Cargando…
An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach
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 informat...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755467/ https://www.ncbi.nlm.nih.gov/pubmed/33381557 http://dx.doi.org/10.1155/2020/5717498 |
_version_ | 1783626354631114752 |
---|---|
author | Wang, Ziwei Zhang, Jun Liu, Yan Zhao, Rong Zhou, Xing Wang, Hongbo |
author_facet | Wang, Ziwei Zhang, Jun Liu, Yan Zhao, Rong Zhou, Xing Wang, Hongbo |
author_sort | Wang, Ziwei |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7755467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-77554672020-12-29 An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach Wang, Ziwei Zhang, Jun Liu, Yan Zhao, Rong Zhou, Xing Wang, Hongbo Biomed Res Int Research Article 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. Hindawi 2020-12-12 /pmc/articles/PMC7755467/ /pubmed/33381557 http://dx.doi.org/10.1155/2020/5717498 Text en Copyright © 2020 Ziwei Wang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article 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 |
title | An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach |
title_full | An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach |
title_fullStr | An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach |
title_full_unstemmed | An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach |
title_short | An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach |
title_sort | integrated autophagy-related long noncoding rna signature as a prognostic biomarker for human endometrial cancer: a bioinformatics-based approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755467/ https://www.ncbi.nlm.nih.gov/pubmed/33381557 http://dx.doi.org/10.1155/2020/5717498 |
work_keys_str_mv | AT wangziwei anintegratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT zhangjun anintegratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT liuyan anintegratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT zhaorong anintegratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT zhouxing anintegratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT wanghongbo anintegratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT wangziwei integratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT zhangjun integratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT liuyan integratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT zhaorong integratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT zhouxing integratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach AT wanghongbo integratedautophagyrelatedlongnoncodingrnasignatureasaprognosticbiomarkerforhumanendometrialcancerabioinformaticsbasedapproach |