Identification of miR-200c and miR141-Mediated lncRNA-mRNA Crosstalks in Muscle-Invasive Bladder Cancer Subtypes

Enhancing m6A modification of lncRNA through METTL3 and RBM15 to promote malignant progression in bladder cancer

Objective

Bladder cancer is one of the most prominent malignancies affecting the urinary tract, characterized by a poor prognosis. Our previous research has underscored the pivotal role of m6A methylation in the progression of bladder cancer. Nevertheless, the precise relationship between N6-methyladenosine (m6A) regulation of long non-coding RNA (lncRNA) and bladder cancer remains elusive.

Methods

This study harnessed sequencing data and clinical records from 408 bladder cancer patients in the TCGA database. Employing R software, we conducted bioinformatics analysis to establish an m6A-lncRNA co-expression network. Analyzing the differences between high and low-risk groups, particularly at the immunological level, and subsequently investigating the primary regulatory factors of these lncRNA, validating the findings through experiments, and exploring their specific cellular functions.

Results

We identified 50 m6A-related lncRNA with prognostic significance through univariate Cox regression analysis. In parallel, we employed a LASSO-Cox regression model to pinpoint 11 lncRNA and calculate risk scores for bladder cancer patients. Based on the median risk score, patients were categorized into low-risk and high-risk groups. The high-risk cohort exhibited notably lower survival rates than their low-risk counterparts. Further analysis pointed to RBM15 and METTL3 as potential master regulators of these m6A-lncRNA. Experimental findings also shed light on the upregulated expression of METTlL3 and RBM15 in bladder cancer, where they contributed to the malignant progression of tumors. The experimental findings demonstrated a significant upregulation of METTL3 and RBM15 in bladder cancer specimens, implicating their contributory role in the oncogenic progression. Knockdown of METTL3 and RBM15 resulted in a marked attenuation of tumor cell proliferation, invasion, and migration, which was concomitant with a downregulation in the cellular m6A methylation status. Moreover, these results revealed that RBM15 and METTL3 function in a synergistic capacity, positing their involvement in cancer promotion via the upregulation of m6A modifications in long non-coding RNAs. Additionally, this study successfully developed an N-methyl-N-nitrosourea (MNU)-induced rat model of in situ bladder carcinoma, confirming the elevated expression of RBM15 and METTL3, which paralleled the overexpression of m6A-related- lncRNAs observed in bladder cancer cell lines. This congruence underscores the potential utility of these molecular markers in in vivo models that mirror human malignancies.

Conclusion

This study not only offers novel molecular targets,but also enriches the research on m6A modification in bladder cancer, thereby facilitating its clinical translation.

The Role of miRNAs to Detect Progression, Stratify, and Predict Relevant Clinical Outcomes in Bladder Cancer

Bladder cancer (BC) is one of the most common types of cancer worldwide, with significant differences in survival depending on the degree of muscle and surrounding tissue invasion. For this reason, the timely detection and monitoring of the disease are important. Surveillance cystoscopy is an invasive, costly, and uncomfortable procedure to monitor BC, raising the need for new, less invasive alternatives. In this scenario, microRNAs (miRNAs) represent attractive prognostic tools given their role as gene regulators in different biological processes, tissue expression, and their ease of evaluation in liquid samples. In cancer, miRNA expression is dynamically modified depending on the tumor type and cancer staging, making them potential biomarkers. This review describes the most recent studies in the last five years exploring the utility of miRNA-based strategies to monitor progression, stratify, and predict relevant clinical outcomes of bladder cancer. Several studies have shown that multimarker miRNA models can better predict overall survival, recurrence, and progression in BC patients than traditional strategies, especially when combining miRNA expression with clinicopathological variables. Future studies should focus on validating their use in different cohorts and liquid samples.

Patterns of transcription factor binding and epigenome at promoters allow interpretable predictability of multiple functions of non-coding and coding genes

Understanding the biological roles of all genes only through experimental methods is challenging. A computational approach with reliable interpretability is needed to infer the function of genes, particularly for non-coding RNAs. We have analyzed genomic features that are present across both coding and non-coding genes like transcription factor (TF) and cofactor ChIP-seq (823), histone modifications ChIP-seq (n = 621), cap analysis gene expression (CAGE) tags (n = 255), and DNase hypersensitivity profiles (n = 255) to predict ontology-based functions of genes. Our approach for gene function prediction was reliable (>90% balanced accuracy) for 486 gene-sets. PubMed abstract mining and CRISPR screens supported the inferred association of genes with biological functions, for which our method had high accuracy. Further analysis revealed that TF-binding patterns at promoters have high predictive strength for multiple functions. TF-binding patterns at the promoter add an unexplored dimension of explainable regulatory aspects of genes and their functions. Therefore, we performed a comprehensive analysis for the functional-specificity of TF-binding patterns at promoters and used them for clustering functions to reveal many latent groups of gene-sets involved in common major cellular processes. We also showed how our approach could be used to infer the functions of non-coding genes using the CRISPR screens of coding genes, which were validated using a long non-coding RNA CRISPR screen. Thus our results demonstrated the generality of our approach by using gene-sets from CRISPR screens. Overall, our approach opens an avenue for predicting the involvement of non-coding genes in various functions.

Immunohistochemical based molecular subtypes of muscle-invasive bladder cancer: association with HER2 and EGFR alterations, neoadjuvant chemotherapy response and survival

Muscle-invasive bladder cancers (MIBCs) is a group of molecularly heterogonous diseases that could be stratified into subtypes with distinct clinical courses and sensitivities to chemotherapy. Clinical application of molecular subtypes could help in prediction of neoadjuvant chemotherapy (NAC) responders. Immunohistochemical (IHC) markers such as GATA3, cytokeratin (CK) 5/6, and p53 are associated with these subtypes and are widely available. Human epidermal growth factor receptor 2 (HER2) and epidermal growth factor receptor (EGFR) are mutated in multiple cancers including MIBC and are potential therapeutic targets. HER2/EGFR status of MIBC subtypes has not been investigated. Tissue microarrays (TMAs) were constructed from transurethral resection of the bladder tumor (TURB) specimens and stained with GATA3,CK5/6,p53 and HER2 in addition to Quantitative Reverse Transcription PCR for detection of EGFR gene. Of the total cases, 45% were luminal, 36.7% basal and 18.3% p53 wild subtype (p53-WT). Univariate analysis showed that overall survival (OS) and disease-free progression survival (DFS) were significantly longer for luminal subtype. In multivariate analysis, molecular subtype, HER2 status and LV invasion were independent prognostic factors for DFS and OS. Basal subtype showed a significantly better response to NAC. HER2 expression was significantly higher in luminal while EGFR expression was significantly higher in basal subtype. Kaplan-Meier survival curves revealed a significant longer OS and DFS for HER2 negative than positive cases. MIBC can be stratified using a simple IHC panel [GATA3,CK5/6,P53] into clinically relevant prognostic molecular subtypes. Basal tumors are aggressive and respond well to NAC while luminal have better OS. P53-WT tumors are chemoresistant and require further treatments. HER2 and EGFR are potential therapeutic targets for molecular subtypes of MIBC where luminal tumors are more likely to benefit from HER2 and basal from EGFR directed therapies.

Identification and Verification of Immune Subtype-Related lncRNAs in Clear Cell Renal Cell Carcinoma

Background

According to clinical study results, immune checkpoint blockade (ICB) treatment enhances the survival outcome of patients with clear cell renal cell carcinoma (ccRCC). Previous research has divided ccRCC patients into immune subtypes with distinct ICB response rates. However, the study on the association between lncRNAs and ccRCC immune subtypes is lacking.

Methods

Differentially expressed lncRNAs/mRNAs between two major immune subgroups were calculated. A weighted gene co-expression network analysis (WGCNA) was conducted to establish the lncRNA-mRNA co-expression network and select the key lncRNAs. Then, prognostic lncRNAs were selected from the network by the bioinformatics method. Next, the risk-score was estimated by lncRNA expression and their coefficients. Finally, a nomogram based on lncRNAs and clinical parameters was created to predict the prognosis of ccRCC.

Results

LncRNAs and mRNAs associated with ccRCC immune subtypes were identified. The lncRNAs and mRNAs from a gene module closely linked to the immune subtype were used to construct a network. The KEGG pathways enriched in the network were related to immune system activation processes. These 8 lncRNAs (AL365361.1, LINC01934, AC090152.1, PCED1B-AS1, LINC00426, AC007728.2, AC243829.4, and LINC00158) were found to be positively correlated with immune cells of the tumor microenvironment. The C-index of the nomogram was 0.777, and the calibration curve data suggests that the nomogram has a high degree of discriminating capacity.

Conclusion

In summary, we discovered core lncRNAs linked with immune subtypes and created corresponding lncRNA–mRNA networks. These lncRNAs are anticipated to have predictive significance for ccRCC and may provide insight into novel biomarkers for the disease.

LncRNA SMARCD3-OT1 Promotes Muscle Hypertrophy and Fast-Twitch Fiber Transformation via Enhancing SMARCD3X4 Expression

Long noncoding RNA (lncRNA) plays a crucial part in all kinds of life activities, especially in myogenesis. SMARCD3 (SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily d, member 3) is a member of the SWI/SNF protein complex and was reported to be required for cell proliferation and myoblast differentiation. In this study, we identified a new lncRNA named SMARCD3-OT1 (SMARCD3overlappinglncRNA), which strongly regulated the development of myogenesis by improving the expression of SMARCD3X4 (SMARCD3transcripts4). We overexpressed and knockdown the expression of SMARCD3-OT1 and SMARCD3X4 to investigate their function on myoblast proliferation and differentiation. Cell experiments proved that SMARCD3-OT1 and SMARCD3X4 promoted myoblast proliferation through the CDKN1A pathway and improved differentiation of differentiated myoblasts through the MYOD pathway. Moreover, they upregulated the fast-twitch fiber-related genes and downregulated the slow-twitch fiber-related genes, which indicated that they facilitated the slow-twitch fiber to transform into the fast-twitch fiber. The animals’ experiments supported the results above, demonstrating that SMARCD3-OT1 could induce muscle hypertrophy and fast-twitch fiber transformation. In conclusion, SMARCD3-OT1 can improve the expression of SMARCD3X4, thus inducing muscle hypertrophy. In addition, SMARCD3-OT1 can facilitate slow-twitch fibers to transform into fast-twitch fibers.

PSRR: A Web Server for Predicting the Regulation of miRNAs Expression by Small Molecules

Background: MicroRNAs (miRNAs) play key roles in a variety of pathological processes by interacting with their specific target mRNAs for translation repression and may function as oncogenes (oncomiRs) or tumor suppressors (TSmiRs). Therefore, a web server that could predict the regulation relations between miRNAs and small molecules is expected to achieve implications for identifying potential therapeutic targets for anti-tumor drug development.

Methods: Upon obtaining positive/known small molecule-miRNA regulation pairs from SM2miR, we generated a multitude of high-quality negative/unknown pairs by leveraging similarities between the small molecule structures. Using the pool of the positive and negative pairs, we created the Dataset1 and Dataset2 datasets specific to up-regulation and down-regulation pairs, respectively. Manifold machine learning algorithms were then employed to construct models of predicting up-regulation and down-regulation pairs on the training portion of pairs in Dataset1 and Dataset2, respectively. Prediction abilities of the resulting models were further examined by discovering potential small molecules to regulate oncogenic miRNAs identified from miRNA sequencing data of endometrial carcinoma samples.

Results: The random forest algorithm outperformed four machine-learning algorithms by achieving the highest AUC values of 0.911 for the up-regulation model and 0.896 for the down-regulation model on the testing datasets. Moreover, the down-regulation and up-regulation models yielded the accuracy values of 0.91 and 0.90 on independent validation pairs, respectively. In a case study, our model showed highly-reliable results by confirming all top 10 predicted regulation pairs as experimentally validated pairs. Finally, our predicted binding affinities of oncogenic miRNAs and small molecules bore a close resemblance to the lowest binding energy profiles using molecular docking. Predictions of the final model are freely accessible through the PSRR web server at https://rnadrug.shinyapps.io/PSRR/.

Conclusion: Our study provides a novel web server that could effectively predict the regulation of miRNAs expression by small molecules.

Single-cell RNA sequencing reveals the epithelial cell heterogeneity and invasive subpopulation in human bladder cancer

Bladder cancer represents a highly heterogeneous disease characterized by distinct histological, molecular and clinical phenotypes, and a detailed analysis of tumor cell invasion and crosstalks within bladder tumor cells has not been determined. Here, we applied droplet-based single-cell RNA sequencing (scRNA-seq) to acquire transcriptional profiles of 36 619 single cells isolated from seven patients. Single cell transcriptional profiles matched well with the pathological basal/luminal subtypes. Notably, in T1 tumors diagnosed as luminal subtype, basal cells displayed characteristics of epithelial-mesenchymal transition (EMT) and mainly located at the tumor-stromal interface as well as micrometastases in the lamina propria. In one T3 tumor, muscle-invasive tumor showed significantly higher expression of cancer stem cell markers SOX9 and SOX2 than the primary tumor. We additionally analyzed communications between tumor cells and demonstrated its relevance to basal/luminal phenotypes. Overall, our single-cell study provides a deeper insight into the tumor cell heterogeneity associated with bladder cancer progression.

Defining muscle-invasive bladder cancer immunotypes by introducing tumor mutation burden, CD8+ T cells, and molecular subtypes

Immunotherapy, especially anti-PD-1, is becoming a pillar of modern muscle-invasive bladder cancer (MIBC) treatment. However, the objective response rates (ORR) are relatively low due to the lack of precise biomarkers to select patients. Herein, the molecular subtype, tumor mutation burden (TMB), and CD8+ T cells were calculated by the gene expression and mutation profiles of MIBC patients. MIBC immunotypes were constructed using clustering analysis based on tumor mutation burden, CD8+ T cells, and molecular subtypes. Mutated genes, enriched functional KEGG pathways and GO terms, and co-expressed network-specific hub genes have been identified. We demonstrated that ORR of immunotype A patients identified by molecular subtype, CD8+ T cells, and TMB is about 36% predictable. PIK3CA, RB1, FGFR3, KMT2C, MACF1, RYR2, and EP300 are differentially mutated among three immunotypes. Pathways such as ECM-receptor interaction, PI3K-Akt signaling pathway, and TGF-beta signaling pathway are top-ranked in enrichment analysis. Low expression of ACTA2 was associated with the MIBC survival benefit. The current study constructs a model that could identify suitable MIBC patients for immunotherapy, and it is an important step forward to the personalized treatment of bladder cancers.

Prognostic Role of FGFR3 Expression Status and Tumor-Related MicroRNAs Level in Association with PD-L1 Expression in Primary Luminal Non-Muscular Invasive Bladder Carcinoma

BACKGROUND

bladder cancer is one of the most common urinary tract malignancies. Establishment of robust predictors of disease progression and outcome is important for personalizing treatment of non-muscular invasive bladder carcinoma (NMIBC). In this study we evaluated association of PD-L1 expression with other prognostic biomarkers, such as expression of miRNA-145 and miRNA-200a, FGFR3 gene expression, and mutation status in tissue specimens of the luminal subtype of newly diagnosed high and low grade NMIBC.

METHODS

twenty patients with primary luminal NMIBC were enrolled in the study. Tumor grade and risk level were determined in accordance with European Organization for Research and Treatment of Cancer (EORTC) guidelines and World Health Organization (WHO) classification. Neoplasm molecular subtype and PD-L1 expression level were assessed by immunohistochemistry. We used real-time PCR to evaluate the expression of microRNAs and FGFR3. We detected FGFR3 hotspot mutations in codons 248 and 249 by Sanger sequencing.

RESULTS

high grade primary luminal NMIBC showed comparatively higher expression of PD-L1 and microRNA-145 than a low grade tumor, whereas the latter had a higher FGFR3 expression and hotspot mutation rate. The tumor grade (HR = 571.72 [11.03-2.96] p = 0.002), PD-L1 expression (HR = 2.33 [0.92-1.92] p = 0.012), and FGFR3 expression (HR = 0.08 [0.17-0.42] p = 0.003) were associated with relapse-free survival.

CONCLUSIONS

tumor grade in association with PD-L1 and FGFR3 expression can be considered as a complex predictor for primary luminal NMIBC progression.

A seven immune-related lncRNA signature predicts the survival of patients with colon adenocarcinoma

This study aimed to explore immune-related lncRNAs for predicting the overall survival of patients with colon adenocarcinoma. RNA-sequencing data were downloaded from the TCGA data portal. The immune-related lncRNAs with differential expression were identified with Cox and LASSO regression analysis. With the stepwise regression analysis, a seven lncRNA signature was established for calculating the Risk Score with following formula: Risk Score = [Expression level of AC027307.2 * (0.156)] + [Expression level of AC074117.1 * (0.294)] + [Expression level of AC103702.2 * (-0.025)] + [Expression level of CYTOR * (0.205)] + [Expression level of LINC02381 * (0.251)] + [Expression level of MIR200CHG * (0.052)] + [Expression level of SNHG16 * (-0.101)]. The Risk Score was validated with survival analysis, achieving moderate area under the curve (AUC) of receiver operating characteristic (ROC) curve over 0.7. GSEA and immune-cell abundance analysis further supported the involved lncRNAs were immune-relevant. Finally, the prognosis prediction efficacy was verified with clinical samples with an AUC of 0.674 in ROC curve. Both the Risk Score and involved immune-related lncRNAs presented promising clinical significance.

Transcriptomic Data Analyses Reveal a Reprogramed Lipid Metabolism in HCV-Derived Hepatocellular Cancer

Reprograming lipid metabolism, one of the major metabolic alterations in cancer, is believed to play an essential role in cancer development, but the exact molecular mechanism remains elusive. Here, we present a computational study of transcriptomic data of HCC with HCV etiology to investigate how lipid metabolism alters during HCC progression. Our analyses reveal that: (1) cancer tissue cells tend to synthesize fatty acids de novo and its phospholipid derivatives; (2) lipid catabolism and fatty acid oxidation are remarkably down-regulated in HCC; (3) the lipid metabolism in HCC is largely independent of lipids in blood circulation; (4) stage-specific co-expression networks for lipid metabolic genes were identified during HCC progression; and (5) the expression levels of several lipid metabolic genes that are differentially expressed or co-expressed specifically at the HCC stage have a strong correlation with cancer survival. Overall, the results provide detailed information about the reprogramed lipid metabolism in HCV-derived HCC.

The value and limitations of urothelial bladder carcinoma molecular classifications to predict oncological outcomes and cancer treatment response: A systematic review and meta-analysis

AIM

To evaluate the predictive value of molecular subtypes on oncological outcomes and response to cancer treatment in patients with urothelial bladder carcinoma (UBC).

MATERIALS AND METHODS

A literature search using PubMed, Scopus, and Cochrane Library was conducted on April 2020 to identify relevant studies according to the preferred reporting items for systematic review and meta-analysis guidelines. The pooled overall survival (OS), cancer-specific survival (CSS), and progression-free survival were calculated using a fixed or random effects model.

RESULTS

We identified 66 studies (including 21,447 molecular subtype records) evaluating the impact of molecular classification on oncologic outcomes in patients with UBC. We found significant association of different molecular subtypes with OS, CSS, progression-free survival, recurrence-free survival, and response to treatment. Totally, 11 studies were included in the meta-analysis. Basal group and NE-like subtypes were associated with worse OS (pooled HR: 1.78, 95%CI: 1.49-2.12, and pooled HR: 2.67, 95%CI: 1.08-6.60, respectively) in patients with muscle invasive bladder cancer. Luminal group was also associated with worse CSS (pooled HR of 3.67, 95%CI: 2.19-6.14).

CONCLUSIONS

Based on these data, UBC molecular classifications are significant predictors of oncological outcomes and identify patients who are most likely to benefit from intensified or different therapies. The optimal consensus on molecular classification remains to be verified in well-designed prospective studies to allow precise prognostic and predictive value assessment.

lncRNA SNHG1 Promotes Basal Bladder Cancer Invasion via Interaction with PP2A Catalytic Subunit and Induction of Autophagy

Although basal muscle-invasive bladder cancers (MIBCs) are predominant, are more aggressive, and have bad prognoses, molecular mechanisms underlying how basal MIBC formation/progression have been barely explored. In the present study, SNHG1, a long non-coding RNA, was shown to be expressed at higher levels in basal MIBC cells than in other types of bladder BC cells, and its presence could promote basal MIBC cell invasion. The results revealed that SNHG1 specifically induced MMP2 expression via increasing its transcription and mRNA stability. In one mechanism, SNHG1 directly bound with PP2A catalytic subunit (PP2A-c) to inhibit interactions of PP2A-c with c-Jun and then promoted c-Jun phosphorylation that, in turn, mediated MMP2 transcription. In another mechanism, SNHG1 markedly induced autophagy in the cells via induction of increases in the abundance of autophagy-related proteins. The latter initiated autophagy and further abolished miR-34a stability, which reduced overall miR-34a binding directly to the 3' UTR of MMP2 mRNA, thereby promoting MMP2 mRNA stabilization. These results provided novel insight into understanding the specific functions of SNHG1 in basal MIBC. Such findings may ultimately prove highly significant for the design/synthesis of new SNHG1-based compounds for the treatment of basal MIBC patients.

Characterization of BRCA1/2-Directed ceRNA Network Identifies a Novel Three-lncRNA Signature to Predict Prognosis and Chemo-Response in Ovarian Cancer Patients With Wild-Type BRCA1/2

Long non-coding RNAs (lncRNAs) have been reported to interact with BRCA1/2 to regulate homologous recombination (HR) by diverse mechanisms in ovarian cancers (OvCa). However, genome-wide screening of BRCA1/2-related lncRNAs and their clinical significance is still unexplored. In this study, we constructed a global BRCA1/2-directed lncRNA-associated ceRNA network by integrating paired lncRNA expression profiles, miRNA expression profiles, and BRCA1/2 expression profiles in BRCA1/2 wild-type patients and identified 111 BRCA1/2-related lncRNAs. Using the stepwise regression and Cox regression analysis, we developed a BRCA1/2-directed lncRNA signature (BRCALncSig), composing of three lncRNAs (LINC01619, DLX6-AS1, and AC004943.2) from the list of 111 BRCA1/2-related lncRNAs, which was an independent prognostic factor and was able to classify the patients into high- and low-risk groups with significantly different survival in the training dataset (HR = 2.73, 95 CI 1.65–4.51, p < 0.001). The prognostic performance of the BRCALncSig was further validated in the testing dataset (HR = 1.9, 95 CI 1.21–2.99, p = 0.005) and entire TCGA dataset (HR = 2.17, 95 CI 1.56–3.01, p < 0.001). Furthermore, the BRCALncSig is associated with chemo-response and was also capable of discriminating nonequivalent outcomes for patients achieving complete response (CR) (log-rank p = 0.003). Functional analyses suggested that mRNAs co-expressed with the BRCALncSig were enriched in cancer-related or cell proliferation-related biological processes and pathways. In summary, our study highlighted the clinical implication of BRCA1/2-directed lncRNAs in the prognosis and treatment response of BRCA1/2 wild-type patients.

Connecting the dots between different networks: miRNAs associated with bladder cancer risk and progression

BACKGROUND

Bladder cancer (BC) is a common urothelial malignancy, characterized by a high recurrence rate. The biology of bladder cancer is complex and needs to be deciphered. The latest evidence reveals the critical role of the non-coding RNAs, particularly microRNAs (miRNAs), as vital regulatory elements in cancer.

METHOD

We performed a miRNAs microarray using paired tissues (tumor and adjacent normal bladder tissue), followed by the validation with qRT-PCR of five selected transcripts. Additional next-generation sequencing investigation established the interconnection among the altered miRNAs and mutated genes. Based on the overlapping between TCGA data and data obtained in the study, we focused on the systematic identification of altered miRNAs and genes mutated involved in bladder cancer tumorigenesis and progression.

RESULTS

By overlapping the miRNAs expression data, the two patient cohorts, we identified 18 miRNAs downregulated and, 187 miRNAs upregulated. qRT-PCR validation was completed using a selected panel of two downregulated (miR-139-5p and miR-143-5p) and three up-regulated miRNAs (miR-141b, miR-200 s or miR-205). Altered miRNAs patterns are interrelated to bladder tumorigenesis, allowing them to be used for the development of novel diagnostic and prognostic biomarkers. Three EMT-related upregulated miRNAs have an essential role in the molecular mechanisms, specifically key processes underlying tumorigenesis, invasion and metastasis. Using the Ampliseq Cancer Panel kit and Ion Torrent PGM Next-Generation Sequencing an increased mutation rate for TP53, FGFR3, KDR, PIK3CA and ATM were observed, but the mutational status for only TP53 was correlated to the survival rate. The miRNAs pattern, along with the gene mutation pattern attained, can assist for better patient diagnosis.

CONCLUSION

This study thereby incorporates miRNAs as critical players in bladder cancer prognosis, where their altered gene expression profiles have a critical biological function in relationship with tumor molecular phenotype. The miRNA-mRNA regulatory networks identified in BC are ripe for exploitation as biomarkers or targeted therapeutic strategies.

A co-expression network for differentially expressed genes in bladder cancer and a risk score model for predicting survival

Background

Urothelial bladder cancer (BLCA) is one of the most common internal malignancies worldwide with poor prognosis. This study aims to explore effective prognostic biomarkers and construct a prognostic risk score model for patients with BLCA.

Methods

Weighted gene co-expression network analysis (WGCNA) was used for identifying the co-expression module related to the pathological stage of BLCA based on the RNA-Seq data retrieved from The Cancer Genome Atlas database. Prognostic biomarkers screened by Cox proportional hazard regression model and random forest were used to construct a risk score model that can predict the prognosis of patients with BLCA. The GSE13507 dataset was used as the independent testing dataset to test the performance of the risk score model in predicting the prognosis of patients with BLCA.

Results

WGCNA identified seven co-expression modules, in which the brown module consisted of 77 genes was most significantly correlated with the pathological stage of BLCA. Cox proportional hazard regression model and random forest identified TPST1 and P3H4 as prognostic biomarkers. Elevated TPST1 and P3H4 expressions were associated with the high pathological stage and worse survival. The risk score model based on the expression level of TPST1 and P3H4 outperformed pathological stage indicators and previously proposed prognostic models.

Conclusion

The gene co-expression network-based study could provide additional insight into the tumorigenesis and progression of BLCA, and our proposed risk score model may aid physicians in the assessment of the prognosis of patients with BLCA.