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基于肿瘤浸润免疫细胞的模型预测睾丸生殖细胞肿瘤患者的复发率。

A model based on tumor-infiltrating immune cells for predicting the relapse rates of patients with testicular germ cell tumors.

机构信息

Department of Urology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.

Department of Gynecology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.

出版信息

Int Immunopharmacol. 2020 Sep;86:106710. doi: 10.1016/j.intimp.2020.106710. Epub 2020 Jul 8.

Abstract

OBJECTIVE

The activities of tumor-infiltrating immune cells (TIICs) play an important role in the outcomes of many types of cancers. Here, we sought to describe the landscape of TIICs in testicular germ cell tumors (TGCT) and to develop a prognostic model based on this information.

METHODS

The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to determine the proportions of 22 types of TIICs in a TGCT dataset (n = 74). Univariate and multivariate Cox regression analysis were used to develop an immune risk score (IRS) based on the association between TIICs and disease-free survival (DFS). The predictive accuracy of the IRS was evaluated using receiver operating characteristic curves, and the predictive accuracy of a prognostic nomogram was assessed using C-index and calibration curves. The biological functions of IRS-associated genes were evaluated by gene set enrichment analysis.

RESULTS

The relative abundances of three TIICs (plasma cells, M2 macrophages, and resting mast cells) were significantly associated with DFS in TGCT patients. In receiver operating characteristic curve analysis, the resulting IRS had areas under the curve of 0.70, 0.793, and 0.827, for predicting 1-, 2-, and 3-year DFS, respectively. Kaplan-Meier analysis confirmed that DFS was shorter for patients with high IRS compared with low IRS. IRS was an independent predictor of disease recurrence (hazard ratio 1.306, 95% confidence interval 1.022-1.668; P = 0.033). The C-index for the nomogram was 0.733. Genes involved in cancer-associated and immunity-associated pathways were enriched in TGCT samples from patients in the high- and low-risk groups, respectively, and expression of four immune checkpoint regulators was significantly lower in the high IRS group compared with the low IRS group.

CONCLUSIONS

A TIIC-based IRS may have utility as a complementary tool to predict relapse in patients with TGCT.

摘要

目的

肿瘤浸润免疫细胞(TIICs)的活性在多种癌症的预后中起着重要作用。在这里,我们试图描述睾丸生殖细胞肿瘤(TGCT)中 TIIC 的全貌,并基于此信息建立一个预后模型。

方法

使用估计相对 RNA 转录本亚群的细胞类型鉴定(CIBERSORT)算法确定 TGCT 数据集(n=74)中 22 种 TIICs 的比例。使用单变量和多变量 Cox 回归分析,基于 TIICs 与无病生存(DFS)之间的关联,建立免疫风险评分(IRS)。使用接收者操作特征曲线评估 IRS 的预测准确性,并使用 C 指数和校准曲线评估预后列线图的预测准确性。通过基因集富集分析评估 IRS 相关基因的生物学功能。

结果

三种 TIIC(浆细胞、M2 巨噬细胞和静止肥大细胞)的相对丰度与 TGCT 患者的 DFS 显著相关。在接受者操作特征曲线分析中,得到的 IRS 在预测 1 年、2 年和 3 年 DFS 时的曲线下面积分别为 0.70、0.793 和 0.827。Kaplan-Meier 分析证实,IRS 较高的患者 DFS 较短。IRS 是疾病复发的独立预测因子(危险比 1.306,95%置信区间 1.022-1.668;P=0.033)。列线图的 C 指数为 0.733。在高风险和低风险组的 TGCT 样本中,分别富集了与癌症相关和免疫相关途径相关的基因,与低 IRS 组相比,高 IRS 组中四种免疫检查点调节剂的表达明显降低。

结论

基于 TIIC 的 IRS 可能作为预测 TGCT 患者复发的补充工具具有实用价值。

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