年龄相关的t细胞动力学对预测免疫治疗停止的生物标志物鉴定的影响:一项前瞻性队列研究

Jason E. Galloway, Andrea M. Holderbaum, Namrata Arya, Suohui Zhang, Michael S. Bodnar, Ruthann Norman, William E. Carson, Lianbo Yu, Kari L. Kendra, Christin E. Burd
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引用次数: 0

摘要

生物老化对免疫检查点抑制剂(ICI)在转移性黑色素瘤(MM)中毒性和疗效的影响尚未得到充分研究。在外周血T淋巴细胞(PBTLs)中,生物衰老的特征是T细胞组成和细胞衰老的变化。MM患者的PBTL生物老化指标是否不同,或是否可用于预测ICI过早停药(pID)尚不清楚。方法前瞻性地收集117例无癌对照和46例计划开始派姆单抗或纳武单抗单药治疗的MM患者的pbtl。用Nanostring测量了t细胞亚群、活化、共刺激/抑制和细胞衰老的74种mrna。在患者和对照组中评估每种mRNA与实际年龄之间的关系。根据对数转换mRNA水平或每个mRNA测量值偏离对照趋势的程度,通过计算pID患者的风险比(HR)来确定候选生物标志物(Δage)。曲线下面积(AUC)分析探讨了每个生物标志物在6个月和1年时区分患有和不患有pID的患者的能力。结果在对照组中,15种mrna与实际年龄相关,包括t细胞亚群、分化、细胞因子产生和共刺激/抑制的标志物。这些mrna都与患者的年龄无关。中位随访时间为94.8(1.6-195.7)周,46例患者中有35例停止治疗(23例进展,7例毒性,5例合并症/患者偏好)。治疗前CD8A (HR = 2.2[1.1-4.9])、CD45RB (HR = 2.9[1.4-5.8])和TNFRSF14 (HR = 2.2[1.1-4.5])水平升高预测pID与Δage-correction无关。CD3ε、CD27和FOXO1仅在Δage-correction后预测pID (HR = 2.5 [1.3-5.1];3.7 (1.8 - -7.8);2.1(1.1 - -4.3))。AUC分析确定Δage-CD3ε和Δage-CD27为pID的候选预测因子(AUC = 0.73和0.75)。结论:在MM中,PBTL组成的转录标记物与实际年龄之间的相关性被破坏。校正正常的、与年龄相关的生物标记物表达趋势,揭示了预测ICI结果的新生物标记物候选物。
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Impact of age-related T-cell dynamics on the identification of biomarkers predictive of immunotherapy discontinuation: A prospective cohort study

Background

The impact of biologic aging on immune checkpoint inhibitor (ICI) toxicity and efficacy is underexplored in metastatic melanoma (MM). In peripheral blood T lymphocytes (PBTLs), biologic aging is characterized by changes in T-cell composition and cellular senescence. Whether indicators of PBTL biologic aging vary in MM patients or can be used to predict premature ICI discontinuation (pID) is unknown.

Methods

We prospectively collected PBTLs from 117 cancer-free controls and 46 MM patients scheduled to begin pembrolizumab or nivolumab monotherapy. Seventy-four mRNAs indicative of T-cell subset, activation, costimulation/inhibition, and cellular senescence were measured by Nanostring. Relationships between each mRNA and chronologic age were assessed in patients and controls. Candidate biomarkers were identified by calculating the hazard ratio (HR) for pID in patients divided into low and high groups based on log-transformed mRNA levels or the magnitude by which each mRNA measurement deviated from the control trend (Δage). Area under the curve (AUC) analyses explored the ability of each biomarker to discriminate between patients with and without pID at 6 months and 1 year.

Results

Fifteen mRNAs correlated with chronologic age in controls, including markers of T-cell subset, differentiation, cytokine production, and costimulation/inhibition. None of these mRNAs remained correlated with age in patients. Median follow-up was 94.8 (1.6-195.7) weeks and 35 of 46 patients discontinued therapy (23 progression, seven toxicity, and five comorbidity/patient preference). Elevated pretherapy CD8A (HR = 2.2 [1.1-4.9]), CD45RB (HR = 2.9 [1.4-5.8]), and TNFRSF14 (HR = 2.2 [1.1-4.5]) levels predicted pID independent of Δage-correction. CD3ε, CD27, and FOXO1 predicted pID only after Δage-correction (HR = 2.5 [1.3-5.1]; 3.7 [1.8-7.8]; 2.1 [1.1-4.3]). AUC analysis identified Δage-CD3ε and Δage-CD27 as candidate predictors of pID (AUC = .73 and .75).

Conclusions

Correlations between transcriptional markers of PBTL composition and chronologic age are disrupted in MM. Correcting for normal, age-related trends in biomarker expression unveils new biomarker candidates predictive of ICI outcomes.

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