Stemness-related gene signatures as a predictive tool for breast cancer radiosensitivity
BackgroundUnderstanding the role of cancer stemness in predicting breast cancer (BRCA) response to radiotherapy is crucial for optimizing treatment outcomes. This study developed a stemness-based signature to identify BRCA patients who are likely to benefit from radiotherapy.MethodsGene expression d...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1536284/full |
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| author | Jinzhi Lai Rongfu Huang Jingshan Huang |
| author_facet | Jinzhi Lai Rongfu Huang Jingshan Huang |
| author_sort | Jinzhi Lai |
| collection | DOAJ |
| description | BackgroundUnderstanding the role of cancer stemness in predicting breast cancer (BRCA) response to radiotherapy is crucial for optimizing treatment outcomes. This study developed a stemness-based signature to identify BRCA patients who are likely to benefit from radiotherapy.MethodsGene expression data for BRCA patients were obtained from the TCGA and METABRIC databases, including 920 TCGA-BRCA and 1980 METABRIC-BRCA patients. Univariate and multivariate Cox regression analyses were used to construct a radiosensitivity signature. Immune cell infiltration and pathway enrichment analyses were conducted using ESTIMATE and GSVA methods. The TIDE algorithm and the pRRophetic platform were employed to predict responses to radiotherapy. Radioresistant BRCA cells were examined using a colony formation assay. Key genes identified in the radiosensitivity signature were validated in vitro by qRT-PCR.ResultsBy analyzing gene expression data from 920 BRCA samples, we identified a set of 267 stemness-related genes between high and low mRNAsi groups. Based on these genes, a radiosensitivity signature comprising two stemness-related genes (EMILIN1 and CYP4Z1) was constructed, stratifying patients into radiosensitive (RS) and radioresistant (RR) groups. Radiotherapy within the RS group significantly improved prognosis compared to non-radiotherapy patients. This signature was further validated in the METABRIC dataset. Notably, patients in the RS group also exhibited a significantly better response to immunotherapy compared to the RR group. We established a radioresistant BRCA cell line using the MCF-7 breast cancer cell line. A radioresistant breast cancer cell line (MCF-7/IR) was established by progressive exposure to increasing radiation doses. Comparative clonogenic and CCK8 assays demonstrated a radioresistant phenotype in the MCF-7/IR compared to MCF-7. In vitro studies utilizing both the MCF-7/IR and MCF-7 cell lines validated the expression of two radiosensitivity genes.ConclusionThis study identified a stemness-related gene signature predictive of radiosensitivity in breast cancer. This signature may guide personalized treatment strategies and inform the development of novel radiosensitizing agents. |
| format | Article |
| id | doaj-art-8f51c2ee970d41c8bf04eceeda3c95ce |
| institution | Kabale University |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Immunology |
| spelling | doaj-art-8f51c2ee970d41c8bf04eceeda3c95ce2025-01-31T06:40:19ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-01-011610.3389/fimmu.2025.15362841536284Stemness-related gene signatures as a predictive tool for breast cancer radiosensitivityJinzhi Lai0Rongfu Huang1Jingshan Huang2Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, ChinaDepartment of Clinical Laboratory, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, ChinaDepartment of General Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, ChinaBackgroundUnderstanding the role of cancer stemness in predicting breast cancer (BRCA) response to radiotherapy is crucial for optimizing treatment outcomes. This study developed a stemness-based signature to identify BRCA patients who are likely to benefit from radiotherapy.MethodsGene expression data for BRCA patients were obtained from the TCGA and METABRIC databases, including 920 TCGA-BRCA and 1980 METABRIC-BRCA patients. Univariate and multivariate Cox regression analyses were used to construct a radiosensitivity signature. Immune cell infiltration and pathway enrichment analyses were conducted using ESTIMATE and GSVA methods. The TIDE algorithm and the pRRophetic platform were employed to predict responses to radiotherapy. Radioresistant BRCA cells were examined using a colony formation assay. Key genes identified in the radiosensitivity signature were validated in vitro by qRT-PCR.ResultsBy analyzing gene expression data from 920 BRCA samples, we identified a set of 267 stemness-related genes between high and low mRNAsi groups. Based on these genes, a radiosensitivity signature comprising two stemness-related genes (EMILIN1 and CYP4Z1) was constructed, stratifying patients into radiosensitive (RS) and radioresistant (RR) groups. Radiotherapy within the RS group significantly improved prognosis compared to non-radiotherapy patients. This signature was further validated in the METABRIC dataset. Notably, patients in the RS group also exhibited a significantly better response to immunotherapy compared to the RR group. We established a radioresistant BRCA cell line using the MCF-7 breast cancer cell line. A radioresistant breast cancer cell line (MCF-7/IR) was established by progressive exposure to increasing radiation doses. Comparative clonogenic and CCK8 assays demonstrated a radioresistant phenotype in the MCF-7/IR compared to MCF-7. In vitro studies utilizing both the MCF-7/IR and MCF-7 cell lines validated the expression of two radiosensitivity genes.ConclusionThis study identified a stemness-related gene signature predictive of radiosensitivity in breast cancer. This signature may guide personalized treatment strategies and inform the development of novel radiosensitizing agents.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1536284/fullbreast cancercancer stemnessradiosensitivityPD-L1tumor immune microenvironment |
| spellingShingle | Jinzhi Lai Rongfu Huang Jingshan Huang Stemness-related gene signatures as a predictive tool for breast cancer radiosensitivity Frontiers in Immunology breast cancer cancer stemness radiosensitivity PD-L1 tumor immune microenvironment |
| title | Stemness-related gene signatures as a predictive tool for breast cancer radiosensitivity |
| title_full | Stemness-related gene signatures as a predictive tool for breast cancer radiosensitivity |
| title_fullStr | Stemness-related gene signatures as a predictive tool for breast cancer radiosensitivity |
| title_full_unstemmed | Stemness-related gene signatures as a predictive tool for breast cancer radiosensitivity |
| title_short | Stemness-related gene signatures as a predictive tool for breast cancer radiosensitivity |
| title_sort | stemness related gene signatures as a predictive tool for breast cancer radiosensitivity |
| topic | breast cancer cancer stemness radiosensitivity PD-L1 tumor immune microenvironment |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1536284/full |
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