ArticleCell cycle (Georgetown, Tex.)2022
Expression status and prognostic value of autophagy-related lncRNAs in prostate cancer.
Article in Cell cycle (Georgetown, Tex.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Utilizing Liquid-liquid phase separation-related lncRNAs to predict the prognosis and treatment response of PCa.Discover oncology · 2024Article
- Autophagy-related long non-coding RNAs act as prognostic biomarkers and associate with tumor microenvironment in prostate cancer.American journal of cancer research · 2024Article
- Construction of lncRNA prognostic model related to cuproptosis in esophageal carcinoma.Frontiers in genetics · 2023Article
- Correlations between serum levels of microRNA-148a-3p and microRNA-485-5p and the progression and recurrence of prostate cancer.BMC urology · 2022Article
- Mutator-Derived lncRNA Landscape: A Novel Insight Into the Genomic Instability of Prostate Cancer.Frontiers in oncology · 2022Article
- SLC25A25-AS1 over-expression could be predicted the dismal prognosis and was related to the immune microenvironment in prostate cancer.Frontiers in oncology · 2022Article
- Prognostic significance of lncRNA AP004608.1 in prostate cancer.Frontiers in oncology · 2022Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
LncRNAs involve in the autophagy to regulate prostate cancer (PCA) initiation and progression. Therefore, it urges to explore more significant AR-lncRNAs in PCa. mRNA data and clinical information of PCa were achieved from TCGA database, and ARGs were obtained from the HADb. AR-lncRNAs were identified by correlation analysis of DE ARGs and lncRNAs. Univariate Cox regression, LASSO regression, and multivariate Cox regression were used to identify the prognostic AR-lncRNA signature and constructed a risk model. GESA was used to biological function analysis between high- and low-risk score group. A nomogram was constructed and used to predicate the survival of PCa patients. A calibration curve was used to determine the accuracy of the predication model. AR-related ceRNA network was constructed by correlation analysis. Expression of six AR-related lncRNAs were detected by qRT-PCR. 222 ARGs and 385 AR-lncRNAs were screened from PCa and normal tissues, and 17 AR-lncRNAs were identified as prognostic signature for PCa. Based on the expression of prognostic signature, a risk score was calculated, and PCa samples were distributed into high- and low-risk score groups. The biological function and predicated value of the prognostic signature were also examined. Finally, based on the correlation between each ARG and its prognostic signature, three modules of AR-lncRNA-miRNA-mRNA regulatory networks were constructed based on 6 AR-lncRNAs, 17 miRNAs, and 12 ARGs. And we found that AC012085.2, UBXN10-AS1, LINC00261 downregulated, whereas AP004608.1, AC104667.2, AC008610.1 upregulated in PCa compared with BPH tissues. Our finding supplied the potential AR-lncRNAs prognostic signature for PCa.
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