ArticleFrontiers in oncology2021
Construction and Validation of an Autophagy-Related Prognostic Signature and a Nomogram for Bladder Cancer.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- Integrating machine learning models with multi-omics analysis to decipher the prognostic significance of mitotic catastrophe heterogeneity in bladder cancer.Biology direct · 2025Article
- Integrative multi-omics analysis for identifying novel therapeutic targets and predicting immunotherapy efficacy in lung adenocarcinoma.Cancer drug resistance (Alhambra, Calif.) · 2025Article
- Integrative multi-omics and machine learning identify a robust signature for discriminating prognosis and therapeutic targets in bladder cancer.Journal of Cancer · 2025Article
- Characterization of an Autophagy-Immune Related Genes Score Signature and Prognostic Model and its Correlation with Immune Response for Bladder Cancer.Cancer management and research · 2022Article
- Characteristic of Molecular Subtypes in Lung Squamous Cell Carcinoma Based on Autophagy-Related Genes and Tumor Microenvironment Infiltration.Journal of oncology · 2022Article
- Identification of immuno-infiltrating MAP1A as a prognosis-related biomarker for bladder cancer and its ceRNA network construction.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveBladder cancer (BC) is one of the top ten cancers endangering human health but we still lack accurate tools for BC patients' risk stratification. This study aimed to develop an autophagy-related signature that could predict the prognosis of BC. In order to provide clinical doctors with a visual tool that could precisely predict the survival probability of BC patients, we also attempted to establish a nomogram based on the risk signature.
methodsWe screened out autophagy-related genes (ARGs) combining weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) in BC. Based on the screened ARGs, we performed survival analysis and Cox regression analysis to identify potential prognostic biomarkers. A risk signature based on the prognostic ARGs by multivariate Cox regression analysis was established, which was validated by using seven datasets. To provide clinical doctors with a useful tool for survival possibility prediction, a nomogram assessed by the ARG-based signature and clinicopathological features was constructed, verified using four independent datasets.
resultsThree prognostic biomarkers including BOC (
conclusionsThree ARGs were identified as prognosis biomarkers in BC. An ARG-based signature was established for the first time, showing strong potential for prognosis prediction in BC. This signature was proven to improve the clinical net benefit of the standard model. A nomogram was established using this signature, which could lead to more effective prognosis prediction for BC patients.
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