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YTHDF3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration

PURPOSE: Thyroid cancer (TC) is one of the most common endocrine malignancies, and its morbidity continues to rise. N(6)-methyladenosine (m(6)A) RNA methylation, an epigenetic modification, is an important regulator of gene expression in TC. Therefore, it’s worth finding the characteristics and pred...

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Autores principales: Zhang, Yihan, Chen, Ying, Chen, Ruihua, Zhou, Hong, Lin, Yi, Li, Bingxin, Song, Huaidong, Zhou, Guoqiang, Dong, Mei, Xu, Huanbai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507848/
https://www.ncbi.nlm.nih.gov/pubmed/37726690
http://dx.doi.org/10.1186/s12885-023-11361-9
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author Zhang, Yihan
Chen, Ying
Chen, Ruihua
Zhou, Hong
Lin, Yi
Li, Bingxin
Song, Huaidong
Zhou, Guoqiang
Dong, Mei
Xu, Huanbai
author_facet Zhang, Yihan
Chen, Ying
Chen, Ruihua
Zhou, Hong
Lin, Yi
Li, Bingxin
Song, Huaidong
Zhou, Guoqiang
Dong, Mei
Xu, Huanbai
author_sort Zhang, Yihan
collection PubMed
description PURPOSE: Thyroid cancer (TC) is one of the most common endocrine malignancies, and its morbidity continues to rise. N(6)-methyladenosine (m(6)A) RNA methylation, an epigenetic modification, is an important regulator of gene expression in TC. Therefore, it’s worth finding the characteristics and predictive value of the m(6)A RNA methylation regulators in thyroid cancer (TC). METHOD: RNA-seq data of TC was downloaded from the Cancer Genome Atlas (TCGA) database to screen out the differential expressed regulators. The absolute contraction selection operator (Lasso) Cox regression was used to construct the risk model of m(6)A methylation regulators. The predictive value of the risk scoring model was evaluated by Kaplan Meier (K-M) analysis and receiver operating characteristic (ROC) curves. The underlying mechanism of m(6)A methylation regulators in TC was predicted by gene set enrichment analysis (GSEA). Further validation was performed by using immunohistochemistry (IHC) and q-PCR. The correlation between risk-related gene and immune infiltration was evaluated by Tumour Immune Estimation Resource (TIMER). RESULTS: IGF2BP2, YTHDF1 and YTHDF3 were screened out as strong independent prognostic factors of TC. Then a risk score model was established to further screen the predictors. Finally, according to the results of overall survival (OS) and clinical characteristics of TC, YTHDF3 was screened out as a potential predictor. Meanwhile, IHC and qPCR confirmed that YTHDF3 was expressed differential in TC. The expression of YTHDF3 was positively associated with the infiltration level of CD4(+) T cells and macrophages. It was strongly correlated with a variety of immune markers in TC. CONCLUSION: We confirmed that YTHDF3 can be used as a potential prognostic biomarker of TC. It not only plays a decisive role in the initiation and development of TC, but also provides a new perspective for understanding the modification of m(6)A RNA in TC.
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spelling pubmed-105078482023-09-20 YTHDF3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration Zhang, Yihan Chen, Ying Chen, Ruihua Zhou, Hong Lin, Yi Li, Bingxin Song, Huaidong Zhou, Guoqiang Dong, Mei Xu, Huanbai BMC Cancer Research PURPOSE: Thyroid cancer (TC) is one of the most common endocrine malignancies, and its morbidity continues to rise. N(6)-methyladenosine (m(6)A) RNA methylation, an epigenetic modification, is an important regulator of gene expression in TC. Therefore, it’s worth finding the characteristics and predictive value of the m(6)A RNA methylation regulators in thyroid cancer (TC). METHOD: RNA-seq data of TC was downloaded from the Cancer Genome Atlas (TCGA) database to screen out the differential expressed regulators. The absolute contraction selection operator (Lasso) Cox regression was used to construct the risk model of m(6)A methylation regulators. The predictive value of the risk scoring model was evaluated by Kaplan Meier (K-M) analysis and receiver operating characteristic (ROC) curves. The underlying mechanism of m(6)A methylation regulators in TC was predicted by gene set enrichment analysis (GSEA). Further validation was performed by using immunohistochemistry (IHC) and q-PCR. The correlation between risk-related gene and immune infiltration was evaluated by Tumour Immune Estimation Resource (TIMER). RESULTS: IGF2BP2, YTHDF1 and YTHDF3 were screened out as strong independent prognostic factors of TC. Then a risk score model was established to further screen the predictors. Finally, according to the results of overall survival (OS) and clinical characteristics of TC, YTHDF3 was screened out as a potential predictor. Meanwhile, IHC and qPCR confirmed that YTHDF3 was expressed differential in TC. The expression of YTHDF3 was positively associated with the infiltration level of CD4(+) T cells and macrophages. It was strongly correlated with a variety of immune markers in TC. CONCLUSION: We confirmed that YTHDF3 can be used as a potential prognostic biomarker of TC. It not only plays a decisive role in the initiation and development of TC, but also provides a new perspective for understanding the modification of m(6)A RNA in TC. BioMed Central 2023-09-19 /pmc/articles/PMC10507848/ /pubmed/37726690 http://dx.doi.org/10.1186/s12885-023-11361-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhang, Yihan
Chen, Ying
Chen, Ruihua
Zhou, Hong
Lin, Yi
Li, Bingxin
Song, Huaidong
Zhou, Guoqiang
Dong, Mei
Xu, Huanbai
YTHDF3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration
title YTHDF3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration
title_full YTHDF3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration
title_fullStr YTHDF3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration
title_full_unstemmed YTHDF3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration
title_short YTHDF3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration
title_sort ythdf3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507848/
https://www.ncbi.nlm.nih.gov/pubmed/37726690
http://dx.doi.org/10.1186/s12885-023-11361-9
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