A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer

Jingyi Liu; Yuwei Ling; Ning Su; Yan Li; Siyuan Tian; Bingxin Hou; Shanquan Luo; Lina Zhao; Mei Shi

doi:10.21037/tcr-21-1455

A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer

Transl Cancer Res. 2022 Jan;11(1):181-192. doi: 10.21037/tcr-21-1455.

Authors

Jingyi Liu^#¹, Yuwei Ling^#², Ning Su¹, Yan Li¹, Siyuan Tian³, Bingxin Hou¹, Shanquan Luo¹, Lina Zhao¹, Mei Shi¹

Affiliations

¹ Department of Radiation Oncology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China.
² Center for Thyroid and Breast Surgery, Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
³ State Key Laboratory of Cancer Biology, Xijing Hospital of Digestive Diseases, The Fourth Military Medical University, Xi'an, China.

^# Contributed equally.

Abstract

Background: Triple-negative breast cancer (TNBC) is a highly aggressive subtype and only some of patients could benefit from the immunotherapy. The present study aims to investigate the expression pattern and prognostic value of immune checkpoint genes (ICGs) in TNBC and develop a novel ICGs-signature to predict the prognosis and immune status in TNBC.

Methods: ICGs expression profiles and clinical characteristics of TNBC samples were obtained from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was employed to construct a multi-gene signature for predicting the prognostic outcome. The risk scores were calculated based on the coefficients of each ICG in LASSO-Cox regression model. The median score was considered as the cut-off value to divide the TNBC patients into a high-risk group and a low-risk group. The Kaplan-Meier survival curves were generated to further explore the association between the risk scores and prognostic outcomes. Finally, single sample gene set enrichment analysis (ssGSEA) was conducted to evaluate the immune status and immunophenoscore (IPS) score was used for the quantitative evaluation of tumor immunogenicity.

Results: PDCD1, PDCD1LG2 and KIR3DL2 were included in the ICGs-signature model and the risk scores were calculated for each sample according to the coefficients in LASSO-Cox regression. Patients in high-risk group were associated with unfavorable prognosis. The receiver operating characteristic (ROC) curves showed the area under the curve (AUC) values for predicting 1-, 2- and 3-year overall survival (OS) by ICGs-signature were 0.925,0.822 and 0.835, respectively. The adaptive immunity cells and innate immunity cells were significantly abundant in the low-risk group, and low-risk patients tended to have higher IPS scores of PD-1, CTLA4, PD-L1 and PD-L2.

Conclusions: A novel ICGs-signature was developed and validated, which may be not only served as a robust prognostic marker, but also a potential indicator reflecting immunotherapy response.

Keywords: Immune checkpoint-related genes (ICRGs); immune status; immunotherapy; overall survival (OS); triple-negative breast cancer (TNBC).