Liu Yajing, Ouyang Wenhao, Huang Hong, Tan Yujie, Zhang Zebang, Yu Yunfang, Yao Herui
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medical Oncology, Breast Tumor Center, Phase I Clinical Trial Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
School of Medicine, Guilin Medical College, Guilin, China.
Front Oncol. 2023 Jan 12;12:960579. doi: 10.3389/fonc.2022.960579. eCollection 2022.
Breast cancer has become the malignancy with the highest mortality rate in female patients worldwide. The limited efficacy of immunotherapy as a breast cancer treatment has fueled the development of research on the tumor immune microenvironment.
In this study, data on breast cancer patients were collected from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohorts. Differential gene expression analysis, univariate Cox regression analysis, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were performed to select overall survival (OS)-related, tumor tissue highly expressed, and immune- and inflammation-related genes. A tumor immune-inflammation signature (TIIS) consisting of 18 genes was finally screened out in the LASSO Cox regression model. Model performance was assessed by time-dependent receiver operating characteristic (ROC) curves. In addition, the CIBERSORT algorithm and abundant expression of immune checkpoints were utilized to clarify the correlation between the risk signature and immune landscape in breast cancer. Furthermore, the association of IL27 with the immune signature was analyzed in pan-cancer and the effect of IL27 on the migration of breast cancer cells was investigated since the regression coefficient of IL27 was the highest.
A TIIS based on 18 genes was constructed LASSO Cox regression analysis. In the TCGA-BRCA training cohort, 10-year AUC reached 0.89, and prediction performance of this signature was also validated in the METABRIC set. The high-risk group was significantly correlated with less infiltration of tumor-killing immune cells and the lower expression level of the immune checkpoint. Furthermore, we recommended some small-molecule drugs as novel targeted drugs for new breast cancer types. Finally, the relationship between IL27, a significant prognostic immune and inflammation cytokine, and immune status was analyzed in pan-cancer. Expression of IL27 was significantly correlated with immune regulatory gene expression and immune cell infiltration in pan-cancer. Furthermore, IL27 treatment improved breast cancer cell migration.
The TIIS represents a promising prognostic tool for estimating OS in patients with breast cancer and is correlated with immune status.
乳腺癌已成为全球女性患者中死亡率最高的恶性肿瘤。免疫疗法作为乳腺癌治疗方法的疗效有限，这推动了肿瘤免疫微环境研究的发展。
在本研究中，从癌症基因组图谱乳腺癌浸润性癌（TCGA-BRCA）和国际乳腺癌分子分类联盟（METABRIC）队列中收集乳腺癌患者的数据。进行差异基因表达分析、单变量Cox回归分析和最小绝对收缩和选择算子（LASSO）Cox回归分析，以选择与总生存期（OS）相关、肿瘤组织高表达以及免疫和炎症相关的基因。最终在LASSO Cox回归模型中筛选出由18个基因组成的肿瘤免疫炎症特征（TIIS）。通过时间依赖的受试者工作特征（ROC）曲线评估模型性能。此外，利用CIBERSORT算法和免疫检查点的丰富表达来阐明风险特征与乳腺癌免疫格局之间的相关性。此外，由于IL27的回归系数最高，因此在泛癌中分析了IL27与免疫特征的关联，并研究了IL27对乳腺癌细胞迁移的影响。
通过LASSO Cox回归分析构建了基于18个基因的TIIS。在TCGA-BRCA训练队列中，10年AUC达到0.89，该特征的预测性能也在METABRIC数据集得到验证。高危组与杀伤肿瘤免疫细胞浸润较少和免疫检查点表达水平较低显著相关。此外，我们推荐了一些小分子药物作为新型乳腺癌类型的靶向药物。最后，在泛癌中分析了重要的预后免疫和炎症细胞因子IL27与免疫状态之间的关系。IL27的表达与泛癌中的免疫调节基因表达和免疫细胞浸润显著相关。此外，IL27治疗可改善乳腺癌细胞迁移。
TIIS是一种有前景的预后工具，可用于估计乳腺癌患者的OS，并与免疫状态相关。
