Photonanomedicines (PNMs) are photochemically-activated nanoscale drug delivery systems that play a niche role in photodynamic therapy (PDT)-based anticancer modalities. PNMs serve as versatile platforms for multi-agent delivery, spatiotemporally-controlled treatment induction and customization for tumor targeting. This work focuses on the systematic tuning of PNMs to achieve precision in tumor targeted photomodulation at three different scales: 1) stroma and interstitium, 2) proto-oncogenic cellular receptors, and 3) subcellular organelles (Figure 1). We show that photomodulation of tumors targeted at these three scales provides unique avenues to circumvent problematic barriers in drug delivery, treatment specificity, safety and tolerability, and treatment response.
Exploiting differences in photosensitizer (PS) localization and mechanisms of action with sequential or simultaneous activation protocols has been shown to improve photodynamic therapy (PDT) efficacy. Various sub-cellular, cellular and stromal components can be targeted, causing selective photodamage. Previous reports have shown that rationally targeting non-overlapping tumor compartments or sub-cellular sites considerably enhances outcomes from PDT. The current presentation describes the benefits of simultaneously targeting lysosomes and mitochondria/endoplasmic reticulum using lipid-anchored and entrapped liposomal preparations of benzoporphyrin derivative, respectively, with an emphasis on results in 3D models of ovarian cancer.
A range of cellular, architectural, and physical cues in the tumor microenvironment influence the intrinsic and acquired resistance mechanisms that lead to treatment failure. Strategies that leverage photodynamic therapy (PDT), a photochemistry-based biophysical treatment modality, to regionally target and prime stubborn tumor populations may be essential to realizing durable improvements in cancer management while minimizing toxicity from traditional agents. Capturing these attributes in rationally-designed combinations has shown promise by synergistically reducing tumor area in 3D models, and durably controlling tumor burden in vivo. Among the areas that remain understudied is the influence of mechanical forces, such as hydrodynamic shear stress, on resistance, and the development of 3D tumor models and in vivo models that account for physical stress. To evaluate and optimize PDT regimens, and PDT-based combinations, designed to overcome resistance to conventional therapies due to physical stress, a multi-faceted approach is needed. Here the impact of hydrodynamic stress is evaluated in bioengineered 3D tumor models in the context of ovarian cancer. The potential value of using biologically inspired in vitro models to guide customized, rationally-designed PDT-based combination regimens will be presented.
In ovarian cancer patients, the build up of fluid in the peritoneal cavity leads to the production of protein and cell rich asciites. Physiological movement establishes ascitic currents in the peritoneal cavity. The ascitic currents represent external flow which plays an important role in disseminating and modulating the biology of the ovarian cancer. Furthermore, the interstitial flow build-up inside tumor nodules establishes outward fluidic streams. The fluidic internal and external streams play an important role in drug delivery, which is also affected by permeability, an important physical property of the tumor. Permeability defines the flow dynamics over and through the tumor nodule, influencing therapy. The permeability of the tumor also affects the magnitude and distribution of fluidic shear stress experienced by the nodule. We propose to use experimental optical observations and mathematical descriptions of flow and mass transport for estimation of (i) the flow pattern around and through 3D porous cancer nodule surrogate, and (ii) the surrogate permeability. The permeability is estimated using an optimization technique in which the permeability value is iteratively modified to minimize the difference between the numerical solution of the mathematical model and the optical measurements. This algorithm is robust to discrepancy between the mathematical model and the experimental measurements. In this presentation, we show the feasibility of using particle image velocimetry (PIV) and confocal microscopy for estimating the permeability of a tumor surrogate by the optimization technique. Results suggest that the developed optimization toolbox can be used to estimate the tumor permeability in live 3D models of ovarian cancer.
Drug resistance to conventional therapies remains a major cause of treatment failure, tumor recurrence and dismal survival rates for patients with advanced stage cancers. Photodynamic therapy (PDT) provides an opportunity to exploit photochemically-triggered death mechanisms via targeting of sub-cellular, cellular and stromal compartments to overcome treatment resistance in unresponsive populations of stubborn disease. The informed design of mechanism-based combinations is emerging as increasingly important to targeting resistance and improving the efficacy of conventional treatments, while minimizing toxicity. PDT has been shown to synergize with conventional agents and to overcome the evasion pathways that cause resistance. Increasing evidence shows that PDT-based combinations cooperate mechanistically with, and improve the therapeutic index of, traditional chemotherapies. These and other findings emphasize the importance of including PDT as part of comprehensive treatment plans for cancer, particularly in complex disease sites. Identifying effective combinations requires a multi-faceted approach that includes the development of bioengineered cancer models and corresponding image analysis tools. The presentation will focus on the molecular and phenotypic basis of verteporfin PDT-based enhancement of chemotherapeutic efficacy and predictability in complex 3D models and in vivo models, with a particular emphasis on ovarian and pancreatic cancer.
Previous studies have demonstrated that flow-induced shear stress induces a motile and aggressive tumor phenotype in a microfluidic model of 3D ovarian cancer. However, the magnitude and distribution of the hydrodynamic forces that influence this biological modulation on the 3D cancer nodules are not known. We have developed a series of numerical and experimental tools to identify these forces within a 3D microchannel. In this work, we used particle image velocimetry (PIV) to find the velocity profile using fluorescent micro-spheres as surrogates and nano-particles as tracers, from which hydrodynamic forces can be derived. The fluid velocity is obtained by imaging the trajectory of a range of florescence nano-particles (500–800 μm) via confocal microscopy. Imaging was done at different horizontal planes and with a 50 μm bead as the surrogate. For an inlet current rate of 2 μl/s, the maximum velocity at the center of the channel was 51 μm/s. The velocity profile around the sphere was symmetric which is expected since the flow is dominated by viscous forces as opposed to inertial forces. The confocal PIV was successfully employed in finding the velocity profile in a microchannel with a nodule surrogate; therefore, it seems feasible to use PIV to investigate the hydrodynamic forces around 3D biological models.
Targeting the molecular and cellular cues that influence treatment resistance in tumors is critical to effectively treating unresponsive populations of stubborn disease. The informed design of mechanism-based combinations is emerging as increasingly important to targeting resistance and improving the efficacy of conventional treatments, while minimizing toxicity. Photodynamic therapy (PDT) has been shown to synergize with conventional agents and to overcome the evasion pathways that cause resistance. Increasing evidence shows that PDT-based combinations cooperate mechanistically with, and improve the therapeutic index of, traditional chemotherapies. These and other findings emphasize the importance of including PDT as part of comprehensive treatment plans for cancer, particularly in complex disease sites. Identifying effective combinations requires a multi-faceted approach that includes the development of bioengineered cancer models and corresponding image analysis tools. The molecular and phenotypic basis of verteporfin-mediated PDT-based enhancement of chemotherapeutic efficacy and predictability in complex 3D models for ovarian cancer will be presented.
Given the consistently poor prognoses for some of the most difficult-to-treat cancers, rapidly translatable treatment regimens that offer improvements in outcomes are much needed. The repurposing of FDA approved non-cancer drugs presents an opportunity to design clinically feasible, novel combinations of therapies with a mechanistic rationale, to overcome resistance and survival pathways that render many current treatments ineffective. Tetracyclines are a class of antibiotics that demonstrate potential for such repurposing, as they have also been shown by others to affect a wide range of targets in cancer. Notably, the unique structure of tetracyclines allows them to act through both light activated and non-light mediated mechanisms. While light activation of tetracyclines can result in singlet oxygen production, their non-light mediated targets include inhibition of DNA repair enzymes and modulation of hypoxia-inducible markers, among others. With these mechanisms in mind, we seek to elucidate the benefit of including tetracyclines as part of an already promising, mechanistically cooperative photochemotherapy combination for ovarian cancer. In ovarian cancer, the dismal rates of recurrence and survival associated with the aggressive disease further emphasize the need to mechanistically reinforce treatments regimens. Thus, the results will highlight insights into the cooperative effect of repurposed tetracyclines on treatment response and molecular markers, both in vitro and in a challenging mouse model of disseminated ovarian cancer.
Biomodulation of cancer cell metabolism represents a promising approach to overcome tumor heterogeneity and poor selectivity, which contribute significantly to treatment resistance. To date, several studies have demonstrated that modulation of cell metabolism including the heme synthesis pathway serves as an elegant approach to improve the efficacy of aminolevulinic acid (ALA) based photodynamic therapy (PDT). However, the ability of biomodulation-enhanced PDT to improve outcomes in low resource settings and to address challenges in treating lethal tumors with exogenous photosensitizers remains underexplored. The ability of vitamin D or methotrexate to enhance PDT efficacy in a carcinogen-induced hamster cheek pouch model of oral squamous cell carcinoma and in 3D cell-based models for pancreatic ductal adenocarcinoma is evaluated. Challenges associated with adapting PDT regimens to low resource settings, understanding the effects of biomodulatory agents on the metabolism of cancer cells, and the differential effects of biomodulatory agents on tumor and stromal cells will be discussed.
It is increasingly evident that the most effective cancer treatments will involve interactive regimens that target multiple non-overlapping pathways, preferably such that each component enhances the others to improve outcomes while minimizing systemic toxicities. Toward this goal, we developed a combination of photodynamic therapy and irinotecan, which mechanistically cooperate with each other, beyond their individual tumor destruction pathways, to cause synergistic reduction in orthotopic pancreatic tumor burden. A three-way mechanistic basis of the observed the synergism will be discussed: (i) PDT downregulates drug efflux transporters to increase intracellular irinotecan levels. (ii) Irinotecan reduces the expression of hypoxia-induced marker, which is upregulated by PDT. (iii) PDT downregulates irinotecan-induced survivin expression to amplify the apoptotic and anti-proliferative effects. The clinical translation potential of the combination will also be highlighted.
A major barrier to treating advanced-stage cancers is heterogeneity in the responsiveness of metastatic disease to conventional therapies leading to resistance and treatment failure. Photodynamic therapy (PDT) has been shown to synergize with conventional agents and to overcome the evasion pathways that cause resistance. Developing PDT-based combinations that target resistant tumor populations and cooperate mechanistically with conventional agents is an increasingly promising approach to improve therapeutic efficacy while minimizing toxicity, particularly in complex disease sites. Identifying the molecular, cellular, and microenvironmental cues that lead to heterogeneity and treatment resistance is critical to developing strategies to target unresponsive regions of stubborn disease. Cell-based research platforms that integrate key microenvironmental cues are emerging as increasingly important tools to improve the translational efficiency of new agents, and to design combination regimens. Among the challenges associated with developing and scaling complex cell-based screening platforms is the need to integrate, and balance, biological relevance with appropriate, high-content imaging routines that provide meaningful quantitative readouts of therapeutic response. The benefits and challenges associated with deriving meaningful insights from complex cell-based models will be presented, with a particular emphasis on overcoming chemoresistance mediated by physical stress and communication with stromal partners (e.g. tumor endothelial cells, which are emerging as dynamic regulators of treatment resistance) using PDT-based combinations.
Photodynamic therapy (PDT) is a light-based modality that shows promise for adaptation and implementation as a cancer treatment technology in resource-limited settings. In this context PDT is particularly well suited for treatment of pre-cancer and early stage malignancy of the oral cavity, that present a major global health challenge, but for which light delivery can be achieved without major infrastructure requirements. In recent reports we demonstrated that a prototype low-cost batterypowered 635nm LED light source for ALA-PpIX PDT achieves tumoricidal efficacy in vitro and vivo, comparable to a commercial turn-key laser source. Here, building on these reports, we describe the further development of a prototype PDT device to enable intraoral light delivery, designed for ALA- PDT treatment of precancerous and cancerous lesions of the oral cavity. We evaluate light delivery via fiber bundles and customized 3D printed light applicators for flexible delivery to lesions of varying size and position within the oral cavity. We also briefly address performance requirements (output power, stability, and light delivery) and present validation of the device for ALA-PDT treatment in monolayer squamous carcinoma cell cultures.
In view of the increase in cancer-related mortality rates in low- to middle-income countries (LMIC), there is an urgent need to develop economical therapies that can be utilized at minimal infrastructure institutions. Photodynamic therapy (PDT), a photochemistry-based treatment modality, offers such a possibility provided that low-cost light sources and photosensitizers are available. In this proof-of-principle study, we focus on adapting the PDT light source to a low-resource setting and compare an inexpensive, portable, battery-powered light-emitting diode (LED) light source with a standard, high-cost laser source. The comparison studies were performed in vivo in a xenograft murine model of human squamous cell carcinoma subjected to 5-aminolevulinic acid-induced protoporphyrin IX PDT. We observed virtually identical control of the tumor burden by both the LED source and the standard laser source. Further insights into the biological response were evaluated by biomarker analysis of necrosis, microvessel density, and hypoxia [carbonic anhydrase IX (CAIX) expression] among groups of control, LED-PDT, and laser-PDT treated mice. There is no significant difference in the percent necrotic volume and CAIX expression in tumors that were treated with the two different light sources. These encouraging preliminary results merit further investigations in orthotopic animal models of cancers prevalent in LMICs.
Common methods to characterize treatment efficacy based on morphological imaging may misrepresent outcomes and exclude effective therapies. Using a three-dimensional model of ovarian cancer, two functional treatment response metrics are used to evaluate photodynamic therapy (PDT) efficacy: total volume, calculated from viable and nonviable cells, and live volume, calculated from viable cells. The utility of these volume-based metrics is corroborated using independent reporters of photodynamic activity: viability, a common fluorescence-based ratiometric analysis, and photosensitizer photobleaching, which is characterized by a loss of fluorescence due in part to the production of reactive species during PDT. Live volume correlated with both photobleaching and viability, suggesting that it was a better reporter of PDT efficacy than total volume, which did not correlate with either metric. Based on these findings, live volume and viability are used to probe the susceptibilities of tumor populations to a range of PDT dose parameters administered using 0.25, 1, and 10 μM benzoporphyrin derivative (BPD). PDT with 0.25 μM BPD produces the most significant reduction in live volume and viability and mediates a substantial shift toward small nodules. Increasingly sophisticated bioengineered models may complement current treatment planning approaches and provide unique opportunities to critically evaluate key parameters including metrics of therapeutic response.
Advanced stage ovarian carcinoma is characterized by poor prognosis and peritoneal micronodules that exhibit treatment
resistance. This is partially due to interactions between multifocal disease and the tumor microenvironment, which
includes tumor endothelial cells (TECs) and extracellular matrix components (ECM). Here we describe the development
of a three-dimensional model of ovarian cancer that incorporates TECs and ECM. A comparison of several
methodologies to generate endothelialized ovarian micronodules along with a preliminary physical characterization is
described. This model will allow for detailed investigation of tumor-stroma interactions and how they impact disease
progression and treatment response.
The dismal survival statistics for pancreatic cancer are due in large part to the notoriously poor response of these tumors
to conventional therapies. Here we examine the ability of photodynamic therapy (PDT), using the photosensitizer
verteporfin to enhance of the efficacy of traditional chemotherapy agents and/or eradicate populations that are nonresponsive
to these agents. Using an in vitro 3D tumor model of pancreatic cancer combined with an imaging-based
methodology for quantifying therapeutic response, we specifically examine PDT combination treatments with
gemcitabine and oxaliplatin. We show that our 3D cell culture model recapitulates a more clinically-relevant dose
response to gemcitabine, with minimal cytotoxic response even at high doses. The same cultures exhibit modest response
to PDT treatments, but are also less responsive to this modality relative to our previous reports of monolayer dose
response in the same cells. In combination we found no evidence of any enhancement in efficacy of either PDT or
gemcitabine treatment regardless of dose or sequence (PDT before gemcitabine, or gemcitabine before PDT). However,
when oxaliplatin chemotherapy was administered immediately after treatment with 2.5J/cm2 verteporfin PDT, there was
an observable enhancement in response that appears to exceed the additive combination of either treatment alone and
suggesting there may be a synergistic interaction. This observation is consistent with previous reports of enhanced
efficacy in combinations of PDT with platinum-based chemotherapy. The contrast in results between the combinations
examined here underscores the need for rational design of mechanism-based PDT combinations.
Photodynamic therapy (PDT) dosimetry is an active area of study that is motivated by the need to reliably predict
treatment outcomes. Implicit dosimetric parameters, such as photosensitizer (PS) photobleaching, may indicate PDT
efficacy and could establish a framework to provide patient-customized PDT. Here, tumor destruction and
benzoporphryin-derivative (BPD) photobleaching are characterized by systematically varying BPD-light combinations
to achieve fixed PDT doses (M * J * cm-2) in a three-dimensional (3D) model of micrometastatic ovarian cancer (OvCa).
It is observed that the BPD-light parameters used to construct a given PDT dose significantly impact nodule viability and
BPD photobleaching. As a result, PDT dose, when measured by the product of BPD concentration and fluence, does not
reliably predict overall efficacy. A PDT dose metric that incorporates a term for BPD photobleaching more robustly
predicts PDT efficacy at low concentrations of BPD. These results suggest that PDT dose metrics that are informed by
implicit approaches to dosimetry could improve the reliability of PDT-based regimens and provide opportunities for
patient-specific treatment planning.
Pancreatic ductal adenocarcinoma is a lethal disease that is often unresectable by the time of diagnosis and is typically
non-responsive to chemo- and radiotherapy, resulting in a five year survival of only 3%. Tumors of the pancreas are
characterized by a dense fibrous stroma rich in extracellular matrix proteins, which is implicated in poor therapeutic
response, though its precise roles remain poorly understood. Indeed, while the use of therapeutics that target the stroma
is an emerging paradigm in the clinical management of this disease, the primary focus of such efforts is to enhance drug
penetration through dense fibrous stroma and it is unclear to what extent the characteristically rigid stroma of pancreatic
tumors imparts drug resistance by acting as a complex signaling partner, or merely as a physical barrier for drug
delivery. Here we use 3D in vitro co-cultures of pancreatic cancer cells and normal human fibroblasts as a model system
to study heterotypic interactions between these populations. Leveraging this in vitro model along with image-based
methods for quantification of growth and therapeutic endpoints, we characterize these co-cultures and examine the role
of verteporfin-based photodynamic therapy (PDT) for targeting tumor-fibroblast interactions in pancreatic tumors.
KEYWORDS: Tumors, 3D modeling, Tumor growth modeling, Photodynamic therapy, Cancer, Animal model studies, 3D image processing, Systems modeling, In vitro testing, 3D displays
The development and translational potential of therapeutic strategies for cancer is limited, in part, by a lack of biological
models that capture important aspects of tumor growth and treatment response. It is also becoming increasingly evident
that no single treatment will be curative for this complex disease. Rationally-designed combination regimens that impact
multiple targets provide the best hope of significantly improving clinical outcomes for cancer patients. Rapidly
identifying treatments that cooperatively enhance treatment efficacy from the vast library of candidate interventions is
not feasible, however, with current systems. There is a vital, unmet need to create cell-based research platforms that
more accurately mimic the complex biology of human tumors than monolayer cultures, while providing the ability to
screen therapeutic combinations more rapidly than animal models. We have developed a highly reproducible in vitro
three-dimensional (3D) tumor model for micrometastatic ovarian cancer (OvCa), which in conjunction with quantitative
image analysis routines to batch-process large datasets, serves as a high throughput reporter to screen rationally-designed
combination regimens. We use this system to assess mechanism-based combination regimens with photodynamic
therapy (PDT), which sensitizes OvCa to chemo and biologic agents, and has shown promise in clinic trials. We show
that PDT synergistically enhances carboplatin efficacy in a sequence dependent manner. In printed heterocellular
cultures we demonstrate that proximity of fibroblasts enhances 3D tumor growth and investigate co-cultures with
endothelial cells. The principles described here could inform the design and evaluation of mechanism-based therapeutic
options for a broad spectrum of metastatic solid tumors.
Three-dimensional in vitro tumor models have emerged as powerful research tools in cancer biology, though the vast
potential of these systems as high-throughput, biologically relevant reporters of treatment response has yet to be
adequately explored. Here, building on previous studies, we demonstrate the utility of using 3D models for ovarian and
pancreatic cancers in conjunction with quantitative image processing to reveal aspects of growth behavior and treatment
response that would not be evident without either modeling or quantitative analysis component. In this report we
specifically focus on recent improvements in the imaging component of this integrative research platform and emphasize
analysis to establish reproducible growth properties in 3D tumor arrays, a key consideration in establishing the utility of
this platform as a reliable reporter of therapeutic response. Building on previous studies using automated segmentation
of low magnification image fields containing large numbers of nodules to study size dependent treatment effects, we
introduce an improvement to this method using multiresolution decomposition to remove gradient background from
transmitted light images for more reliable feature identification. This approach facilitates the development of a new
treatment response metric, disruption fraction (Dfrac), which quantifies dose dependent distribution shifts from nodular
fragmentation induced by cytotoxic therapies. Using this approach we show that PDT treatment is associated with
significant dose-dependent increases in Dfrac, while this is not observed with carboplatin treatment. The ability to
quantify this response to therapy could play a key role in design of combination regimens involving these two
modalities.
Advances in imaging and spectroscopic technologies have enabled the optimization of many therapeutic modalities in
cancer and noncancer pathologies either by earlier disease detection or by allowing therapy monitoring. Amongst the
therapeutic options benefiting from developments in imaging technologies, photodynamic therapy (PDT) is exceptional.
PDT is a photochemistry-based therapeutic approach where a light-sensitive molecule (photosensitizer) is activated with
light of appropriate energy (wavelength) to produce reactive molecular species such as free radicals and singlet oxygen.
These molecular entities then react with biological targets such as DNA, membranes and other cellular components to
impair their function and lead to eventual cell and tissue death. Development of PDT-based imaging also provides a
platform for rapid screening of new therapeutics in novel in vitro models prior to expensive and labor-intensive animal
studies. In this study we demonstrate how an imaging platform can be used for strategizing a novel combination
treatment strategy for multifocal ovarian cancer. Using an in vitro 3D model for micrometastatic ovarian cancer in
conjunction with quantitative imaging we examine dose and scheduling strategies for PDT in combination with
carboplatin, a chemotherapeutic agent presently in clinical use for management of this deadly form of cancer.
Three-dimensional tumor models have emerged as valuable in vitro research tools, though the power of such systems as quantitative reporters of tumor growth and treatment response has not been adequately explored. We introduce an approach combining a 3-D model of disseminated ovarian cancer with high-throughput processing of image data for quantification of growth characteristics and cytotoxic response. We developed custom MATLAB routines to analyze longitudinally acquired dark-field microscopy images containing thousands of 3-D nodules. These data reveal a reproducible bimodal log-normal size distribution. Growth behavior is driven by migration and assembly, causing an exponential decay in spatial density concomitant with increasing mean size. At day 10, cultures are treated with either carboplatin or photodynamic therapy (PDT). We quantify size-dependent cytotoxic response for each treatment on a nodule by nodule basis using automated segmentation combined with ratiometric batch-processing of calcein and ethidium bromide fluorescence intensity data (indicating live and dead cells, respectively). Both treatments reduce viability, though carboplatin leaves micronodules largely structurally intact with a size distribution similar to untreated cultures. In contrast, PDT treatment disrupts micronodular structure, causing punctate regions of toxicity, shifting the distribution toward smaller sizes, and potentially increasing vulnerability to subsequent chemotherapeutic treatment.
Ovarian epithelial cancer has a high morbidity due to its propensity to metastasize onto surfaces in the abdomen. In order to effectively treat these metastatic lesions with photodynamic therapy (PDT), it is critical to understand the detailed dynamics of the PDT response. 3D in vitro models of ovarian cancer are a promising system for studying the response to PDT of these lesions, as they replicate the size, appearance, and characteristics of metastatic disease observed in the clinic. An ideal approach capable of non-purturbative, 3D imaging of this model is optical coherence tomography (OCT). An ultrahigh resolution time-lapse OCT (TL-OCT) system was used to visualize the photodynamic therapeutic
response in the hours and days following treatment. Tumor nodules were observed to experience rapid cell death within
the first 24 hours post-treatment using benzophorphyrin derivative monoacid A (BPD), characterized by structural breakdown of the model nodules. Highly scattering bodies were observed with OCT contrast to form at the periphery of the tumor nodules. These highly scattering moieties were identified as apoptotic bodies, indicating that OCT is capable of tracking the PDT-induced apoptosis in real-time without the need for labels.
We introduce a new platform to study treatment response in adherent micrometastatic ovarian cancer, combining an in vitro 3D model, with custom quantitative analysis routines to report growth and cytotoxic response in large sets of image data. OVCAR-5 human ovarian cancer cells were grown on a bed of Growth Factor Reduced MatrigelTM (GFR MatrigelTM). Using batch analysis routines to analyze longitudinal image data we show that in vitro tumor growth leads to a reproducible log-normal size distribution with two well-defined peaks. These distinct growth modes correspond to a
population with approximately constant diameter of 20μm over the time probed, while the other peak corresponds to a more rapidly assembling sub-distribution of micronodules which shifts towards larger peak center positions with mean equivalent diameters of 92μm, 120μm and 150μm at days 7, 10 and 17 following plating. At day 10, 3D and monolayer cultures were treated with a regimen of either carboplatin or photodynamic therapy. Using a quantitative fluorescence imaging approach we report dose response curves and demonstrate that 3D nodules are significantly less sensitive to treatment than the same cells grown in monolayer. 3D cultures subject to 5J/cm2 PDT (250nM BPD-MA) exhibited a
mean viability of 80% (95% CI = 73% to 82%) relative to no treatment control. 3D cultures subject to carboplatin treatment at 100μM concentration exhibited a mean viability of 92% (95% CI =86% to 97%). A combination treatment of 5J/cm2 PDT followed by 100μM carboplatin yielded an enhanced cytotoxic effect with mean viability of 46%, 95% confidence interval (CI) = (35 % to 46%).
Pancreatic cancer is an aggressive disease with a poor prognosis, usually treated with chemoradiation therapy.
Interstitial photodynamic therapy is a potentially effective adjuvant treatment that is under development. In the current
study, two orthotopic pancreatic cancer models (AsPC-1 and Panc-1), have been characterized with respect to growth
rates, morphology and liposomal drug (Verteporfin) uptake and distribution in SCID mice. Fluorescence of Verteporfin
was measured in liver and tumor in vivo using a PDT fluorescence dosimeter with measurements taken before and up to
one hour after tail vein injection. Fluorescence reached a plateau by about 15 minutes and did not decrease over the first
hour. At time points from 15 minutes to 24 hrs, the internal organs (kidney, spleen, pancreas, tumor, muscle, lung, liver,
and skin were excised and scanned on a Typhoon imager. The ratio of fluorescence in tumor versus normal tissues was
analyzed with image processing, calculated at each time point and compared to in vivo results. Tissue distribution of
Verteporfin in relation to functional vasculature marked by DiOc7 was carried out on frozen sections. Final analysis will
result in determination of the ideal time point to administer light to achieve maximum tumor destruction while
preserving normal tissue.
Our laboratory has constructed a custom fluorescence microendoscope for detecting and monitoring tumor nodules in a
mouse model of metastatic ovarian carcinoma (OVCA). The microendoscope is being applied for tumor recognition and
for quantifying tumor burden reduction following photodynamic therapy (PDT). Benzoporphyrin derivative monoacid
ring A (BPD-MA), a photosensitizing agent for PDT, is administered to the mice and imaged with the microendoscope
prior to PDT. BPD-MA fluorescence is a convenient means for locating tumor sites and quantifying tumor burden
(despite the fact that BPD-MA is a non-targeted contrast agent). The miniature, flexible microendoscope probe is
delivered via a 14-gauge catheter for imaging metastases along the outer surfaces of the internal organs and the inner
walls of the peritoneal cavity. The minimal invasiveness of this approach facilitates frequent imaging of the mice in
order to monitor cancer progression and treatment response. We present promising data for intravital imaging of
treatment response following PDT and new developments in the microendoscope instrumentation for improved image
quality.
Pancreatic cancer generally has very poor prognosis, with less than 4% survival at 5 years after diagnosis. This dismal survival rate is in part due to the aggressive nature of the adenocarcinoma, leading to a late-stage at diagnosis and exhibits resistance to most therapies. Photodynamic therapy (PDT) is a model cellular and vascular therapy agent, which uses light activation of the delivered drug to photosensitize the local cellular millieu. We suggest that interstitial verteporfin (benzoporphyrin derivative monoacid ring A) PDT has the potential to be an adjuvant therapy to the commonly used Gemcitabine chemotherapy. In the current study, an orthotopic pancreatic cancer model (Panc-1) has undergone interstitial verteporfin PDT (40 J/cm with verteporfin and 40 J/cm without verteporfin). Prior to PDT, magnetic resonance (MR) imaging was used to determine the location and size of the tumor within the pancreas, allowing accurate placement of the diffusing fiber. The success of therapy was monitored in vivo by assessing the total tumor and vascular perfusion volumes 24 hours pre- and 48 hours post-PDT. Total tumor and vascular perfusion volumes were determined using T2 weighted (T2W) and Gd-DTPA difference T1 weighted (T1W) turbo spin echo (TSE) MR imaging sequences, respectively. The validity of the in vivo imaging for therapeutic response was confirmed by ex vivo fluorescence and histological staining of frozen tissue sections. The ex vivo DiOC7(3) fluorescence analysis correlates well with the information provided from the MR images, indicating that MR imaging will be a successful surrogate marker for interstitial PDT.
Photodynamic therapy (PDT) is a viable treatment option for a wide range of applications, including oncology, dermatology, and ophthalmology. Singlet oxygen is believed to play a key role in the efficacy of PDT, and on-line monitoring of singlet oxygen during PDT could provide a methodology to establish and customize the treatment dose clinically. This work is the first report of monitoring singlet oxygen luminescence in vivo in human subjects during PDT, demonstrating the correlation of singlet oxygen levels during PDT with the post-PDT photobiological response.
Cytokines are important messengers in cell-to-cell communications that regulate vital cellular and physiological
processes, and play an important role in defining the diagnosis, prognosis and treatment response in various diseases.
Although current ex vivo biochemical assays for cytokine quantitation are useful, their capabilities for studying dynamic
cytokine expression in living systems are limited. Optical molecular imaging technology can help probe the
spatiotemporal dynamics of cytokine expression in vivo and in real-time. We developed an in vivo optical molecular
imaging strategy for monitoring one of these cytokines, the vascular endothelial growth factor (VEGF). With the
imaging strategy, changes in tumoral VEGF concentration following cobalt chloride treatment and photodynamic
therapy (PDT) were monitored. This was the first systematic study to test the feasibility of VEGF-targeted molecular
imaging, and can potentially set the basis for online monitoring of cytokines that will help develop effective tools for
diagnosis, prognosis, treatment planning and monitoring.
Recent advances in light sources, detectors and other optical imaging technologies coupled with the development of
novel optical contrast agents have enabled real-time, high resolution, in vivo monitoring of molecular targets. Noninvasive
monitoring of molecular targets can help optimize photodynamic therapy (PDT) by providing the capabilities to
monitor the efficacy of treatment. Our lab has developed optical imaging technologies to investigate a wide range of
molecular, physiological and morphological responses to photodynamic therapy (PDT). With the idea that drug delivery
to the different compartments in the tumor is an important determinant of the treatment effect, we studied drug delivery
in vitro and in vivo using optical imaging tools. A molecular specific contrast agent that targets the vascular endothelial
growth factor (VEGF) was developed to monitor the changes in the protein expression following PDT. We also studied
the PDT-induced physiological changes in vascular permeability and metastasis with in vivo imaging.
Recent advances in light sources, detectors and other optical imaging technologies coupled with the development of novel optical contrast agents have enabled real-time, high resolution, in vivo monitoring of molecular targets. Noninvasive monitoring of molecular targets is particularly relevant to photodynamic therapy (PDT), including the delivery of photosensitizer in the treatment site and monitoring of molecular and physiological changes following treatment. Our lab has developed optical imaging technologies to investigate these various aspects of photodynamic therapy (PDT). We used a laser scanning confocal microscope to monitor the pharmacokinetics of various photosensitizers in in vitro as well as ex vivo samples, and developed an intravital fluorescence microscope to monitor photosensitizer delivery in vivo in small animals. A molecular specific contrast agent that targets the vascular endothelial growth factor (VEGF) was developed to monitor the changes in the protein expression following PDT. We were then able to study the physiological changes due to post-treatment VEGF upregulation by quantifying vascular permeability with in vivo imaging.
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