ArticleFrontiers in genetics2020
The Construction and Analysis of Tumor-Infiltrating Immune Cells and ceRNA Networks in Bladder Cancer.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- The miRNA-immune axis in bladder cancer: systematic evidence for a new era of immunotherapy precision.Frontiers in immunology · 2025Pooled it
- Clinical and prognostic significance of follicular helper and regulatory T cells in bladder cancer draining lymph nodes.Scientific reports · 2024Article
- The urothelial gene regulatory network: understanding biology to improve bladder cancer management.Oncogene · 2024Review
- Tumor microenvironment heterogeneity in bladder cancer identifies biologically distinct subtypes predicting prognosis and anti-PD-L1 responses.Scientific reports · 2023Article
- Integrated bioinformatics and validation reveal SOX12 as potential biomarker in colon adenocarcinoma based on an immune infiltration-related ceRNA network.Journal of cancer research and clinical oncology · 2023Article
- Network analysis reveals miRNA crosstalk between periodontitis and oral squamous cell carcinoma.BMC oral health · 2023Article
- Integrated analysis to identify the AC005154.6/hsa-miR-29c-3p/CCNL2 axis as a novel prognostic biomarker associated with immune infiltration in prostate cancer.Cancer cell international · 2022Article
- HYAL3 as a potential novel marker of BLCA patient prognosis.BMC genomic data · 2022Article
- NXPH4 Used as a New Prognostic and Immunotherapeutic Marker for Muscle-Invasive Bladder Cancer.Journal of oncology · 2022Article
- Integrated analysis of the functions and clinical implications of exosome circRNAs in colorectal cancer.Frontiers in immunology · 2022Article
- MMP25-AS1/hsa-miR-10a-5p/SERPINE1 axis as a novel prognostic biomarker associated with immune cell infiltration in KIRC.Molecular therapy oncolytics · 2021Article
- Bioinformatics analysis based on immune-autophagy-related lncRNAs combined with immune infiltration in bladder cancer.Translational andrology and urology · 2021Article
- Identification of Novel Biomarkers for Predicting Prognosis and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma Based on ceRNA Network and Immune Infiltration Analysis.BioMed research international · 2021Article
Corrections and comments
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Authors and funding
13 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBladder cancer (BLCA) is the 11th most common malignancy worldwide. Although significant improvements have been made in screening, diagnosis, and precise management in recent years, the prognosis of BLCA remains bleak.
objectivesThis study aimed to investigate the prognostic significance of tumor-infiltrating immune cells and construct ceRNA networks in BLCA patients.
methodsThe expression data of BLCA patients were obtained from The Cancer Genome Atlas (TCGA) database. A competing endogenous RNA (ceRNA) network was constructed to identify the hub genes involved in the prognosis of BLCA. The CIBERSORT algorithm was utilized to investigate the infiltration levels of 22 subsets of immune cells. Ultimately, the nomogram was generated to visualize the survival probability of each patient, with the calibration curve being performed to assess its performance. Furthermore, the Pearson correlation test was used to explore the correlation between the identified hub genes in the ceRNA network and the prognostic-related immune cells.
resultsA total of eight elements in the ceRNA network were considered as key members and correlated with the prognosis of BLCA, including
conclusionOur results suggest that the mechanism of
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.