Open Access

ARTICLE

PD-1 Relevant Genes Predict the Prognosis of Breast Cancer and Their Prediction Effect in Tumor Response to Immunotherapy

Yu Xiao^1,2,#, Jianping Jiang^3,#, Yan Chen^1,4, Yi Huang¹, Changyuan Wei^1,*

1 Guangxi Medical University Cancer Hospital, Nanning, China
2 Department of Thyroid and Breast Surgery, Shenzhen Second People’s Hospital, Shenzhen, China
3 Department of Thyroid and Breast Surgery, Shaoyang Center Hospital, Shaoyang, China
4 Department of Thyroid and Breast Surgery, Liuzhou People’s Hospital, Liuzhou, China

* Corresponding Author: Changyuan Wei. Email:
# Yu Xiao, Jianping Jiang contributed equally to this work

(This article belongs to the Special Issue: Biomarkers for Breast Cancer Diagnosis and Treatment Selection: from Basic Research to Practice)

Oncologie 2022, 24(4), 729-742. https://doi.org/10.32604/oncologie.2022.026118

Received 16 August 2022; Accepted 07 September 2022; Issue published 31 December 2022

Abstract

Background: Immunotherapy is becoming a powerful approach in the treatment of breast cancer. However, high response rates in the majority of breast cancer patients have yet to be achieved. Materials and Methods: Based on public data sources, we identified 22 genes that are correlated with PD-1 expression as well as differentially expressed between tumor tissues and normal tissues, and high expression of all the key genes was correlated with a superior survival outcome. Using the least absolute shrinkage and selection operator Cox regression model, a risk score was constructed. Results: A multivariate Cox analysis showed that the constructed risk score was an independent prognostic factor (AUC of risk score: 0.63, HR of risk score: 11.7, C-index: 0.69). Furthermore, an analysis of TILs in the TCGA BRCA cohort identified 28 distinct immune cell types. T lymphocytes and myeloid-derived suppressor cells were enriched in low-risk patients. The risk score was positively correlated with immune checkpoint genes for PD-1, PD-L1, PD-L2, and CTLA4 (P < 0.05). In addition, two independent cohorts validated the prognostic value and the predictive value of the immunotherapy response of the risk score. Conclusions: The risk score demonstrated a stable predictive ability in breast cancer prognosis and a predictive value in tumor response to immunotherapy. The analysis of TILs revealed the correlation between risk score and immune cells, which also helps elucidate the complexity of the relationship between TILs and immunotherapy response.

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Keywords

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Supplementary Material

Supplementary Material File

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