Identification and development of an independent immune-related genes prognostic model for breast cancer

BMC Cancer

Rong Deng¹  Lin Chen¹  Jianing Lu²  Yuhan Zhang²  Yuxiang Dong²  Junyi Wang³  Chen Chen³  Yun Yu⁴  Yitong Pan⁵  Ping Liu⁶ 

[1] Department of General Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, 210009, Nanjing, China;First Clinical Medical College of Nanjing Medical University, 210029, Nanjing, China;Nanjing Medical University, 211116, Nanjing, China;Nanjing Medical University, 211116, Nanjing, China;Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, 211116, Nanjing, China;Nanjing Medical University, 211116, Nanjing, China;University of Chinese Academy of Sciences, 100101, Beijing, China;Nanjing University of Chinese Medicine, 210029, Nanjing, China;

关键词: Breast cancer;    Immune genes;    Prognosis;    Risk scores model;    Nomogram;   

DOI  :  10.1186/s12885-021-08041-x

来源: Springer

【 摘 要 】

BackgroundBreast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index.MethodsThe list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant.ResultsIn total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways.ConclusionIn conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.

【 授权许可】

CC BY