Identification and verification of an immune-related lncRNA signature for predicting the prognosis of patients with bladder cancer

Wang, Jirong; Shen, Chengquan; Dong, Dahai; Zhong, Xiulong; Wang, Yonghua; Yang, Xiaokun

doi:10.1016/j.intimp.2020.107146

Cited by 54 publications

(41 citation statements)

References 50 publications

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“…26 In bladder cancer, the signature consisting of 7 immunerelated lncRNAs, including TNFRSF14-AS1, was clarified to be a prognostic marker, whereas the TNFRSF14-AS1 was considered as a protective effector. 27 Similarly, these reports also supported our conclusions that LINC01871 and TNFRSF14-AS1 were prone to prolonging the survival time of BC patients. It was noted that few studies explored the prognostic value of DLGAP1-AS1 in BC, but the dysregulation of DLGAP1-AS1 had been reported to function as oncogene roles in several tumour types, including glioma, 28 colorectal cancer, 29 gastric cancer 30,31 and HCC.…”

Section: Discussionsupporting

confidence: 82%

Identification of pyroptosis‐related lncRNAs for constructing a prognostic model and their correlation with immune infiltration in breast cancer

Tan

Zhao

et al. 2021

J Cellular Molecular Medi

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Breast cancer (BC) is the most frequently diagnosed female malignancy and one of the leading causes of cancer-related mortality among women worldwide. 1 BC is a highly complex cancer type with histological and molecular heterogeneity, posing an enormous threat to women health due to its extremely high recurrence rate and mortality rate. 2 Although the therapeutic efficacy of BC gains momentum dramatically, unfortunately, the lack of effective hallmarks and diagnostic tools to predict prognosis or long-term survival in BC patients remains a major obstacle to improving strategies for BC detection and treatment. 3 Therefore, it is imperative to explore novel therapeutic targets and reliable prognostic models for optimal clinical outcomes in BC.

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Section: Discussionsupporting

confidence: 82%

Identification of pyroptosis‐related lncRNAs for constructing a prognostic model and their correlation with immune infiltration in breast cancer

Tan

Zhao

et al. 2021

J Cellular Molecular Medi

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“…is result is consistent with the results of previous studies, which have revealed that lncRNA-related signatures play a vital role in predicting the prognosis of bladder cancer patients. Wang et al performed a bioinformatics analysis to identify a signature of seven immune-related lncRNAs, which could serve as prognostic biomarkers for bladder cancer [23].…”

Section: Discussionmentioning

confidence: 99%

m6A-Related lncRNA to Develop Prognostic Signature and Predict the Immune Landscape in Bladder Cancer

Zhong

et al. 2021

Journal of Oncology

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Abnormal m6A methylation plays a significant role in cancer progression. Increasingly, researchers have focused on developing lncRNA signatures to evaluate the prognosis of cancer patients. The specific function of m6A-related lncRNAs in the prognosis of bladder cancer patients and the immune microenvironment of bladder cancer remains elusive. Herein, we performed a comprehensive analysis of m6A-related lncRNA prognostic values and their association with the immune microenvironment in bladder cancer using the TCGA dataset. A total of 9 m6A-related lncRNAs were dramatically correlated with overall survival outcomes in bladder cancer. Two molecular subtypes (cluster 1 and cluster 2) were identified by consensus clustering for 9 m6A-related prognostic lncRNAs. Cluster 1 was significantly correlated with poor prognosis, advanced clinical stage, higher PD-L1 expression, a higher ESTIMATEScore and immuneScore, and distinct immune cell infiltration. GSEA revealed the enrichment of apoptosis and the JAK-STAT signaling pathway in cluster 2. A prognostic risk score was constructed using 9 m6A-related prognostic lncRNAs, which functioned as an independent prognostic factor for bladder cancer. Moreover, bladder cancer patients in the low-risk score group had a higher pN stage, pT stage, and clinical stage and a lower tumor grade and immuneScore. The risk score was correlated with the infiltration levels of certain immune cells, including B cells, plasma cells, follicular helper T cells, regulatory T cells, resting NK cells, neutrophils, M0 macrophages, M1 macrophages, and M2 macrophages. Collectively, our study elucidated the important role of m6A-related lncRNAs in the prognosis of bladder cancer patients and in the bladder cancer immune microenvironment. The results suggest that the components of the m6A-related prognostic lncRNA signature might serve as a crucial mediator of the immune microenvironment in bladder cancer, representing promising therapeutic targets for improving immunotherapeutic efficacy.

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“…Tong et al found that AL049840.3, AL031775.1, and USP30-AS1 may predict the prognosis and progression of patients with BC as an epithelial-mesenchymal transition- (EMT-) related lncRNAs [ 29 ]. Wang et al found that OCIAD1-AS1 and AL354919.2 may predict the prognosis and progression of patients with BC as immune-related lncRNAs [ 30 ]. USP30-AS1 has also been found to be associated with autophagy, which may be involved in the diagnosis and prognosis of BC [ 31 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of a Nomogram from Ferroptosis-Related Long Noncoding RNAs Signature to Analyze Overall Survival in Patients with Bladder Cancer

Cui

Chai

Che

et al. 2021

Journal of Oncology

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Purpose. This study aimed to establish a nomogram to predict the overall survival (OS) of patients with bladder cancer (BC) by ferroptosis-related long noncoding RNAs (FRlncRNAs) signature. Methods. We obtained FRlncRNAs expression profiles and clinical data of patients with BC from the Cancer Genome Atlas database. The patients were divided into the training set, testing set, and overall set. Lasso regression and multivariate Cox regression were used to establish the FRlncRNAs signature, the prognosis of each group was compared by Kaplan–Meier (K-M) analysis, and the receiver operating characteristic (ROC) curve evaluated the accuracy of the model. The Gene Set Enrichment Analysis (GSEA) was used for the visualization of the functional enrichment for FRlncRNAs. The databases of GEPIA and K-M Plotter were used for subsequent functional analysis of major FRlncRNAs. Results. Thirteen prognostic FRlncRNAs (LINC00942, MAFG-DT, AL049840.3, AL136084.3, OCIAD1-AS1, AC062017.1, AC008074.2, AC018653.3, AL031775.1, USP30-AS1, LINC01767, AC132807.2, and AL354919.2) were identified to be significantly different, constituting an FRlncRNAs signature. Patients with BC were divided into low-risk group and high-risk group by this signature in the training, testing, and overall sets. K-M analysis showed that the prognosis of patients in the high-risk group was poor and the difference in the subgroup analyses was statistically significant. ROC analysis revealed that the predictive ability of the model was more accurate than traditional assessment methods. A risk score based on FRlncRNAs signature was an independent prognostic factor for the patients with BC (HR = 1.388, 95%CI = 1.228–1.568, P < 0.001 ). Combining the FRlncRNAs signature and clinicopathological factors, a predictive nomogram was constructed. The nomogram can accurately predict the overall survival of patients and had high clinical practicability. The GSEA analysis showed that the primary pathways were WNT, MAPK, and cell-matrix adhesion signaling pathways. The major FRlncRNAs (MAFG-DT) were associated with poor prognosis in the GEPIA and K-M Plotter database. Conclusion. Thirteen prognostic FRlncRNAs and their nomogram were accurate tools for predicting the OS of BC, which might be molecular biomarkers and therapeutic targets.

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Identification and verification of an immune-related lncRNA signature for predicting the prognosis of patients with bladder cancer

Cited by 54 publications

References 50 publications

Identification of pyroptosis‐related lncRNAs for constructing a prognostic model and their correlation with immune infiltration in breast cancer

Identification of pyroptosis‐related lncRNAs for constructing a prognostic model and their correlation with immune infiltration in breast cancer

m6A-Related lncRNA to Develop Prognostic Signature and Predict the Immune Landscape in Bladder Cancer

Identification of a Nomogram from Ferroptosis-Related Long Noncoding RNAs Signature to Analyze Overall Survival in Patients with Bladder Cancer

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