A novel super-enhancer-related gene signature predicts prognosis and immune microenvironment for breast cancer
Abstract Background This study targeted at developing a robust, prognostic signature based on super-enhancer-related genes (SERGs) to reveal survival prognosis and immune microenvironment of breast cancer. Methods RNA-sequencing data of breast cancer were retrieved from The Cancer Genome Atlas (TCGA...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-08-01
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| Series: | BMC Cancer |
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| Online Access: | https://doi.org/10.1186/s12885-023-11241-2 |
| _version_ | 1797559121505943552 |
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| author | Qing Wu Xuan Tao Yang Luo Shiyao Zheng Nan Lin Xianhe Xie |
| author_facet | Qing Wu Xuan Tao Yang Luo Shiyao Zheng Nan Lin Xianhe Xie |
| author_sort | Qing Wu |
| collection | DOAJ |
| description | Abstract Background This study targeted at developing a robust, prognostic signature based on super-enhancer-related genes (SERGs) to reveal survival prognosis and immune microenvironment of breast cancer. Methods RNA-sequencing data of breast cancer were retrieved from The Cancer Genome Atlas (TCGA), 1069 patients of which were randomly assigned into training or testing set in 1:1 ratio. SERGs were downloaded from Super-Enhancer Database (SEdb). After which, a SERGs signature was established based on the training set, with its prognostic value further validated in the testing set. Subsequently, we identified the potential function enrichment and tumor immune infiltration of the model. Moreover, in vitro experiments were completed to further explore the biological functions of ZIC2 gene (one of the risk genes in the prognostic model) in breast cancer. Results A risk score system of prognostic value was constructed with 6 SERGs (ZIC2, NFE2, FOXJ1, KLF15, POU3F2 and SPIB) to find patients in high-risk group with significantly worse prognosis in both training and testing sets. In addition, a multivariate regression was established via integrating the 6 genes with age and N stage, indicating well performance by calibration, time-dependent receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Further analysis demonstrated that tumor-associated pathological processes and pathways were significantly enriched in the high-risk group. In general, the novel SERGs signature could be applied to screen breast cancer with immunosuppressive microenvironment for the risk score was negatively correlated with ESTIMATE score, tumor-infiltration lymphocytes (such as CD4 + and CD8 + T cell), immune checkpoints and chemotactic factors. Furthermore, down-regulation of ZIC2 gene expression inhibited the cell viability, cellular migration and cell cycle of breast cancer cells. Conclusions The novel SERGs signature could predict the prognosis of breast cancer; and SERGs might serve as potential therapeutic targets for breast cancer. |
| first_indexed | 2024-03-10T17:40:56Z |
| format | Article |
| id | doaj.art-8d80d1cd04e4442eb1dd85007df88488 |
| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-03-10T17:40:56Z |
| publishDate | 2023-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj.art-8d80d1cd04e4442eb1dd85007df884882023-11-20T09:43:01ZengBMCBMC Cancer1471-24072023-08-0123111810.1186/s12885-023-11241-2A novel super-enhancer-related gene signature predicts prognosis and immune microenvironment for breast cancerQing Wu0Xuan Tao1Yang Luo2Shiyao Zheng3Nan Lin4Xianhe Xie5Department of Oncology, Molecular Oncology Research Institute, The First Affiliated Hospital of Fujian Medical UniversityDepartment of Pathology, The First Affiliated Hospital of Fujian Medical UniversityDepartment of Oncology, Molecular Oncology Research Institute, The First Affiliated Hospital of Fujian Medical UniversityCollege of Clinical Medicine for Oncology, Fujian Medical UniversityFuzong Clinical Medical College of Fujian Medical UniversityDepartment of Oncology, Molecular Oncology Research Institute, The First Affiliated Hospital of Fujian Medical UniversityAbstract Background This study targeted at developing a robust, prognostic signature based on super-enhancer-related genes (SERGs) to reveal survival prognosis and immune microenvironment of breast cancer. Methods RNA-sequencing data of breast cancer were retrieved from The Cancer Genome Atlas (TCGA), 1069 patients of which were randomly assigned into training or testing set in 1:1 ratio. SERGs were downloaded from Super-Enhancer Database (SEdb). After which, a SERGs signature was established based on the training set, with its prognostic value further validated in the testing set. Subsequently, we identified the potential function enrichment and tumor immune infiltration of the model. Moreover, in vitro experiments were completed to further explore the biological functions of ZIC2 gene (one of the risk genes in the prognostic model) in breast cancer. Results A risk score system of prognostic value was constructed with 6 SERGs (ZIC2, NFE2, FOXJ1, KLF15, POU3F2 and SPIB) to find patients in high-risk group with significantly worse prognosis in both training and testing sets. In addition, a multivariate regression was established via integrating the 6 genes with age and N stage, indicating well performance by calibration, time-dependent receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Further analysis demonstrated that tumor-associated pathological processes and pathways were significantly enriched in the high-risk group. In general, the novel SERGs signature could be applied to screen breast cancer with immunosuppressive microenvironment for the risk score was negatively correlated with ESTIMATE score, tumor-infiltration lymphocytes (such as CD4 + and CD8 + T cell), immune checkpoints and chemotactic factors. Furthermore, down-regulation of ZIC2 gene expression inhibited the cell viability, cellular migration and cell cycle of breast cancer cells. Conclusions The novel SERGs signature could predict the prognosis of breast cancer; and SERGs might serve as potential therapeutic targets for breast cancer.https://doi.org/10.1186/s12885-023-11241-2Breast cancerSuper-enhancerOverall survivalTumor immune microenvironmentImmune checkpoints |
| spellingShingle | Qing Wu Xuan Tao Yang Luo Shiyao Zheng Nan Lin Xianhe Xie A novel super-enhancer-related gene signature predicts prognosis and immune microenvironment for breast cancer BMC Cancer Breast cancer Super-enhancer Overall survival Tumor immune microenvironment Immune checkpoints |
| title | A novel super-enhancer-related gene signature predicts prognosis and immune microenvironment for breast cancer |
| title_full | A novel super-enhancer-related gene signature predicts prognosis and immune microenvironment for breast cancer |
| title_fullStr | A novel super-enhancer-related gene signature predicts prognosis and immune microenvironment for breast cancer |
| title_full_unstemmed | A novel super-enhancer-related gene signature predicts prognosis and immune microenvironment for breast cancer |
| title_short | A novel super-enhancer-related gene signature predicts prognosis and immune microenvironment for breast cancer |
| title_sort | novel super enhancer related gene signature predicts prognosis and immune microenvironment for breast cancer |
| topic | Breast cancer Super-enhancer Overall survival Tumor immune microenvironment Immune checkpoints |
| url | https://doi.org/10.1186/s12885-023-11241-2 |
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