Highly sensitive eight-channel light sensing system for biomedical applications.

We demonstrate the potential of an eight-channel light sensing platform system, named Black Box I (BBI), for rapid and highly sensitive measurement of low-level light using a nonradioactive optical readout. We developed, normalized, and characterized the photon sensitivities of the eight channels of the BBI using placental alkaline phosphatase (PLAP) as a model imaging reporter. We found that the BBI system had a statistically strong linear correlation with the reference IVIS Lumina II system. When we applied normalization constants, we were able to optimize the photomultiplier tubes (PMT) of all eight channels of the BBI (up to r2 = 0.998). We investigated the biomedical utilities of BBI by: (i) determining alkaline phosphatase activities in mouse plasma samples as a diagnostic secretory biomarker of cancer, and (ii) diagnosing cancer metastases in the organs of mice bearing triple negative breast cancer. We provide an important new addition to low-cost biomedical instruments intended for pre-clinical diagnostic imaging with high sensitivity, high sample throughput, portability, and rapid on-site analysis of low-level light.

Compact Eight-Channel Light-Sensing System for Bioassays.

The present protocol introduces a new instrumental setup as a luminometer to simultaneously measure eight light samples with high sensitivity. The system consists of 8-channel photomultiplier tubes (8-PMTs) with different sensitivities to light. Therefore, it is critical to normalize the sensitivities of PMTs to light samples and integrate them as a system. We first introduce how to normalize the diverse light sensitivity among the PMTs using placental alkaline phosphatase (PLAP) as a model chemiluminescence light source. The normalized BBI system shows a statistically strong linear correlation graph to photon counts. The biomedical utility of this system is exemplified by (i) determining the alkaline phosphatase (AP) activities in mouse plasma samples as a cancer biomarker and (ii) diagnosing metastatic tissues during cancer progression using bioluminescent reporter.

A mathematical model of ctDNA shedding predicts tumor detection size.

Early cancer detection aims to find tumors before they progress to an incurable stage. To determine the potential of circulating tumor DNA (ctDNA) for cancer detection, we developed a mathematical model of tumor evolution and ctDNA shedding to predict the size at which tumors become detectable. From 176 patients with stage I to III lung cancer, we inferred that, on average, 0.014% of a tumor cell's DNA is shed into the bloodstream per cell death. For annual screening, the model predicts median detection sizes of 2.0 to 2.3 cm representing a ~40% decrease from the current median detection size of 3.5 cm. For informed monthly cancer relapse testing, the model predicts a median detection size of 0.83 cm and suggests that treatment failure can be detected 140 days earlier than with imaging-based approaches. This mechanistic framework can help accelerate clinical trials by precomputing the most promising cancer early detection strategies.

A Model-Based Personalized Cancer Screening Strategy for Detecting Early-Stage Tumors Using Blood-Borne Biomarkers.

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. Cancer Res; 77(10); 2570-84. ©2017 AACR.

Detection and quantitation of circulating tumor cell dynamics by bioluminescence imaging in an orthotopic mammary carcinoma model.

Circulating tumor cells (CTCs) have been detected in the bloodstream of both early-stage and advanced cancer patients. However, very little is know about the dynamics of CTCs during cancer progression and the clinical relevance of longitudinal CTC enumeration. To address this, we developed a simple bioluminescence imaging assay to detect CTCs in mouse models of metastasis. In a 4T1 orthotopic metastatic mammary carcinoma mouse model, we demonstrated that this quantitative method offers sensitivity down to 2 CTCs in 0.1-1mL blood samples and high specificity for CTCs originating from the primary tumor, independently of their epithelial status. In this model, we simultaneously monitored blood CTC dynamics, primary tumor growth, and lung metastasis progression over the course of 24 days. Early in tumor development, we observed low numbers of CTCs in blood samples (10-15 cells/100 µL) and demonstrated that CTC dynamics correlate with viable primary tumor growth. To our knowledge, these data represent the first reported use of bioluminescence imaging to detect CTCs and quantify their dynamics in any cancer mouse model. This new assay is opening the door to the study of CTC dynamics in a variety of animal models. These studies may inform clinical decision on the appropriate timing of blood sampling and value of longitudinal CTC enumeration in cancer patients.