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.

Highlights

  • Breast cancer (BC) is currently one of the deadliest tumors worldwide

  • The differentially expressed genes (DEGs) were compared with The Cancer Genome Atlas (TCGA) and GSE24450 data to select coexpressed genes in the two databases

  • breast cancer stem cells (BCSCs) are a small group of tumor cells that have self-renewal capacity and play an important role in tumor formation, recurrence and m­ etastasis[19]

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Summary

Result

In the TCGA prognostic model, univariate Cox regression analyses (Fig. 5A) showed that older age (> 65) (hazard ratio [HR 1.532; 95% confidence interval [CI] = 1.117–2.047; P < 0.001), high American Joint Committee on Cancer (AJCC) stage (III-IV) (HR = 2.048; 95% CI = 1.603–2.616; P < 0.001), high tumor (T) stage (3–4) (HR = 1.379; 95% CI = 1.101–1.729; P = 0.005), lymph node metastasis (positive) (HR = 1.572; 95% CI = 1.300–1.900; P < 0.001), and high risk score (HR = 3.108; 95% CI = 2.049–4.715; P < 0.001) were significant risk factors for poor prognosis. The low-risk-score group had enrichment in the following KEGG pathways (Fig. 8): the cell cycle, apoptosis, chemokine, cytokine and JAK-STAT pathways

Discussion
Findings
Material and methods
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