Lymph node metastasis and the physicochemical micro-environment of pancreatic ductal adenocarcinoma xenografts

Vascular regional analysis unveils differential responses to anti-angiogenic therapy in pancreatic xenografts through macroscopic photoacoustic imaging

Pancreatic cancer (PC) is a highly lethal malignancy and the third leading cause of cancer deaths in the U.S. Despite major innovations in imaging technologies, there are limited surrogate radiographic indicators to aid in therapy planning and monitoring. Amongst the various imaging techniques Ultrasound-guided photoacoustic imaging (US-PAI) is a promising modality based on endogenous blood (hemoglobin) and blood oxygen saturation (StO 2 ) contrast to monitor response to anti-angiogenic therapies. Adaptation of US-PAI to the clinical realm requires macroscopic configurations for adequate depth visualization, illuminating the need for surrogate radiographic markers, including the tumoral microvessel density (MVD). In this work, subcutaneous xenografts with PC cell lines AsPC-1 and MIA-PaCa-2 were used to investigate the effects of receptor tyrosine kinase inhibitor (sunitinib) treatment on MVD and StO 2 . Through histological correlation, we have shown that regions of high and low vascular density (HVD and LVD) can be identified through frequency domain filtering of macroscopic PA images which could not be garnered from purely global analysis. We utilized vascular regional analysis (VRA) of treatment-induced StO 2 and total hemoglobin (HbT) changes. VRA as a tool to monitor treatment response allowed us to identify potential timepoints of vascular remodeling, highlighting its ability to provide insights into the TME not only for sunitinib treatment but also other anti-angiogenic therapies.

Predictive Design and Analysis of Drug Transport by Multiscale Computational Models Under Uncertainty

Computational modeling of drug delivery is becoming an indispensable tool for advancing drug development pipeline, particularly in nanomedicine where a rational design strategy is ultimately sought. While numerous in silico models have been developed that can accurately describe nanoparticle interactions with the bioenvironment within prescribed length and time scales, predictive design of these drug carriers, dosages and treatment schemes will require advanced models that can simulate transport processes across multiple length and time scales from genomic to population levels. In order to address this problem, multiscale modeling efforts that integrate existing discrete and continuum modeling strategies have recently emerged. These multiscale approaches provide a promising direction for bottom-up in silico pipelines of drug design for delivery. However, there are remaining challenges in terms of model parametrization and validation in the presence of variability, introduced by multiple levels of heterogeneities in disease state. Parametrization based on physiologically relevant in vitro data from microphysiological systems as well as widespread adoption of uncertainty quantification and sensitivity analysis will help address these challenges.

Fluid-sensitive migration mechanisms predict association between metastasis and high interstitial fluid pressure in pancreatic cancer

A remarkable feature in pancreatic cancer is the propensity to metastasize early, even for small, early stage cancers. We use a computer-based pancreatic model to simulate tumor progression behavior where fluid-sensitive migration mechanisms are accounted for as a plausible driver for metastasis. The model has been trained to comply with in vitro results to determine input parameters that characterize the migration mechanisms. To mimic previously studied preclinical xenografts we run the computer model informed with an ensemble of stochastic-generated realizations of unknown parameters related to tumor microenvironment only constrained such that pathological realistic values for interstitial fluid pressure (IFP) are obtained. The in silico model suggests the occurrence of a steady production of small clusters of cancer cells that detach from the primary tumor and form isolated islands and thereby creates a natural prerequisite for a strong invasion into the lymph nodes and venous system. The model predicts that this behavior is associated with high interstitial fluid pressure (IFP), consistent with published experimental findings. The continuum-based model is the first to explain published results for preclinical models which have reported associations between high IFP and high metastatic propensity and thereby serves to shed light on possible mechanisms behind the clinical aggressiveness of pancreatic cancer.

Assessment of Intratumor Heterogeneity in Parametric Dynamic Contrast-Enhanced MR Images: A Comparative Study of Novel and Established Methods

Intratumor heterogeneity is associated with aggressive disease and poor survival rates in several types of cancer. A novel method for assessing intratumor heterogeneity in medical images, named the spatial gradient method, has been developed in our laboratory. In this study, we measure intratumor heterogeneity in K^trans maps derived by dynamic contrast-enhanced magnetic resonance imaging using the spatial gradient method, and we compare the performance of the novel method with that of histogram analyses and texture analyses using the Haralick method. K^trans maps of 58 untreated and sunitinib-treated pancreatic ductal adenocaricoma (PDAC) xenografts from two PDAC models were investigated. Intratumor heterogeneity parameters derived by the spatial gradient method were sensitive to tumor line differences as well as sunitinib-induced changes in intratumor heterogeneity. Furthermore, the parameters provided additional information to the median value and were not severely affected by imaging noise. The parameters derived by histogram analyses were insensitive to spatial heterogeneity and were strongly correlated to the median value, and the Haralick features were severely influenced by imaging noise and did not differentiate between untreated and sunitinib-treated tumors. The spatial gradient method was superior to histogram analyses and Haralick features for assessing intratumor heterogeneity in K^trans maps of untreated and sunitinib-treated PDAC xenografts, and can possibly be used to assess intratumor heterogeneity in other medical images and to evaluate effects of other treatments as well.

In silico investigations of intratumoral heterogeneous interstitial fluid pressure

Recent preclinical studies have shown that interstitial fluid pressure (IFP) within tumors can be heterogeneous Andersen et al. (2019). In that study tumors of two xenograft models, respectively, HL-16 cervical carcinoma and Panc-1 pancreatic carcinoma, were investigated. Significant heterogeneity in IFP was reported and it was proposed that this was associated with division of tissue into compartments separated by thick connective tissue bands for the HL-16 tumors and with dense collagen-rich extracellular matrix for the Panc-1 tumors. The purpose of the current work is to explore these experimental observations by using in silico generated tumor models. We consider a mathematical multiphase model which accounts for tumor cells, fibroblasts and interstitial fluid. The model has been trained to comply with experimental in vitro results reported in Shieh et al. (2011) which has identified autologous chemotaxis, ECM remodeling, and cell-fibroblast interaction as drivers for invasive tumor cell behavior. The in silico model is informed with parameters that characterize the leaky intratumoral vascular network, the peritumoral lymphatics which collect the fluid, and the density of ECM as represented through the hydraulic conductivity of the interstitial space. Heterogeneous distribution of solid stress may result in heterogeneous compression of blood vessels and, thus, heterogeneous vascular density inside the tumor. To mimic this we expose the in silico tumor to an intratumoral vasculature whose net effect of density of blood vesssels and vessel wall conductivity is varied through a 2D Gaussian variogram constrained such that the resulting IFPs lie within the range as reported from the preclinical study. The in silico cervical carcinoma model illustrates that sparse ECM was associated with uniform intratumoral IFP in spite of heterogeneous microvascular network, whereas compartment structures resulted in more heterogeneous IFP. Similarly, the in silico pancreatic model shows that heterogeneity in the microvascular network combined with dense ECM structure prevents IFP to even out and gives rise to heterogeneous IFP. The computer model illustrates how a heterogeneous invasive front might form where groups of tumor cells detach from the primary tumor and form isolated islands, a behavior which is natural to associate with metastatic propensity. However, unlike experimental studies, the current version of the in silico model does not show an association between metastatic propensity and elevated IFP.

Collective tumor cell migration in the presence of fibroblasts

In this work we investigate fibroblast-enhanced tumor cell migration in an idealized tumor setting through a computational model based on a multiphase approach consisting of three phases, namely tumor cells, fibroblasts and interstitial fluid. The interaction between fibroblasts and tumor cells has previously been investigated through this model (Urdal et al., 2019) to comply with reported in vitro experimental results (Shieh et al., 2011). Using the information gained from in vitro single-cell behavior, what will the effect of fibroblast-enhanced tumor cell migration be in a tumor setting? In particular, how will tumor cells migrate in a heterogeneous tumor environment compared to controlled in vitro microfluidic-based experiments? From what we know about the behavior of a tumor, is that collective invasion into adjacent tissue is frequently observed. Here, we want to elucidate how fibroblasts may guide tumor cells towards draining lymphatics to which tumor cells may subsequently intravasate and thus spread to other parts of the body. Fibroblasts can act as leader cells, where they create tracks within the extracellular matrix (ECM) by matrix remodeling and contraction. In addition, a heterotypic mechanical adhesion between fibroblasts and tumor cells also assist the fibroblasts to act as leader cells. Our simulation results show how the interaction between the two cell types yields collective migration of tumor cells outwards from the tumor where fibroblasts dictate the direction of migration. The model also describes how this well-orchestrated invasive behavior is the result of a proper combination of different interaction forces between cell-ECM, fibroblast-ECM, fluid-ECM and cell-fibroblast.

Intratumor Heterogeneity in Interstitial Fluid Pressure in Cervical and Pancreatic Carcinoma Xenografts

Preclinical studies have suggested that interstitial fluid pressure (IFP) is uniformly elevated in the central region of tumors, whereas clinical studies have revealed that IFP may vary among different measurement sites in the tumor center. IFP measurements are technically difficult, and it has been claimed that the intratumor heterogeneity in IFP reported for human tumors is due to technical problems. The main purpose of this study was to determine conclusively whether IFP may be heterogeneously elevated in the central tumor region, and if so, to reveal possible mechanisms and possible consequences. Tumors of two xenograft models were included in the study: HL-16 cervical carcinoma and Panc-1 pancreatic carcinoma. IFP was measured with Millar SPC 320 catheters in two positions in each tumor and related to tumor histology or the metastatic status of the host mouse. Some tumors of both models showed significant intratumor heterogeneity in IFP, and this heterogeneity was associated with a compartmentalized histological appearance (i.e., the tissue was divided into compartments separated by thick connective tissue bands) in HL-16 tumors and with a dense collagen-I-rich extracellular matrix in Panc-1 tumors, suggesting that these connective tissue structures prevented efficient interstitial convection. Furthermore, some tumors of both models developed lymph node metastases, and of the two IFP values measured in each tumor, only the higher value was significantly higher in metastatic than in non-metastatic tumors, suggesting that metastatic propensity was determined by the tumor region having the highest IFP.

DCE-MRI of Sunitinib-Induced Changes in Tumor Microvasculature and Hypoxia: A Study of Pancreatic Ductal Adenocarcinoma Xenografts

The purpose of this study was dual: to investigate (a) whether sunitinib may induce changes in tumor microvasculature and hypoxia in pancreatic ductal adenocarcinoma (PDAC) and (b) whether any changes can be detected by DCE-MRI. Sunitinib-treated and untreated control tumors of two PDAC xenograft models (BxPC-3 and Panc-1) were subjected to DCE-MRI before the imaged tumors were prepared for quantitative analysis of immunohistochemical preparations. Pimonidazole was used as a hypoxia marker, and fraction of hypoxic tissue (HFPim), density of CD31-positive microvessels (MVDCD31), and density of αSMA-positive microvessels (MVDαSMA) were measured. Parametric images of Ktrans and ve were derived from the DCE-MRI data by using the Tofts pharmacokinetic model. BxPC-3 tumors showed increased HFPim, decreased MVDCD31, unchanged MVDαSMA, and increased vessel maturation index (VMI = MVDαSMA/MVDCD31) after sunitinib treatment. The increase in VMI was seen because sunitinib induced selective pruning rather than maturation of αSMA-negative microvessels. Even though the microvessels in sunitinib-treated tumors were less abnormal than those in untreated tumors, this microvessel normalization did not improve the function of the microvascular network or normalize the tumor microenvironment. In Panc-1 tumors, HFPim, MVDCD31, MVDαSMA, and VMI were unchanged after sunitinib treatment. Median Ktrans increased with increasing MVDCD31 and decreased with increasing HFPim, and the correlations were similar for treated and untreated BXPC-3 and Panc-1 tumors. These observations suggest that sunitinib may induce significant changes in the microenvironment of PDACs, and furthermore, that Ktrans may be an adequate measure of tumor vascular density and hypoxia in untreated as well as sunitinib-treated PDACs.

Increasing aggressiveness of patient-derived xenograft models of cervix carcinoma during serial transplantation

Four patient-derived xenograft (PDX) models (BK-12, ED-15, HL-16, LA-19) of carcinoma of the uterine cervix have been developed in our laboratory, and their stability during serial transplantation in vivo was investigated in this study. Two frozen cell stocks were established, one from xenografted tumors in passage 2 (early generation) and the other from xenografted tumors transplanted serially in mice for approximately two years (late generation), and the biology of late generation tumors was compared with that of early generation tumors. Late generation tumors showed higher incidence of lymph node metastases than early generation tumors in three models (ED-15, HL-16, LA-19), and the increased metastatic propensity was associated with increased tumor growth rate, increased microvascular density, and increased expression of angiogenesis-related and cancer stem cell-related genes. Furthermore, late generation tumors showed decreased fraction of pimonidazole-positive tissue (i.e., decreased fraction of hypoxic tissue) in two models (HL-16, LA-19) and decreased fraction of collagen-I-positive tissue (i.e., less extensive extracellular matrix) in two models (ED-15, HL-16). This study showed that serially transplanted PDXs may not necessarily mirror the donor patients’ diseases, and consequently, proper use of serially transplanted PDX models in translational cancer research requires careful molecular monitoring of the models.

Metastatic pathway and the microvascular and physicochemical microenvironments of human melanoma xenografts

BACKGROUND

Malignant melanoma of the skin can metastasize through blood vessels and lymphatics. The primary tumor develops a vascular microenvironment characterized by abnormal blood vessels and lymphatics and a physicochemical microenvironment characterized by low oxygen tension, regions with hypoxic tissue, and high interstitial fluid pressure (IFP). This study aimed at identifying relationships between the metastatic route of melanomas and characteristic features of the microvascular and physicochemical microenvironments of the primary tumor.

METHODS

Two patient-derived xenograft (PDX) models (E-13, N-15) and four cell line-derived xenografts (CDX) models (C-10, D-12, R-18, T-22) of human melanoma were included in the study. Tumors were transplanted to an orthotopic site in BALB/c-nu/nu mice, and when the tumors had grown to a volume of 500-600 mm3, the IFP of the primary tumor was measured and the hypoxia marker pimonidazole was administered before the host mouse was euthanized. The primary tumor, lungs, and six pairs of lymph nodes were evaluated by examining hematoxylin/eosin-stained and immunostained histological preparations. The expression of angiogenesis-related genes was assessed by quantitative PCR.

RESULTS

C-10, D-12, and E-13 tumors disseminated primarily by the hematogenous route and developed pulmonary metastases. These tumors showed high angiogenic activity and high expression of the F3 gene as well as ANGPT2 and TIE1, genes encoding proteins of the angiopoietin-tie system. N-15, R-18, and T-22 tumors disseminated mainly by the lymphogenous route and developed metastases in draining lymph nodes. These tumors had highly elevated IFP and showed high expression of NRP2, a gene encoding neuropilin-2.

CONCLUSION

The primary metastatic route of orthotopic human melanoma xenografts and the development of lung and lymph node metastases are influenced significantly by the microvascular and physicochemical microenvironments of the primary tumor.