A four-factor immune risk score signature predicts the clinical outcome of patients with spinal chordoma
A four-factor immune risk score signature predicts the clinical outcome of patients with spinal chordoma
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四因素免疫风险评分特征可预测脊髓脊索瘤患者的临床结果
DOI：
10.1002/ctm2.4
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发表时间：
2020-03-01
影响因子：
10.6
通讯作者：
Li, Jing
中科院分区：
文献类型：
--
作者：
Zou, Ming-Xiang;Pan, Yue;Li, Jing
背景目前，以往研究中免疫细胞的测量通常是主观的，并且尚未建立脊索瘤的基于免疫的预后模型。在这项研究中，我们试图同时测量肿瘤浸润淋巴细胞（TIL）亚型在脉络膜样本使用客观的方法，并开发一个免疫风险评分（IRS）模型的生存预测。方法采用多重定量免疫荧光染色法测定114例脊髓脉络膜标本（训练组54例，验证组60例）肿瘤和间质亚区的TIL水平，检测程序性死亡-1（PD-1）、CD 3、CD 8、CD 20（CD为分化簇）和FOXP 3。对另外5份新鲜脉络膜标本进行流式细胞术，以验证淋巴细胞测量的免疫荧光试验。随后，使用最小绝对收缩和选择算子（LASSO）考克斯回归方法建立IRS模型。结果流式细胞术和定量免疫荧光法显示新鲜肿瘤组织中淋巴细胞百分比和TIL亚群比例相似。利用训练数据，LASSO模型确定了IRS构建的四个免疫特征：（肿瘤）FOXP 3，肿瘤PD-1，（基质）FOXP 3和（基质）CD 8。在这两个队列中，高IRS与肿瘤程序性细胞死亡-1配体1表达、Enneking不适当的肿瘤切除和肿瘤周围肌肉浸润显著相关。多因素考克斯回归分析和分层分析显示，IRS是一个独立的预测因子，可以有效地将具有相似Enneking分期的患者分为不同的风险亚组，其生存率有显著差异。进一步的受试者操作特征分析发现，IRS分类比传统的临床病理因素有更好的预后价值，并弥补了Enneking分期对预后预测的不足。更重要的是，基于IRS和临床预测因子的列线图在估计疾病复发和患者生存方面表现出足够的性能。结论这些数据支持使用IRS信号作为脊髓脉络膜炎的可靠预后工具，并可促进患者的个体化治疗决策。
Background Currently, the measurement of immune cells in previous studies is usually subjective, and no immune-based prognostic model has been established for chordoma. In this study, we sought to simultaneously measure tumor-infiltrating lymphocyte (TIL) subtypes in chordoma samples using an objective method and develop an immune risk score (IRS) model for survival prediction. Methods Multiplexed quantitative immunofluorescence staining was used to determine the TIL levels in the tumoral and stromal subareas of 114 spinal chordoma specimens (54 in the training and 60 in the validation cohort) for programmed death-1 (PD-1), CD3, CD8, CD20 (where CD is cluster of differentiation), and FOXP3. Flow cytometry was performed to validate the immunofluorescence assay for lymphocyte measurement on an additional five fresh chordoma specimens. Subsequently, the IRS model was built using the least absolute shrinkage and selection operator (LASSO) Cox regression method. Results Flow cytometry and quantitative immunofluorescence showed similar lymphocytic percentages and TIL subpopulation proportions in the fresh tumor specimens. With the training data, the LASSO model identified four immune features for IRS construction:(tumoral)FOXP3,tumoralPD-1,(stromal)FOXP3, and(stromal)CD8. In both cohorts, a high IRS was significantly associated with tumoral programmed cell death-1 ligand 1 expression, Enneking inappropriate tumor resection, and surrounding muscle invasion by tumor. Multivariate Cox regression and stratified analysis in the two cohorts revealed that the IRS was an independent predictor and could effectively separate patients with similar Enneking staging into different risk subgroups, with significantly different survival rates. Further receiver operating characteristic analysis found that the IRS classifier had a better prognostic value than the traditional clinicopathological factors and compensated for the deficiency of Enneking staging for outcome prediction. More importantly, a nomogram based on the IRS and clinical predictors showed adequate performance in estimating disease recurrence and survival of patients. Conclusions These data support the use of the IRS signature as a reliable prognostic tool in spinal chordoma and may facilitate individualized therapy decision making for patients.