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...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Xin, Li, Xingchen, Zhou, Jingyi, Wang, Jianliu
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