Integration analysis for novel lncRNA markers predicting tumor recurrence in human colon adenocarcinoma

Predictive Values of Homeobox Gene A-Antisense Transcript 3 (HOXA-AS3), Cystatin 6 (CST6), and Chromobox Homolog 4 (CBX4) Expressions in Cancer Tissues for Recurrence of Early Colon Cancer After Surgery

Purpose

We aim to explore the predictive values of homeobox gene A-antisense transcript 3 (HOXA-AS3), cystatin 6 (CST6), and chromobox homolog 4 (CBX4) expressions in cancer tissues for the recurrence of early colon cancer after surgery.

Patients and Methods

A total of 136 patients who received surgery from January 2020 to January 2021 were enrolled and followed up for 24 months to observe the recurrence after surgery, based on which they were assigned into recurrence and non-recurrence groups. All patients underwent a histopathological examination on admission.

Results

The recurrence group had a lower degree of differentiation as well as a higher HOXA-AS3 level and CST6 and CBX4 expression scores than those of the non-recurrence group (P<0.05). HOXA-AS3 level, CST6 expression score, and CBX4 expression score were risk factors for the recurrence of early colon cancer after surgery [odds ratio (OR)>1, P<0.05]. The receiver operating characteristic curve analysis showed that the areas under the curves of HOXA-AS3 level, CST6 expression score, CBX4 expression score, and their combination for predicting recurrence were 0.909 [95% confidence interval (95% CI): 0.785-1.000], 0.819 (95% CI: 0.690-0.948), 0.794 (95% CI: 0.663-0.926), and 0.942 (95% CI: 0.882-1.000), respectively.

Conclusion

The expressions of HOXA-AS3, CST6, and CBX4 in cancer tissues have close correlations with the recurrence of early colon cancer after surgery and are thus of high predictive values.

Circadian rhythm-associated lncRNA RP11-414H17.5 as a key therapeutic target in osteosarcoma affects the tumor immune microenvironment and enhances malignancy

BACKGROUND

It has previously been proven that circadian rhythm disruption is associated with the incidence and deterioration of several tumors, which potentially leads to increased tumor susceptibility and a worse prognosis for tumor-bearing patients. However, their potential role in osteosarcoma has yet to be sufficiently investigated.

METHODS

Transcriptomic and clinical data of 84 osteosarcoma samples and 70 normal bone tissue samples were obtained from the TARGET and GTEx databases, circadian rhythm-related genes were obtained from Genecards, and circadian rhythm-related lncRNAs (CRLs) were obtained by Pearson correlation analysis, differential expression analysis, and protein-protein interaction (PPI) analysis. COX regression and LASSO regression were performed on the CRLs in order to construct a circadian rhythm-related prognostic prediction signature (CRPS). CRPS reliability was verified by Kaplan-Meier (KM), principal component analysis (PCA), nomogram, and receiver operating characteristic (ROC) curve. CRPS effects on the immune microenvironment of osteosarcoma were explored by enrichment analysis and immune infiltration analysis, and the effect of critical gene RP11-414H17.5 on osteosarcoma was experimentally verified.

RESULT

CRPS consisting of three CRLs was constructed and its area under the curve (AUC) values predicted that osteosarcoma prognosis reached 0.892 in the training group and 0.843 in the test group, with a p value of < 0.05 for the KM curve and stable performance across different clinical subgroups. PCA analysis found that CRPS could significantly distinguish between different risk subgroups, and exhibited excellent performance in the prediction of the immune microenvironment. The experiment verified that RP11-414H17.5 can promote metastasis and inhibit apoptosis of osteosarcoma cells.

CONCLUSION

The study revealed that circadian rhythm plays a crucial role in osteosarcoma progression and identified the impact of the key gene RP11-414H17.5 on osteosarcoma, which provides novel insights into osteosarcoma diagnosis and therapy.

A review on the role of CASC11 in cancers

The long non-coding RNA (lncRNA) cancer susceptibility 11 (CASC11) is a newly identified lncRNA located on chromosome 8q24.21. The expression of lncRNA CASC11 has been found to be elevated in different cancer types and the prognosis of the tumor is inversely correlated with the high CASC11 expression. Moreover, lncRNA CASC11 has an oncogenic function in cancers. The biological characteristics of the tumors, such as proliferation, migration, invasion, autophagy, and apoptosis can be controlled by this lncRNA. In addition to interacting with miRNAs, proteins, transcription factors, and other molecules, the lncRNA CASC11 modulates signaling pathways including Wnt/β-catenin and epithelial-mesenchymal transition. In this review, we have summarized studies on the role of lncRNA CASC11 in the carcinogenesis from cell lines, in vivo, and clinical perspectives.

Comprehensive analysis of ERCC3 prognosis value and ceRNA network in AML

BACKGROUND

Acute myeloid leukemia (AML) is a hematological malignancy with high molecular and clinical heterogeneity, and is the most common type of acute leukemia in adults. Due to limited treatment options, AML is prone to relapse and has a poor prognosis. Excision repair cross-complementing 3 (ERCC3) is an important member of nucleotide excision repair (NER) that is overexpressed in types of solid cancers and potentially regarded as a prognostic factor. However, its role in AML remains unclear. The purpose of this study was to explore ERCC3 expression and functions in AML.

METHODS

The Cancer Genome Atlas (TCGA) and GEO (Gene Expression Omnibus) were used to test the accuracy of ERCC3 expression levels for AML diagnosis. Using online databases and R packages, we also explored the signaling pathway, epigenetic regulation, infiltration of immune cells, clinical prognostic value, and ceRNA network in AML.

RESULTS

Our results revealed that ERCC3 expression was increased in AML and that high ERCC3 expression had good value for disease-free survival and overall survival in AML patients who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT). We found that ERCC3 and co-expressed genes were mainly involved in chemical carcinogenesis/reactive oxygen species, ubiquitin-mediated protein degradation and oxidative phosphorylation. In addition, almost all the m⁶A-related coding genes (except GF2BP1) were positively associated with ERCC3 expression. We also constructed a ceRNA regulatory network containing ERCC3 in AML and identified 6 pairs of ceRNA networks, indicating that ERCC3 expression is regulated by a noncoding RNA system.

CONCLUSION

This study demonstrated that ERCC3 was overexpressed in AML and that high ERCC3 expression can be considered a biomarker conducive to allo-HSCT in AML patients.

Metabolism-related long non-coding RNA in the stomach cancer associated with 11 AMMLs predictive nomograms for OS in STAD

Background: The metabolic processes involving amino acids are intimately linked to the onset and progression of cancer. Long non-coding RNAs (LncRNAs) perform an indispensable function in the modulation of metabolic processes as well as the advancement of tumors. Non-etheless, research into the role that amino acid metabolism-related LncRNAs (AMMLs) might play in predicting the prognosis of stomach adenocarcinoma (STAD) has not been done. Therefore, This study sought to design a model for AMMLs to predict STAD-related prognosis and elucidate their immune properties and molecular mechanisms.

Methods: The STAD RNA-seq data in the TCGA-STAD dataset were randomized into the training and validation groups in a 1:1 ratio, and models were constructed and validated respectively. In the molecular signature database, This study screened for genes involved in amino acid metabolism. AMMLs were obtained by Pearson’s correlation analysis, and predictive risk characteristics were established using least absolute shrinkage and selection operator (LASSO) regression, univariate Cox analysis, and multivariate Cox analysis. Subsequently, the immune and molecular profiles of high- and low-risk patients and the benefit of the drug were examined.

Results: Eleven AMMLs (LINC01697, LINC00460, LINC00592, MIR548XHG, LINC02728, RBAKDN, LINCOG, LINC00449, LINC01819, and UBE2R2-AS1) were used to develop a prognostic model. Moreover, high-risk individuals had worse overall survival (OS) than low-risk patients in the validation and comprehensive groups. A high-risk score was associated with cancer metastasis as well as angiogenic pathways and high infiltration of tumor-associated fibroblasts, Treg cells, and M2 macrophages; suppressed immune responses; and a more aggressive phenotype.

Conclusion: This study identified a risk signal associated with 11 AMMLs and established predictive nomograms for OS in STAD. These findings will help us personalize treatment for gastric cancer patients.

Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer

The considerable burden of colorectal cancer and the rising trend in young adults emphasize the necessity of understanding its underlying mechanisms, providing new diagnostic and prognostic markers, and improving therapeutic approaches. Precision medicine is a new trend all over the world and identification of novel biomarkers and therapeutic targets is a step forward towards this trend. In this context, multi-omics data and integrated analysis are being investigated to develop personalized medicine in the management of colorectal cancer. Given the large amount of data from multi-omics approach, data integration and analysis is a great challenge. In this Review, we summarize how statistical and machine learning techniques are applied to analyze multi-omics data and how it contributes to the discovery of useful diagnostic and prognostic biomarkers and therapeutic targets. Moreover, we discuss the importance of these biomarkers and therapeutic targets in the clinical management of colorectal cancer in the future. Taken together, integrated analysis of multi-omics data has great potential for finding novel diagnostic and prognostic biomarkers and therapeutic targets, however, there are still challenges to overcome in future studies.

LncRNA STK4 antisense RNA 1 (STK4-AS1) promoted osteosarcoma by inhibiting p53 expression

BACKGROUND

LncRNA STK4 antisense RNA 1 (STK4-AS1) has been identified as a potential biomarker associated with multiple cancers. We proposed that STK4-AS1 plays a role in the proliferation of osteosarcoma by regulating the cell cycle.

METHODS

We compared the expression of STK4-AS1, p53, and p21 in osteosarcoma vs normal samples in clinical tissues and cell lines. We determined the effect of overexpression and knockdown of STK4-AS1 in p53 expressing osteosarcoma cells U2OS, p53 muted osteosarcoma cells MG63, and osteoblast cells hFOB on p53 and p21 expression and the cell viability. For U2OS and MG63, the cell cycle was analyzed and the expression of cyclin proteins was determined. We overexpressed p53 or p21 in STK4-AS1 overexpressed cells to explore the association of STK4-AS1 and p53 in U2OS.

RESULTS

The STK4-AS1 expression was higher and p53 and p21 expression were lower in osteosarcoma tissue and cells than in their non-cancer counterparts. The expression of STK4-AS1 was negatively correlated with the expression of p53 or p21. Knockdown of STK4-AS1 in U2OS decreased the cell viability, increased cells in the G0/G1 phase, decreased cells in the S and G2/M phase, decreased expression of cyclin A and B, increased p53 and p21, and had no effect on cyclin D and cyclin E, while overexpression of STK4-AS1 did the opposes. Overexpression of p53 or p21 recovered some changes caused by STK4-AS1 overexpression in U2OS. MG63 expressed no p53 and the expression of p21, cyclin A, and cyclin B, cell viability, and cell cycle were not affected by altered STK4-AS1 levels. In hFOB cells, the expression of p53 and p21 was decreased and the cell viability was increased when STK4-AS1 was overexpressed, but they were not affected when STK4-AS1 was knocked down.

CONCLUSION

LncRNA STK4-AS1 promoted the cell cycle of osteosarcoma cells by inhibiting p53 expression.

Identification and development of TP53 mutation-associated Long non-coding RNAs signature for optimized prognosis assessment and treatment selection in hepatocellular carcinoma

BACKGROUND

The TP53 gene is estimated to be mutated in over 50% of tumors, with the majority of tumors exhibiting abnormal TP53 signaling pathways. However, the exploration of TP53 mutation-related LncRNAs in Hepatocellular carcinoma (HCC) remains incomplete. This study aims to identify such LncRNAs and enhance the prognostic accuracy for Hepatoma patients.

MATERIAL AND METHODS

Differential gene expression was identified using the "limma" package in R. Prognosis-related LncRNAs were identified via univariate Cox regression analysis, while a prognostic model was crafted using multivariate Cox regression analysis. Survival analysis was conducted using Kaplan-Meier curves. The precision of the prognostic model was assessed through ROC analysis. Subsequently, the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were executed on the TCGA dataset via the TIDE database. Fractions of 24 types of immune cell infiltration were obtained from NCI Cancer Research Data Commons using deconvolution techniques. The protein expression levels encoded by specific genes were obtained through the TPCA database.

RESULTS

In this research, we have identified 85 LncRNAs associated with TP53 mutations and developed a corresponding signature referred to as TP53MLncSig. Kaplan-Meier analysis revealed a lower 3-year survival rate in high-risk patients (46.9%) compared to low-risk patients (74.2%). The accuracy of the prognostic TP53MLncSig was further evaluated by calculating the area under the ROC curve. The analysis yielded a 5-year ROC score of 0.793, confirming its effectiveness. Furthermore, a higher score for TP53MLncSig was found to be associated with an increased response rate to immune checkpoint blocker (ICB) therapy (p = .005). Patients possessing high-risk classification exhibited lower levels of P53 protein expression and higher levels of genomic instability.

CONCLUSION

The present study aimed to identify and validate LncRNAs associated with TP53 mutations. We constructed a prognostic model that can predict chemosensitivity and response to ICB therapy in HCC patients. This novel approach sheds light on the role of LncRNAs in TP53 mutation and provides valuable resources for analyzing patient prognosis and treatment selection.

LINC00665 activates Wnt/β-catenin signaling pathway to facilitate tumor progression of colorectal cancer via upregulating CTNNB1

Background LINC00665 is a newly identified oncogene, which has been reported to be oncogene in various cancers. Nevertheless, its role in the progression of colorectal cancer (CRC) remains obscure to the extent. This study aimed at exploring the role and mechanism of LINC00665 in CRC progression. Materials and methods RNA and protein expression were detected via qRT-PCR and western blot. Functional assays were conducted to investigate the role of LINC00665 in the CRC cellular processes. TOP/FOP assay was performed to detect the activity of Wnt/β-catenin signaling pathway. Mechanism investigations were carried out to explore the regulatory relationship among genes. Results LINC00665 was overtly expressed in CRC cell lines at high levels. Functionally, silencing of LINC00665 could curb in vitro CRC cell growth, migration and invasion, while stimulating cell apoptosis. Mechanically, LINC00665 sponged miR-214-3p to up-regulate CTNNB1 expression, consequently activating Wnt/β-catenin signaling pathway. Furthermore, LINC00665 could bind to U2AF2 and enhance the association between U2AF2 and CTNNB1, increasing the stability of CTNNB1. CTNNB1 overexpression could reverse the suppressive effects of LINC00665 downregulation. Conclusion LINC00665 stimulates CRC progression through the activation of Wnt/β-catenin signaling pathway, which hopefully might be a therapeutic target for CRC.

LncRNA ACTA2-AS1 suppress colon adenocarcinoma progression by sponging miR-4428 upregulation BCL2L11

BACKGROUND

Long non-coding RNA is considered to be essential to modulate the development and progression of human malignant cancers. And long non-coding RNA can act as crucial modulators by sponging the corresponding microRNA in tumorigenesis. We aimed to elucidate the function of ACTA2-AS1 and its molecular mechanism in colon adenocarcinoma.

MATERIALS AND METHODS

The expression of ACTA2-AS1, miR-4428 and BCL2L11 in colon adenocarcinoma tissues were detected via qRT-PCR. SW480 and HT29 cells were transfected with shRNA ACTA2-AS1, OE ACTA2-AS1, miRNA mimics of miR-4428, miR-4428 inhibitor, si-BCL2L11 and over-expression of si-BCL2L11. Cell proliferation, colony formation and apoptosis were respectively assessed using CCK-8 assay, colony assay and flow cytometry. Luciferase reporter assay was performed to verify the targets of ACTA2-AS1 and miR-4428. Tumor subcutaneous xenograft mode was constructed to explore tumor growth in vivo.

RESULTS

ACTA2-AS1 was obviously downregulated in human colon adenocarcinoma tissues and colon adenocarcinoma cell lines. Silence or over-expression of ACTA2-AS1 promoted or inhibited cell proliferation and colony formation abilities, and regulated apoptosis. The silence of ACTA2-AS1 resulted in the decrease of Bax and increase of Bal2, while restored in OE ACTA2-AS1 group when compared with the control transfected cells. In addition, luciferase reporter assay revealed that ACTA2-AS1 interacted with miR-4428 and suppressed its expression. miR-4428 could bind to 3' untranslated region of BCL2L11 and modulated the expression of BCL2L11 negatively. Knockdown of ACTA2-AS1 and over-expression of BCL2L11 reversed the biological function that ACTA2-AS1 mediated by knockdown ACTA2-AS1 alone.

CONCLUSION

Our data demonstrated that ACTA2-AS1 could suppress colon adenocarcinoma progression via sponging miR-4428 to regulate BCL2L11 expression.

The role of M6A modification in the regulation of tumor-related lncRNAs

N⁶-methyladenosine (m⁶A) is the most abundant modification in eukaryotic cells, and it regulates RNA transcription, processing, splicing, degradation, and translation. Long non-coding RNAs (lncRNAs), as transcriptional products with no or limited protein coding ability more than 200 nt in length, play an important role in epigenetic modification, mRNA transcription, splicing, stability, translation, and other biological functions. Extensive studies have shown that both m⁶A modification and lncRNAs are involved in the pathogenesis of various diseases, such as kinds of cancers, heart failure, Alzheimer’s disease, periodontitis, human abdominal aortic aneurysm, and obesity. To date, m⁶A modification has been identified as an important biological function in enrichment and regulation of lncRNAs. In this review, we summarize the role of m⁶A modification in the regulation and function of tumor-related lncRNAs. Moreover, we discuss the potential applications and possible future directions in the field.

The lncRNA LINC00691Functions as a ceRNA for miRNA-1256 to Suppress Osteosarcoma by Regulating the Expression of ST5

Introduction

Osteosarcoma is the most common primary malignant tumor in children and young patients. Although neoadjuvant chemotherapy and surgery could improve the prognosis of these patients, treatment outcomes are poor because of its low early diagnosis rate and high degree of malignancy as well as its tendency for early metastasis. In the field of osteosarcoma, lncRNAs have become a hot spot for studying the molecular mechanisms driving malignant biological characteristics and exploring effective treatment methods. An lncRNA is a long noncoding RNA lacking protein-encoding ability, and in its RNA form, it regulates various gene expression processes, such as epigenetic regulation, transcriptional regulation, and posttranscriptional regulation. LncRNAs play an important role in tumorigenesis and metastasis.

Methods

We used bioinformatics software to analyze the data in geo database. CCK-8 and Transwell were used to detect the effect of lncRNA LINC00691 on the proliferation and migration of osteosarcoma cells. The target gene of LINC00691 was detected by bioinformatics analysis and RNA pull down.

Results

In this study, we identified the lncRNA LINC00691 and confirmed its expression in osteosarcoma cells through GEO database analysis. Expression analysis showed that the levels of lncRNA LINC00691 in osteosarcoma cells were decreased compared to those of control cells. Overexpression of LINC00691 could inhibit the proliferation, migration, invasion, and induction of G1 cell cycle arrest in osteosarcoma cells, which was shown through in vitro and in vivo studies. Using bioinformatics analysis, RNA pull down experiments and luciferase reporter gene detection assays, we found that LINC00691 regulated ST5 expression by binding miR-1256. LINC00691 overexpression inhibited EMT by promoting the expression of E-cadherin and increasing the expression of ZEB1, Snail, and Fibronectin.

Conclusion

These results suggested that overexpressed LINC00691 promoted the expression of ST5 by regulating the function of miR-1256 through a ceRNA mechanism. The LINC00691/miR-1256/ST5 pathway plays an important role in the progression and metastasis of osteosarcoma and represents a good therapeutic target.

Prognosis prediction model based on competing endogenous RNAs for recurrence of colon adenocarcinoma

BACKGROUND

Colon adenocarcinoma (COAD) patients who develop recurrence have poor prognosis. Our study aimed to establish effective prognosis prediction model based on competing endogenous RNAs (ceRNAs) for recurrence of COAD.

METHODS

COAD expression profilings downloaded from The Cancer Genome Atlas (TCGA) were used as training dataset, and expression profilings of GSE29623 retrieved from Gene Expression Omnibus (GEO) were set as validation dataset. Differentially expressed RNAs (DERs) between non-recurrent and recurrent specimens in training dataset were screened, and optimum prognostic signature DERs were revealed to establish prognostic score (PS) model. Kaplan-Meier survival analysis was conducted for PS model, and GEO dataset was used for validation. Prognosis prediction efficiencies were evaluated by area under curve (AUC) and C-index. Meanwhile, ceRNA regulatory network was constructed by using signature mRNAs, lncRNAs and miRNAs.

RESULTS

We identified 562 DERs including 42 lncRNAs, 36 miRNAs, and 484 mRNAs. PS prediction model, consisting of 17 optimum prognostic signature DERs, showed that high risk group had significantly poorer prognosis (5-year AUC = 0.951, C-index = 0.788), which also validated in GSE29623. Prognosis prediction model incorporating multi-RNAs with pathologic distant metastasis (M) and pathologic primary tumor (T) (5-year AUC = 0.969, C-index = 0.812) had better efficiency than clinical prognosis prediction model (5-year AUC = 0.712, C-index = 0.680). In the constructed ceRNA regulatory network, lncRNA NCBP2-AS1 could interact with hsa-miR-34c and hsa-miR-363, and lncRNA LINC00115 could interact with hsa-miR-363 and hsa-miR-4709. SIX4, GRAP, NKAIN4, MMAA, and ERVMER34-1 are regulated by hsa-miR-4709.

CONCLUSION

Prognosis prediction model incorporating multi-RNAs with pathologic M and pathologic T may have great value in COAD prognosis prediction.

Comprehensive analysis of competitive endogenous RNAs network reveals potential prognostic lncRNAs in gastric cancer

Long non-coding RNAs (lncRNAs) are key regulators of a range of human diseases, including various cancers, with multiple previous studies having explored lncRNA dysregulation in the context of gastric cancer (GC). The present study sought to expand upon these previous results by downloading lncRNA, mRNA, and microRNA (miRNA) expression profiles derived from 180 GC tissues and 24 normal control tissues within the Cancer Genome Atlas (TCGA) database. These datasets were then interrogated to identify GC-related differentially expressed (DE) RNAs (|fold change| ≥ 2, FDR< 0.01), leading to the identification of 1946 DE lncRNAs, 123 DE miRNAs, and 3159 DE mRNAs. These results were then used to generate a putative GC-related competitive endogenous RNA (ceRNA) network composed of 131 lncRNAs, 9 miRNAs, and 78 mRNAs. Subsequent survival analyses based upon this network revealed 17 of these lncRNAs to be significantly associated with GC patient survival (P < 0.05). Further multivariable Cox regression and lasso analyses allowed for the construction of an 8-lncRNA risk score that was able to effectively predict GC patient survival with good discriminative ability. The Kaplan-Meier Plotter database further confirmed that network hub genes that were related to these 8 lncRNAs were associated with GC patient prognosis (P < 0.05). As the ceRNA network in the present study was constructed with a focus on both disease stage and differential gene expression, it represents a key resource that will offer valuable insights into the mechanistic roles of ceRNA pathways in GC development and progression.

Long non-coding RNA DDX11-AS1 promotes non-small cell lung cancer development via regulating PI3K/AKT signalling

Non-small cell lung cancer (NSCLC) has been considered to be the most common category of lung cancer, comprising approximately 80% of lung cancers. Long non-coding RNAs (lncRNAs) were diffusely documented to modulate carcinogenesis or progression of tumours. However, the role of DDX11-AS1 was still unclear in NSCLC. Bioinformatics analysis and experimental assays including hematoxylin and eosin (H&E) staining, RT-qPCR, colony formation, CCK-8, flow cytometry, western blot and xenograft assays were applied to investigate the biological role and molecular mechanism of DDX11-AS1 in NSCLC. The level of lncRNA DDX11-AS1 was up-regulated in NSCLC tumour tissues and cells. In function aspect, knockdown of DDX11-AS1 caused an apparent inhibitive effect on cell proliferation in vitro and in vivo. DDX11-AS1 inhibition promoted cell apoptosis in vitro. In mechanism, the protein level of phosphorylated AKT was reduced by DDX11-AS1 inhibition but increased by DDX11-AS1 overexpression. These results indicated that DDX11-AS1 exacerbated NSCLC progression via activating PI3K/AKT signalling pathway. All in all, DDX11-AS1 promotes NSCLC development via regulating PI3K/AKT signalling.

To construct a ceRNA regulatory network as prognostic biomarkers for bladder cancer

Emerging evidence demonstrates that competing endogenous RNA (ceRNA) hypothesis has played a role in molecular biological mechanisms of cancer occurrence and development. But the effect of ceRNA network in bladder cancer (BC), especially lncRNA‐miRNA‐mRNA regulatory network of BC, was not completely expounded. By means of The Cancer Genome Atlas (TCGA) database, we compared the expression of RNA sequencing (RNA‐Seq) data between 19 normal bladder tissue and 414 primary bladder tumours. Then, weighted gene co‐expression network analysis (WGCNA) was conducted to analyse the correlation between two sets of genes with traits. Interactions between miRNAs, lncRNAs and target mRNAs were predicted by MiRcode, miRDB, starBase, miRTarBase and TargetScan. Next, by univariate Cox regression and LASSO regression analysis, the 86 mRNAs obtained by prediction were used to construct a prognostic model which contained 4 mRNAs (ACTC1 + FAM129A + OSBPL10 + EPHA2). Then, by the 4 mRNAs in the prognostic model, a ceRNA regulatory network with 48 lncRNAs, 14 miRNAs and 4 mRNAs was constructed. To sum up, the ceRNA network can further explore gene regulation and predict the prognosis of BC patients.