ArticleDisease markers2020
Construction and Validation of a Robust Cancer Stem Cell-Associated Gene Set-Based Signature to Predict Early Biochemical Recurrence in Prostate Cancer.
Article in Disease markers, 2020. 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.
- Investigating the Role ofCancers · 2024Article
- Systematic review and integrated analysis of prognostic gene signatures for prostate cancer patients.Discover oncology · 2023Article
- Construction and validation of N6-methyladenosine long non-coding RNAs signature of prognostic value for early biochemical recurrence of prostate cancer.Journal of cancer research and clinical oncology · 2023Article
- Identification of tumor-agnostic biomarkers for predicting prostate cancer progression and biochemical recurrence.Frontiers in oncology · 2023Article
- Identification and validation of an E2F-related gene signature for predicting recurrence-free survival in human prostate cancer.Cancer cell international · 2022Article
- Risk subtyping and prognostic assessment of prostate cancer based on consensus genes.Communications biology · 2022Article
- A novel 8-gene panel for prediction of early biochemical recurrence in patients with prostate cancer after radical prostatectomy.American journal of cancer research · 2022Article
- Signature for Prostate Cancer Based on Autophagy-Related Genes and a Nomogram for Quantitative Risk Stratification.Disease markers · 2022Article
- Characterization of a Pyroptosis-Related Signature for Prognosis Prediction and Immune Microenvironment Infiltration in Prostate Cancer.Computational and mathematical methods in medicine · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPostoperative early biochemical recurrence (BCR) was an essential indicator for recurrence and distant metastasis of prostate cancer (PCa). The aim of this study was to construct a cancer stem cell- (CSC-) associated gene set-based signature to identify a subgroup of PCa patients who are at high risk of early BCR.
methodsThe PCa dataset from The Cancer Genome Atlas (TCGA) was randomly separated into discovery and validation set. Patients in discovery set were divided into early BCR group and long-term survival group. Propensity score matching analysis and differentially expressed gene selection were used to identify candidate CSC-associated genes. The LASSO Cox regression model was finally performed to filter the most useful prognostic CSC-associated genes for predicting early BCR.
resultsBy applying the LASSO Cox regression model, we built a thirteen-CSC-associated gene-based early BCR-predicting signature. In the discovery set, patients in high-risk group showed significantly poorer BCR free survival than that patients in low-risk group (HR: 4.91, 95% CI: 2.75-8.76,
conclusionsWe successfully developed a CSC-associated gene set-based signature that can accurately predict early BCR in PCa cancer.
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