Identification of hub genes and pathways associated with bladder cancer based on co-expression network analysis

A Novel IGLC2 Gene Linked With Prognosis of Triple-Negative Breast Cancer

BACKGROUND

Immunoglobulin-related genes are associated with the favorable prognosis of triple-negative breast cancer (TNBC) patients. We aimed to analyze the function and prognostic value of immunoglobulin lambda constant 2 (IGLC2) in TNBC patients.

METHODS

We knocked down the gene expression of IGLC2 (IGLC2-KD) in MDA-MB-231 cells to evaluate the proliferation, migration, and invasion of tumors via 3-(4,5-Dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay, wound healing, and transwell cell migration assay respectively. Relapse-free survival (RFS) and distant metastasis-free survival (DMFS) analyses were conducted using the KM plotter online tool. The GSE76275 data set was used to analyze the association of IGLC2 and clinical characteristics. A pathway enrichment analysis was conducted using the next-generation sequencing data of wild-type and IGLC2-KD MDA-MB-231 cells.

RESULTS

The low gene expression of IGLC2 was related to unfavorable RFS, DMFS. The high expression of IGLC2 was exhibited in the basal-like immune-activated (BLIA) TNBC molecular subtype, which was immune-activated and showed excellent response to immune therapy. IGLC2 was positively correlated with programmed death-ligand 1 (PD-L1) as shown by Spearman correlation (r = 0.25, p < 0.0001). IGLC2 had a strong prognostic effect on lymph node-negative TNBC (RFS range: 0.31, q value= 8.2e-05; DMFS = 0.16, q value = 8.2e-05) but had no significance on lymph node-positive ones. The shRNA-mediated silencing of IGLC2 increased the proliferation, migration, and invasion of MDA-MB-231 cells. The results of pathway enrichment analysis showed that IGLC2 is related to the PI3K-Akt signaling pathway, MAPK signaling pathway, and extracellular matrix-receptor interaction. We confirmed that MDA-MB-231 tumor cells expressed IGLC2, subverting the traditional finding of generation by immune cells.

CONCLUSIONS

IGLC2 linked with the proliferation, migration, and invasion of MDA-MB-231 cells. A high expression of IGLC2 was related to favorable prognosis for TNBC patients. IGLC2 may serve as a biomarker for the identification of TNBC patients who can benefit the most from immune checkpoint blockade treatment.

Identification of key genes in human urothelial cells corresponding to interstitial cystitis/bladder pain syndrome in a lipopolysaccharide-induced cystitis model

AIMS

The cellular functions of bladder urothelial cells in interstitial cystitis/bladder pain syndrome (IC/BPS) have not been well revealed and understood. Thus, the study aims to identify key genes and significant pathways in urothelium corresponding to IC/BPS in a lipopolysaccharide (LPS)-induced cystitis model and provide novel clues related to diagnosis and treatment of IC/BPS.

METHODS

Human urothelial cells (HUCs) were incubated with LPS (50 μg/ml for 24 h). Microarray was applied to analyze the differentially expressed genes (DEGs) between HUCs under LPS treatment and the control group. DEGs in the two groups were identified and then used for enrichment analysis. Subsequently, protein-protein interaction (PPI) network based on DEGs was constructed. Lastly, the top five key genes were identified through the Cytoscape (version 3.7.2) using the "Clustering Coefficient" algorithm.

RESULTS

One hundred and seventy-one DEGs (96 upregulated genes and 75 downregulated genes) were identified between the LPS treatment and control group. The established PPI network was composed of 169 nodes and 678 edges. Moreover, C19orf33, TRIM31, MUC21, ELF3, and IFI27 were identified as hub genes in the PPI network. Subsequently, a statistically increased expression level of TRIM31 and ELF3 was validated by real-time quantitative-polymerase chain reaction and immunohistochemistry in bladder tissues from 20 patients with IC/BPS.

CONCLUSIONS

TRIM31 and ELF3 may be the two hub genes in urothelium corresponding to IC/BPS. More studies are warranted to further validate the findings. The identified marker genes may be useful targets for further studies to develop diagnostic tools and more effective therapies for a broader group of women with IC/PBS.

Identification of KIF4A and its effect on the progression of lung adenocarcinoma based on the bioinformatics analysis

BACKGROUND

Lung adenocarcinoma (LUAD) is the most frequent histological type of lung cancer, and its incidence has displayed an upward trend in recent years. Nevertheless, little is known regarding effective biomarkers for LUAD.

METHODS

The robust rank aggregation method was used to mine differentially expressed genes (DEGs) from the gene expression omnibus (GEO) datasets. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to extract hub genes from the protein-protein interaction (PPI) network. The expression of the hub genes was validated using expression profiles from TCGA and Oncomine databases and was verified by real-time quantitative PCR (qRT-PCR). The module and survival analyses of the hub genes were determined using Cytoscape and Kaplan-Meier curves. The function of KIF4A as a hub gene was investigated in LUAD cell lines.

RESULTS

The PPI analysis identified seven DEGs including BIRC5, DLGAP5, CENPF, KIF4A, TOP2A, AURKA, and CCNA2, which were significantly upregulated in Oncomine and TCGA LUAD datasets, and were verified by qRT-PCR in our clinical samples. We determined the overall and disease-free survival analysis of the seven hub genes using GEPIA. We further found that CENPF, DLGAP5, and KIF4A expressions were positively correlated with clinical stage. In LUAD cell lines, proliferation and migration were inhibited and apoptosis was promoted by knocking down KIF4A expression.

CONCLUSION

We have identified new DEGs and functional pathways involved in LUAD. KIF4A, as a hub gene, promoted the progression of LUAD and might represent a potential therapeutic target for molecular cancer therapy.

RNAseq expression patterns of canine invasive urothelial carcinoma reveal two distinct tumor clusters and shared regions of dysregulation with human bladder tumors

BACKGROUND

Invasive urothelial carcinoma (iUC) is highly similar between dogs and humans in terms of pathologic presentation, molecular subtypes, response to treatment and age at onset. Thus, the dog is an established and relevant model for testing and development of targeted drugs benefiting both canine and human patients. We sought to identify gene expression patterns associated with two primary types of canine iUC tumors: those that express a common somatic mutation in the BRAF gene, and those that do not.

METHODS

We performed RNAseq on tumor and normal tissues from pet dogs. Analysis of differential expression and clustering, and positional and individual expression was used to develop gene set enrichment profiles distinguishing iUC tumors with and without BRAFV595E mutations, as well as genomic regions harboring excessive numbers of dysregulated genes.

RESULTS

We identified two expression clusters that are defined by the presence/absence of a BRAFV595E (BRAFV600E in humans) somatic mutation. BRAFV595E tumors shared significantly more dysregulated genes than BRAF wild-type tumors, and vice versa, with 398 genes differentiating the two clusters. Key genes fall into clades of limited function: tissue development, cell cycle regulation, immune response, and membrane transport. The genomic site with highest number of dysregulated genes overall lies in a locus corresponding to human chromosome 8q24, a region frequently amplified in human urothelial cancers.

CONCLUSIONS

These data identify critical sets of genes that are differently regulated in association with an activating mutation in the MAPK/ERK pathway in canine iUC tumors. The experiments also highlight the value of the canine system in identifying expression patterns associated with a common, shared cancer.

LGALS4 as a Prognostic Factor in Urothelial Carcinoma of Bladder Affects Cell Functions

BACKGROUND

To identify the hub genes related to urothelial carcinoma of the bladder prognosis and to understand their underlying mechanism.

METHODS

The expression profiles of 18 pairs of urothelial carcinoma of the bladder patient tissue and paired adjacent tissue obtained from the Cancer Genome Atlas were performed. Weighted gene coexpression network analysis was employed to screen gene modules and hub genes with significant differential expressions in urothelial carcinoma of the bladder. The hub genes expression in urothelial carcinoma of the bladder tissues was validated by reverse transcription-quantitative polymerase chain reaction. The overall survival curve and disease-free survival curve of prognostic factor (LGALS4) were plotted using the Kaplan-Meier method. Furthermore, LGALS4 messenger RNA and protein expression were also assessed in 2 urothelial carcinoma of the bladder cell lines (T24 and 5637) by quantitative reverse transcription-polymerase chain reaction and Western blot. The functions of urothelial carcinoma of the bladder cells with transfected pcDNA3.1-LGALS4 were identified through MTT assay, plate clone formation assay, flow cytometry, and cell migration experiments.

RESULTS

LGALS4 was the hub gene of pink module and it was related to prognosis. Higher LGALS4 expression predicted higher probabilities of overall survival and disease-free survival. Overexpression of LGALS4 in urothelial carcinoma of the bladder cells suppressed cell viability and migration but induced apoptosis.

CONCLUSION

LGALS4 played a critical role in the progression of urothelial carcinoma of the bladder and held a promise to be the biomarker for diagnosis and treatment of urothelial carcinoma of the bladder. It predicted good prognosis of urothelial carcinoma of the bladder and restrained the growth and migration of urothelial carcinoma of the bladder cells.

A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer

Objectives: Bladder carcinoma is a clinical heterogeneous disease, which is with significant variability of the prognosis and high risk of death. This revealed prominently the need to identify high-efficiency cancer characteristics to predict clinical prognosis.

Methods: Gene expression profiles of 93 bladder tumor patients from Gene Expression Omnibus data sets was performed in this study, along with 408 bladder tumor patients retrieved from The Cancer Genome Atlas database. The relationship of gene signature and overall survival was analyzed in the training cohort (n = 46). The validation for that was performed in an internal validation cohort (n = 47) and an external validation cohort (n = 408).

Results: Four genes (TMPRSS11E, SCEL, KRT78, TMEM185A) were identified by univariable and multivariable Cox regression analysis. According to a risk score on the bases on the four-gene signature, we grouped these patients in high-risk group and low-risk group with significantly different overall survival in the training series and successfully validated it in both the internal and external validation cohorts. Subsequent studies demonstrated that the four-gene expression risk score was independent of radical cystectomy stage, chemotherapy and lymph node status. Higher rates of FAT4 mutation and MACF1 mutation in bladder tumors with high risk score were found compared with tumors with low risk score. Gene set enrichment analysis revealed high-risk score was associated with some tumor progression and recurrence associated pathways.

Conclusions: This four-gene risk score might have potential clinical implications in the selection of high-risk urinary bladder cancer patients for aggressive therapy. The selected four genes might become potential therapeutic targets and diagnostic markers for urinary bladder cancer.

Graph Theoretic and Pearson Correlation-Based Discovery of Network Biomarkers for Cancer

Two graph theoretic concepts—clique and bipartite graphs—are explored to identify the network biomarkers for cancer at the gene network level. The rationale is that a group of genes work together by forming a cluster or a clique-like structures to initiate a cancer. After initiation, the disease signal goes to the next group of genes related to the second stage of a cancer, which can be represented as a bipartite graph. In other words, bipartite graphs represent the cross-talk among the genes between two disease stages. To prove this hypothesis, gene expression values for three cancers— breast invasive carcinoma (BRCA), colorectal adenocarcinoma (COAD) and glioblastoma multiforme (GBM)—are used for analysis. First, a co-expression gene network is generated with highly correlated gene pairs with a Pearson correlation coefficient ≥ 0.9. Second, clique structures of all sizes are isolated from the co-expression network. Then combining these cliques, three different biomarker modules are developed—maximal clique-like modules, 2-clique-1-bipartite modules, and 3-clique-2-bipartite modules. The list of biomarker genes discovered from these network modules are validated as the essential genes for causing a cancer in terms of network properties and survival analysis. This list of biomarker genes will help biologists to design wet lab experiments for further elucidating the complex mechanism of cancer.

Identification of Hub Genes Associated With Progression and Prognosis in Patients With Bladder Cancer

Given that most bladder cancers (BCs) are diagnosed in advanced stages with poor prognosis, this study aims to find novel biomarkers associated with the progression and prognosis in patients with BC. 1,779 differentially expressed genes (DEGs) between BC samples and normal bladder tissues were identified in total. Then, 24 DEGs were regarded as candidate hub genes by constructing a protein–protein interaction (PPI) network and a random forest model. Among them, six genes (BUB1B, CCNB1, CDK1, ISG15, KIF15, and RAD54L) were eventually identified by using five analysis methods (one-way Analysis of Variance analysis, spearman correlation analysis, distance correlation analysis, receiver operating characteristic curve, and expression values comparison), which were correlated with the progression and prognosis of BC. Moreover, the validation of hub genes was conducted based on GSE13507, Oncomine, and CBioPortal. Results of univariate Cox regression analysis showed that the expression levels of all the hub genes were influence features of overall survival (OS) and cancer specific survival (CSS) based on GSE13507, and we further established a six-gene signature based on the expression levels of the six genes and their Cox regression coefficients. This signature showed good potential for clinical application suggested by survival analysis (OS: Hazard Ratio = 0.484, 95%CI: 0.298–0.786; P = 0.0034; CSS: Hazard Ratio = 0.244, 95%CI: 0.121–0.493, P < 0.0001) and decision curve analysis. In conclusion, our study indicates that six hub genes have great predictive value for the prognosis and progression of BC and may contribute to the exploration of further basic and clinical research of BC.

Integrated analysis of a competing endogenous RNA network reveals key lncRNAs as potential prognostic biomarkers for human bladder cancer

Human bladder cancer (BCa) is one of the most commonly diagnosed malignancies worldwide. It has high recurrence rates and low-grade malignancy, thus representing an important public health concern. An increasing number of studies suggest that long-noncoding RNAs (lncRNAs) play important roles in various biological processes and disease pathologies, including cancer.We analyzed the expression profiles of lncRNA, miRNA, and mRNA, along with the clinical information of BCa patients collected from the Cancer Genome Atlas database to identify lncRNA biomarkers for prognosis. We also constructed an lncRNA-miRNA-mRNA global triple network (competitive endogenous RNA network) by bioinformational approach.This BCa lncRNA-miRNA-mRNA network consisted of 23 miRNA nodes, 52 mRNA nodes, 59 lncRNA nodes, and 365 edges. Subsequent gene ontology (GO) and pathway analyses were performed using BinGO for Cytoscape and Database for Annotation, Visualization, and Integration Discovery, respectively, highlighting important GO terms and pathways that were enriched in the network. Subnetworks were created using 3 key lncRNAs (MAGI2-AS3, ADAMTS9-AS2, and LINC00330), revealing associations with BCa-linked mRNAs and miRNAs. Finally, an analysis of significantly differentiating RNAs found 6 DElncRNAs (AC112721.1, ADAMTS9-AS1, ADAMTS9-AS2, HCG22, MYO16-AS1, and SACS-AS1), 1 DEmiRNA (miRNA-195), and 6 DEmRNAs (CCNB1, FAM129A, MAP1B, TMEM100, AIFM3, and HOXB5) that correlated with BCa patient survival.Our results provide a novel perspective from which to study the lncRNA-related ceRNA network in BCa, contributing to the development of future diagnostic biomarkers and therapeutic targets.

Melittin Constrains the Expression of Identified Key Genes Associated with Bladder Cancer

This work is aimed at investigating the effect of melittin on identified key genes in bladder cancer (BC) and further providing a theoretical basis for BC treatment. GSE35014 downloaded from the Gene Expression Omnibus (GEO) database was used to screen differentially expressed genes (DEGs) in BC cells and control. Results showed that a total of 389 upregulated and 169 downregulated genes were identified. Subsequently, GO analysis, KEGG pathway enrichment analysis, and PPI network analysis were employed to disclose the crucial genes and signaling pathways involved in BC. Fifteen module-related DEGs and their associated signaling pathways were obtained according to the PPI network and modular analyses. Based on the analysis of articles retrieved in the PubMed database, we found that melittin could induce apoptosis and constrain the progression of tumor cells as a result of regulating critical cancer-related signaling pathways, such as PI3K-Akt and TNF signaling pathways. Furthermore, PI3K-Akt and TNF signaling pathways were also found to be associated with module-related DEGs according to biological analyses. At last, qRT-PCR analysis demonstrated that melittin could constrain the expression of module-related DEGs (LPAR1, COL5A1, COL6A2, CXCL1, CXCL2, and CXCL3) associated with PI3K-Akt and TNF signaling pathways in BC cells. Functional assays revealed that melittin could constrain the proliferative and migrated abilities of BC cells. Conjointly, these findings provide a theoretical basis for these six genes as drug-sensitive markers of melittin in BC treatment.

TRIM31 regulates chronic inflammation via NF-κB signal pathway to promote invasion and metastasis in colorectal cancer

Tripartite motif 31(TRIM31) is a new member of the E3 ubiquitin ligase family, which plays a role in many biological processes. It has been indicated that TRIM31 is strongly correlated with tumorigenesis. However, the impact of TRIM31 in colorectal cancer (CRC) and its underlying mechanisms are largely unknown. In this study, we found an increase in TRIM31 expression in CRC cells and a positive correlation between TRIM31 and CRC malignancy. Applying genetic interventions and cellular function tests, our results showed that TRIM31 acted as an epithelial-mesenchymal transition (EMT) inducer to promote CRC invasion and metastasis. Mechanical exploration revealed that TRIM31 mediated the upregulation of inflammatory cytokines TNF, IL-1β, and IL-6 through the NF-κB pathway, thus contributing to EMT in CRC progression. Collectively, we concluded that TRIM31 mediated chronic inflammation via the NF-κB pathway to promote invasion and metastasis in CRC. Therefore, we can infer that TRIM31 may be a valuable detective marker in primary CRC, and therapeutic intervention related to EMT suppression via TRIM31 can be a viable option for patients with advanced CRC.