ArticleFrontiers in oncology2020
Identification of an Autophagy-Related Prognostic Signature for Clear Cell Renal Cell Carcinoma.
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 27 citations in OpenAlex.
- A novel programmed cell death signature predicts clinical outcomes in clear cell renal cell carcinoma and identifies PLK1 as a therapeutic target.Apoptosis : an international journal on programmed cell death · 2025Article
- Identification of CWH43 as a novel prognostic biomarker and therapeutic target in clear cell renal cell carcinoma by a multi-omics approach and correlation with autophagy progression.Discover oncology · 2025Article
- Article
- A novel autophagy-related long non-coding RNAs prognostic risk score for clear cell renal cell carcinoma.BMC urology · 2022Article
- The association between several autophagy-related genes and their prognostic values in hepatocellular carcinoma: a study on the foundation of TCGA, GEPIA and HPA databases.Molecular biology reports · 2022Article
- Leukotriene B4 receptor 2 correlates with prognosis and immune infiltration in clear cell renal cell carcinoma.Investigational new drugs · 2022Article
- Overexpression of TP53INP2 Promotes Apoptosis in Clear Cell Renal Cell Cancer via Caspase-8/TRAF6 Signaling Pathway.Journal of immunology research · 2022Article
- An Aging and Senescence-Related Gene Signature for Prognosis Prediction in Clear Cell Renal Cell Carcinoma.Frontiers in genetics · 2022Article
- Identification of autophagy-related long non-coding RNA prognostic and immune signature for clear cell renal cell carcinoma.Translational andrology and urology · 2021Article
- Identification of autophagy-related long non-coding RNA prognostic signature for breast cancer.Journal of cellular and molecular medicine · 2021Article
- Construction and validation of an autophagy-related long noncoding RNA signature for prognosis prediction in kidney renal clear cell carcinoma patients.Cancer medicine · 2021Article
- Systematic profiling of diagnostic and prognostic value of autophagy-related genes for sarcoma patients.BMC cancer · 2021Article
- Identification of Autophagy-Related Prognostic Signature and Analysis of Immune Cell Infiltration in Low-Grade Gliomas.BioMed research international · 2021Article
- A Novel Autophagy-Related lncRNA Gene Signature to Improve the Prognosis of Patients with Melanoma.BioMed research international · 2021Article
- Pathogenic Single Nucleotide Polymorphisms on Autophagy-Related Genes.International journal of molecular sciences · 2020Review
- IGFLR1 as a Novel Prognostic Biomarker in Clear Cell Renal Cell Cancer Correlating With Immune Infiltrates.Frontiers in molecular biosciences · 2020Article
- A novel immune cell signature for predicting glioblastoma after radiotherapy prognosis and guiding therapy.International journal of immunopathology and pharmacologyArticle
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abnormal autophagy is closely related to the development of cancer. Many studies have demonstrated that autophagy plays an important role in biological function in clear cell renal cell carcinoma (ccRCC). This study aimed to construct a prognostic signature for ccRCC based on autophagy-related genes (ARGs) to predict the prognosis of ccRCC. Differentially expressed ARGs were obtained from ccRCC RNA-seq data in The Cancer Genome Atlas (TCGA) database. ARGs were enriched by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The prognostic ARGs used to construct the risk score models for overall survival (OS) and disease-free survival (DFS) were identified by Cox regression analyses. According to the median value of the risk score, patients were divided into a high-risk group and a low-risk group. The OS and DFS were analyzed by the Kaplan-Meier method. The predictive accuracy was determined by a receiver operating characteristic (ROC) curve analysis. Additionally, we performed stratification analyses based on different clinical variables and evaluated the correlation between the risk score and the clinical variables. The differentially expressed ARGs were mainly enriched in the platinum drug resistance pathway. The prognostic signatures based on 11 ARGs for OS and 5 ARGs for DFS were constructed and showed that the survive time was significantly shorter in the high-risk group than in the low-risk group (
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