乳腺癌的免疫相关预后标志物的鉴定

Identification of a novel immune-related prognostic signature of breast cancer

目的探讨乳腺癌预后的免疫生物学标志物并构建风险评估模型。方法从癌症基因组图谱(the cancer genome map,TCGA)数据库中检索乳腺癌样本基因表达,同时从ImmPort数据库中检索与免疫相关的基因(immune related genes,IRGs);使用Cox比例风险回归和最小绝对收缩和选择算子(least absolute shrinkage and selection operator,LASSO)模型进行预后分析;使用基因集富集分析(gene set enrichment analysis,GSEA)以探索生物信号通路。使用ESTIMATE和CIBERSORT算法探索风险评分与肿瘤免疫微环境之间的关系。结果共鉴定出9个与乳腺癌预后独立相关的免疫相关差异表达基因,包括肾上腺素受体β1(ADRB1)、白介素12B(IL12B)、多配体蛋白聚糖-1(SDC1)、胸腺基质淋巴细胞生成素(TSLP)、成纤维细胞生长因子19(FGF19)、脂肪酸结合蛋白7(FABP7)、干扰素ε(IFNE)、肿瘤坏死因子受体超家族成员18(TNFRSF18)和白介素27(IL27),根据这9个IRGs构建的多IRGs预后模型显示了一定的预后预测能力。高风险组患者的"神经营养素信号通路"以及"脂肪细胞因子信号途径"通路活跃,而低风险组患者的"白细胞跨内皮迁移""WNT信号通路""FcεRI信号通路""缬氨酸、亮氨酸和异亮氨酸生物合成"以及"蛋白质输出途径"通路显著活跃。多种肿瘤杀伤性免疫细胞在低风险组患者的肿瘤浸润性免疫细胞中显著富集,而免疫抑制型免疫细胞在高风险组患者的肿瘤浸润性免疫细胞中显著富集。结论免疫相关基因预后生物标志物是乳腺癌治疗中一种有效的潜在预测预后指标。

Objective To explore the immune biomarkers for prognosis of breast cancer and to construct a risk assessment model. Methods The gene expression of breast cancer samples was retrieved from The Cancer Genome Map(TCGA) database and immune related genes(IRGs) were retrieved from the ImmPort database. Cox proportional hazards regression and least absolute shrinkage and selection operator(LASSO) regression were used for prognostic analysis. Gene set enrichment analysis( GSEA) was used to explore biological signaling pathways. ESTIMATE and CIBERSORT algorithms were used to explore the relationship between risk score and tumor immune microenvironment. Results Nine kinds of immune-related differentially expressed genes independently related to prognosis were identified:adrenoceptor beta 1(ADRB1), interleukin 12 B(IL12 B), syndecan 1(SDC1), thymic stromal lymphopoietin(TSLP),fibroblast growth factor 19(FGF19), fatty acid binding protein 7(FABP7), interferon epsilon(IFNE), tumor necrosis factor receptor superfamily member 18(TNFRSF18) and interleukin 27(IL27). The risk assessment equation constructed by these nine kinds of genes had powerful predictive ability. The “neurotrophin signaling pathway” and“adipocyte factor signaling pathway” were activated in patients of high-risk group, and “leukocyte transendothelial migration” “WNT signaling pathway” “FcεRI signaling pathway” “valine, leucine and isoleucine biosynthesis” and“protein export pathway” were activated in patients of low-risk group. A variety of tumor-killing immune cells were significantly enriched in the tumor-infiltrating immune cells of patients in the low-risk group. The immunosuppressive immune cells were significantly enriched in tumor infiltrating immune cells of patients in high-risk group. Conclusion IRGs prognostic signatures are an effective potential predictive classifier in breast cancer treatment.