Cargando…
Mechanical Stimulus-Related Risk Signature Plays a Key Role in the Prognostic Nomogram For Endometrial Cancer
BACKGROUND: Tumor biomechanics correlates with the progression and prognosis of endometrial carcinoma (EC). The objective of this study is to construct a risk model using the mechanical stimulus-related genes in EC. METHODS: We retrieved the transcriptome profiling and clinical data of EC from The C...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526889/ https://www.ncbi.nlm.nih.gov/pubmed/34692538 http://dx.doi.org/10.3389/fonc.2021.753910 |
_version_ | 1784585959973584896 |
---|---|
author | Xu, Xin Li, Xingchen Zhou, Jingyi Wang, Jianliu |
author_facet | Xu, Xin Li, Xingchen Zhou, Jingyi Wang, Jianliu |
author_sort | Xu, Xin |
collection | PubMed |
description | BACKGROUND: Tumor biomechanics correlates with the progression and prognosis of endometrial carcinoma (EC). The objective of this study is to construct a risk model using the mechanical stimulus-related genes in EC. METHODS: We retrieved the transcriptome profiling and clinical data of EC from The Cancer Genome Atlas (TCGA) and Molecular Signatures Database (MSigDB). Differentially expressed mechanical stimulus-related genes were extracted from the databases, and then the least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a risk model. A nomogram integrating the genes and the clinicopathological characteristics was established and validated using the Kaplan-Meier survival and receiver operating characteristic (ROC) curves to estimate the overall survival (OS) of EC patients. Protein profiling technology and immunofluorescence technique were performed to verify the connection between biomechanics and EC. RESULTS: In total, 79 mechanical stimulus-related genes were identified by analyzing the two databases. Based on the LASSO regression analysis, 7 genes were selected for the establishment of the risk model. This model showed a good performance in terms of the prognostic accuracy in high- and low-risk groups. The area under the ROC curves (AUC) of this model was 0.697, 0.712 and 0.723 for 3-, 5- and 7-year OS, respectively. Then, a nomogram integrating the genes of the risk model and clinical features was constructed. The nomogram could accurately predict the OS (AUC = 0.779, 0.812 and 0.806 for 3-, 5- and 7-year OS, respectively). The results of the protein profiling technology and immunofluorescence revealed the expression of cytoskeleton proteins to be correlated with the Matrigel stiffness degree. CONCLUSIONS: In summary, a risk model of 7 mechanical stimulus-related genes was identified in EC. A nomogram based on this risk model and combining the clinicopathological features to assess the overall survival of EC showed high practical value. |
format | Online Article Text |
id | pubmed-8526889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85268892021-10-21 Mechanical Stimulus-Related Risk Signature Plays a Key Role in the Prognostic Nomogram For Endometrial Cancer Xu, Xin Li, Xingchen Zhou, Jingyi Wang, Jianliu Front Oncol Oncology BACKGROUND: Tumor biomechanics correlates with the progression and prognosis of endometrial carcinoma (EC). The objective of this study is to construct a risk model using the mechanical stimulus-related genes in EC. METHODS: We retrieved the transcriptome profiling and clinical data of EC from The Cancer Genome Atlas (TCGA) and Molecular Signatures Database (MSigDB). Differentially expressed mechanical stimulus-related genes were extracted from the databases, and then the least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a risk model. A nomogram integrating the genes and the clinicopathological characteristics was established and validated using the Kaplan-Meier survival and receiver operating characteristic (ROC) curves to estimate the overall survival (OS) of EC patients. Protein profiling technology and immunofluorescence technique were performed to verify the connection between biomechanics and EC. RESULTS: In total, 79 mechanical stimulus-related genes were identified by analyzing the two databases. Based on the LASSO regression analysis, 7 genes were selected for the establishment of the risk model. This model showed a good performance in terms of the prognostic accuracy in high- and low-risk groups. The area under the ROC curves (AUC) of this model was 0.697, 0.712 and 0.723 for 3-, 5- and 7-year OS, respectively. Then, a nomogram integrating the genes of the risk model and clinical features was constructed. The nomogram could accurately predict the OS (AUC = 0.779, 0.812 and 0.806 for 3-, 5- and 7-year OS, respectively). The results of the protein profiling technology and immunofluorescence revealed the expression of cytoskeleton proteins to be correlated with the Matrigel stiffness degree. CONCLUSIONS: In summary, a risk model of 7 mechanical stimulus-related genes was identified in EC. A nomogram based on this risk model and combining the clinicopathological features to assess the overall survival of EC showed high practical value. Frontiers Media S.A. 2021-10-06 /pmc/articles/PMC8526889/ /pubmed/34692538 http://dx.doi.org/10.3389/fonc.2021.753910 Text en Copyright © 2021 Xu, Li, Zhou and Wang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Xu, Xin Li, Xingchen Zhou, Jingyi Wang, Jianliu Mechanical Stimulus-Related Risk Signature Plays a Key Role in the Prognostic Nomogram For Endometrial Cancer |
title | Mechanical Stimulus-Related Risk Signature Plays a Key Role in the Prognostic Nomogram For Endometrial Cancer |
title_full | Mechanical Stimulus-Related Risk Signature Plays a Key Role in the Prognostic Nomogram For Endometrial Cancer |
title_fullStr | Mechanical Stimulus-Related Risk Signature Plays a Key Role in the Prognostic Nomogram For Endometrial Cancer |
title_full_unstemmed | Mechanical Stimulus-Related Risk Signature Plays a Key Role in the Prognostic Nomogram For Endometrial Cancer |
title_short | Mechanical Stimulus-Related Risk Signature Plays a Key Role in the Prognostic Nomogram For Endometrial Cancer |
title_sort | mechanical stimulus-related risk signature plays a key role in the prognostic nomogram for endometrial cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526889/ https://www.ncbi.nlm.nih.gov/pubmed/34692538 http://dx.doi.org/10.3389/fonc.2021.753910 |
work_keys_str_mv | AT xuxin mechanicalstimulusrelatedrisksignatureplaysakeyroleintheprognosticnomogramforendometrialcancer AT lixingchen mechanicalstimulusrelatedrisksignatureplaysakeyroleintheprognosticnomogramforendometrialcancer AT zhoujingyi mechanicalstimulusrelatedrisksignatureplaysakeyroleintheprognosticnomogramforendometrialcancer AT wangjianliu mechanicalstimulusrelatedrisksignatureplaysakeyroleintheprognosticnomogramforendometrialcancer |