Modeling of tumor response to macrophage and T lymphocyte interactions in the liver metastatic microenvironment.

The dynamic interactions between macrophages and T-lymphocytes in the tumor microenvironment exert both antagonistic and synergistic functions affecting tumor growth. Extensive experimental effort has been expended to investigate immunotherapeutic strategies targeting macrophage polarization as well as T-cell activation with the goal to promote tumor cell killing and cancer elimination. However, these interactions remain poorly understood, and cancer immunotherapeutic strategies are often disappointing. The complex system encompassing innate and adaptive immune cell activity in response to tumor growth could benefit from a systems perspective built upon mathematical modeling. This study develops a modeling system to help evaluate the effects of macrophage and T-lymphocyte interactions on tumor growth. The system enables simulating the combined cytotoxic and tumor-promoting interactions of these two immune cell populations in a vascularized organ microenvironment, such as in liver metastases. A hypothetical immunotherapeutic strategy is simulated to increase the number of tumor-suppressive (M1-phenotype) vs. tumor-promoting (M2-phenotype) macrophages to gauge their effects on CD8+ T-cells and CD4+ T-helper cells, which in turn affect the macrophage functions. The results highlight the dynamic interactions between macrophages and T-lymphocytes in the tumor microenvironment and show that with the chosen set of parameter values, the overall cytotoxic effect from macrophages and T-lymphocytes obtained by driving the M1:M2 ratio higher could saturate and fail to achieve tumor regression. Further expansion of this modeling platform to include additional tumor-immune cell interactions, coupled with parameters representing particular tumor characteristics, could enable systematic evaluation of immunotherapeutic strategies tailored to patient-tumor specific conditions, including metastatic disease.

Nonlinear response to cancer nanotherapy due to macrophage interactions revealed by mathematical modeling and evaluated in a murine model via CRISPR-modulated macrophage polarization.

Tumor-associated macrophages (TAMs) have been shown to both aid and hinder tumor growth, with patient outcomes potentially hinging on the proportion of M1, pro-inflammatory/growth-inhibiting, to M2, growth-supporting, phenotypes. Strategies to stimulate tumor regression by promoting polarization to M1 are a novel approach that harnesses the immune system to enhance therapeutic outcomes, including chemotherapy. We recently found that nanotherapy with mesoporous particles loaded with albumin-bound paclitaxel (MSV-nab-PTX) promotes macrophage polarization towards M1 in breast cancer liver metastases (BCLM). However, it remains unclear to what extent tumor regression can be maximized based on modulation of the macrophage phenotype, especially for poorly perfused tumors such as BCLM. Here, for the first time, a CRISPR system is employed to permanently modulate macrophage polarization in a controlled in vitro setting. This enables the design of 3D co-culture experiments mimicking the BCLM hypovascularized environment with various ratios of polarized macrophages. We implement a mathematical framework to evaluate nanoparticle-mediated chemotherapy in conjunction with TAM polarization. The response is predicted to be not linearly dependent on the M1:M2 ratio. To investigate this phenomenon, the response is simulated via the model for a variety of M1:M2 ratios. The modeling indicates that polarization to an all-M1 population may be less effective than a combination of both M1 and M2. Experimental results with the CRISPR system confirm this model-driven hypothesis. Altogether, this study indicates that response to nanoparticle-mediated chemotherapy targeting poorly perfused tumors may benefit from a fine-tuned M1:M2 ratio that maintains both phenotypes in the tumor microenvironment during treatment.

Modeling of Combination Chemotherapy and Immunotherapy for Lung Cancer.

Cancer has traditionally been studied from a basic science perspective, focusing on the underlying biology, physiology, and biochemistry. Engineering has supplemented this effort via the development of technology, e.g., microscopy. In recent times, engineering and the physical sciences have positioned themselves as approaches on par with the traditional basic sciences to tackle the study of cancer. Mathematical modeling and computational simulation have become key elements of this engineering-focused effort, evaluating the growth of tumors and their response to therapy as problems that could benefit from a systems analysis perspective. Building upon previous work in this field, here is developed a modeling framework to help evaluate the response of tumors to the combination of chemotherapy and immunotherapy, focusing on non-small cell lung cancer (NSCLC). With system parameters set with patient tumor-specific parameters, the longer term goal of this work is to advance personalized cancer treatment.

Pharmacokinetic/pharmacodynamic modeling of combination-chemotherapy for lung cancer.

Chemotherapy for non-small cell lung cancer (NSCLC) typically involves a doublet regimen for a number of cycles. For any particular patient, a course of treatment is usually chosen from a large number of combinational protocols with drugs in concomitant or sequential administration. In spite of newer drugs and protocols, half of patients with early disease will live less than five years and 95% of those with advanced disease survive for less than one year. Here, we apply mathematical modeling to simulate tumor response to multiple drug regimens, with the capability to assess maximum tolerated dose (MTD) as well as metronomic drug administration. We couple pharmacokinetic-pharmacodynamic intracellular multi-compartment models with a model of vascularized tumor growth, setting input parameters from in vitro data, and using the models to project potential response in vivo. This represents an initial step towards the development of a comprehensive virtual system to evaluate tumor response to combinatorial drug regimens, with the goal to more efficiently identify optimal course of treatment with patient tumor-specific data. We evaluate cisplatin and gemcitabine with clinically-relevant dosages, and simulate four treatment NSCLC scenarios combining MTD and metronomic therapy. This work thus establishes a framework for systematic evaluation of tumor response to combination chemotherapy. The results with the chosen parameter set indicate that although a metronomic regimen may provide advantage over MTD, the combination of these regimens may not necessarily offer improved response. Future model evaluation of chemotherapy possibilities may help to assess their potential value to obtain sustained NSCLC regression for particular patients, with the ultimate goal of optimizing multiple-drug chemotherapy regimens in clinical practice.

Mathematical modeling of tumor-associated macrophage interactions with the cancer microenvironment.

BACKGROUND: Immuno-oncotherapy has emerged as a promising means to target cancer. In particular, therapeutic manipulation of tumor-associated macrophages holds promise due to their various and sometimes opposing roles in tumor progression. It is established that M1-type macrophages suppress tumor progression while M2-types support it. Recently, Tie2-expressing macrophages (TEM) have been identified as a distinct sub-population influencing tumor angiogenesis and vascular remodeling as well as monocyte differentiation. METHODS: This study develops a modeling framework to evaluate macrophage interactions with the tumor microenvironment, enabling assessment of how these interactions may affect tumor progression. M1, M2, and Tie2 expressing variants are integrated into a model of tumor growth representing a metastatic lesion in a highly vascularized organ, such as the liver. Behaviors simulated include M1 release of nitric oxide (NO), M2 release of growth-promoting factors, and TEM facilitation of angiogenesis via Angiopoietin-2 and promotion of monocyte differentiation into M2 via IL-10. RESULTS: The results show that M2 presence leads to larger tumor growth regardless of TEM effects, implying that immunotherapeutic strategies that lead to TEM ablation may fail to restrain growth when the M2 represents a sizeable population. As TEM pro-tumor effects are less pronounced and on a longer time scale than M1-driven tumor inhibition, a more nuanced approach to influence monocyte differentiation taking into account the tumor state (e.g., under chemotherapy) may be desirable. CONCLUSIONS: The results highlight the dynamic interaction of macrophages within a growing tumor, and, further, establish the initial feasibility of a mathematical framework that could longer term help to optimize cancer immunotherapy.

Development of Halofluorochromic Polymer Nanoassemblies for the Potential Detection of Liver Metastatic Colorectal Cancer Tumors Using Experimental and Computational Approaches.

PURPOSE: To develop polymer nanoassemblies (PNAs) modified with halofluorochromic dyes to allow for the detection of liver metastatic colorectal cancer (CRC) to improve therapeutic outcomes. METHODS: We combine experimental and computational approaches to evaluate macroscopic and microscopic PNA distributions in patient-derived xenograft primary and orthotropic liver metastatic CRC tumors. Halofluorochromic and non-halofluorochromic PNAs (hfPNAs and n-hfPNAs) were prepared from poly(ethylene glycol), fluorescent dyes (Nile blue, Alexa546, and IR820), and hydrophobic groups (palmitate), all of which were covalently tethered to a cationic polymer scaffold [poly(ethylene imine) or poly(lysine)] forming particles with an average diameter < 30 nm. RESULTS: Dye-conjugated PNAs showed no aggregation under opsonizing conditions for 24 h and displayed low tissue diffusion and cellular uptake. Both hfPNAs and n-hfPNAs accumulated in primary and liver metastatic CRC tumors within 12 h post intravenous injection. In comparison to n-hfPNAs, hfPNAs fluoresced strongly only in the acidic tumor microenvironment (pH < 7.0) and distinguished small metastatic CRC tumors from healthy liver stroma. Computational simulations revealed that PNAs would steadily accumulate mainly in acidic (hypoxic) interstitium of metastatic tumors, independently of the vascularization degree of the tissue surrounding the lesions. CONCLUSION: The combined experimental and computational data confirms that hfPNAs detecting acidic tumor tissue can be used to identify small liver metastatic CRC tumors with improved accuracy.

Macrophage Polarization Contributes to the Anti-Tumoral Efficacy of Mesoporous Nanovectors Loaded with Albumin-Bound Paclitaxel.

Therapies targeted to the immune system, such as immunotherapy, are currently shaping a new, rapidly developing branch of promising cancer treatments, offering the potential to change the prognosis of previously non-responding patients. Macrophages comprise the most abundant population of immune cells in the tumor microenvironment (TME) and can undergo differentiation into functional phenotypes depending on the local tissue environment. Based on these functional phenotypes, tumor-associated macrophages (TAMs) can either aid tumor progression (M2 phenotype) or inhibit it (M1 phenotype). Presence of M2 macrophages and a high ratio of M2/M1 macrophages in the TME are clinically associated with poor prognosis in many types of cancers. Herein, we evaluate the effect of macrophage phenotype on the transport and anti-cancer efficacy of albumin-bound paclitaxel (nAb-PTX) loaded into porous silicon multistage nanovectors (MSV). Studies in a coculture of breast cancer cells (3D-spheroid) with macrophages and in vivo models were conducted to evaluate the therapeutic efficacy of MSV-nAb-PTX as a function of macrophage phenotype. Association with MSV increased drug accumulation within the macrophages and the tumor spheroids, shifting the inflammation state of the TME toward the pro-inflammatory, anti-tumorigenic milieu. Additionally, the treatment increased macrophage motility toward cancer cells, promoting the active transport of therapeutic nanovectors into the tumor lesion. Consequently, apoptosis of cancer cells was increased and proliferation decreased in the MSV-nAb-PTX-treated group as compared to controls. The results also confirmed that the tested system shifts the macrophage differentiation toward an M1 phenotype, possessing an anti-proliferative effect toward the breast cancer cells. These factors were further incorporated into a mathematical model to help analyze the synergistic effect of the macrophage polarization state on the efficacy of MSV-nAb-PTX in alleviating hypovascularized tumor lesions. In conclusion, the ability of MSV-nAb-PTX to polarize TAM to the M1 phenotype, causing (1) enhanced penetration of the drug-carrying macrophages to the center of the tumor lesion and (2) increased toxicity to tumor cells may explain the increased anti-cancer efficacy of the system in comparison to nAb-PTX and other controls.

Pancreatic adenocarcinoma response to chemotherapy enhanced with non-invasive radio frequency evaluated via an integrated experimental/computational approach.

Although chemotherapy combined with radiofrequency exposure has shown promise in cancer treatment by coupling drug cytotoxicity with thermal ablation or thermally-induced cytotoxicity, limited access of the drug to tumor loci in hypo-vascularized lesions has hampered clinical application. We recently showed that high-intensity short-wave capacitively coupled radiofrequency (RF) electric-fields may reach inaccessible targets in vivo. This non-invasive RF combined with gemcitabine (Gem) chemotherapy enhanced drug uptake and effect in pancreatic adenocarcinoma (PDAC), notorious for having poor response and limited therapeutic options, but without inducing thermal injury. We hypothesize that the enhanced cytotoxicity derives from RF-facilitated drug transport in the tumor microenvironment. We propose an integrated experimental/computational approach to evaluate chemotherapeutic response combined with RF-induced phenotypic changes in tissue with impaired transport. Results show that RF facilitates diffusive transport in 3D cell cultures representing hypo-vascularized lesions, enhancing drug uptake and effect. Computational modeling evaluates drug vascular extravasation and diffusive transport as key RF-modulated parameters, with transport being dominant. Assessment of hypothetical schedules following current clinical protocol for Stage-IV PDAC suggests that unresponsive lesions may be growth-restrained when exposed to Gem plus RF. Comparison of these projections to experiments in vivo indicates that synergy may result from RF-induced cell phenotypic changes enhancing drug transport and cytotoxicity, thus providing a potential baseline for clinically-focused evaluation.

The Tumor Microenvironment as a Barrier to Cancer Nanotherapy.

Although extensive research effort and resources have been dedicated to the development of nanotherapeutics to treat cancer, few formulations have reached clinical application. A major reason is that the large number of parameters available to tune nanotherapy characteristics coupled with the variability in tumor tissue precludes evaluation of complex interactions through experimentation alone. In order to optimize the nanotechnology design and gain further insight into these phenomena, mathematical modeling and computational simulation have been applied to complement empirical work. In this chapter, we discuss modeling work related to nanotherapy and the tumor microenvironment. We first summarize the biology underlying the dysregulated tumor microenvironment, followed by a description of major nano-scale parameters. We then present an overview of the mathematical modeling of cancer nanotherapy, including evaluation of nanotherapy in multi-dimensional tumor tissue, coupling of nanotherapy with vascular flow, modeling of nanotherapy in combination with in vivo imaging, modeling of nanoparticle transport based on in vitro data, modeling of vasculature-bound nanoparticles, evaluation of nanotherapy using pharmacokinetic modeling, and modeling of nano-based hyperthermia. We conclude that an even tighter interdisciplinary effort between biological, material, and physical scientists is needed in order to eventually overcome the tumor microenvironment barrier to successful nanotherapy.

A Computational/Experimental Assessment of Antitumor Activity of Polymer Nanoassemblies for pH-Controlled Drug Delivery to Primary and Metastatic Tumors.

PURPOSE: Polymer nanoassemblies (PNAs) with drug release fine-tuned to occur in acidic tumor regions (pH < 7) while sparing normal tissues (pH = 7.4) were previously shown to hold promise as nanoparticle drug carriers to effectively suppress tumor growth with reduced systemic toxicity. However, therapeutic benefits of pH-controlled drug delivery remain elusive due to complex interactions between the drug carriers, tumor cells with varying drug sensitivity, and the tumor microenvironment. METHODS: We implement a combined computational and experimental approach to evaluate the in vivo antitumor activity of acid-sensitive PNAs controlling drug release in pH 5 ~ 7.4 at different rates [PNA1 (fastest) > PNA2 > PNA3 (slowest)]. RESULTS: Computational simulations projecting the transport, drug release, and antitumor activity of PNAs in primary and metastatic tumor models of colorectal cancer correspond well with experimental observations in vivo. The simulations also reveal that all PNAs could reach peak drug concentrations in tumors at 11 h post injection, while PNAs with slower drug release (PNA2 and PNA3) reduced tumor size more effectively than fast drug releasing PNA1 (24.5 and 20.3 vs 7.5%, respectively, as fraction of untreated control). CONCLUSION: A combined computational/experimental approach may help to evaluate pH-controlled drug delivery targeting aggressive tumors that have substantial acidity.

Enhanced uptake and transport of PLGA-modified nanoparticles in cervical cancer.

BACKGROUND: Uncoordinated cellular proliferation and dysregulated angiogenesis in solid tumors are coupled with inadequate tissue, blood, and lymphatic vascularization. Consequently, tumors are often characterized by hypoxic regions with limited access to vascular-borne substances. In particular, systemically administered nanoparticles (NPs) targeting tumor cells and relying on vascular access to reach tumor tissue can suffer from limited therapeutic efficacy due to inhomogeneous intra-tumor distribution and insufficient cellular internalization of NPs. To circumvent these challenges, NP surfaces can be modified to facilitate tumor interstitial transport and cellular uptake. RESULTS: We create poly(lactic-co-glycolic) acid NPs modified with MPG, polyethylene glycol (PEG), MPG/PEG, and Vimentin (VIM), and evaluate their cellular uptake in 2D (monolayer) cell culture of human cervical carcinoma (HeLa). We compare NP performance by evaluating uptake by non-cancerous vaginal (VK2) cells. We further assess NP interstitial transport in hypo-vascularized lesions by evaluating the effect of the various modifications on NP penetration in 3D cell culture of the HeLa cells. Results show that after 24 h incubation with HeLa cells in monolayer, MPG, MPG/PEG, PEG, and VIM NPs were internalized at 66×, 24×, 30×, and 15× that of unmodified NPs, respectively. In contrast, incubation with VK2 cells in monolayer showed that MPG , MPG/PEG , PEG , and VIM NPs internalized at 6.3×, 4.3×, 12.4×, and 3.0× that of unmodified NPs, respectively. Uptake was significantly enhanced in tumorigenic vs. normal cells, with internalization of MPG NPs by HeLa cells being twice that of PEG NPs by VK2 cells. After 24 h incubation in HeLa 3D cell culture, MPG and MPG/PEGNPs were internalized 2× and 3× compared to PEG and VIM NPs, respectively. Whereas MPG NPs were internalized mostly in the cell culture periphery (1.2×, 1.4×, and 2.7× that of PEG, MPG/PEG, and VIM NPs, respectively), PEG NPs at 250 µm penetrated 2× farther into the tissue culture than MPG NPs. For all NP types, cellular internalization was severely hindered in 3D compared to monolayer. CONCLUSIONS: Although MPG surface modification enhances internalization and uptake in hypo-vascularized cervical tissue culture, coating with PEG reduces this internalization while enhancing penetration. A delivery strategy combining NPs with either modification may balance cellular internalization vs. tissue penetration in hypo-vascularized cervical cancer lesions.

An interdisciplinary computational/experimental approach to evaluate drug-loaded gold nanoparticle tumor cytotoxicity.

AIM: Clinical translation of cancer nanotherapy has largely failed due to the infeasibility of optimizing the complex interaction of nano/drug/tumor/patient parameters. We develop an interdisciplinary approach modeling diffusive transport of drug-loaded gold nanoparticles in heterogeneously-vascularized tumors. MATERIALS & METHODS: Evaluated lung cancer cytotoxicity to paclitaxel/cisplatin using novel two-layer (hexadecanethiol/phosphatidylcholine) and three-layer (with high-density-lipoprotein) nanoparticles. Computer simulations calibrated to in-vitro data simulated nanotherapy of heterogeneously-vascularized tumors. RESULTS: Evaluation of free-drug cytotoxicity between monolayer/spheroid cultures demonstrates a substantial differential, with increased resistance conferred by diffusive transport. Nanoparticles had significantly higher efficacy than free-drug. Simulations of nanotherapy demonstrate 9.5% (cisplatin) and 41.3% (paclitaxel) tumor radius decrease. CONCLUSION: Interdisciplinary approach evaluating gold nanoparticle cytotoxicity and diffusive transport may provide insight into cancer nanotherapy.

Enhanced performance of macrophage-encapsulated nanoparticle albumin-bound-paclitaxel in hypo-perfused cancer lesions.

Hypovascularization in tumors such as liver metastases originating from breast and other organs correlates with poor chemotherapeutic response and higher mortality. Poor prognosis is linked to impaired transport of both low- and high-molecular weight drugs into the lesions and to high washout rate. Nanoparticle albumin-bound-paclitaxel (nAb-PTX) has demonstrated benefits in clinical trials when compared to paclitaxel and docetaxel. However, its therapeutic efficacy for breast cancer liver metastasis is disappointing. As macrophages are the most abundant cells in the liver tumor microenvironment, we design a multistage system employing macrophages to deliver drugs into hypovascularized metastatic lesions, and perform in vitro, in vivo, and in silico evaluation. The system encapsulates nAb-PTX into nanoporous biocompatible and biodegradable multistage vectors (MSV), thus promoting nAb-PTX retention in macrophages. We develop a 3D in vitro model to simulate clinically observed hypo-perfused tumor lesions surrounded by macrophages. This model enables evaluation of nAb-PTX and MSV-nab PTX efficacy as a function of transport barriers. Addition of macrophages to this system significantly increases MSV-nAb-PTX efficacy, revealing the role of macrophages in drug transport. In the in vivo model, a significant increase in macrophage number, as compared to unaffected liver, is observed in mice, confirming the in vitro findings. Further, a mathematical model linking drug release and retention from macrophages is implemented to project MSV-nAb-PTX efficacy in a clinical setting. Based on macrophage presence detected via liver tumor imaging and biopsy, the proposed experimental/computational approach could enable prediction of MSV-nab PTX performance to treat metastatic cancer in the liver.

Simulation of the Protein-Shedding Kinetics of a Fully Vascularized Tumor.

Circulating biomarkers are of significant interest for cancer detection and treatment personalization. However, the biophysical processes that determine how proteins are shed from cancer cells or their microenvironment, diffuse through tissue, enter blood vasculature, and persist in circulation remain poorly understood. Since approaches primarily focused on experimental evaluation are incapable of measuring the shedding and persistence for every possible marker candidate, we propose an interdisciplinary computational/experimental approach that includes computational modeling of tumor tissue heterogeneity. The model implements protein production, transport, and shedding based on tumor vascularization, cell proliferation, hypoxia, and necrosis, thus quantitatively relating the tumor and circulating proteomes. The results highlight the dynamics of shedding as a function of protein diffusivity and production. Linking the simulated tumor parameters to clinical tumor and vascularization measurements could potentially enable this approach to reveal the tumor-specific conditions based on the protein detected in circulation and thus help to more accurately manage cancer diagnosis and treatment.

Computational Modeling of Tumor Response to Drug Release from Vasculature-Bound Nanoparticles.

Systemically injected nanoparticle (NPs) targeting tumor vasculature offer a venue for anti-angiogenic therapies as well as cancer detection and imaging. Clinical application has been limited, however, due to the challenge of elucidating the complex interplay of nanotechnology, drug, and tumor parameters. A critical factor representing the likelihood of endothelial adhesion is the NP vascular affinity, a function of vascular receptor expression and NP size and surface-bound ligand density. We propose a theoretical framework to simulate the tumor response to vasculature-bound drug-loaded NPs and examine the interplay between NP distribution and accumulation as a function of NP vascular affinity, size, and drug loading and release characteristics. The results show that uniform spatial distribution coupled with high vascular affinity is achievable for smaller NPs but not for larger sizes. Consequently, small (100 nm) NPs with high vascular affinity are predicted to be more effective than larger (1000 nm) NPs with similar affinity, even though small NPs have lower drug loading and local drug release compared to the larger NPs. Medium vascular affinity coupled with medium or larger sized NPs is also effective due to a more uniform distribution with higher drug loading and release. Low vascular affinity hampered treatment efficacy regardless of NP size, with larger NPs additionally impeded by heterogeneous distribution and drug release. The results further show that increased drug diffusivity mainly benefits heterogeneously distributed NPs, and would negatively affect efficacy otherwise due to increased wash-out. This model system enables evaluation of efficacy for vascular-targeted drug-loaded NPs as a function of critical NP, drug, and tumor parameters.