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Identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation

OBJECTIVE: The current research aimed to development and validation in signature immune genes for lymphatic metastasis in papillary thyroid cancer (PTC). METHOD: Weighted correlation network analysis (WGCNA) was performed to identify genes closely correlated with lymphatic metastasis in PTC from TCG...

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Autores principales: Yu, Yang, Guo, Xing, Chai, Jian, Han, Zhuoyi, Ji, Yaming, Sun, Jirui, Zhang, Huiqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233024/
https://www.ncbi.nlm.nih.gov/pubmed/37274228
http://dx.doi.org/10.3389/fonc.2023.1181325
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author Yu, Yang
Guo, Xing
Chai, Jian
Han, Zhuoyi
Ji, Yaming
Sun, Jirui
Zhang, Huiqing
author_facet Yu, Yang
Guo, Xing
Chai, Jian
Han, Zhuoyi
Ji, Yaming
Sun, Jirui
Zhang, Huiqing
author_sort Yu, Yang
collection PubMed
description OBJECTIVE: The current research aimed to development and validation in signature immune genes for lymphatic metastasis in papillary thyroid cancer (PTC). METHOD: Weighted correlation network analysis (WGCNA) was performed to identify genes closely correlated with lymphatic metastasis in PTC from TCGA database. Information on immune-related genes (IRGs) was obtained from the ImmPort database. Crossover genes were used with the R package clusterProfiler for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment. Key genes in the protein–protein interaction network of cross-targets were obtained using Cytoscape. Lasso and Random Forest (RF) models were utilized to identify pivotal genes. We constructed a nomogram based on the hub genes. The correlation between hub genes and immune cell infiltration was explored. We collected and assessed clinical samples via immunohistochemistry to detect the expression of hub genes. RESULT: In total, 122 IRGs were correlated with lymphatic metastases from PTC. There are 10 key IRGs in the protein–protein interaction network. Then, three hub genes including PTGS2, MET, and ICAM1 were established using the LASSO and RF models. The expression of these hub genes was upregulated in samples collected from patients with lymphatic metastases. The average area under the curve of the model reached 0.83 after a 10-fold and 200-time cross-validation, which had a good prediction ability. Immuno-infiltration analysis showed that the three hub genes were significantly positively correlated with resting dendritic cells and were negatively correlated with activated natural cells, monocytes, and eosinophils. Immunohistochemistry results revealed that lymph node metastasis samples had a higher expression of the three hub genes than non-metastasis samples. CONCLUSION: Via bioinformatics analysis and experimental validation, MET and ICAM1 were found to be upregulated in lymph node metastasis from papillary thyroid carcinoma. Further, the two hub genes were closely correlated with activated natural killer cells, monocytes, resting dendritic cells, and eosinophils. Therefore, these two genes may be novel molecular biomarkers and therapeutic targets in lymph node metastasis from papillary thyroid carcinoma.
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spelling pubmed-102330242023-06-02 Identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation Yu, Yang Guo, Xing Chai, Jian Han, Zhuoyi Ji, Yaming Sun, Jirui Zhang, Huiqing Front Oncol Oncology OBJECTIVE: The current research aimed to development and validation in signature immune genes for lymphatic metastasis in papillary thyroid cancer (PTC). METHOD: Weighted correlation network analysis (WGCNA) was performed to identify genes closely correlated with lymphatic metastasis in PTC from TCGA database. Information on immune-related genes (IRGs) was obtained from the ImmPort database. Crossover genes were used with the R package clusterProfiler for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment. Key genes in the protein–protein interaction network of cross-targets were obtained using Cytoscape. Lasso and Random Forest (RF) models were utilized to identify pivotal genes. We constructed a nomogram based on the hub genes. The correlation between hub genes and immune cell infiltration was explored. We collected and assessed clinical samples via immunohistochemistry to detect the expression of hub genes. RESULT: In total, 122 IRGs were correlated with lymphatic metastases from PTC. There are 10 key IRGs in the protein–protein interaction network. Then, three hub genes including PTGS2, MET, and ICAM1 were established using the LASSO and RF models. The expression of these hub genes was upregulated in samples collected from patients with lymphatic metastases. The average area under the curve of the model reached 0.83 after a 10-fold and 200-time cross-validation, which had a good prediction ability. Immuno-infiltration analysis showed that the three hub genes were significantly positively correlated with resting dendritic cells and were negatively correlated with activated natural cells, monocytes, and eosinophils. Immunohistochemistry results revealed that lymph node metastasis samples had a higher expression of the three hub genes than non-metastasis samples. CONCLUSION: Via bioinformatics analysis and experimental validation, MET and ICAM1 were found to be upregulated in lymph node metastasis from papillary thyroid carcinoma. Further, the two hub genes were closely correlated with activated natural killer cells, monocytes, resting dendritic cells, and eosinophils. Therefore, these two genes may be novel molecular biomarkers and therapeutic targets in lymph node metastasis from papillary thyroid carcinoma. Frontiers Media S.A. 2023-05-18 /pmc/articles/PMC10233024/ /pubmed/37274228 http://dx.doi.org/10.3389/fonc.2023.1181325 Text en Copyright © 2023 Yu, Guo, Chai, Han, Ji, Sun and Zhang 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
Yu, Yang
Guo, Xing
Chai, Jian
Han, Zhuoyi
Ji, Yaming
Sun, Jirui
Zhang, Huiqing
Identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation
title Identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation
title_full Identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation
title_fullStr Identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation
title_full_unstemmed Identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation
title_short Identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation
title_sort identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233024/
https://www.ncbi.nlm.nih.gov/pubmed/37274228
http://dx.doi.org/10.3389/fonc.2023.1181325
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