I utilize an integrative biological-mathematical-engineering approach to study the growth, development, early detection, and treatment of cancer. This includes:
1. The development of animal models of cancer, including subcutaneous and orthotopic xenograft cancer mouse models (primarily breast and ovarian cancer).
2. The detection of circulating biomarkers in blood and urine.
3. Molecular and anatomical imaging of cancer, including in vivo imaging modalities such as bioluminescence, fluorescence and ultrasound.
4. The development of mathematical models of cancer, with focus on parameter estimation and identifiability, hypothesis testing and discrimination, and nonlinear optimization.
A mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation.
2021; 11 (1): 1341
The targeted inactivation of individual oncogenes can elicit regression of cancers through a phenomenon called oncogene addiction. Oncogene addiction is mediated by cell-autonomous and immune-dependent mechanisms. Therapeutic resistance to oncogene inactivation leads to recurrence but can be counteracted by immune surveillance. Predicting the timing of resistance will provide valuable insights in developing effective cancer treatments. To provide a quantitative understanding of cancer response to oncogene inactivation, we developed a new 3-compartment mathematical model of oncogene-driven tumor growth, regression and recurrence, and validated the model using a MYC-driven transgenic mouse model of T-cell acute lymphoblastic leukemia. Our mathematical model uses imaging-based measurements of tumor burden to predict the relative number of drug-sensitive and drug-resistant cancer cells in MYC-dependent states. We show natural killer (NK) cell adoptive therapy can delay cancer recurrence by reducing the net-growth rate of drug-resistant cells. Our studies provide a novel way to evaluate combination therapy for personalized cancer treatment.
View details for DOI 10.1038/s41598-020-78947-2
View details for PubMedID 33446671
View details for PubMedCentralID PMC7809285
A Model-Based Personalized Cancer Screening Strategy for Detecting Early-Stage Tumors Using Blood-Borne Biomarkers
2017; 77 (10): 2570-2584
An effective cancer blood biomarker screening strategy must distinguish aggressive from non-aggressive tumors at an early, intervenable time. However, for blood-based strategies to be useful, the quality and quantiy of the 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 an 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, while tumor viability and volume was monitored by bioluminescence imaging and ultrasound imaging. From these metrics we developed a mathematical model of cancer biomarker kinetics in different compartments 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 where 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 was capable of enabling the detection and discrimination of simulated aggressive (2-month tumor doubling time) and non-aggressive (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 offer broad impact in their applicability to any solid cancer and the biomarkers they shed, thereby allowing a distinction between aggressive vs. non-aggressive tumors using blood biomarker sampling data alone.
View details for DOI 10.1158/0008-5472.CAN-16-2904
View details for Web of Science ID 000401252900003
View details for PubMedID 28283654
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 π/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
View details for PubMedCentralID PMC3423335
Tumor volume doubling time estimated from digital breast tomosynthesis mammograms distinguishes invasive breast cancers from benign lesions.
OBJECTIVES: The aim of this study was to determine whether lesion size metrics on consecutive screening mammograms could predict malignant invasive carcinoma versus benign lesion outcome.METHODS: We retrospectively reviewed suspicious screen-detected lesions confirmed by biopsy to be invasive breast cancers or benign that were visible on current and in-retrospect prior screening mammograms performed with digital breast tomosynthesis from 2017 to 2020. Four experienced radiologists recorded mammogram dates, breast density, lesion type, lesion diameter, and morphology on current and prior exams. We used logistic regression models to evaluate the association of invasive breast cancer outcome with lesion size metrics such as maximum dimension, average dimension, volume, and tumor volume doubling time (TVDT).RESULTS: Twenty-eight patients with invasive ductal carcinoma or invasive lobular carcinoma and 40 patients with benign lesions were identified. The mean TVDT was significantly shorter for invasive breast cancers compared to benign lesions (0.84 vs. 2.5 years; p = 0.0025). Patients with a TVDT of less than 1 year were shown to have an odds ratio of invasive cancer of 6.33 (95% confidence interval, 2.18-18.43). Logistic regression adjusted for age, lesion maximum dimension, and lesion volume demonstrated that shorter TVDT was the size variable significantly associated with invasive cancer outcome.CONCLUSION: Invasive breast cancers detected on current and in-retrospect prior screening mammograms are associated with shorter TVDT compared to benign lesions. If confirmed to be sufficiently predictive of benignity in larger studies, lesions visible on mammograms which in comparison to prior exams have longer TVDTs could potentially avoid additional imaging and/or biopsy.KEY POINTS: We propose tumor volume doubling time as a measure to distinguish benign from invasive breast cancer lesions. Logistic regression results summarized the utility of the odds ratio in retrospective clinical mammography data.
View details for DOI 10.1007/s00330-022-08966-2
View details for PubMedID 35779088
Compact Eight-Channel Light-Sensing System for Bioassays.
Methods in molecular biology (Clifton, N.J.)
2022; 2525: 377-386
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.
View details for DOI 10.1007/978-1-0716-2473-9_29
View details for PubMedID 35836084
Minicircles for a two-step blood biomarker and PET imaging early cancer detection strategy.
Journal of controlled release : official journal of the Controlled Release Society
Early cancer detection can dramatically increase treatment options and survival rates for patients, yet detection of early-stage tumors remains difficult. Here, we demonstrate a two-step strategy to detect and locate cancerous lesions by delivering tumor-activatable minicircle (MC) plasmids encoding a combination of blood-based and imaging reporter genes to tumor cells. We genetically engineered the MCs, under the control of the pan-tumor-specific Survivin promoter, to encode: 1) Gaussia Luciferase (GLuc), a secreted biomarker that can be easily assayed in blood samples; and 2) Herpes Simplex Virus Type 1 Thymidine Kinase mutant (HSV-1 sr39TK), a PET reporter gene that can be used for highly sensitive and quantitative imaging of the tumor location. We evaluated two methods of MC delivery, complexing the MCs with the chemical transfection agent jetPEI or encapsulating the MCs in extracellular vesicles (EVs) derived from a human cervical cancer HeLa cell line. MCs delivered by EVs or jetPEI yielded significant expression of the reporter genes in cell culture versus MCs delivered without a transfection agent. Secreted GLuc correlated with HSV-1 sr39TK expression with R2 = 0.9676. MC complexation with jetPEI delivered a larger mass of MC for enhanced transfection, which was crucial for in vivo animal studies, where delivery of MCs via jetPEI resulted in GLuc and HSV-1 sr39TK expression at significantly higher levels than controls. To the best of our knowledge, this is the first report of the PET reporter gene HSV-1 sr39TK delivered via a tumor-activatable MC to tumor cells for an early cancer detection strategy. This work explores solutions to endogenous blood-based biomarker and molecular imaging limitations of early cancer detection strategies and elucidates the delivery capabilities and limitations of EVs.
View details for DOI 10.1016/j.jconrel.2021.05.026
View details for PubMedID 34029631
A mathematical model of ctDNA shedding predicts tumor detection size.
2020; 6 (50)
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.
View details for DOI 10.1126/sciadv.abc4308
View details for PubMedID 33310847
ctDNA shedding dynamics dictate early lung cancer detection potential
AMER ASSOC CANCER RESEARCH. 2020: 25
View details for Web of Science ID 000537848000023
Highly sensitive eight-channel light sensing system for biomedical applications.
Photochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology
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.
View details for DOI 10.1039/d0pp00017e
View details for PubMedID 32159572
A blood biomarker for monitoring response to anti-EGFR therapy.
Cancer biomarkers : section A of Disease markers
BACKGROUND AND OBJECTIVE: To monitor therapies targeted to epidermal growth factor receptors (EGFR) in non-small cell lung cancer (NSCLC), we investigated Peroxiredoxin 6 (PRDX6) as a biomarker of response to anti-EGFR agents.METHODS: We studied cells that are sensitive (H3255, HCC827) or resistant (H1975, H460) to gefitinib. PRDX6 was examined with either gefitinib or vehicle treatment using enzyme-linked immunosorbent assays. We created xenograft models from one sensitive (HCC827) and one resistant cell line (H1975) and monitored serum PRDX6 levels during treatment.RESULTS: PRDX6 levels in cell media from sensitive cell lines increased significantly after gefitinib treatment vs. vehicle, whereas there was no significant difference for resistant lines. PRDX6 accumulation over time correlated positively with gefitinib sensitivity. Serum PRDX6 levels in gefitinib-sensitive xenograft models increased markedly during the first 24 hours of treatment and then decreased dramatically during the following 48 hours. Differences in serum PRDX6 levels between vehicle and gefitinib-treated animals could not be explained by differences in tumor burden.CONCLUSIONS: Our results show that changes in serum PRDX6 during the course of gefitinib treatment of xenograft models provide insight into tumor response and such an approach offers several advantages over imaging-based strategies for monitoring response to anti-EGFR agents.
View details for PubMedID 29689709
Engineering Intracellularly Retained Gaussia Luciferase Reporters for Improved Biosensing and Molecular Imaging Applications.
ACS chemical biology
Gaussia luciferase (GLUC) is a bioluminescent reporter protein of increasing importance. As a secretory protein, it has increased sensitivity in vitro and in vivo (∼20 000-fold, and ∼1000-fold, respectively) over its competitor, secreted alkaline phosphatase. Unfortunately, this same advantageous secretory nature of GLUC limits its usefulness for many other possible intracellular applications, e.g., imaging signaling pathways in intact cells, in vivo imaging, and in developing molecular imaging biosensors to study protein-protein interactions and protein folding. Hence, to widen the research applications of GLUC, we developed engineered variants that increase its intracellular retention both by modifying the N-terminal secretory signal peptide and by tagging additional sequences to its C-terminal region. We found that when GLUC was expressed in mammalian cells, its N-terminal secretory signal peptide comprising amino acids 1-16 was essential for GLUC folding and functional activity in addition to its inherent secretory property. Modification of the C-terminus of GLUC by tagging a four amino acid (KDEL) endoplasmic reticulum targeting peptide in multiple repeats significantly improved its intracellular retention, with little impact on its folding and enzymatic activity. We used stable cells expressing this engineered GLUC with KDEL repeats to monitor chemically induced endoplasmic reticulum stress on cells. Additionally, we engineered an apoptotic sensor using modified variants of GLUC containing a four amino acid caspase substrate peptide (DEVD) between the GLUC protein and the KDEL repeats. Its use in cell culture resulted in increased GLUC secretion in the growth medium when cells were treated with the chemotherapeutic drugs doxorubicin, paclitaxel, and carboplatin. We thus successfully engineered a new variant GLUC protein that is retained inside cells rather than secreted extracellularly. We validated this novel reporter by incorporating it in biosensors for detection of cellular endoplasmic reticulum stress and caspase activation. This new molecularly engineered enzymatic reporter has the potential for widespread applications in biological research.
View details for PubMedID 28767220
On-Target Probes for Early Detection
Nature Biomedical Engineering
2017; 1: 1-3
View details for DOI 10.1038/s41551-017-0062
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 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 PubMedID 25734548
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 PubMedID 25713388
View details for PubMedCentralID PMC4364239
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
View details for PubMedCentralID PMC4154864
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