-5p/FOXM1 axis in ovarian cancer

Long non-coding RNA plasmacytoma variant translocation 1 (PVT1) is a dysregulated gene in malignancy and is associated with oncogenesis. In this study, we found PVT1 RNA was an ovarian specific expressing gene, and overexpressed in multiple cancer types, including ovarian cancer (OV). Higher expression levels of PVT1 are related to shorter survival time in OV patients, especially in patients with advanced stage and grade. Recent studies indicated circular PVT1 also had an important role in cancer progression, whose roles in OV remain unclear. Knockdown of circular PVT1 significantly suppressed OV cell proliferation, migration and invasion. Bioinformatics analysis demonstrated that circular PVT1 was involved in regulating angiogenesis, osteoblast differentiation, regulation of cell growth, type B pancreatic cell proliferation, negative regulation of apoptotic process, phospholipid homeostasis, regulation of neurogenesis, definitive hemopoiesis, cell migration, regulation of glucose metabolic process, central nervous system development and type 2 immune response. Our data showed miR-149-5p targeted FOXM1, which was regulated by circular PVT1. Forkhead Box M1 (FOXM1) expression in ovarian cancer exhibited high level when compared with normal tissues, and had relation with relatively poor survival. FOXM1 promoted cell viability and reduced FOXM1 could rescue circular influence of circular PVT1-caused carcinoma induction. In conclusion, circular PVT1 increased FOXM1 level via binding to miR-149-5p and thus affected ovarian cancer cell viability and migration.

Identification of driver genes with aberrantly alternative splicing events in pediatric patients with retinoblastoma

Retinoblastoma (RB) is one of the most common cancer in children. However, the specific mechanism about RB tumorigenesis has not been fully understood. In this study, to comprehensively characterize the splicing alterations in the tumorigenesis of RB, we analyzed the differential alternative splicing events in RB. Specifically, the isoforms of RB1 were downregulated in the RB samples, and a large proportion of differentially expressed genes had multiple differentially expressed transcripts (64%). We identified 1453 genes with differential alternative splicing, among which, SE accounted for the majority, followed by MXE, RI, A3SS, and A5SS. Furthermore, the biological function related to the normal function of eyes, and E2F family TFs were significantly enriched by the genes with differential alternative splicing. Among the genes associated with visual sense, ABCA4 was found to have two mutually exclusive exons, resulting in two isoforms with different functionalities. Notably, DAZAP1 was identified as one of the critical splicing factors in RB, which was potentially involved in E2F and RB pathways. Functionally, differential binding sites in DAZAP1 protein were significantly observed between RB and normal samples. Based on the comprehensive analysis of the differential alternative splicing events and splicing factors, we identified some driver genes with differential alternative splicing and critical splicing factors involved in RB, which would greatly improve our understanding of the alternative splicing process in the tumorigenesis of RB.

RNA m6A Modification in Cancers: Molecular Mechanisms and Potential Clinical Applications

N6-Methyladenosine (m6A) RNA modification brings a new dawn for RNA modification researches in recent years. This posttranscriptional RNA modification is dynamic and reversible, and is regulated by methylases ("writers"), demethylases ("erasers"), and proteins that preferentially recognize m6A modifications ("readers"). The change of RNA m6A modification regulates RNA metabolism in eucaryon, including translation, splicing, exporting, decay, and processing. Thereby the dysregulation of m6A may lead to tumorigenesis and progression. Given the tumorigenic role of abnormal m6A expression, m6A regulators may function as potential clinical therapeutic targets for cancers. In this review, we emphasize on the underlying mechanisms of m6A modifications in tumorigenesis and further introduce the potential m6A regulators-associated therapeutic targets for tumor therapy.

Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer

Background

Breast cancer (BC) is the most common malignant tumor in women. The immunophenotype of tumor microenvironment (TME) has shown great therapeutic potential in tumor.

Method

The transcriptome was obtained from TCGA and GEO data. Immune infiltration was analyzed by single-sample gene set enrichment (ssGSEA). The immune feature was constructed by Cox regression analysis. In addition, the coexpression of differential expression genes (DEGs) was identified. Through enrichment analysis, the function and pathway of module genes were identified. The somatic mutations related to immune characteristics were analyzed by Maftools. By using the consistency clustering algorithm, the molecular subtypes were constructed, and the overall survival time (OS) was predicted.

Results

Immune landscape can be divided into low immune infiltration and high immune infiltration. Cox regression analysis identified seven immune cells as protective factors of BC. In the coexpression modules for DEGs of high and low immune infiltration, module 1 was related to T cells and high immune infiltration. In particular, the area under the curve (AUC) value of hub gene SASH3 was the highest, and the correlation with T cells was stronger in the high immune infiltration. Enrichment analysis found that oxidative stress, T cell aggregation, and apoptosis were observed in high immune infiltration. In addition, TP53 was identified as the most important somatic gene mutation related to immune characteristics. Importantly, we also constructed seven immune cell-based breast cancer subtypes to predict OS.

Conclusion

We evaluated the immune landscape of BC and constructed the gene characteristics related to the immune landscape. The potential of T cells and SASH3 in immunotherapy of BC was revealed, which may guide the development of new clinical treatment strategies.

Identification of Key Genes Involved in Acute Myocardial Infarction by Comparative Transcriptome Analysis

Background

Acute myocardial infarction (AMI) is regarded as an urgent clinical entity, and identification of differentially expressed genes, lncRNAs, and altered pathways shall provide new insight into the molecular mechanisms behind AMI.

Materials and Methods

Microarray data was collected to identify key genes and lncRNAs involved in AMI pathogenesis. The differential expression analysis and gene set enrichment analysis (GSEA) were employed to identify the upregulated and downregulated genes and pathways in AMI. The protein-protein interaction network and protein-RNA interaction analysis were utilized to reveal key long noncoding RNAs.

Results

In the present study, we utilized gene expression profiles of circulating endothelial cells (CEC) from 49 patients of AMI and 50 controls and identified a total of 552 differentially expressed genes (DEGs). Based on these DEGs, we also observed that inflammatory response-related genes and pathways were highly upregulated in AMI. Mapping the DEGs to the protein-protein interaction (PPI) network and identifying the subnetworks, we found that OMD and WDFY3 were the hub nodes of two subnetworks with the highest connectivity, which were found to be involved in circadian rhythm and organ- or tissue-specific immune response. Furthermore, 23 lncRNAs were differentially expressed between AMI and control groups. Specifically, we identified some functional lncRNAs, including XIST and its antisense RNA, TSIX, and three lncRNAs (LINC00528, LINC00936, and LINC01001), which were predicted to be interacting with TLR2 and participate in Toll-like receptor signaling pathway. In addition, we also employed the MMPC algorithm to identify six gene signatures for AMI diagnosis. Particularly, the multivariable SVM model based on the six genes has achieved a satisfying performance (AUC = 0.97).

Conclusion

In conclusion, we have identified key regulatory lncRNAs implicated in AMI, which not only deepens our understanding of the lncRNA-related molecular mechanism of AMI but also provides computationally predicted regulatory lncRNAs for AMI researchers.

Network-Based Coexpression Analysis Identifies Functional and Prognostic Long Noncoding RNAs in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a primary liver cancer associated with a growing incidence and extremely high mortality. However, the pathogenic mechanism is still not fully understood. In the present study, we identified 1,631 upregulated and 1,515 downregulated genes and found that cell cycle and metabolism-related pathways or biological processes highly dysregulated in HCC. To assess the biological importance of these DEGs, we carried out weighted gene coexpression network analysis (WGCNA) to identify the functional modules potentially involved in HCC pathogenesis or progression. The five modules were detected with Dynamic Tree Cut algorithm, and GO enrichment analysis revealed that these modules exhibited different biological processes or signaling pathways, such as metabolism-related pathways, cell proliferation-related pathways, and molecules in tumor microenvironment. Moreover, we also observed two immune cells, namely, cytotoxic cells and macrophage enriched in modules grey and brown, respectively, while T helper cell-2 (Th2) was enriched in module turquoise. Among the WGCNA network, four hub long noncoding RNAs (lncRNAs) were identified to be associated with HCC prognostic outcomes, suggesting that coexpression network analysis could uncover lncRNAs with functional importance, which may be associated with prognostic outcomes of HCC patients. In summary, this study demonstrated that network-based analysis could identify some functional modules and some hub-lncRNAs, which may be critical for HCC pathogenesis or progression.

CircDENND2A Promotes Non-small Cell Lung Cancer Progression via Regulating MiR-34a/CCNE1 Signaling

The mechanism regulating non-small cell lung cancers (NSCLCs) is unclear. In this study, we aimed to determine the roles of DENN domain containing 2A (circDENND2A) in the progression of NSCLC. Circular RNAs (circRNAs) are composited by “head to tail” splicing of coding or non-coding RNAs (ncRNAs), whose crucial roles in human cancers had been revealed. CircDENND2A, a new circRNA, was revealed to induce cell proliferation and migration. Our data indicated that circDENND2A was a probable oncogene in human cancers. However, the roles of circDENND2A in NSCLC remained unknown. Here, we demonstrated that circDENND2A was down-regulated in NSCLC samples. Loss-of-function assays showed circDENND2A knockdown suppressed cell growth via inducing cell cycle arrest and apoptosis and inhibited cell migration and invasion. Bioinformatics analysis and competing endogenous RNA (ceRNA) network analysis revealed that circDENND2A was involved in regulating cell cycle and tumor protein p53 (TP53) signaling via miR-34a/CCNE1 (cyclin E1). Further validation showed that circDENND2A could directly bind to miR-34a, promoting CCNE1 expression in NSCLC. In addition, rescue assays demonstrated that restoration of CCNE1 significantly impaired the suppressive effects of circDENND2A silencing in terms of NSCLC growth, migration, and invasion. We thought this study indicated that circDENND2A/miR-34a/CCNE1 may be a potential therapeutic target for NSCLC.

Identification and Characterization of Copy Number-Associated Driver Genes in Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is a leading malignancy with both high incidence and mortality worldwide. However, the molecular mechanisms of the poor prognosis in ESCC are still unclear.

Methods

We conducted differential expression analysis between ESCC and normal tissues and between ESCC samples with and without CNAs in a given gene. Overrepresentation enrichment and gene set enrichment analyses were used to identify the oncogenic pathways and abnormal transcription factors (TFs). The survival analysis was employed to identify the genes associated with overall survival.

Results

In this study, we aimed to identify and interpret the driver genes triggered by the copy number alterations (CNAs), including CCND1, TEAD4, EIF4EBP1, EGFR, FGFR3, and FZD6. Furthermore, we identified oncogenic pathways, including RTK-RAS, WNT, PI3K, Hippo, and cell cycle, and key TFs including TEAD4, a transcription factor in the Hippo signaling pathway, and LEF1 in the WNT signaling pathway. Furthermore, we observed that upregulations of FGFR3 and EIF4EBP1 were significantly associated with shorter overall survival in ESCC.

Conclusion

In conclusion, the driver genes triggered by CNAs not only exhibited critical functionality but also were clinically relevant in ESCC, which greatly improved our understanding of the molecular mechanisms in ESCC.

Functional Modular Network Identifies the Key Genes of Preoperative Inhalation Anesthesia and Intravenous Anesthesia in Off-Pump Coronary Artery Bypass Grafting

Off-pump coronary artery bypass grafting (OPCABG) is an effective strategy for revascularization. Preoperative anesthesia appears critical due to surgical instability and the risk of organ damage. This study, based on a functional module network, analysed the effects of preoperative inhalation anesthesia and intravenous anesthesia on OPCABG and performed a pivot analysis of its potential drug regulators. We obtained microarray data of sevoflurane anesthesia and propofol anesthesia from the GEO database and analysed the difference between the two groups of data, resulting in 5701 and 3210 differential genes to construct the expression matrix. WGCNA analysis showed that sevoflurane anesthesia clustered into 7 functional disorder modules, including PDCD6IP, WDR3, and other core genes; propofol anesthesia clustered to form two functional disorder modules, including KCNB2 and LHX2, two core genes Enrichment analysis of the functions and pathways of interest suggests that both anesthesia-related module genes tend to function as pathways associated with ion and transmembrane transport. The underlying mechanism may be that targeted regulation of transmembrane-associated biological processes and ion pathways in the core genes of each module affect the surgical process. Pivot analysis of potential drug regulators revealed 229 potential drugs for sevoflurane anesthesia surgery, among which zinc regulates three functional disorder modules via AHSG, F12, etc., and 67 potential drugs for propofol anesthesia surgery, among which are propofol, methadone, and buprenorphine, regulate two functional disorder modules through four genes, CYP2C8, OPRM1, CYP2C18, and CYP2C19. This study provides guidance on clinical use or treatment by comparing the effects of two anesthesias on surgery and its potential drugs.

TEAD4 promotes tumor development in patients with lung adenocarcinoma via ERK signaling pathway

OBJECTIVE

Whether TEAD4 itself plays a vital role in the tumorigenesis and development of lung adenocarcinoma remains unclear. In our study, we aim to investigate the expression pattern and biological functions of TEAD4 and further investigate the potential mechanisms.

METHODS

Clinical tumor and paired normal samples were collected for preparing tissue microarray. Western blot and immunohistochemical (IHC) staining of TEAD4 expression in these tissues were conducted to explore the expression pattern. Moreover, A549 cell line was select for investigating the function of TEAD4 for lung adenocarcinoma in vitro and in vivo. RNA sequencing was finally performed to further detect the potential downstream genes.

RESULTS

The elevated TEAD4 expression level was observed in tumor tissues and the patients with higher TEAD4 expression tended to have worse overall survival. The knockdown of TEAD4 inhibits A549 cells proliferation ability and migration ability. A total of 431 differentially expressed genes (DEGs), including 239 down-regulated genes and 191 up-regulated genes, were finally identified and some of DEGs were validated. Moreover, knockdown of TEAD4 led to the down-regulation of pERK, which maybe the potential TEAD4-targeted signaling pathway to play the pro-tumorigenic function.

CONCLUSIONS

The expression level of TEAD4 is high in lung adenocarcinoma tumor tissues and positively associated with worse prognosis. Up-regulation of TEAD4 may lead to excessive transcription and phosphorylation of ERK proteins and therefore accelerates the process of tumor development. Our results demonstrate that overexpression of TEAD4 is a new mechanism of dysregulation of Hippo pathway.

Identification of Tumorigenic and Prognostic Biomarkers in Colorectal Cancer Based on microRNA Expression Profiles

Objective

Although noncoding RNAs, especially the microRNAs, have been found to play key roles in CRC development in intestinal tissue, the specific mechanism of these microRNAs has not been fully understood.

Methods

GEO and TCGA database were used to explore the microRNA expression profiles of normal mucosa, adenoma, and carcinoma. And the differential expression genes were selected. Computationally, we built the SVM model and multivariable Cox regression model to evaluate the performance of tumorigenic microRNAs in discriminating the adenomas from normal tissues and risk prediction.

Results

In this study, we identified 20 miRNA biomarkers dysregulated in the colon adenomas. The functional enrichment analysis showed that MAPK activity and MAPK cascade were highly enriched by these tumorigenic microRNAs. We also investigated the target genes of the tumorigenic microRNAs. Eleven genes, including PIGF, TPI1, KLF4, RARS, PCBP2, EIF5A, HK2, RAVER2, HMGN1, MAPK6, and NDUFA2, were identified to be frequently targeted by the tumorigenic microRNAs. The high AUC value and distinct overall survival rates between the two risk groups suggested that these tumorigenic microRNAs had the potential of diagnostic and prognostic value in CRC.

Conclusions

The present study revealed possible mechanisms and pathways that may contribute to tumorigenesis of CRC, which could not only be used as CRC early detection biomarkers, but also be useful for tumorigenesis mechanism studies.