ArticleOncology letters2018
A risk score staging system based on the expression of seven genes predicts the outcome of bladder cancer.
Article in Oncology letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Circulating innate lymphoid cells are dysregulated in patients with prostate cancer.Cellular & molecular biology letters · 2025Article
- Article
- Apolipoprotein L3 inhibits breast cancer proliferation and modulates cell cycle via the P53 pathway.Journal of Cancer · 2024Article
- Review
- AHNAKs roles in physiology and malignant tumors.Frontiers in oncology · 2023Review
- Article
- Comprehensive analysis of cuproptosis-related lncRNAs in the prognosis and therapy response of patients with bladder cancer.Annals of translational medicine · 2022Article
- Development and validation of an RNA-seq-based transcriptomic risk score for asthma.Scientific reports · 2022Article
- Andrographolide Inhibits Proliferation and Promotes Apoptosis in Bladder Cancer Cells by Interfering with NF- κ B and PI3K/AKT Signaling In Vitro and In Vivo.Chinese journal of integrative medicine · 2022Article
- The Role of Gender-Related Immune Genes in Childhood Acute Myeloid Leukemia.BioMed research international · 2022Article
- Identification of hub genes and pathways in bladder cancer using bioinformatics analysis.American journal of clinical and experimental urology · 2022Article
- Identification of Ten-Gene Related to Lipid Metabolism for Predicting Overall Survival of Breast Invasive Carcinoma.Contrast media & molecular imaging · 2022Article
- Article
- The function of apolipoproteins L (APOLs): relevance for kidney disease, neurotransmission disorders, cancer and viral infection.The FEBS journal · 2021Review
- Small Nucleolar RNAs (snoRNAs)-Based Risk Score Classifier Predicts Overall Survival in Bladder Carcinoma.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
- Identification and Validation of an Individualized Prognostic Signature of Bladder Cancer Based on Seven Immune Related Genes.Frontiers in genetics · 2020Article
- Cryptotanshinone Inhibites Bladder Cancer Cell Proliferation and Promotes Apoptosis via the PTEN/PI3K/AKT Pathway.Journal of Cancer · 2020Article
- Apolipoproteins and cancer.Cancer medicine · 2019Review
- A Qualitative Transcriptional Signature for Predicting Recurrence Risk of Stage I-III Bladder Cancer Patients After Surgical Resection.Frontiers in oncology · 2019Article
- A co-expression network for differentially expressed genes in bladder cancer and a risk score model for predicting survival.Hereditas · 2019Article
Corrections and comments
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3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bladder cancer (BLCA) is among the most malignant types of cancer. At present, the prognostic tools available for this disease are insufficient. In the present study, the transcriptome of 1,049 BLCA samples from four datasets from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) were analyzed. By utilizing the RNA-seq data provided by TCGA, a risk score staging system model was built to predict the outcome of patients with BLCA using random forest variable hunting and Cox multivariate regression. A total of 7 genes, including zinc finger protein 230, Bcl2-like 14, AHNAK, transmembrane protein 109, apolipoprotein L2, advanced glycation end-product specific receptor and amine oxidase, copper containing 2 were identified as predicting the survival time of patients with BLCA. The patients with a low risk score had a significantly higher survival rate than those with a high-risk score both in the training and validation datasets. Association analyses between risk score and other clinical information were additionally performed; it was demonstrated that the risk score was significantly associated with pathological stage. A nomogram was plotted to compare risk score and other clinical information. The risk score spanned the greatest range of points, indicating the relative accuracy of risk score. In summary, the risk staging model based on the expression of 7 genes is robust and performs more effectively than other clinical information in predicting a prognosis.
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