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An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach
Joint Authors
Zhang, Jun
Zhou, Xing
Zhao, Rong
Wang, Ziwei
Wang, Hongbo
Liu, Yan
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-15
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Endometrial cancer is one of the most common malignant tumors, lowering the quality of life among women worldwide.
Autophagy plays dual roles in these malignancies.
To search for prognostic markers for endometrial cancer, we mined The Cancer Genome Atlas and the Human Autophagy Database for information on endometrial cancer and autophagy-related genes and identified five autophagy-related long noncoding RNAs (lncRNAs) (LINC01871, SCARNA9, SOS1-IT1, AL161618.1, and FIRRE).
Based on these autophagy-related lncRNAs, samples were divided into high-risk and low-risk groups.
Survival analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group.
Univariate and multivariate independent prognostic analyses showed that patients’ age, pathological grade, and FIGO stage were all risk factors for poor prognosis.
A clinical correlation analysis of the relationship between the five autophagy-related lncRNAs and patients’ age, pathological grade, and FIGO stage was also per https://orcid.org/0000-0001-7090-1750 formed.
Histopathological assessment of the tumor microenvironment showed that the ESTIMATE, immune, and stromal scores in the high-risk group were lower than those in the low-risk group.
Principal component analysis and functional annotation were performed to confirm the correlations.
To further evaluate the effect of the model constructed on prognosis, samples were divided into training (60%) and validation (40%) groups, regarding the risk status as an independent prognostic risk factor.
A prognostic nomogram was constructed using patients’ age, pathological grade, FIGO stage, and risk status to estimate the patients’ survival rate.
C-index and multi-index ROC curves were generated to verify the stability and accuracy of the nomogram.
From this analysis, we concluded that the five lncRNAs identified in this study could affect the incidence and development of endometrial cancer by regulating the autophagy process.
Therefore, these molecules may have the potential to serve as novel therapeutic targets and biomarkers.
American Psychological Association (APA)
Wang, Ziwei& Zhang, Jun& Liu, Yan& Zhao, Rong& Zhou, Xing& Wang, Hongbo. 2020. An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach. BioMed Research International،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1134888
Modern Language Association (MLA)
Wang, Ziwei…[et al.]. An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach. BioMed Research International No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1134888
American Medical Association (AMA)
Wang, Ziwei& Zhang, Jun& Liu, Yan& Zhao, Rong& Zhou, Xing& Wang, Hongbo. An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1134888
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1134888