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• W4233992078 abstract "Abstract Objective Increasing evidence has indicated an association between immune micro-environment in breast cancer and clinical outcomes. The aim of this research is to comprehensively investigate the effect of tumor immune genes on the prognosis of breast cancer patients. Methods 2498 immune genes were downloaded from ImmPort database. Additionally, we identified and downloaded the transcriptome data of patients with breast cancer from the TCGA database through the R package, as well as relevant clinical information. Survival R package was applied in survival analyses for hub-genes. Cox regression analysis was used to analyze the effect of immune genes on the prognosis of breast cancer. Immune risk scoring model was constructed based on the statistical correlation between hub immune genes and survival. Meanwhile, multivariate cox regression analysis was utilized to investigate whether the immune genes risk score model was an independent factor for predicting the prognosis of breast cancer. Nomogram was constructed to comprehensively predict the survival rate of breast cancer. P < 0.05 was considered to be statistically significant. Results The results of the difference analysis showed that 556 immune genes exhibited differential expression between normal and breast cancer tissues (p < 0. 05). Univariate cox regression analysis revealed 66 immune genes statistically correlated with breast cancer related survival risk, of which 30 were associated with overall survival (P < 0.05). In addition, a 15-genes based immune genes risk scoring model was constructed through lasso COX regression analysis. KM curve indicated that patients in high-risk were associated with poor outcomes (p < 0.001). ROC curve indicated that the immune risk score model was reliable in predicting survival risk (5-year OS, AUC = 0.752). Our model showed satisfying AUC and survival correlation in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Furthermore, multivariate cox regression analysis confirmed that the immune risk score model was an independent factor for predicting the prognosis of breast cancer. A nomogram was established to comprehensively predict the survival of breast cancer patients with the results of multivariate cox regression analysis. Finally, we found that 15 immune genes and risk scores were significantly associated with clinical factors and prognosis, and were involved in multiple oncogenic pathways. Conclusion Collectively, tumor immune genes played an essential role in the prognosis of breast cancer. Furthermore, immune risk score was an independent predictive factor of breast cancer, indicating a poor survival." @default.
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• W4233992078 date "2020-07-30" @default.
• W4233992078 modified "2023-09-23" @default.
• W4233992078 title "Identification of an independent immune-genes prognostic index for breast cancer" @default.
• W4233992078 doi "https://doi.org/10.21203/rs.3.rs-41670/v1" @default.
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