Ph.D., University of California Los Angeles, Biomedical Engineering
M.S., University of California Los Angeles, Biomedical Engineering
B.S., University of California Los Angeles, Cybernetics
B.S., University of California Los Angeles, Applied Mathematics
Photoacoustic Tomography Detects Early Vessel Regression and Normalization During Ovarian Tumor Response to the Antiangiogenic Therapy Trebananib
JOURNAL OF NUCLEAR MEDICINE
2015; 56 (12): 1942-1947
The primary aim of this study was to assess the potential of in vivo photoacoustic tomography (PAT) for direct functional measurement of ovarian tumor response to anti-angiogenic therapy.In vivo studies were performed with institutional animal care and use committee approval. We used an orthotopic mouse model of ovarian cancer treated with Trebananib (n = 9) or vehicle (n = 9). Tumor-bearing mice were randomized into Trebananib or vehicle groups at day 10 and dosed on days 12, 15 and 18 post implantation. PAT and blood draws were performed at day 10, then 24 hours after each drug dose. Tumors were excised for histopathology following the final studies on day 19. Data analysis to test for statistical significance was performed blinded.Blockade of angiopoietin signaling using Trebananib resulted in reduced total hemoglobin-weighted PA signal (n = 9, P = 0.01) and increased oxyhemoglobin-weighted PA signal (n = 9, P<0.01). The latter observation indicated normalization of the residual tumor vessels, which was also implied by low levels of angiopoietin 1 in serum biomarker profiling (0.76±0.12ng/mL). These non-invasive measures reflected a 30% reduction in microvessel density and increased vessel maturation in ex vivo sections.PAT is able to evaluate both vessel regression and normalization in response to Trebananib. Non-invasive imaging data was supported by modulation of serum markers in vitro and ex vivo histopathology.
View details for DOI 10.2967/jnumed.115.160002
View details for Web of Science ID 000365724800023
View details for PubMedID 26315834
Development and Validation of an Immuno-PET Tracer as a Companion Diagnostic Agent for Antibody-Drug Conjugate Therapy to Target the CA6 Epitope
2015; 276 (1): 191-198
Purpose To develop and compare three copper 64 ((64)Cu)-labeled antibody fragments derived from a CA6-targeting antibody (huDS6) as immuno-positron emission tomography (immuno-PET)-based companion diagnostic agents for an antibody-drug conjugate by using huDS6. Materials and Methods Three antibody fragments derived from huDS6 were produced, purified, conjugated to 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA), and evaluated in the following ways: (a) the affinity of the fragments and the DOTA conjugates was measured via flow cytometry, (b) the stability of the labeled fragments was determined ex vivo in human serum over 24 hours, and (c) comparison of the in vivo imaging potential of the fragments was evaluated in mice bearing subcutaneous CA6-positive and CA6-negative xenografts by using serial PET imaging and biodistribution. Isotype controls with antilysozyme and anti-DM4 B-Fabs and blocking experiments with an excess of either B-Fab or huDS6 were used to determine the extent of the antibody fragment (64)Cu-DOTA-B-Fab binding specificity. Immunoreactivity and tracer kinetics were evaluated by using cellular uptake and 48-hour imaging experiments, respectively. Statistical analyses were performed by using t tests, one-way analysis of variance, and Wilcoxon and Mann-Whitney tests. Results The antibody fragment (64)Cu-DOTA-B-Fab was more than 95% stable after 24 hours in human serum, had an immunoreactivity of more than 70%, and allowed differentiation between CA6-positive and CA6-negative tumors in vivo as early as 6 hours after injection, with a 1.7-fold uptake ratio between tumors. Isotype and blocking studies experiments showed tracer-specific uptake in antigen-positive tumors, despite some nonspecific uptake in both tumor models. Conclusion Three antibody fragments were produced and examined as potential companion diagnostic agents. (64)Cu-DOTA-B-Fab is a stable and effective immuno-PET tracer for CA6 imaging in vivo. (©) RSNA, 2015 Online supplemental material is available for this article.
View details for DOI 10.1148/radiol.15140058
View details for Web of Science ID 000359708400021
Detecting cancers through tumor-activatable minicircles that lead to a detectable blood biomarker
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2015; 112 (10): 3068-3073
Earlier detection of cancers can dramatically improve the efficacy of available treatment strategies. However, despite decades of effort on blood-based biomarker cancer detection, many promising endogenous biomarkers have failed clinically because of intractable problems such as highly variable background expression from nonmalignant tissues and tumor heterogeneity. In this work we present a tumor-detection strategy based on systemic administration of tumor-activatable minicircles that use the pan-tumor-specific Survivin promoter to drive expression of a secretable reporter that is detectable in the blood nearly exclusively in tumor-bearing subjects. After systemic administration we demonstrate a robust ability to differentiate mice bearing human melanoma metastases from tumor-free subjects for up to 2 wk simply by measuring blood reporter levels. Cumulative change in reporter levels also identified tumor-bearing subjects, and a receiver operator-characteristic curve analysis highlighted this test's performance with an area of 0.918 ± 0.084. Lung tumor burden additionally correlated (r(2) = 0.714; P < 0.05) with cumulative reporter levels, indicating that determination of disease extent was possible. Continued development of our system could improve tumor detectability dramatically because of the temporally controlled, high reporter expression in tumors and nearly zero background from healthy tissues. Our strategy's highly modular nature also allows it to be iteratively optimized over time to improve the test's sensitivity and specificity. We envision this system could be used first in patients at high risk for tumor recurrence, followed by screening high-risk populations before tumor diagnosis, and, if proven safe and effective, eventually may have potential as a powerful cancer-screening tool for the general population.
View details for DOI 10.1073/pnas.1414156112
View details for Web of Science ID 000350646500049
- Detection and Quantitation of Circulating Tumor Cell Dynamics by Bioluminescence Imaging in an Orthotopic Mammary Carcinoma Model PLOS ONE 2014; 9 (9)
Detection and quantitation of circulating tumor cell dynamics by bioluminescence imaging in an orthotopic mammary carcinoma model.
2014; 9 (9)
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.
View details for DOI 10.1371/journal.pone.0105079
View details for PubMedID 25188396
Mathematical Model Identifies Blood Biomarker-Based Early Cancer Detection Strategies and Limitations
SCIENCE TRANSLATIONAL MEDICINE
2011; 3 (109)
Most clinical blood biomarkers lack the necessary sensitivity and specificity to reliably detect cancer at an early stage, when it is best treatable. It is not yet clear how early a clinical blood assay can be used to detect cancer or how biomarker-based strategies can be improved to enable earlier detection of smaller tumors. To address these issues, we developed a mathematical model describing dynamic plasma biomarker kinetics in relation to the growth of a tumor, beginning with a single cancer cell. To exemplify a realistic scenario in which biomarker is shed by both cancerous and noncancerous cells, we primed the model on ovarian tumor growth and CA125 shedding data, for which tumor growth parameters and shedding rates are readily available in published literature. We found that a tumor could grow unnoticed for more than 10.1 years and reach a volume of about ?/6(25.36 mm)(3), corresponding to a spherical diameter of about 25.36 mm, before becoming detectable by current clinical blood assays. Model parameters were perturbed over log orders of magnitude to quantify ideal shedding rates and identify other blood-based strategies required for early submillimeter tumor detectability. The detection times we estimated are consistent with recently published tumor progression time lines based on clinical genomic sequencing data for several cancers. Here, we rigorously showed that shedding rates of current clinical blood biomarkers are likely 10(4)-fold too low to enable detection of a developing tumor within the first decade of tumor growth. The model presented here can be extended to virtually any solid cancer and associated biomarkers.
View details for DOI 10.1126/scitranslmed.3003110
View details for Web of Science ID 000297218300004
View details for PubMedID 22089452
Role of endosomal trafficking dynamics on the regulation of hepatic insulin receptor activity: Models for fao cells
ANNALS OF BIOMEDICAL ENGINEERING
2006; 34 (5): 879-892
Evidence indicates that endosomal insulin receptor (IR) trafficking plays a role in regulating insulin signal transduction. To evaluate its importance, we developed a series of biokinetic models for quantifying activated surface and endosomal IR dynamics from published experimental data. Starting with a published two-compartment Fao hepatoma model, a four-pool model was formulated that depicts IR autophosphorylation after receptor binding, IR endosomal internalization/trafficking, insulin dissociation from and dephosphorylation of internalized IR, and recycling of unliganded, dephosphorylated IR to the plasma membrane. Quantification required three additional data sets, two measured, but unmodeled by the same group. A five-pool model created to include endosomal trafficking of the nonphosphorylated insulin-IR complex was fitted using the same data sets, augmented with another published data set. Creation of a six-pool model added the physiologically relevant dissociation of insulin ligand from the activated endosomal IR. More importantly, all three models, validated against additional data not used in model fitting, predict that, mechanistically, internalization of activated IR is a rate-limiting step, at least under the receptor saturating conditions of the fitting data. This rate includes the transit time to a site where insulin dissociation from and/or dephosphorylation of the IR occurs by docking with protein-tyrosine phosphatases (PTPases), or where a sufficient conformational change occurs in the IR, perhaps due to insulin-IR dissociation, where associated PTPases may complete IR dephosphorylation. Our new models indicate that key events in endosomal IR trafficking have significance in mediating IR activity, possibly serving to regulate insulin signal transduction.
View details for DOI 10.1007/s10439-005-9065-5
View details for Web of Science ID 000237656900015
View details for PubMedID 16708271