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Weighted gene co-expression network analysis identifies a novel immune-related gene signature and nomogram to predict the survival and immune infiltration status of breast cancer

JUNXIA LIU1, KE PANG2, FEI HE2,*

1 Department of Oncology, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
2 Department of Geriatrics, Yongchuan Hospital of Chongqing Medical University, Chongqing, China

* Corresponding Author: FEI HE. Email: email

(This article belongs to the Special Issue: Decoding Gene (including circRNA, lincRNA miRNA and mRNA) Expression)

BIOCELL 2022, 46(7), 1661-1673. https://doi.org/10.32604/biocell.2022.018023

Abstract

Breast cancer is one of the most common cancers in the world and seriously threatens the health of women worldwide. Prognostic models based on immune-related genes help to improve the prognosis prediction and clinical treatment of breast cancer patients. In the study, we used weighted gene co-expression network analysis to construct a co-expression network to screen out highly prognostic immune-related genes. Subsequently, the prognostic immune-related gene signature was successfully constructed from highly immune-related genes through COX regression and LASSO COX analysis. Survival analysis and time receiver operating characteristic curves indicate that the prognostic signature has strong predictive performance. And we developed a nomogram by combing the risk score with multiple clinical characteristics. CIBERSORT and TIMER algorithms confirmed that there are significant differences in tumor-infiltrating immune cells in different risk groups. In addition, gene set enrichment analysis shows 6 pathways that differ between high- and low-risk group. The immune-related gene signature effectively predicts the survival and immune infiltration of breast cancer patients and is expected to provide more effective immunotherapy targets for the prognosis prediction of breast cancer.

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APA Style
LIU, J., PANG, K., HE, F. (2022). Weighted gene co-expression network analysis identifies a novel immune-related gene signature and nomogram to predict the survival and immune infiltration status of breast cancer. BIOCELL, 46(7), 1661-1673. https://doi.org/10.32604/biocell.2022.018023
Vancouver Style
LIU J, PANG K, HE F. Weighted gene co-expression network analysis identifies a novel immune-related gene signature and nomogram to predict the survival and immune infiltration status of breast cancer. BIOCELL . 2022;46(7):1661-1673 https://doi.org/10.32604/biocell.2022.018023
IEEE Style
J. LIU, K. PANG, and F. HE "Weighted gene co-expression network analysis identifies a novel immune-related gene signature and nomogram to predict the survival and immune infiltration status of breast cancer," BIOCELL , vol. 46, no. 7, pp. 1661-1673. 2022. https://doi.org/10.32604/biocell.2022.018023



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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