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Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data
OBJECTIVE: The purpose of this study was to explore the composition of tumor-infiltrating immune cells (TIIC) and prognostic significance of tumor-infiltrating mast cells (TIMC) in adrenocortical carcinoma (ACC). METHODS: The gene expression profiles of ACC were downloaded from the Cancer Genome Atl...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7458645/ https://www.ncbi.nlm.nih.gov/pubmed/32923148 http://dx.doi.org/10.1080/2162402X.2020.1784529 |
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author | Tian, Xi Xu, Wenhao Wang, Yuchen Anwaier, Aihetaimujiang Wang, Hongkai Wan, Fangning Zhu, Yu Cao, Dalong Shi, Guohai Zhu, Yiping Qu, Yuanyuan Zhang, Hailiang Ye, Dingwei |
author_facet | Tian, Xi Xu, Wenhao Wang, Yuchen Anwaier, Aihetaimujiang Wang, Hongkai Wan, Fangning Zhu, Yu Cao, Dalong Shi, Guohai Zhu, Yiping Qu, Yuanyuan Zhang, Hailiang Ye, Dingwei |
author_sort | Tian, Xi |
collection | PubMed |
description | OBJECTIVE: The purpose of this study was to explore the composition of tumor-infiltrating immune cells (TIIC) and prognostic significance of tumor-infiltrating mast cells (TIMC) in adrenocortical carcinoma (ACC). METHODS: The gene expression profiles of ACC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GSE90713, GSE12368). The abundance of TIICs in ACC samples was calculated by CIBERSORT algorithm and immunohistochemistry was used to identify mast cells of 39 tumor samples from Fudan University Shanghai Cancer Center (FUSCC). Differentially expressed genes (DEGs) were analyzed by LIMMA package using R software. Survival analysis was analyzed by Kaplan-Meier method and Cox regression models. RESULTS: The abundance of mast cells (p = .008) was positively correlated with ACC patients’ outcome in TCGA cohort and was also positively correlated with both overall survival (p < .05) and progression-free survival (p < .05) in FUSCC cohort. Different TIMC infiltrations showed significant changes in signaling pathways including DNA replication, nuclear chromosome segregation, and meiotic cell cycle process of ACC. In addition, elevated expression of eight hub genes (KIF18A, CDCA8, SKA1, CEP55, BUB1, CDK1, SGOL1, SGOL2) related to the abundance of TIMC in ACC was significantly correlated with the poor prognosis of the patients. CONCLUSION: In conclusion, higher TIMC infiltration was positively correlated with ACC patients’ outcome in both TCGA and FUSCC cohort. Lower TIMC infiltration and elevated expression of hub genes (KIF18A, CDCA8, SKA1, CEP55, BUB1, CDK1, SGOL1, SGOL2) are markedly correlated with aggressive progression and poor prognosis, which might shed lights on novel targets for treatment strategies. |
format | Online Article Text |
id | pubmed-7458645 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-74586452020-09-11 Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data Tian, Xi Xu, Wenhao Wang, Yuchen Anwaier, Aihetaimujiang Wang, Hongkai Wan, Fangning Zhu, Yu Cao, Dalong Shi, Guohai Zhu, Yiping Qu, Yuanyuan Zhang, Hailiang Ye, Dingwei Oncoimmunology Original Research OBJECTIVE: The purpose of this study was to explore the composition of tumor-infiltrating immune cells (TIIC) and prognostic significance of tumor-infiltrating mast cells (TIMC) in adrenocortical carcinoma (ACC). METHODS: The gene expression profiles of ACC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GSE90713, GSE12368). The abundance of TIICs in ACC samples was calculated by CIBERSORT algorithm and immunohistochemistry was used to identify mast cells of 39 tumor samples from Fudan University Shanghai Cancer Center (FUSCC). Differentially expressed genes (DEGs) were analyzed by LIMMA package using R software. Survival analysis was analyzed by Kaplan-Meier method and Cox regression models. RESULTS: The abundance of mast cells (p = .008) was positively correlated with ACC patients’ outcome in TCGA cohort and was also positively correlated with both overall survival (p < .05) and progression-free survival (p < .05) in FUSCC cohort. Different TIMC infiltrations showed significant changes in signaling pathways including DNA replication, nuclear chromosome segregation, and meiotic cell cycle process of ACC. In addition, elevated expression of eight hub genes (KIF18A, CDCA8, SKA1, CEP55, BUB1, CDK1, SGOL1, SGOL2) related to the abundance of TIMC in ACC was significantly correlated with the poor prognosis of the patients. CONCLUSION: In conclusion, higher TIMC infiltration was positively correlated with ACC patients’ outcome in both TCGA and FUSCC cohort. Lower TIMC infiltration and elevated expression of hub genes (KIF18A, CDCA8, SKA1, CEP55, BUB1, CDK1, SGOL1, SGOL2) are markedly correlated with aggressive progression and poor prognosis, which might shed lights on novel targets for treatment strategies. Taylor & Francis 2020-06-23 /pmc/articles/PMC7458645/ /pubmed/32923148 http://dx.doi.org/10.1080/2162402X.2020.1784529 Text en © 2020 The Author(s). Published with license by Taylor & Francis Group, LLC. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Tian, Xi Xu, Wenhao Wang, Yuchen Anwaier, Aihetaimujiang Wang, Hongkai Wan, Fangning Zhu, Yu Cao, Dalong Shi, Guohai Zhu, Yiping Qu, Yuanyuan Zhang, Hailiang Ye, Dingwei Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data |
title | Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data |
title_full | Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data |
title_fullStr | Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data |
title_full_unstemmed | Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data |
title_short | Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data |
title_sort | identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7458645/ https://www.ncbi.nlm.nih.gov/pubmed/32923148 http://dx.doi.org/10.1080/2162402X.2020.1784529 |
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