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Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer
Yichao Wang1, Qianyi Zhong1, Zhaoyun Li1
1Department of Clinical Laboratory Medicine, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, 318000, People's Republic of China.
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.
Insights
Cyclin A2 (CCNA2) is a potential biomarker for breast cancer immunotherapy. Its elevated expression in metastatic breast cancer suggests its role in predicting treatment response and patient survival.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Breast cancer remains a leading cause of cancer-related deaths in women.
- Immunosuppressive therapies are emerging for cancer treatment.
- Effective biomarkers for breast cancer immunotherapy are lacking.
Purpose of the Study:
- To identify novel immune-related biomarkers for breast cancer immunotherapy.
- To explore the role of gene expression in breast cancer prognosis and treatment.
Main Methods:
- Weighted gene co-expression network analysis (WGCNA) on TCGA breast cancer data.
- Identification and functional enrichment analysis of hub genes.
- Validation using GSE15852 dataset and immunohistochemistry for CCNA2.
Main Results:
- Six modules associated with immune cell infiltration were identified.
- CCNA2 was identified as a hub gene, negatively correlated with overall survival.
- CCNA2 expression was significantly higher in metastatic breast cancer and tumor tissues.
Conclusions:
- CCNA2 is a potential immune therapy marker for breast cancer.
- Further research is warranted to validate CCNA2's role in immunotherapy.
- CCNA2 may serve as a prognostic biomarker in breast cancer.
