ArticleJournal of immunology research2022
Prediction of Prognosis and Recurrence of Bladder Cancer by ECM-Related Genes.
Article in Journal of immunology research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- AI predicting recurrence in non-muscle-invasive bladder cancer: systematic review with study strengths and weaknesses.Frontiers in oncology · 2024Pooled it
- Role of the stromal and immune microenvironment in intrahepatic cholangiocarcinoma.JHEP reports : innovation in hepatology · 2026Review
- Naringenin, a Food-Derived Flavanone, Suppresses ITGA11-Associated Gastric Cancer Progression via the FAK/PI3K/AKT/mTOR Axis.Cancers · 2026Article
- Overexpression of Long Non-Coding RNA, LINC01748, Predicts Extracellular Matrix Remodeling in Colorectal Cancer Through Let-7b-5p/CTHRC1 Axis.Chonnam medical journal · 2026Article
- EPHA2-Ephrin-B1 cis-interaction drives an oncogenic reverse signaling, leading to the recurrence of oral cancer.Cell communication and signaling : CCS · 2026Article
- Multi-omic profiling defines three distinct molecular subtypes of urothelial carcinoma with implications for precision therapy.Clinical and translational medicine · 2026Article
- TROP2 expression is associated with early stage and favorable prognosis in upper tract urothelial carcinoma.World journal of urology · 2026Article
- High FSTL1 expression promotes bladder cancer progression by enhancing tumor cell migration.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Machine Learning-Based Gene Expression Analysis to Identify Prognostic Biomarkers in Upper Tract Urothelial Carcinoma.Cancers · 2025Article
- Machine learning derived development and validation of extracellular matrix related signature for predicting prognosis in adolescents and young adults glioma.Scientific reports · 2025Article
- Cancer-Associated Fibroblasts: Heterogeneity, Cancer Pathogenesis, and Therapeutic Targets.MedComm · 2025Review
- Immune-related genes can accurately predict survival in bladder cancer: a retrospective study via two independent immunotherapy cohorts.Translational andrology and urology · 2025Article
- Article
- Oncogenic mechanisms of COL10A1 in cancer and clinical challenges (Review).Oncology reports · 2024Review
- Development and validation of a recurrence risk assessment model for high-grade bladder cancer based on TCGA and GEO.Translational cancer research · 2024Article
- Identification of immune-associated biomarkers of diabetes nephropathy tubulointerstitial injury based on machine learning: a bioinformatics multi-chip integrated analysis.BioData mining · 2024Article
- CTHRC1 is a prognostic biomarker correlated with immune infiltration in head and neck squamous cell carcinoma.BMC oral health · 2024Article
- The role of collagen triple helix repeat containing 1 (CTHRC1) in cancer development and progression.Expert opinion on therapeutic targets · 2024Review
- A novel anoikis-related gene signature identifies LYPD1 as a novel therapy target for bladder cancer.Scientific reports · 2024Article
- A risk model based on lncRNA-miRNA-mRNA gene signature for predicting prognosis of patients with bladder cancer.Cancer biomarkers : section A of Disease markers · 2024Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Bladder cancer (BLCA) is one of the most common cancers and ranks ninth among all cancers. Extracellular matrix (ECM) genes activate a number of pathways that facilitate tumor development. This study is aimed at providing models to predict BLCA survival and recurrence by ECM genes. Methods: Expression data from BLCA samples in GSE32894, GSE13507, GSE31684, GSE32548, and TCGA-BLCA cohorts were downloaded and analyzed. The ECM-related genes were obtained by differentially expressed gene analysis, stage-associated gene analysis, and random forest variable selection. The ECM was constructed in GSE32894 by the hub ECM-related genes and validated in GSE13507, GSE31684, GSE32548, and TCGA-BLCA cohorts. The correlations of the ECM score with cells (T cells, fibroblasts, etc.) and the response to immunotherapeutic drugs were investigated. Four machine learning models were selected and used to construct models to predict the recurrence of BLCA. A total of 15 paired BLCA and normal tissue specimens, human immortalized uroepithelial cell lines, and bladder cancer cell lines were selected for the validation of the difference in expression of FSTL1 between normal tissues and BLCA. Results: Six ECM genes (CTHRC1, MMP11, COL10A1, FSTL1, SULF1, and COL5A3) were recognized to be the hub ECM-related genes. The ECM score of each BLCA patient was calculated using these six selected ECM-related genes. BLCA patients with a high ECM score group had significantly lower overall survival rates than patients in the low ECM score group. We found that the ECM score was positively associated with immune cells and fibroblasts and negatively correlated with tumor purity. When treated with immunotherapy, BLCA patients with a high ECM score presented a high response rate and better prognosis. We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence. Based on the RT-qPCR results of FSTL1 gene expression, there was an overall decrease in the mRNA expression of FSTL1 in cancer tissues compared to their adjacent normal tissues. Subsequent Conclusion: Taken together, our results indicate that ECM-related genes correlate with immune cells, overall survival, and recurrence of BLCA. This study provides a machine learning model for predicting the survival and recurrence of BLCA patients.
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