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Reclassification of endometrial cancer and identification of key genes based on neural-related genes

Endometrial cancer (EC) is the most common gynecologic malignancy, and its incidence has been increasing every year. Nerve signaling is part of the tumor microenvironment and plays an active role in tumor progression and invasion. However, the relationship between the expression of neural-related ge...

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Autores principales: Chen, Fan, Qin, Tiansheng, Zhang, Yigan, Wei, Linzhen, Dang, Yamei, Liu, Peixia, Jin, Weilin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9537575/
https://www.ncbi.nlm.nih.gov/pubmed/36212450
http://dx.doi.org/10.3389/fonc.2022.951437
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author Chen, Fan
Qin, Tiansheng
Zhang, Yigan
Wei, Linzhen
Dang, Yamei
Liu, Peixia
Jin, Weilin
author_facet Chen, Fan
Qin, Tiansheng
Zhang, Yigan
Wei, Linzhen
Dang, Yamei
Liu, Peixia
Jin, Weilin
author_sort Chen, Fan
collection PubMed
description Endometrial cancer (EC) is the most common gynecologic malignancy, and its incidence has been increasing every year. Nerve signaling is part of the tumor microenvironment and plays an active role in tumor progression and invasion. However, the relationship between the expression of neural-related genes (NRGs) and prognosis in endometrial cancer remains unknown. In this study, we obtained RNA sequencing data of EC from The Cancer Genome Atlas (TCGA). Endometrial cancer was classified into two subtypes based on the expression of neural-associated genes (NRGs), with statistical differences in clinical stage, pathological grading, and prognosis. A prognostic prediction model was established by LASSO-Cox analysis, and the results showed that high expression of NRGs was associated with poor survival prognosis. Further, CHRM2, GRIN1, L1CAM, and SEMA4F were found to be significantly associated with clinical stage, immune infiltration, immune response, and important signaling pathways in endometrial cancer. The reclassification of endometrial cancer based on NRG expression would be beneficial for future clinical practice. The genes CHRM2, GRIN1, L1CAM, and SEMA4F might serve as potential biomarkers of EC prognosis.
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spelling pubmed-95375752022-10-08 Reclassification of endometrial cancer and identification of key genes based on neural-related genes Chen, Fan Qin, Tiansheng Zhang, Yigan Wei, Linzhen Dang, Yamei Liu, Peixia Jin, Weilin Front Oncol Oncology Endometrial cancer (EC) is the most common gynecologic malignancy, and its incidence has been increasing every year. Nerve signaling is part of the tumor microenvironment and plays an active role in tumor progression and invasion. However, the relationship between the expression of neural-related genes (NRGs) and prognosis in endometrial cancer remains unknown. In this study, we obtained RNA sequencing data of EC from The Cancer Genome Atlas (TCGA). Endometrial cancer was classified into two subtypes based on the expression of neural-associated genes (NRGs), with statistical differences in clinical stage, pathological grading, and prognosis. A prognostic prediction model was established by LASSO-Cox analysis, and the results showed that high expression of NRGs was associated with poor survival prognosis. Further, CHRM2, GRIN1, L1CAM, and SEMA4F were found to be significantly associated with clinical stage, immune infiltration, immune response, and important signaling pathways in endometrial cancer. The reclassification of endometrial cancer based on NRG expression would be beneficial for future clinical practice. The genes CHRM2, GRIN1, L1CAM, and SEMA4F might serve as potential biomarkers of EC prognosis. Frontiers Media S.A. 2022-09-23 /pmc/articles/PMC9537575/ /pubmed/36212450 http://dx.doi.org/10.3389/fonc.2022.951437 Text en Copyright © 2022 Chen, Qin, Zhang, Wei, Dang, Liu and Jin 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
Chen, Fan
Qin, Tiansheng
Zhang, Yigan
Wei, Linzhen
Dang, Yamei
Liu, Peixia
Jin, Weilin
Reclassification of endometrial cancer and identification of key genes based on neural-related genes
title Reclassification of endometrial cancer and identification of key genes based on neural-related genes
title_full Reclassification of endometrial cancer and identification of key genes based on neural-related genes
title_fullStr Reclassification of endometrial cancer and identification of key genes based on neural-related genes
title_full_unstemmed Reclassification of endometrial cancer and identification of key genes based on neural-related genes
title_short Reclassification of endometrial cancer and identification of key genes based on neural-related genes
title_sort reclassification of endometrial cancer and identification of key genes based on neural-related genes
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9537575/
https://www.ncbi.nlm.nih.gov/pubmed/36212450
http://dx.doi.org/10.3389/fonc.2022.951437
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