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Lymph node metastasis-related gene signature shows good performance in predicting prognosis and immune infiltration in cervical cancer

AIMS: This study aimed to construct a lymph node metastasis-related gene signature to predict prognosis and immune infiltration in patients with cervical cancer. METHODS: Clinical and RNA sequencing data of 193 patients with cervical cancer, which were divided into lymph node metastasis (N1) and non...

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Autores principales: Guo, Yilin, Wang, Lu, Xu, Zhen, Li, Mengqi, Wang, Wuliang, Bai, Yangyang, Xu, Xingyue, Li, Rui, Zhao, Hu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10325684/
https://www.ncbi.nlm.nih.gov/pubmed/37427104
http://dx.doi.org/10.3389/fonc.2023.1190251
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author Guo, Yilin
Wang, Lu
Xu, Zhen
Li, Mengqi
Wang, Wuliang
Bai, Yangyang
Xu, Xingyue
Li, Rui
Zhao, Hu
author_facet Guo, Yilin
Wang, Lu
Xu, Zhen
Li, Mengqi
Wang, Wuliang
Bai, Yangyang
Xu, Xingyue
Li, Rui
Zhao, Hu
author_sort Guo, Yilin
collection PubMed
description AIMS: This study aimed to construct a lymph node metastasis-related gene signature to predict prognosis and immune infiltration in patients with cervical cancer. METHODS: Clinical and RNA sequencing data of 193 patients with cervical cancer, which were divided into lymph node metastasis (N1) and non-lymph node metastasis (N0) groups, were acquired from TCGA. Differentially expressed genes (DEGs) between the N1 and N0 groups were detected, and protein-protein interaction combined with LASSO analysis was conducted to further screen lymph node metastasis-related genes. Univariate and multivariate Cox regression analyses were performed to establish a predictive signature. The genetic features, potential biological behavior, and immune infiltration characteristics of the predictive signature were explored. Furthermore, the sensitivity of patients to chemotherapy drugs was estimated based on the predictive signature and the expression of TEKT2 and RPGR was investigated in the cervical cancer tissue samples. RESULTS: A total of 271 lymph node metastasis-related DEGs, including 100 upregulated and 171 downregulated genes, were identified. Two genes, TEKT2 and RPGR, were associated with lymph node metastasis and prognosis in cervical cancer, and were used to construct a lymph node metastasis-related predictive signature. Based on the predictive signature, patients with cervical cancer were divided into high- and low-risk groups. The high-risk group, characterized by a higher tumor mutation burden and somatic mutation rate, indicated a poor overall survival. The activation of immune infiltration and increased expression of checkpoint genes were observed in the high-risk group, indicating that they might benefit from immunotherapy. Cytarabine, FH535, and procaspase-activating compound-1 were estimated as reasonable chemotherapy options for patients in the high-risk group, whereas two taxanes and five tyrosine kinase inhibitors, including etoposide and vinorelbine, had therapeutic significance for patients in the low-risk group. The expression of TEKT2 and RPGR was significantly downregulated in cervical cancer tissues, especially in metastatic lymph node tissues. DISCUSSION: The lymph node metastasis-related predictive signature based on TEKT2 and RPGR showed good performance in predicting the survival outcomes of patients with cervical cancer. The risk score of the predictive signature was related to genetic variation and immune infiltration, which could guide immunotherapy and chemotherapy strategies.
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spelling pubmed-103256842023-07-07 Lymph node metastasis-related gene signature shows good performance in predicting prognosis and immune infiltration in cervical cancer Guo, Yilin Wang, Lu Xu, Zhen Li, Mengqi Wang, Wuliang Bai, Yangyang Xu, Xingyue Li, Rui Zhao, Hu Front Oncol Oncology AIMS: This study aimed to construct a lymph node metastasis-related gene signature to predict prognosis and immune infiltration in patients with cervical cancer. METHODS: Clinical and RNA sequencing data of 193 patients with cervical cancer, which were divided into lymph node metastasis (N1) and non-lymph node metastasis (N0) groups, were acquired from TCGA. Differentially expressed genes (DEGs) between the N1 and N0 groups were detected, and protein-protein interaction combined with LASSO analysis was conducted to further screen lymph node metastasis-related genes. Univariate and multivariate Cox regression analyses were performed to establish a predictive signature. The genetic features, potential biological behavior, and immune infiltration characteristics of the predictive signature were explored. Furthermore, the sensitivity of patients to chemotherapy drugs was estimated based on the predictive signature and the expression of TEKT2 and RPGR was investigated in the cervical cancer tissue samples. RESULTS: A total of 271 lymph node metastasis-related DEGs, including 100 upregulated and 171 downregulated genes, were identified. Two genes, TEKT2 and RPGR, were associated with lymph node metastasis and prognosis in cervical cancer, and were used to construct a lymph node metastasis-related predictive signature. Based on the predictive signature, patients with cervical cancer were divided into high- and low-risk groups. The high-risk group, characterized by a higher tumor mutation burden and somatic mutation rate, indicated a poor overall survival. The activation of immune infiltration and increased expression of checkpoint genes were observed in the high-risk group, indicating that they might benefit from immunotherapy. Cytarabine, FH535, and procaspase-activating compound-1 were estimated as reasonable chemotherapy options for patients in the high-risk group, whereas two taxanes and five tyrosine kinase inhibitors, including etoposide and vinorelbine, had therapeutic significance for patients in the low-risk group. The expression of TEKT2 and RPGR was significantly downregulated in cervical cancer tissues, especially in metastatic lymph node tissues. DISCUSSION: The lymph node metastasis-related predictive signature based on TEKT2 and RPGR showed good performance in predicting the survival outcomes of patients with cervical cancer. The risk score of the predictive signature was related to genetic variation and immune infiltration, which could guide immunotherapy and chemotherapy strategies. Frontiers Media S.A. 2023-06-22 /pmc/articles/PMC10325684/ /pubmed/37427104 http://dx.doi.org/10.3389/fonc.2023.1190251 Text en Copyright © 2023 Guo, Wang, Xu, Li, Wang, Bai, Xu, Li and Zhao 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
Guo, Yilin
Wang, Lu
Xu, Zhen
Li, Mengqi
Wang, Wuliang
Bai, Yangyang
Xu, Xingyue
Li, Rui
Zhao, Hu
Lymph node metastasis-related gene signature shows good performance in predicting prognosis and immune infiltration in cervical cancer
title Lymph node metastasis-related gene signature shows good performance in predicting prognosis and immune infiltration in cervical cancer
title_full Lymph node metastasis-related gene signature shows good performance in predicting prognosis and immune infiltration in cervical cancer
title_fullStr Lymph node metastasis-related gene signature shows good performance in predicting prognosis and immune infiltration in cervical cancer
title_full_unstemmed Lymph node metastasis-related gene signature shows good performance in predicting prognosis and immune infiltration in cervical cancer
title_short Lymph node metastasis-related gene signature shows good performance in predicting prognosis and immune infiltration in cervical cancer
title_sort lymph node metastasis-related gene signature shows good performance in predicting prognosis and immune infiltration in cervical cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10325684/
https://www.ncbi.nlm.nih.gov/pubmed/37427104
http://dx.doi.org/10.3389/fonc.2023.1190251
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