Wang Xiaowei, Su Wenjia, Tang Dabei, Jing Jing, Xiong Jing, Deng Yuwei, Liu Huili, Ma Wenjie, Liu Zhaoliang, Zhang Qingyuan
Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin 150081, China.
Department of Hematology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, China.
Cancers (Basel). 2021 Oct 25;13(21):5342. doi: 10.3390/cancers13215342.
Tumor-immune cell compositions and immune checkpoints comprehensively affect TNBC outcomes. With the significantly improved survival rate of TNBC patients treated with ICI therapies, a biomarker integrating multiple aspects of TIME may have prognostic value for improving the efficacy of ICI therapy. Immune-related hub genes were identified with weighted gene co-expression network analysis and differential gene expression assay using The Cancer Genome Atlas TNBC data set ( = 115). IRGPI was constructed with Cox regression analysis. Immune cell compositions and TIL status were analyzed with CIBERSORT and TIDE. The discovery was validated with the Molecular Taxonomy of Breast Cancer International Consortium data set ( = 196) and a patient cohort from our hospital. Tumor expression or serum concentrations of CCL5, CCL25, or PD-L1 were determined with immunohistochemistry or ELISA. The constructed IRGPI was composed of CCL5 and CCL25 genes and was negatively associated with the patient's survival. IRGPI also predicts the compositions of M0 and M2 macrophages, memory B cells, CD8 T cells, activated memory CD4 T cells, and the exclusion and dysfunction of TILs, as well as PD-1 and PD-L1 expression of TNBC. IRGPI is a promising biomarker for predicting the prognosis and multiple immune characteristics of TNBC.
肿瘤免疫细胞组成和免疫检查点全面影响三阴性乳腺癌(TNBC)的预后。随着接受免疫检查点抑制剂(ICI)治疗的TNBC患者生存率显著提高,整合肿瘤免疫微环境(TIME)多个方面的生物标志物可能对提高ICI治疗疗效具有预后价值。使用癌症基因组图谱TNBC数据集(n = 115),通过加权基因共表达网络分析和差异基因表达分析鉴定免疫相关枢纽基因。通过Cox回归分析构建免疫相关基因预后指数(IRGPI)。使用CIBERSORT和TIDE分析免疫细胞组成和肿瘤浸润淋巴细胞(TIL)状态。该发现通过国际乳腺癌分子分类联盟数据集(n = 196)和我院的患者队列进行验证。通过免疫组织化学或酶联免疫吸附测定(ELISA)测定CCL5、CCL25或程序性死亡受体配体1(PD-L1)的肿瘤表达或血清浓度。构建的IRGPI由CCL5和CCL25基因组成,与患者生存率呈负相关。IRGPI还可预测M0和M2巨噬细胞、记忆B细胞、CD8 T细胞、活化记忆CD4 T细胞的组成,以及TIL的排除和功能障碍,以及TNBC的程序性死亡受体1(PD-1)和PD-L1表达。IRGPI是预测TNBC预后和多种免疫特征的有前景的生物标志物。