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Updated: Dec 3, 2025
Isolation and Functional Assessment of Human Breast Cancer Stem Cells from Cell and Tissue Samples
Published on: October 2, 2020
Assessing the prognostic value of stemness-related genes in breast cancer patients
Wen-Jie Wang1, Han Wang2, Meng-Sen Wang3
1Department of Radio-Oncology, The Affiliated Suzhou Hospital of Nanjing Medical University, 26 Daoqian Street, Suzhou, 215001, Jiangsu, People's Republic of China.
Abstract:
Breast cancer (BC) is currently one of the deadliest tumors worldwide. Cancer stem cells (CSCs) are a small group of tumor cells with self-renewal and differentiation abilities and high treatment resistance. One of the reasons for treatment failures is the inability to completely eliminate tumor stem cells. By using the edgeR package, we identified stemness-related differentially expressed genes in GSE69280. Via Lasso-penalized Cox regression analysis and univariate Cox regression analysis, survival genes were screened out to construct a prognostic model. Via nomograms and ROC curves, we verified the accuracy of the prognostic model. We selected 4 genes (PSMB9, CXCL13, NPR3, and CDKN2C) to establish a prognostic model from TCGA data and a validation model from GSE24450 data. We found that the low-risk score group had better OS than the high-risk score group, whether using TCGA or GSE24450 data. A prognostic model including four stemness-related genes was constructed in our study to determine targets of breast cancer stem cells (BCSCs) and improve the treatment effect.
Insights
This study identifies four stemness-related genes (PSMB9, CXCL13, NPR3, CDKN2C) crucial for breast cancer stem cells (BCSCs). A prognostic model using these genes predicts patient survival, offering new therapeutic targets.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Breast cancer (BC) remains a leading cause of cancer mortality globally.
- Cancer stem cells (CSCs) contribute to treatment resistance and tumor recurrence in BC.
- Eliminating CSCs is critical for effective breast cancer treatment.
Purpose of the Study:
- To identify stemness-related genes in breast cancer.
- To develop a prognostic model for breast cancer patients based on these genes.
- To explore potential therapeutic targets within breast cancer stem cells (BCSCs).
Main Methods:
- Differential gene expression analysis using the edgeR package on GSE69280 dataset.
- Prognostic model construction via Lasso-penalized and univariate Cox regression.
- Model validation using TCGA and GSE24450 datasets, employing nomograms and ROC curves.
Main Results:
- Identified stemness-related differentially expressed genes.
- Developed a prognostic model using four genes: PSMB9, CXCL13, NPR3, and CDKN2C.
- Validated the model's accuracy and found that a low-risk score correlated with better overall survival (OS) in both TCGA and GSE24450 datasets.
Conclusions:
- A novel prognostic model for breast cancer was established using four stemness-related genes.
- This model accurately predicts patient outcomes and can identify breast cancer stem cells (BCSCs).
- The identified genes represent potential therapeutic targets for improving breast cancer treatment efficacy.
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