ArticleBMC medical genomics2022
Construction of an lncRNA model for prognostic prediction of bladder cancer.
Article in BMC medical genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 9 citations in OpenAlex.
- Integrative Multi-Omics Analysis Reveals HNRNPLL as a Potential Biomarker Associated with Hepatocellular Carcinoma Progression.Metabolites · 2026Article
- Multi-Omics and Functional Analysis of BFSP1 as a Prognostic and Therapeutic Target in Liver Hepatocellular Carcinoma.Medicina (Kaunas, Lithuania) · 2025Article
- A nomogram integrating mutation signatures and clinical features for prognostic stratification in bladder cancer.Discover oncology · 2025Article
- VPS26A as a Prognostic Biomarker and Therapeutic Target in Liver Hepatocellular Carcinoma: Insights from Comprehensive Bioinformatics Analysis.Medicina (Kaunas, Lithuania) · 2025Article
- Vitamin D Reshapes Genomic Hierarchies in Skin Cells: lncRNA-Driven Responses in Carcinoma Versus Transcription Factor-Based Regulation in Healthy Skin.International journal of molecular sciences · 2025Article
- LINC01518 predicts poor prognosis of prostate cancer and promotes its progression by regulating hsa-miR-320a/CNKSR2 axis.Discover oncology · 2024Article
- Deciphering Transcriptomic Variations in Hematopoietic Lineages: HSCs, EBs, and MKs.International journal of molecular sciences · 2024Article
- Identification of sepsis-associated mitochondrial genes through RNA and single-cell sequencing approaches.BMC medical genomics · 2024Article
- A panel based on three-miRNAs as diagnostic biomarker for prostate cancer.Frontiers in genetics · 2024Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe aimed to investigate the role and potential mechanisms of long non-coding RNAs (lncRNAs) in bladder cancer (BC), as well as determine their prognostic value.
methodsLncRNA expression data and clinical data from BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. R software was used to carry out principal component analysis (PCA), differential analysis, and prognostic analysis. Lasso regression and multivariate Cox regression analyses were performed to identify potential prognostic genes. The expression of five identified genes and their correlation with prognosis were verified using TCGA and GSE13507 datasets. In addition, quantitative real-time polymerase chain reaction (qRT-PCR) was used to confirm the expression of these five genes in cell lines (two human BC cell lines and one human bladder epithelial cell line) and tissues (84 pairs of BC tissues and the corresponding paracancerous tissues). Risk scores that had been generated from the five genes and their prognostic ability were assessed by receiver operating characteristic (ROC) and Kaplan-Meier (KM) curves. Co-expressed genes were screened by WGCNA and analyzed by GO and KEGG, while functional enrichment and immune infiltration analyses were performed using STRING ( https://cn.string-db.org/ ) and TIMER2.0 ( http://timer.cistrome.org/ ) online tools, respectively.
resultsCYP4F8, FAR2P1, LINC01518, LINC01764, and DTNA were identified as potential prognostic genes. We found that these five genes were differentially expressed in BC tissue, as well as in BC cell lines, and were significantly correlated with the prognosis of BC patients. KM analysis considering risk scores as independent parameters revealed differences in overall survival (OS) by subgroups. The ROC curve revealed that a combined model consisting of all five genes had good predictive ability at 1, 3, and 5 years. GO and KEGG analyses of 567 co-expressed genes revealed that these genes were significantly associated with muscle function.
conclusionLncRNAs can be good predictors of BC development and prognosis, and may act as potential tumor markers and therapeutic targets that may be beneficial in helping clinicians decide the most effective treatment strategies.
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