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Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer
INTRODUCTION: Breast cancer is the main reason for cancer-related deaths in women and the most common malignant cancer among women. In recent years, immunosuppressive factors have become a new type of treatment for cancer. However, there are no effective biomarkers for breast cancer immunotherapy. T...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043851/ https://www.ncbi.nlm.nih.gov/pubmed/33859479 http://dx.doi.org/10.2147/OTT.S296373 |
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author | Wang, Yichao Zhong, Qianyi Li, Zhaoyun Lin, Zhu Chen, Hanjun Wang, Pan |
author_facet | Wang, Yichao Zhong, Qianyi Li, Zhaoyun Lin, Zhu Chen, Hanjun Wang, Pan |
author_sort | Wang, Yichao |
collection | PubMed |
description | INTRODUCTION: Breast cancer is the main reason for cancer-related deaths in women and the most common malignant cancer among women. In recent years, immunosuppressive factors have become a new type of treatment for cancer. However, there are no effective biomarkers for breast cancer immunotherapy. Therefore, exploring immune-related biomarkers is presently an important topic in breast cancer. METHODS: Gene expression profile data of breast cancer from The Cancer Genome Atlas (TCGA) was downloaded. Scale-free gene co-expression networks were built with weighted gene co-expression network analysis. The correlation of genes was performed with Pearson’s correlation values. The potential associations between clinical features and gene sets were studied, and the hub genes were screened out. Gene Ontology and gene set enrichment analysis were used to reveal the function of hub gene in breast cancer. The gene expression profiles of GSE15852, downloaded from the Gene Expression Omnibus database, were used for hub gene verification. In addition, candidate biomarkers expression in breast cancer was studied. Survival analysis was performed using Log rank test and Kaplan–Meier. Immunohistochemistry was used to analyze the expression of CCNA2. RESULTS: A total of 6 modules related to immune cell infiltration were identified via the average linkage hierarchical clustering. According to the threshold criteria (module membership >0.9 and gene significance >0.35), a significant module consisting of 13 genes associated with immune cells infiltration were identified as candidate hub genes after performed with the human protein interaction network. And 3 genes with high correlation to clinical traits were identified as hub genes, which were negatively associated with the overall survival. Among them, the expression of CCNA2 was increased in metastatic breast cancer compare with non-metastatic breast cancer, who underwent immunotherapy. Immunohistochemistry results showed that CCNA2 expression in carcinoma tissues was elevated compared with normal control. DISCUSSION: CCNA2 identified as a potential immune therapy marker in breast cancer, which were first reported here and deserved further research. |
format | Online Article Text |
id | pubmed-8043851 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-80438512021-04-14 Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer Wang, Yichao Zhong, Qianyi Li, Zhaoyun Lin, Zhu Chen, Hanjun Wang, Pan Onco Targets Ther Original Research INTRODUCTION: Breast cancer is the main reason for cancer-related deaths in women and the most common malignant cancer among women. In recent years, immunosuppressive factors have become a new type of treatment for cancer. However, there are no effective biomarkers for breast cancer immunotherapy. Therefore, exploring immune-related biomarkers is presently an important topic in breast cancer. METHODS: Gene expression profile data of breast cancer from The Cancer Genome Atlas (TCGA) was downloaded. Scale-free gene co-expression networks were built with weighted gene co-expression network analysis. The correlation of genes was performed with Pearson’s correlation values. The potential associations between clinical features and gene sets were studied, and the hub genes were screened out. Gene Ontology and gene set enrichment analysis were used to reveal the function of hub gene in breast cancer. The gene expression profiles of GSE15852, downloaded from the Gene Expression Omnibus database, were used for hub gene verification. In addition, candidate biomarkers expression in breast cancer was studied. Survival analysis was performed using Log rank test and Kaplan–Meier. Immunohistochemistry was used to analyze the expression of CCNA2. RESULTS: A total of 6 modules related to immune cell infiltration were identified via the average linkage hierarchical clustering. According to the threshold criteria (module membership >0.9 and gene significance >0.35), a significant module consisting of 13 genes associated with immune cells infiltration were identified as candidate hub genes after performed with the human protein interaction network. And 3 genes with high correlation to clinical traits were identified as hub genes, which were negatively associated with the overall survival. Among them, the expression of CCNA2 was increased in metastatic breast cancer compare with non-metastatic breast cancer, who underwent immunotherapy. Immunohistochemistry results showed that CCNA2 expression in carcinoma tissues was elevated compared with normal control. DISCUSSION: CCNA2 identified as a potential immune therapy marker in breast cancer, which were first reported here and deserved further research. Dove 2021-04-09 /pmc/articles/PMC8043851/ /pubmed/33859479 http://dx.doi.org/10.2147/OTT.S296373 Text en © 2021 Wang et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Wang, Yichao Zhong, Qianyi Li, Zhaoyun Lin, Zhu Chen, Hanjun Wang, Pan Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer |
title | Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer |
title_full | Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer |
title_fullStr | Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer |
title_full_unstemmed | Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer |
title_short | Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer |
title_sort | integrated profiling identifies ccna2 as a potential biomarker of immunotherapy in breast cancer |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043851/ https://www.ncbi.nlm.nih.gov/pubmed/33859479 http://dx.doi.org/10.2147/OTT.S296373 |
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