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Identification of an integrated kinase-related prognostic gene signature associated with tumor immune microenvironment in human uterine corpus endometrial carcinoma
In the worldwide, uterine corpus endometrial carcinoma (UCEC) is the sixth most common malignancy in women, and the number of women diagnosed is increasing. Kinase plays an important role in the occurrence and development of malignant tumors. However, the research about kinase in endometrial cancer...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491090/ https://www.ncbi.nlm.nih.gov/pubmed/36158685 http://dx.doi.org/10.3389/fonc.2022.944000 |
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author | Wei, Sitian Zhang, Jun Shi, Rui Yu, Zhicheng Chen, Xingwei Wang, Hongbo |
author_facet | Wei, Sitian Zhang, Jun Shi, Rui Yu, Zhicheng Chen, Xingwei Wang, Hongbo |
author_sort | Wei, Sitian |
collection | PubMed |
description | In the worldwide, uterine corpus endometrial carcinoma (UCEC) is the sixth most common malignancy in women, and the number of women diagnosed is increasing. Kinase plays an important role in the occurrence and development of malignant tumors. However, the research about kinase in endometrial cancer is still unclear. Here, we first downloaded the gene expression data of 552 UCEC patients and 23 healthy endometrial tissues from The Cancer Genome Atlas (TCGA), obtained 538 kinase-related genes from the previous literature, and calculated 67 differentially expressed kinases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were referenced to identify multiple important biological functions and signaling pathways related to 67 differentially expressed kinases. Using univariate Cox regression and Least absolute shrinkage and selection operator (LASSO), seven kinases (ALPK2, CAMKV, TTK, PTK6, MAST1, CIT, and FAM198B) were identified to establish a prognostic model of endometrial cancer. Then, patients were divided into high- and low-risk groups based on risk scores. Receiver operating characteristic (ROC) curves were plotted to evaluate that the model had a favorable predictive ability. Kaplan–Meier survival analysis suggested that high-risk groups experienced worse overall survival than low-risk groups. qRT-PCR and ISH assays confirmed the consistency between predicted candidate genes and real sample contents. CIBERSORT algorithm and ssGSEA were adopted to investigate the relationship between this signature and tumor immune microenvironment, and revealed that in low- and high-risk groups, the types of tumor-infiltrating immune cells and the immune cell-related functions were significantly different. In summary, a seven-gene signature risk model has been constructed, and could accurately predict the prognosis of UCEC, which may offer ideas and breakthrough points to the kinase-associated development of UCEC. |
format | Online Article Text |
id | pubmed-9491090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94910902022-09-22 Identification of an integrated kinase-related prognostic gene signature associated with tumor immune microenvironment in human uterine corpus endometrial carcinoma Wei, Sitian Zhang, Jun Shi, Rui Yu, Zhicheng Chen, Xingwei Wang, Hongbo Front Oncol Oncology In the worldwide, uterine corpus endometrial carcinoma (UCEC) is the sixth most common malignancy in women, and the number of women diagnosed is increasing. Kinase plays an important role in the occurrence and development of malignant tumors. However, the research about kinase in endometrial cancer is still unclear. Here, we first downloaded the gene expression data of 552 UCEC patients and 23 healthy endometrial tissues from The Cancer Genome Atlas (TCGA), obtained 538 kinase-related genes from the previous literature, and calculated 67 differentially expressed kinases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were referenced to identify multiple important biological functions and signaling pathways related to 67 differentially expressed kinases. Using univariate Cox regression and Least absolute shrinkage and selection operator (LASSO), seven kinases (ALPK2, CAMKV, TTK, PTK6, MAST1, CIT, and FAM198B) were identified to establish a prognostic model of endometrial cancer. Then, patients were divided into high- and low-risk groups based on risk scores. Receiver operating characteristic (ROC) curves were plotted to evaluate that the model had a favorable predictive ability. Kaplan–Meier survival analysis suggested that high-risk groups experienced worse overall survival than low-risk groups. qRT-PCR and ISH assays confirmed the consistency between predicted candidate genes and real sample contents. CIBERSORT algorithm and ssGSEA were adopted to investigate the relationship between this signature and tumor immune microenvironment, and revealed that in low- and high-risk groups, the types of tumor-infiltrating immune cells and the immune cell-related functions were significantly different. In summary, a seven-gene signature risk model has been constructed, and could accurately predict the prognosis of UCEC, which may offer ideas and breakthrough points to the kinase-associated development of UCEC. Frontiers Media S.A. 2022-09-07 /pmc/articles/PMC9491090/ /pubmed/36158685 http://dx.doi.org/10.3389/fonc.2022.944000 Text en Copyright © 2022 Wei, Zhang, Shi, Yu, Chen 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 Wei, Sitian Zhang, Jun Shi, Rui Yu, Zhicheng Chen, Xingwei Wang, Hongbo Identification of an integrated kinase-related prognostic gene signature associated with tumor immune microenvironment in human uterine corpus endometrial carcinoma |
title | Identification of an integrated kinase-related prognostic gene signature associated with tumor immune microenvironment in human uterine corpus endometrial carcinoma |
title_full | Identification of an integrated kinase-related prognostic gene signature associated with tumor immune microenvironment in human uterine corpus endometrial carcinoma |
title_fullStr | Identification of an integrated kinase-related prognostic gene signature associated with tumor immune microenvironment in human uterine corpus endometrial carcinoma |
title_full_unstemmed | Identification of an integrated kinase-related prognostic gene signature associated with tumor immune microenvironment in human uterine corpus endometrial carcinoma |
title_short | Identification of an integrated kinase-related prognostic gene signature associated with tumor immune microenvironment in human uterine corpus endometrial carcinoma |
title_sort | identification of an integrated kinase-related prognostic gene signature associated with tumor immune microenvironment in human uterine corpus endometrial carcinoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491090/ https://www.ncbi.nlm.nih.gov/pubmed/36158685 http://dx.doi.org/10.3389/fonc.2022.944000 |
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