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TTN mutations predict a poor prognosis in patients with thyroid cancer
Objective: We aimed to investigate the relationship between titin (TTN) gene mutations and thyroid cancer (THCA) and to explore the feasibility of the TTN gene as a potential prognostic indicator of THCA. Methods: From TCGA-THCA cohort, we performed a series of analyses to evaluate the prognostic va...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310696/ https://www.ncbi.nlm.nih.gov/pubmed/35766333 http://dx.doi.org/10.1042/BSR20221168 |
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author | Han, Xiudan Chen, Jianrong Wang, Jiao Xu, Jixiong Liu, Ying |
author_facet | Han, Xiudan Chen, Jianrong Wang, Jiao Xu, Jixiong Liu, Ying |
author_sort | Han, Xiudan |
collection | PubMed |
description | Objective: We aimed to investigate the relationship between titin (TTN) gene mutations and thyroid cancer (THCA) and to explore the feasibility of the TTN gene as a potential prognostic indicator of THCA. Methods: From TCGA-THCA cohort, we performed a series of analyses to evaluate the prognostic value and potential mechanism of TTN in THCA. These patients were divided into the mutant-type (MUT) group and the wild-type (WT) group. Differentially expressed genes (DEGs) in the two groups were screened using the ‘DESeq2’ R package. Functional enrichment analysis was performed, and the protein–protein interaction (PPI) network, transcription factor (TF)-target interaction networks, and competitive endogenous RNA (ceRNA) regulatory networks were established for the DEGs. The TIMER database was applied for immune cell infiltration. Survival analysis and Cox regression analysis were used to analyze the potential prognostic value of the TTN gene. Results: Differential expression analysis showed that 409 genes were significantly up-regulated and 36 genes were down-regulated. Functional enrichment analysis revealed that TTN gene mutations played a potential role in the development of THCA. Analysis of the immune microenvironment indicated that TTN gene mutations were significantly associated with enrichment of M0 macrophages. Survival analysis showed that the MUT group predicted poorer prognosis than the WT group. Cox regression analysis demonstrated that TTN gene mutations were an independent risk factor for THCA. Nomograms also confirmed the prognostic values of the TTN gene in THCA. Conclusions In summary, our results demonstrated that TTN gene mutations predict poor prognosis in patients with THCA. This is the first study to research TTN gene mutations in THCA and to investigate their prognostic value in THCA. |
format | Online Article Text |
id | pubmed-9310696 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93106962022-08-04 TTN mutations predict a poor prognosis in patients with thyroid cancer Han, Xiudan Chen, Jianrong Wang, Jiao Xu, Jixiong Liu, Ying Biosci Rep Bioinformatics Objective: We aimed to investigate the relationship between titin (TTN) gene mutations and thyroid cancer (THCA) and to explore the feasibility of the TTN gene as a potential prognostic indicator of THCA. Methods: From TCGA-THCA cohort, we performed a series of analyses to evaluate the prognostic value and potential mechanism of TTN in THCA. These patients were divided into the mutant-type (MUT) group and the wild-type (WT) group. Differentially expressed genes (DEGs) in the two groups were screened using the ‘DESeq2’ R package. Functional enrichment analysis was performed, and the protein–protein interaction (PPI) network, transcription factor (TF)-target interaction networks, and competitive endogenous RNA (ceRNA) regulatory networks were established for the DEGs. The TIMER database was applied for immune cell infiltration. Survival analysis and Cox regression analysis were used to analyze the potential prognostic value of the TTN gene. Results: Differential expression analysis showed that 409 genes were significantly up-regulated and 36 genes were down-regulated. Functional enrichment analysis revealed that TTN gene mutations played a potential role in the development of THCA. Analysis of the immune microenvironment indicated that TTN gene mutations were significantly associated with enrichment of M0 macrophages. Survival analysis showed that the MUT group predicted poorer prognosis than the WT group. Cox regression analysis demonstrated that TTN gene mutations were an independent risk factor for THCA. Nomograms also confirmed the prognostic values of the TTN gene in THCA. Conclusions In summary, our results demonstrated that TTN gene mutations predict poor prognosis in patients with THCA. This is the first study to research TTN gene mutations in THCA and to investigate their prognostic value in THCA. Portland Press Ltd. 2022-07-22 /pmc/articles/PMC9310696/ /pubmed/35766333 http://dx.doi.org/10.1042/BSR20221168 Text en © 2022 The Author(s). https://creativecommons.org/licenses/by/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Bioinformatics Han, Xiudan Chen, Jianrong Wang, Jiao Xu, Jixiong Liu, Ying TTN mutations predict a poor prognosis in patients with thyroid cancer |
title | TTN mutations predict a poor prognosis in patients with thyroid cancer |
title_full | TTN mutations predict a poor prognosis in patients with thyroid cancer |
title_fullStr | TTN mutations predict a poor prognosis in patients with thyroid cancer |
title_full_unstemmed | TTN mutations predict a poor prognosis in patients with thyroid cancer |
title_short | TTN mutations predict a poor prognosis in patients with thyroid cancer |
title_sort | ttn mutations predict a poor prognosis in patients with thyroid cancer |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310696/ https://www.ncbi.nlm.nih.gov/pubmed/35766333 http://dx.doi.org/10.1042/BSR20221168 |
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