Liu Yingmiao, Li Jiatong, Lyu Jing, Howard Lauren E, Sibley Alexander B, Starr Mark D, Brady John C, Arrowood Christy, Kohn Elise C, Ivy S Percy, Hurwitz Herbert I, Abbruzzese James L, Owzar Kouros, Nixon Andrew B
Department of Medicine, Duke University Medical Center, Durham, North Carolina.
Yale University, New Haven, Connecticut.
Cancer Epidemiol Biomarkers Prev. 2025 Jan 9;34(1):93-99. doi: 10.1158/1055-9965.EPI-24-0644.
Biomarker analyses are an integral part of cancer research. Despite the intense efforts to identify and characterize biomarkers in patients with cancer, little is known regarding the natural variation of biomarkers in healthy populations. Here we conducted a clinical study to evaluate the natural variability of biomarkers over time in healthy participants.
The angiome multiplex array, a panel of 25 circulating protein biomarkers, was assessed in 28 healthy participants across eight timepoints over the span of 60 days. We utilized the intraclass correlation coefficient (ICC) to quantify the reliability of the biomarkers. Adjusted ICC values were calculated under the framework of a linear mixed-effects model, taking into consideration age, sex, body mass index, fasting status, and sampling factors.
ICC was calculated to determine the reliability of each biomarker. Hepatocyte growth factor was the most stable marker (ICC = 0.973), while platelet-derived growth factor (PDGF)-BB was the most variable marker (ICC = 0.167). In total, ICC analyses revealed that 22 out of 25 measured biomarkers display good (≥0.4) to excellent (>0.75) ICC values. Three markers (PDGF-BB, TGFβ1, PDGF-AA) had ICC values <0.4. Greater age was associated with higher IL6 (P = 0.0114). Higher body mass index was associated with higher levels of IL6 (P = 0.0003) and VEGF-R3 (P = 0.0045).
Of the 25 protein biomarkers measured over this short time period, 22 markers were found to have good or excellent ICC values, providing additional validation for this biomarker assay.
These data further support the validation of the angiome biomarker assay and its application as an integrated biomarker in clinical trial testing.
生物标志物分析是癌症研究的一个重要组成部分。尽管人们为识别和表征癌症患者的生物标志物付出了巨大努力,但对于健康人群中生物标志物的自然变异情况却知之甚少。在此,我们开展了一项临床研究,以评估健康参与者体内生物标志物随时间的自然变异性。
对28名健康参与者在60天内的8个时间点进行了血管生成多重阵列检测,该检测可检测25种循环蛋白生物标志物。我们利用组内相关系数(ICC)来量化生物标志物的可靠性。在考虑年龄、性别、体重指数、禁食状态和采样因素的线性混合效应模型框架下计算调整后的ICC值。
计算ICC以确定每种生物标志物的可靠性。肝细胞生长因子是最稳定的标志物(ICC = 0.973),而血小板衍生生长因子(PDGF)-BB是变异性最大的标志物(ICC = 0.167)。总体而言,ICC分析显示,25种检测的生物标志物中有22种显示出良好(≥0.4)至优秀(>0.75)的ICC值。三种标志物(PDGF-BB、TGFβ1、PDGF-AA)的ICC值<0.4。年龄越大,IL6水平越高(P = 0.0114)。体重指数越高,IL6(P = 0.0003)和VEGF-R3(P = 0.0045)水平越高。
在这一短时间内检测的25种蛋白质生物标志物中,发现22种标志物具有良好或优秀的ICC值,为该生物标志物检测提供了额外的验证。
这些数据进一步支持了血管生成生物标志物检测的验证及其作为临床试验检测中综合生物标志物的应用。