Liu Jingyi, Ling Yuwei, Su Ning, Li Yan, Tian Siyuan, Hou Bingxin, Luo Shanquan, Zhao Lina, Shi Mei
Department of Radiation Oncology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China.
Center for Thyroid and Breast Surgery, Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
Transl Cancer Res. 2022 Jan;11(1):181-192. doi: 10.21037/tcr-21-1455.
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.
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.
, and 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 , , and .
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.
三阴性乳腺癌（TNBC）是一种侵袭性很强的亚型，只有部分患者能从免疫治疗中获益。本研究旨在探讨免疫检查点基因（ICGs）在TNBC中的表达模式及预后价值，并开发一种新的ICGs特征来预测TNBC的预后和免疫状态。
从癌症基因组图谱（TCGA）和国际乳腺癌分子分类联盟（METABRIC）数据库中获取TNBC样本的ICGs表达谱和临床特征。采用最小绝对收缩和选择算子（LASSO）Cox回归分析构建预测预后结果的多基因特征。根据LASSO-Cox回归模型中每个ICG的系数计算风险评分。将中位数作为临界值，将TNBC患者分为高危组和低危组。绘制Kaplan-Meier生存曲线，进一步探讨风险评分与预后结果之间的关联。最后，进行单样本基因集富集分析（ssGSEA）以评估免疫状态，并使用免疫表型评分（IPS）对肿瘤免疫原性进行定量评估。
、 和 被纳入ICGs特征模型，并根据LASSO-Cox回归中的系数为每个样本计算风险评分。高危组患者的预后较差。受试者工作特征（ROC）曲线显示，ICGs特征预测1年、2年和3年总生存期（OS）的曲线下面积（AUC）值分别为0.925、0.822和0.835。低危组的适应性免疫细胞和固有免疫细胞明显丰富，低危患者的 、 、 和 的IPS评分往往更高。
开发并验证了一种新的ICGs特征，它不仅可以作为一个可靠的预后标志物，还可能是反映免疫治疗反应的潜在指标。
