A Model-Based Personalized Cancer Screening Strategy for Detecting Early-Stage Tumors Using Blood-Borne Biomarkers
A Model-Based Personalized Cancer Screening Strategy for Detecting Early-Stage Tumors Using Blood-Borne Biomarkers
复制标题
DOI：
10.1158/0008-5472.can-16-2904
复制
发表时间：
2017-05-15
期刊：
影响因子：
11.2
通讯作者：
Gambhir, Sanjiv Sam
中科院分区：
文献类型：
--
作者：
Hori, Sharon Seiko;Lutz, Amelie M.;Gambhir, Sanjiv Sam
有效的癌症血液生物标记物筛选策略必须在早期、可干预的时间区分侵袭性和非侵袭性肿瘤。然而，要使基于血液的治疗策略发挥作用，必须验证进入血液的生物标记物的数量及其与肿瘤生长或进展的关系。为了研究血液生物标记物水平与人类癌症小鼠模型早期存活肿瘤生长的相关性，我们监测了原位移植到裸鼠体内的工程化人卵巢癌细胞(A2780)的早期肿瘤生长。生物标记物的脱落通过连续采血监测，而肿瘤的存活率和体积通过生物发光成像和超声成像监测。根据这些指标，我们建立了一个癌症生物标记物动力学的数学模型，该模型解释了生物标记物从肿瘤和健康细胞中脱落，生物标记物进入血管系统，生物标记物从血浆中消除，以及特定受试者的肿瘤生长。我们在另一组小鼠身上验证了该模型，在这些小鼠中，特定受试者的肿瘤生长速度得到了准确的预测。为了说明这一策略的临床翻译，我们对从小鼠到人的模型参数进行了异位测量，并使用了PSA脱落和前列腺癌的参数。通过这种方式，我们发现，仅凭血液生物标记物采样数据就能够分别在临床成像前7.2个月和8.9年检测和区分模拟侵袭性(2个月肿瘤倍增时间)和非侵袭性(18个月肿瘤倍增时间)肿瘤。我们的模型和筛查策略在适用于任何实体癌和相关生物标记物脱落方面提供了广泛的影响，从而仅使用血液生物标记物采样数据就可以区分侵袭性和非侵袭性肿瘤。(C)2017年AACR。
An effective cancer blood biomarker screening strategy must distinguish aggressive from nonaggressive tumors at an early, intervenable time. However, for blood-based strategies to be useful, the quantity of biomarker shed into the blood and its relationship to tumor growth or progression must be validated. To study how blood biomarker levels correlate with early-stage viable tumor growth in a mouse model of human cancer, we monitored early tumor growth of engineered human ovarian cancer cells (A2780) implanted orthotopically into nude mice. Biomarker shedding was monitored by serial blood sampling, whereas tumor viability and volume were monitored by bioluminescence imaging and ultrasound imaging. From these metrics, we developed a mathematical model of cancer biomarker kinetics that accounts for biomarker shedding from tumor and healthy cells, biomarker entry into vasculature, biomarker elimination from plasma, and subject-specific tumor growth. We validated the model in a separate set of mice in which subject-specific tumor growth rates were accurately predicted. To illustrate clinical translation of this strategy, we allometrically scaled model parameters from mouse to human and used parameters for PSA shedding and prostate cancer. In this manner, we found that blood biomarker sampling data alone were capable of enabling the detection and discrimination of simulated aggressive (2-month tumor doubling time) and nonaggressive (18-month tumor doubling time) tumors as early as 7.2 months and 8.9 years before clinical imaging, respectively. Our model and screening strategy offers broad impact in their applicability to any solid cancer and associated biomarkers shed, thereby allowing a distinction between aggressive and nonaggressive tumors using blood biomarker sampling data alone. (C) 2017 AACR.