Diffusion-weighted and dynamic contrast-enhanced MRI of pancreatic adenocarcinoma xenografts: associations with tumor differentiation and collagen content

The collagen matrix regulates the survival and function of pancreatic islets

The extracellular matrix (ECM) provides an appropriate microenvironment for many kinds of cells, including pancreatic cells. Collagens are the most abundant components of the ECM. Type I, IV, V and VI collagen has been detected in pancreatic islets, and each type plays important role in the proliferation, survival, function and differentiation of pancreatic cells. In some cases, collagens show behaviours similar to those of growth factors and regulate the biological behaviour of β cells by binding with certain growth factors, including IGFs, EGFs and FGFs. The transcriptional coactivator YAP/TAZ has been widely recognised as a mechanosensor that senses changes in the physical characteristics of the ECM and inhibition of YAP/TAZ enhances insulin production and secretion. Type 1 diabetes mellitus (T1DM) is an autoimmune disease characterised by the destruction of insulin-producing β cells. The crosstalk between collagens and immune cells plays a key role in the development and differentiation of immune cells. Further, Supplementation with collagens during islet transplantation is a promising strategy for improving the quality of the islets. But, excessive collagen deposition results in pancreatic fibrosis and pancreatic carcinoma. Targeting inhibit Piezo, autophagy or IL-6 may reduce excessive collagen deposition-induced pancreatic fibrosis and pancreatic carcinoma. This review provides insights into the treatment of T1DM to prolong life expectancy and provides the potential targets for treating collagen deposition-induced pancreatic fibrosis and pancreatic carcinoma.

The role of peroxidasin in solid cancer progression

Peroxidasin is a heme-containing peroxidase enzyme that plays a vital role in the cross-linking of collagen IV molecules in basement membranes. Collagen IV cross-links are essential for providing structure and mechanical stability throughout tissue development, homeostasis, and wound healing. During cancer progression, the basement membrane is degraded, and proteins typically found in the basement membrane, including peroxidasin and collagen IV, can be found spread throughout the tumour microenvironment where they interact with cancer cells and alter cell behaviour. Whilst peroxidasin is reported to be up-regulated in a number of different cancers, the role that it plays in disease progression and metastasis has only recently begun to be studied. This review highlights the current literature exploring the known roles of peroxidasin in normal tissues and cancer progression, regulators of peroxidasin expression, and the reported relationships between peroxidasin expression and patient outcome in cancer.

A multimodal imaging study to highlight elastin-derived peptide pro-tumoral effect in a pancreatic xenograft model

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is highly malignant with a very poor prognosis due to its silent development and metastatic profile with a 5-year survival rate below 10%. PDAC is characterised by an abundant desmoplastic stroma modulation that influences cancer development by extracellular matrix/cell interactions. Elastin is a key element of the extracellular matrix. Elastin degradation products (EDPs) regulate numerous biological processes such as cell proliferation, migration and invasion. The aim of the present study was to characterise for the first time the effect of two EDPs with consensus sequences "GxxPG" and "GxPGxGxG" (VG-6 and AG-9) on PDAC development. The ribosomal protein SA (RPSA) has been discovered recently, acting as a new receptor of EDPs on the surface of tumour cells, contributing to poor prognosis.

METHODS

Six week-old female Swiss nude nu/nu (Nu(Ico)-Foxn1nu) mice were subcutaneously injected with human PDAC MIA PaCa-2/eGFP-FLuc+ cells, transduced with a purpose-made lentiviral vector, encoding green fluorescent protein (GFP) and Photinus pyralis (firefly) luciferase (FLuc). Animals were treated three times per week with AG-9 (n = 4), VG-6 (n = 5) or PBS (n = 5). The influence of EDP on PDAC was examined by multimodal imaging (bioluminescence imaging (BLI), fluorescence imaging (FLI) and magnetic resonance imaging (MRI). Tumour volumes were also measured using a caliper. Finally, immunohistology was performed at the end of the in vivo study.

RESULTS

After in vitro validation of MIA PaCa-2 cells by optical imaging, we demonstrated that EDPs exacerbate tumour growth in the PDAC mouse model. While VG-6 stimulated tumour growth to some extent, AG-9 had greater impact on tumour growth. We showed that the expression of the RPSA correlates with a possible effect of EDPs in the PDAC model. Multimodal imaging allowed for longitudinal in vivo follow-up of tumour development. In all groups, we showed mature vessels ending in close vicinity of the tumour, except for the AG-9 group where mature vessels are penetrating the tumour reflecting an increase of vascularisation.

CONCLUSIONS

Our results suggest that AG-9 strongly increases PDAC progression through an increase in tumour vascularisation.

Therapeutic Strategies to Overcome Fibrotic Barriers to Nanomedicine in the Pancreatic Tumor Microenvironment

Pancreatic cancer is notorious for its dismal prognosis. The enhanced permeability and retention (EPR) effect theory posits that nanomedicines (therapeutics in the size range of approximately 10-200 nm) selectively accumulate in tumors. Nanomedicine has thus been suggested to be the "magic bullet"-both effective and safe-to treat pancreatic cancer. However, the densely fibrotic tumor microenvironment of pancreatic cancer impedes nanomedicine delivery. The EPR effect is thus insufficient to achieve a significant therapeutic effect. Intratumoral fibrosis is chiefly driven by aberrantly activated fibroblasts and the extracellular matrix (ECM) components secreted. Fibroblast and ECM abnormalities offer various potential targets for therapeutic intervention. In this review, we detail the diverse strategies being tested to overcome the fibrotic barriers to nanomedicine in pancreatic cancer. Strategies that target the fibrotic tissue/process are discussed first, which are followed by strategies to optimize nanomedicine design. We provide an overview of how a deeper understanding, increasingly at single-cell resolution, of fibroblast biology is revealing the complex role of the fibrotic stroma in pancreatic cancer pathogenesis and consider the therapeutic implications. Finally, we discuss critical gaps in our understanding and how we might better formulate strategies to successfully overcome the fibrotic barriers in pancreatic cancer.

The extracellular matrix alteration, implication in modulation of drug resistance mechanism: friends or foes?

The extracellular matrix (ECM) is an important component of the tumor microenvironment (TME), having several important roles related to the hallmarks of cancer. In cancer, multiple components of the ECM have been shown to be altered. Although most of these alterations are represented by the increased or decreased quantity of the ECM components, changes regarding the functional alteration of a particular ECM component or of the ECM as a whole have been described. These alterations can be induced by the cancer cells directly or by the TME cells, with cancer-associated fibroblasts being of particular interest in this regard. Because the ECM has this wide array of functions in the tumor, preclinical and clinical studies have assessed the possibility of targeting the ECM, with some of them showing encouraging results. In the present review, we will highlight the most relevant ECM components presenting a comprehensive description of their physical, cellular and molecular properties which can alter the therapy response of the tumor cells. Lastly, some evidences regarding important biological processes were discussed, offering a more detailed understanding of how to modulate altered signalling pathways and to counteract drug resistance mechanisms in tumor cells.

Tumor fibrosis correlates with the survival of patients with pancreatic adenocarcinoma and is predictable using clinicoradiological features

OBJECTIVES

To evaluate the prognostic value of fibrosis for patients with pancreatic adenocarcinoma (PDAC) and preoperatively predict fibrosis using clinicoradiological features. Tumor fibrosis plays an important role in the chemoresistance of PDAC. However, the prognostic value of tumor fibrosis remains contradiction and accurate prediction of tumor fibrosis is required.

METHODS

The study included 131 patients with PDAC who underwent first-line surgery. The prognostic value of fibrosis and rounded cutoff fibrosis points for median overall survival (OS) and disease-free survival (DFS) were determined using Cox regression and receiver operating characteristic (ROC) analyses. Then the whole cohort was randomly divided into training (n = 88) and validation (n = 43) sets. Binary logistic regression analysis was performed to select independent risk factors for fibrosis in the training set, and a nomogram was constructed. Nomogram performance was assessed using a calibration curve and decision curve analysis (DCA).

RESULTS

Hazard ratios of fibrosis for OS and DFS were 1.121 (95% confidence interval [CI]: 1.082-1.161) and 1.110 (95% CI: 1.067-1.155). ROC analysis identified 40% as the rounded cutoff fibrosis point for median OS and DFS. Tumor diameter, carbohydrate antigen 19-9 level, and peripancreatic tumor infiltration were independent risk factors; areas under the nomogram curve were 0.810 and 0.804 in the training and validation sets, respectively. The calibration curve indicated good agreement of the nomogram, and DCA demonstrated good clinical usefulness.

CONCLUSIONS

Tumor fibrosis was associated with poor OS and DFS in patients with PDAC. The nomogram incorporating clinicoradiological features was useful for preoperatively predicting tumor fibrosis.

KEY POINTS

• Tumor fibrosis is correlated with poor prognosis in patients with pancreatic adenocarcinoma. • Tumor fibrosis can be categorized according to its association with overall survival and disease-free survival. • A nomogram incorporating carbohydrate antigen 19-9 level, tumor diameter, and peripancreatic tumor infiltration is useful for preoperatively predicting tumor fibrosis.

Application of Magnetic Resonance Imaging in Neoadjuvant Treatment of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignant tumors of the human digestive system. Due to its insidious onset, many patients have already lost the opportunity for radical resection upon tumor diagnosis. In recent years, neoadjuvant treatment for patients with borderline resectable PDAC has been recommended by multiple guidelines to increase the resection rate of radical surgery and improve the postoperative survival. However, further developments are required to accurately assess the tumor response to neoadjuvant therapy and to select the population suitable for such treatment. Reductions in drug toxicity and the number of neoadjuvant cycles are also critical. At present, the clinical evaluation of neoadjuvant treatment is mainly based on several serological and imaging indicators; however, the unique characteristics of PDAC and the insufficient sensitivity and specificity of the markers render this system ineffective. The imaging evaluation system, magnetic resonance imaging (MRI), has its own unique imaging advantages compared with computed tomography (CT) and other imaging examinations. One key advantage is the ability to reflect the changes more rapidly in tumor tissue components, such as the degree of fibrosis, microvessel density, and tissue hypoxia. It can also perform multiparameter quantitative analysis of tumor tissue and changes, attributing to its increasingly important role in imaging evaluation, and potentially the evaluation of neoadjuvant treatment of pancreatic cancer, as several current articles have studied. At the same time, owing to the complexity of MRI and some of its limitations, its wider application is limited. Compared with CT imaging, few relevant studies have been conducted. In this review article, we will investigate and summarize the advantages, limitations, and future development of MRI in the evaluation of neoadjuvant treatment of PDAC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Magnetic Resonance Radiomics and Machine-learning Models: An Approach for Evaluating Tumor-stroma Ratio in Patients with Pancreatic Ductal Adenocarcinoma

OBJECTIVE

To develop and validate a magnetic resonance imaging (MRI)-based machine learning classifier for evaluating the tumor-stroma ratio (TSR) in patients with pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

In this retrospective study, 148 patients with PDAC underwent an MR scan and surgical resection. We used hematoxylin and eosin to quantify the TSR. For each patient, we extracted 1,409 radiomics features and reduced them using the least absolute shrinkage and selection operator logistic regression algorithm. The extreme gradient boosting (XGBoost) classifier was developed using a training set comprising 110 consecutive patients, admitted between December 2016 and December 2017. The model was validated in 38 consecutive patients, admitted between January 2018 and April 2018. We determined the performance of the XGBoost classifier based on its discriminative ability, calibration, and clinical utility.

RESULTS

A log-rank test revealed significantly longer survival in the TSR-low group. The prediction model displayed good discrimination in the training (area under the curve [AUC], 0.82) and validation set (AUC, 0.78). While the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for the training set were 77.14%, 75.00%, 0.76%, 0.84%, and 0.65%, respectively, those for the validation set were 58.33%, 92.86%, 0.71%, 0.93%, and 0.57%, respectively.

CONCLUSION

We developed an XGBoost classifier based on MRI radiomics features, a non-invasive prediction tool that can evaluate the TSR of patients with PDAC. Moreover, it will provide a basis for interstitial targeted therapy selection and monitoring.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Monoclonal Antibody Tumor Disposition

The prediction of monoclonal antibody (mAb) disposition within solid tumors for individual patients is difficult due to inter-patient variability in tumor physiology. Improved a priori prediction of mAb pharmacokinetics in tumors may facilitate the development of patient-specific dosing protocols and facilitate improved selection of patients for treatment with anti-cancer mAb. Here, we report the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), with tumor penetration of the contrast agent gadobutrol used as a surrogate, to improve physiologically based pharmacokinetic model (PBPK) predictions of cetuximab pharmacokinetics in epidermal growth factor receptor (EGFR) positive xenografts. In the initial investigations, mice bearing Panc-1, NCI-N87, and LS174T xenografts underwent DCE-MRI imaging with the contrast agent gadobutrol, followed by intravenous dosing of an 125Iodine-labeled, non-binding mAb (8C2). Tumor concentrations of 8C2 were determined following the euthanasia of mice (3 h-6 days after 8C2 dosing). Potential predictor relationships between DCE-MRI kinetic parameters and 8C2 PBPK parameters were evaluated through covariate modeling. The addition of the DCE-MRI parameter Ktrans alone or Ktrans in combination with the DCE-MRI parameter Vp on the PBPK parameters for tumor blood flow (QTU) and tumor vasculature permeability (σTUV) led to the most significant improvement in the characterization of 8C2 pharmacokinetics in individual tumors. To test the utility of the DCE-MRI covariates on a priori prediction of the disposition of mAb with high-affinity tumor binding, a second group of tumor-bearing mice underwent DCE-MRI imaging with gadobutrol, followed by the administration of 125Iodine-labeled cetuximab (a high-affinity anti-EGFR mAb). The MRI-PBPK covariate relationships, which were established with the untargeted antibody 8C2, were implemented into the PBPK model with considerations for EGFR expression and cetuximab-EGFR interaction to predict the disposition of cetuximab in individual tumors (a priori). The incorporation of the Ktrans MRI parameter as a covariate on the PBPK parameters QTU and σTUV decreased the PBPK model prediction error for cetuximab tumor pharmacokinetics from 223.71 to 65.02%. DCE-MRI may be a useful clinical tool in improving the prediction of antibody pharmacokinetics in solid tumors. Further studies are warranted to evaluate the utility of the DCE-MRI approach to additional mAbs and additional drug modalities.

The PDAC Extracellular Matrix: A Review of the ECM Protein Composition, Tumor Cell Interaction, and Therapeutic Strategies

Pancreatic ductal adenocarcinoma (PDAC) is notorious for a dense fibrotic stroma that is interlaced with a collagen-based extracellular matrix (ECM) that plays an important role in tumor biology. Traditionally thought to only provide a physical barrier from host responses and systemic chemotherapy, new studies have demonstrated that the ECM maintains biomechanical and biochemical properties of the tumor microenvironment (TME) and restrains tumor growth. Recent studies have shown that the ECM augments tumor stiffness, interstitial fluid pressure, cell-to-cell junctions, and microvascularity using a mix of biomechanical and biochemical signals to influence tumor fate for better or worse. In addition, PDAC tumors have been shown to use ECM-derived peptide fragments as a nutrient source in nutrient-poor conditions. While collagens are the most abundant proteins found in the ECM, several studies have identified growth factors, integrins, glycoproteins, and proteoglycans in the ECM. This review focuses on the dichotomous nature of the PDAC ECM, the types of collagens and other proteins found in the ECM, and therapeutic strategies targeting the PDAC ECM.

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.

Combining sonodynamic therapy with chemoradiation for the treatment of pancreatic cancer

Treatment options for patients with pancreatic cancer are limited and survival prospects have barely changed over the past 4 decades. Chemoradiation treatment (CRT) has been used as neoadjuvant therapy in patients with borderline resectable disease to reduce tumour burden and increase the proportion of patients eligible for surgery. Antimetabolite drugs such as gemcitabine and 5-fluorouracil are known to sensitise pancreatic tumours to radiation treatment. Likewise, photodynamic therapy (PDT) has also been shown to enhance the effect of radiation therapy. However, PDT is limited to treating superficial lesions due to the attenuation of light by tissue. The ability of the related technique, sonodynamic therapy (SDT), to enhance CRT was investigated in two murine models of pancreatic cancer (PSN-1 and BxPC-3) in this study. SDT uses low intensity ultrasound to activate an otherwise non-toxic sensitiser, generating toxic levels of reactive oxygen species (ROS) locally. It is applicable to greater target depths than PDT due to the ability of ultrasound to propagate further than light in tissue. Both CRT and the combination of CRT plus SDT delayed tumour growth in the two tumour models. In the PSN-1 model, but not the BxPC-3 model, the combination treatment caused an increase in survival relative to CRT alone (p = 0.038). The improvement in survival conferred by the addition of SDT in this model may be related to differences in tumour architecture between the two models. MRI and US images showed that PSN-1 tumours were less well perfused and vascularised than BxPC-3 tumours. This poor vascularisation may explain why PSN-1 tumours were more susceptible to the effects of vascular damage exerted by SDT treatment.

Performance of radiomics models for tumour-infiltrating lymphocyte (TIL) prediction in breast cancer: the role of the dynamic contrast-enhanced (DCE) MRI phase

OBJECTIVE

To systematically investigate the effect of imaging features at different DCE-MRI phases to optimise a radiomics model based on DCE-MRI for the prediction of tumour-infiltrating lymphocyte (TIL) levels in breast cancer.

MATERIALS AND METHODS

This study retrospectively collected 133 patients with pathologically proven breast cancer, including 73 patients with low TIL levels and 60 patients with high TIL levels. The volumes of breast cancer lesions were manually delineated on T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and each phase of DCE-MRI, followed by 6250 quantitative feature extractions. The least absolute shrinkage and selection operator (LASSO) method was used to select predictive feature sets for the classifiers. Four models were developed for predicting TILs: (1) single enhanced phase radiomics models; (2) fusion enhanced multi-phase radiomics models; (3) fusion multi-sequence radiomics models; and (4) a combined radiomics-based clinical model.

RESULTS

Image features extracted from the delayed phase MRI, especially DCE_Phase 6 (DCE_P6), demonstrated dominant predictive performances over features from other phases. The fusion multi-sequence radiomics model and combined radiomics-based clinical model achieved the highest predictive performances with areas under the curve (AUCs) of 0.934 and 0.950, respectively; however, the differences were not statistically significant.

CONCLUSION

The DCE-MRI radiomics model, especially image features extracted from the delayed phases, can help improve the performance in predicting TILs. The radiomics nomogram is effective in predicting TILs in breast cancer.

KEY POINTS

• Radiomics features extracted from DCE-MRI, especially delayed phase images, help predict TIL levels in breast cancer. • We developed a nomogram based on MRI to predict TILs in breast cancer that achieved the highest AUC of 0.950.

Assessment of Hypoxic Tissue Fraction and Prediction of Survival in Cervical Carcinoma by Dynamic Contrast-Enhanced MRI

Tumor hypoxia is a major cause of treatment resistance and poor survival in locally-advanced cervical carcinoma (LACC). It has been suggested that K^trans and v_e maps derived by dynamic contrast-enhanced magnetic resonance imaging can provide information on the oxygen supply and oxygen consumption of tumors, but it is not clear whether and how these maps can be combined to identify tumor hypoxia. The aim of the current study was to find the optimal strategy for calculating hypoxic fraction and predicting survival from K^trans and v_e maps in cervical carcinoma. K^trans and v_e maps of 98 tumors of four patient-derived xenograft models of cervical carcinoma as well as 80 patients with LACC were investigated. Hypoxic fraction calculated by using K^trans maps correlated strongly (P < 0.0001) to hypoxic fraction assessed with immunohistochemistry using pimonidazole as a hypoxia marker and was associated with disease-free and overall survival in LACC patients. Maps of v_e did not provide information on hypoxic fraction and patient outcome, and combinations of K^trans and v_e were not superior to K^trans alone for calculating hypoxic fraction. These observations imply that K^trans maps reflect oxygen supply and may be used to identify hypoxia and predict outcome in cervical carcinoma, whereas v_e is a poor parameter of oxygen consumption and does not provide information on tumor oxygenation status.

Morphological Heterogeneity in Pancreatic Cancer Reflects Structural and Functional Divergence

Simple Summary

Pancreatic cancer has a poor prognosis, which is largely due to resistance to treatment. Tumor heterogeneity is a known cause for treatment failure and has been studied at the molecular level. Morphological heterogeneity is common but has not been investigated, despite the fact that pathology examination is an integral part of clinical diagnostics. This study assessed whether morphological heterogeneity reflects structural and functional diversity in key cancer biological processes. Using archival tissues from resected pancreatic cancer, we selected four common and distinct morphological phenotypes and demonstrated that these differed significantly for a panel of 26 structural and functional features of the cancer-cell and stromal compartments. The strong link between these features and morphological phenotypes allowed prediction of the latter based on the results for the panel of features. The findings of this study indicate that morphological heterogeneity reflects biological diversity and that its assessment may potentially provide clinically relevant information.

Abstract

Inter- and intratumor heterogeneity is an important cause of treatment failure. In human pancreatic cancer (PC), heterogeneity has been investigated almost exclusively at the genomic and transcriptional level. Morphological heterogeneity, though prominent and potentially easily assessable in clinical practice, remains unexplored. This proof-of-concept study aims at demonstrating that morphological heterogeneity reflects structural and functional divergence. From the wide morphological spectrum of conventional PC, four common and distinctive patterns were investigated in 233 foci from 39 surgical specimens. Twenty-six features involved in key biological processes in PC were analyzed (immuno-)histochemically and morphometrically: cancer cell proliferation (Ki67) and migration (collagen fiber alignment, MMP14), cancer stem cells (CD44, CD133, ALDH1), amount, composition and spatial arrangement of extracellular matrix (epithelial proximity, total collagen, collagen I and III, fibronectin, hyaluronan), cancer-associated fibroblasts (density, αSMA), and cancer-stroma interactions (integrins α2, α5, α1; caveolin-1). All features differed significantly between at least two of the patterns. Stromal and cancer-cell-related features co-varied with morphology and allowed prediction of the morphological pattern. In conclusion, morphological heterogeneity in the cancer-cell and stromal compartments of PC correlates with structural and functional diversity. As such, histopathology has the potential to inform on the operationality of key biological processes in individual tumors.

Rapid Clearing for High Resolution 3D Imaging of Ex Vivo Pancreatic Cancer Spheroids

The currently accepted imaging methods have been a central hurdle to imaging the finer details of tumor behavior in three-dimensional (3D) ex vivo multicellular culture models. In our search for an improved way of imaging tumor behavior in its physiological-like niche, we developed a simple, efficient, and straightforward procedure using standard reagents and imaging equipment that significantly enhanced 3D imaging up to a ~200-micron depth. We tested its efficacy on pancreatic spheroids, prototypes of high-density tissues that are difficult to image. We found we could both save time with this method and extract information about pancreatic tumor spheroids that previously was difficult to obtain. We were able to discern clear differences in the organization of pancreatic tumor spheroids generated from different origins, suggesting cell-specific, inherent, bottom-up organization with a correlation to the level of malignancy. We also examined the dynamic changes in the spheroids at predetermined time points, providing important information related to tissue morphogenesis and its metabolic state. Lastly, this process enabled us to assess a drug vehicle's potential to penetrate dense tumor tissue by improving our view of the inert particles' diffusion in the 3D spheroid. This clearing method, a simple procedure, can open the door to more accurate imaging and reveal more about cancer behavior.

Phase I clinical trial repurposing all-trans retinoic acid as a stromal targeting agent for pancreatic cancer

Pre-clinical models have shown that targeting pancreatic stellate cells with all-trans-retinoic-acid (ATRA) reprograms pancreatic stroma to suppress pancreatic ductal adenocarcinoma (PDAC) growth. Here, in a phase Ib, dose escalation and expansion, trial for patients with advanced, unresectable PDAC (n = 27), ATRA is re-purposed as a stromal-targeting agent in combination with gemcitabine-nab-paclitaxel chemotherapy using a two-step adaptive continual re-assessment method trial design. The maximum tolerated dose (MTD) and recommended phase 2 dose (RP2D, primary outcome) is the FDA/EMEA approved dose of gemcitabine-nab-paclitaxel along-with ATRA (45 mg/m2 orally, days 1-15/cycle). Dose limiting toxicity (DLT) is grade 4 thrombocytopenia (n = 2). Secondary outcomes show no detriment to ATRA pharmacokinetics.. Median overall survival for RP2D treated evaluable population, is 11.7 months (95%CI 8.6-15.7 m, n = 15, locally advanced (2) and metastatic (13)). Exploratory pharmacodynamics studies including changes in diffusion-weighted (DW)-MRI measured apparent diffusion coefficient after one cycle, and, modulation of cycle-specific serum pentraxin 3 levels over various cycles indicate stromal modulation. Baseline stromal-specific retinoid transport protein (FABP5, CRABP2) expression may be predicitve of response. Re-purposing ATRA as a stromal-targeting agent with gemcitabine-nab-paclitaxel is safe and tolerable. This combination will be evaluated in a phase II randomized controlled trial for locally advanced PDAC. Clinical trial numbers: EudraCT: 2015-002662-23; NCT03307148. Trial acronym: STARPAC.

Pathological validation and prognostic potential of quantitative MRI in the characterization of pancreas cancer: preliminary experience

Patient stratification based on biological variation in pancreatic ductal adenocarcinoma (PDAC) subtypes could help to improve clinical outcome. However, noninvasive assessment of the entire tumor microenvironment remains challenging. In this study, we investigate the biological basis of dynamic contrast-enhanced (DCE), intravoxel incoherent motion (IVIM), and R2*-derived magnetic resonance imaging (MRI) parameters for the noninvasive characterization of the PDAC tumor microenvironment and evaluate their prognostic potential in PDAC patients. Patients diagnosed with treatment-naïve resectable PDAC underwent MRI. After resection, a whole-mount tumor slice was analyzed for collagen fraction, vessel density, and hypoxia and matched to the MRI parameter maps. MRI parameters were correlated to immunohistochemistry-derived tissue characteristics and evaluated for prognostic potential. Thirty patients were included of whom 21 underwent resection with whole-mount histology available in 15 patients. DCE Ktrans and ve , ADC, and IVIM D correlated with collagen fraction. DCE kep and IVIM f correlated with vessel density and R2* with tissue hypoxia. Based on MRI, two main PDAC phenotypes could be distinguished; a stroma-high phenotype demonstrating high vessel density and high collagen fraction and a stroma-low phenotype demonstrating low vessel density and low collagen fraction. Patients with the stroma-high phenotype (high kep and high IVIM D, n = 8) showed longer overall survival (not reached vs. 14 months, P = 0.001, HR = 9.1, P = 0.004) and disease-free survival (not reached vs. 2 months, P < 0.001, HR 9.3, P = 0.003) compared to the other patients (n = 22). Median follow-up was 41 (95% CI: 36-46) months. MRI was able to accurately characterize tumor collagen fraction, vessel density, and hypoxia in PDAC. Based on imaging parameters, a subgroup of patients with significantly better prognosis could be identified. These first results indicate that stratification-based MRI-derived biomarkers could help to tailor treatment and improve clinical outcome and warrant further research.

The role of collagen in cancer: from bench to bedside

Collagen is the major component of the tumor microenvironment and participates in cancer fibrosis. Collagen biosynthesis can be regulated by cancer cells through mutated genes, transcription factors, signaling pathways and receptors; furthermore, collagen can influence tumor cell behavior through integrins, discoidin domain receptors, tyrosine kinase receptors, and some signaling pathways. Exosomes and microRNAs are closely associated with collagen in cancer. Hypoxia, which is common in collagen-rich conditions, intensifies cancer progression, and other substances in the extracellular matrix, such as fibronectin, hyaluronic acid, laminin, and matrix metalloproteinases, interact with collagen to influence cancer cell activity. Macrophages, lymphocytes, and fibroblasts play a role with collagen in cancer immunity and progression. Microscopic changes in collagen content within cancer cells and matrix cells and in other molecules ultimately contribute to the mutual feedback loop that influences prognosis, recurrence, and resistance in cancer. Nanoparticles, nanoplatforms, and nanoenzymes exhibit the expected gratifying properties. The pathophysiological functions of collagen in diverse cancers illustrate the dual roles of collagen and provide promising therapeutic options that can be readily translated from bench to bedside. The emerging understanding of the structural properties and functions of collagen in cancer will guide the development of new strategies for anticancer therapy.

Vascularization, Oxygenation, and the Effect of Sunitinib Treatment in Pancreatic Ductal Adenocarcinoma Xenografts

The purpose of the study was to investigate vascularization, oxygenation, and the effect of sunitinib treatment in pancreatic ductal adenocarcinoma (PDAC). BxPC-3 and Capan-2 xenografts grown in dorsal window chambers were used as preclinical models of human PDAC. Tumor angiogenesis and the morphology and function of tumor vascular networks were studied by intravital microscopy, and tumor hypoxia was assessed by immunohistochemistry. The PDAC models differed in vessel distribution and oxygenation, and the differences were induced by the initial tumor angiogenesis. In both models, sunitinib treatment reduced intratumor and peritumor vessel densities by selectively removing small-diameter vessels. Sunitinb treatment resulted in a general decrease in vessel density and scattered hypoxia in BxPC-3 tumors, and depleted most vessels and induced massive hypoxia in central parts of Capan-2 tumors. The study demonstrates that PDAC xenografts can differ in vascularization, and the differences can impact oxygenation and effects of treatment. Neoadjuvant sunitinib treatment is inappropriate in combination with conventional therapy for human PDACs resembling the PDAC xenografts used here, because sunitinib-induced hypoxia can impair the effect of most conventional therapies.

DCE-MRI and Quantitative Histology Reveal Enhanced Vessel Maturation but Impaired Perfusion and Increased Hypoxia in Bevacizumab-Treated Cervical Carcinoma

PURPOSE

This study had a dual purpose: to investigate (1) whether bevacizumab can change the microvasculature and oxygenation of cervical carcinomas and (2) whether any changes can be detected with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

METHODS AND MATERIALS

Two patient-derived xenograft models of cervical cancer (BK-12 and HL-16) were included in the study. Immunostained histologic preparations from untreated and bevacizumab-treated tumors were analyzed with respect to microvascular density, vessel pericyte coverage, and tumor hypoxia using CD31, α-SMA, and pimonidazole as markers, respectively. DCE-MRI was performed at 7.05 T, and parametric images of K^trans and v_e were derived from the data using the Tofts pharmacokinetic model.

RESULTS

The tumors of both models showed decreased microvascular density, increased vessel pericyte coverage, and increased vessel maturation after bevacizumab treatment. Bevacizumab-treated tumors were more hypoxic and had lower K^trans values than untreated tumors in the BK-12 model, whereas bevacizumab-treated and untreated HL-16 tumors had similar hypoxic fractions and similar K^trans values. Significant correlations were found between median K^trans and hypoxic fraction, and the data for untreated and bevacizumab-treated tumors were well fitted by the same curve in both tumor models.

CONCLUSIONS

Bevacizumab-treated tumors show less abnormal microvessels than untreated tumors do, but because of treatment-induced vessel pruning, the overall function of the microvasculature might be impaired after bevacizumab treatment, resulting in increased tumor hypoxia. DCE-MRI has great potential for monitoring bevacizumab-induced changes in tumor hypoxia in cervical carcinoma.

Multiparametric MR for non-invasive evaluation of tumour tissue histological characteristics after radionuclide therapy

Early non-invasive tumour therapy response assessment requires methods sensitive to biological and physiological tumour characteristics. The aim of this study was to find and evaluate magnetic resonance imaging (MRI) derived tumour tissue parameters that correlate with histological parameters and that reflect effects of radionuclide therapy. Mice bearing a subcutaneous human small-intestine neuroendocrine tumour were i.v. injected with ¹⁷⁷ Lu-octreotate. MRI was performed (7 T Bruker Biospec) on different post-therapy intervals (1 and 13 days) using T2-weighted imaging, mapping of T2* and T1 relaxation time constants, as well as diffusion and dynamic contrast enhancement (DCE-MRI) techniques. After MRI, animals were killed and tumours excised. Four differently stained histological sections of the most central imaged tumour plane were digitized, and segmentation techniques were used to produce maps reflecting fibrotic and vascular density, apoptosis, and proliferation. Histological maps were aligned with MRI-derived parametric maps using landmark-based registration. Correlations and predictive power were evaluated using linear mixed-effects models and cross-validation, respectively. Several MR parameters showed statistically significant correlations with histological parameters. In particular, three DCE-MRI-derived parameters reflecting capillary function additionally showed high predictive power regarding apoptosis (2/3) and proliferation (1/3). T1 could be used to predict vascular density, and perfusion fraction derived from diffusion MRI could predict fibrotic density, although with lower predictive power. This work demonstrates the potential to use multiparametric MRI to retrieve important information on the tumour microenvironment after radiotherapy. The non-invasiveness of the method also allows longitudinal tumour tissue characterization. Further investigation is warranted to evaluate the parameters highlighted in this study longitudinally, in larger studies, and with additional histological methods.

MARCH1 encourages tumour progression of hepatocellular carcinoma via regulation of PI3K-AKT-β-catenin pathways

Membrane‐associated RING‐CH‐1 (MARCH1) is a membrane‐anchored E3 ubiquitin ligase that is involved in a variety of cellular processes. MARCH1 was aberrantly expressed as a tumour promoter in ovarian cancer, but the signalling about the molecular mechanism has not yet been fully illuminated. Here, we first determined that MARCH1 was obviously highly expressed in human hepatocellular carcinoma samples and cells. In addition, our findings demonstrated that the proliferation, migration and invasion of hepatocellular carcinoma were suppressed, but the apoptosis was increased, as a result of MARCH1 knockdown by either siRNA targeting MARCH1 or pirarubicin treatment. Conversely, the proliferation, migration and invasion of hepatocellular carcinoma were obviously accelerated, and the apoptosis was decreased, by transfecting the MARCH1 plasmid to make MARCH1 overexpressed. Moreover, in vivo, the results exhibited a significant inhibition of the growth of hepatocellular carcinoma in nude mice, which were given an intra‐tumour injection of siRNA targeting MARCH1. Furthermore, our study concluded that MARCH1 functions as a tumour promoter, and its role was up‐regulated the PI3K‐AKT‐β‐catenin pathways both in vitro and in vivo. In summary, our work determined that MARCH1 has an important role in the development and progression of hepatocellular carcinoma and may be used as a novel potential molecular therapeutic target in the future treatment of hepatocellular carcinoma.

Development of a Novel 3D Tumor-tissue Invasion Model for High-throughput, High-content Phenotypic Drug Screening

While much progress has been made in the war on cancer, highly invasive cancers such as pancreatic cancer remain difficult to treat and anti-cancer clinical trial success rates remain low. One shortcoming of the drug development process that underlies these problems is the lack of predictive, pathophysiologically relevant preclinical models of invasive tumor phenotypes. While present-day 3D spheroid invasion models more accurately recreate tumor invasion than traditional 2D models, their shortcomings include poor reproducibility and inability to interface with automated, high-throughput systems. To address this gap, a novel 3D tumor-tissue invasion model which supports rapid, reproducible setup and user-definition of tumor and surrounding tissue compartments was developed. High-cell density tumor compartments were created using a custom-designed fabrication system and standardized oligomeric type I collagen to define and modulate ECM physical properties. Pancreatic cancer cell lines used within this model showed expected differential invasive phenotypes. Low-passage, patient-derived pancreatic cancer cells and cancer-associated fibroblasts were used to increase model pathophysiologic relevance, yielding fibroblast-mediated tumor invasion and matrix alignment. Additionally, a proof-of-concept multiplex drug screening assay was applied to highlight this model's ability to interface with automated imaging systems and showcase its potential as a predictive tool for high-throughput, high-content drug screening.

Pancreatic cancer stem cells: A state or an entity?

Pancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer, has a median overall survival of 6-12 months and a 5-year survival of less than 7%. While PDAC currently represents the 4th most frequent cause of death due to cancer worldwide, it is expected to become the second leading cause of cancer-related death by 2030. These alarming statistics are primarily due to both the inherent chemoresistant and metastatic nature of this tumor, and the existence of a subpopulation of highly plastic "stem"-like cells within the tumor, known as cancer stem cells (CSCs). Since their discovery in PDAC in 2007, we have come to realize that pancreatic CSCs have unique metabolic, autophagic, invasive, and chemoresistance properties that allow them to continuously self-renew and escape chemo-therapeutic elimination. More importantly, the concept of the CSC as a fixed entity within the tumor has also evolved, and current data suggest that CSCs are states rather than defined entities. Consequently, current treatments for the majority of PDAC patients are not effective, and do not significantly impact overall patient survival, as they do not adequately target the plastic CSC sub-population nor the transient/hybrid cells that can replenish the CSC pool. Thus, it is necessary that we improve our understanding of the characteristics and signals that maintain and drive the pancreatic CSC population in order to develop new therapies to target these cells. Herein, we will provide the latest updates and knowledge on the inherent characteristics of pancreatic CSCs and the CSC niche, specifically the cross-talk that exists between CSCs and niche resident cells. Lastly, we will address the question of whether a CSC is a state or an entity and discuss how the answer to this question can impact treatment approaches.

Diffusion-Weighted MRI Is Insensitive to Changes in the Tumor Microenvironment Induced by Antiangiogenic Therapy

Antiangiogenic treatment (AAT) used in combination with radiation therapy or chemotherapy is a promising strategy for the treatment of several cancer diseases. The vascularity and oxygenation of tumors may be changed significantly by AAT, and consequently, a noninvasive method for monitoring AAT-induced changes in these microenvironmental parameters is needed. The purpose of this study was to evaluate the potential usefulness of diffusion-weighted magnetic resonance imaging (DW-MRI). DW-MRI was conducted with a Bruker Biospec 7.05-T scanner using four diffusion weightings and diffusion sensitization gradients in three orthogonal directions. Maps of the apparent diffusion coefficient (ADC) were calculated by using a monoexponential diffusion model. Two cervical carcinoma xenograft models (BK-12, HL-16) were treated with bevacizumab, and two pancreatic carcinoma xenograft models (BxPC-3, Panc-1) were treated with sunitinib. Pimonidazole and CD31 were used as markers of hypoxia and blood vessels, respectively, and fraction of hypoxic tissue (HF_Pim) and microvascular density (MVD) were quantified by analyzing immunohistochemical preparations. MVD decreased significantly after AAT in BK-12, HL-16, and BxPC-3 tumors, and this decrease was sufficiently large to cause a significant increase in HF_Pim in BK-12 and BxPC-3 tumors. The ADC maps of treated tumors and untreated control tumors were not significantly different in any of these three tumor models, suggesting that the AAT-induced microenvironmental changes were not detectable by DW-MRI. DW-MRI is insensitive to changes in tumor vascularity and oxygenation induced by bevacizumab or sunitinib treatment.

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.

Quantitative free-breathing dynamic contrast-enhanced MRI in hepatocellular carcinoma using gadoxetic acid: correlations with Ki67 proliferation status, histological grades, and microvascular density

PURPOSE

To validate a free-breathing dynamic contrast-enhanced-MRI (DCE-MRI) in hepatocellular carcinoma (HCC) patients using gadoxetic acid, and to determine the relationship between DCE-MRI parameters and histological results.

METHODS

Thirty-four HCC patients were included in this prospective study. Free-breathing DCE-MRI data was acquired preoperatively on a 3.0 Tesla scanner. Perfusion parameters (K ^trans, K _ep, V _e and the semi-quantitative parameter of initial area under the gadolinium concentration-time curve, iAUC) were calculated and compared with tumor enhancement at contrast-enhanced CT. The relationship between DCE-MRI parameters and Ki67 indices, histological grades and microvascular density (MVD) was determined by correlation analysis. Differences of perfusion parameters between different histopathological groups were compared. Receiver operation characteristic (ROC) analysis of discriminating high-grades (grade III and IV) from low-grades (grade I and II) HCC was performed for perfusion parameters.

RESULTS

Significant relationship was found between DCE-MRI and CT results. The DCE-MRI derived K ^trans were significantly negatively correlated with Ki-67 indices (rho = - 0.408, P = 0.017) and the histological grades (rho = - 0.444, P = 0.009) of HCC, and K _ep and V _e were significantly related with tumor MVD (rho = - 0.405, P = 0.017 for K _ep; and rho = 0.385, P = 0.024 for V _e). K ^trans, K _ep, and iAUC demonstrated moderate diagnostic performance (iAUC = 0.78, 0.77 and 0.80, respectively) for discriminating high-grades from low-grades HCC without significant differences.

CONCLUSIONS

The DCE-MRI derived parameters demonstrated weak but significant correlations with tumor proliferation status, histological grades or microvascular density, respectively. This free-breathing DCE-MRI is technically feasible and offers a potential avenue toward non-invasive evaluation of HCC malignancy.

Changes in the microarchitecture of the pancreatic cancer stroma are linked to neutrophil-dependent reprogramming of stellate cells and reflected by diffusion-weighted magnetic resonance imaging

In pancreatic cancer (PDAC) intratumor infiltration of polymorphonuclear neutrophils (PMN) is associated with histologically apparent alterations of the tumor growth pattern. The aim of this study was to examine possible associations between PMN infiltration, tumor microarchitecture, and water diffusivity in diffusion-weighted magnetic resonance imaging (DW-MRI), and to further asses the underlying mechanisms.

Methods: DW-MRI was performed in 33 PDAC patients prior to surgery. In parallel, tissue specimen were examined histologically for growth pattern, azurocidin-positive PMN infiltrates, and the presence of alpha-smooth muscle actin (α-SMA) and metalloproteinase 9 (MMP9)-positive myofibroblastic cells. For confirmation of the histological findings, a tissue microarray of a second cohort of patients (n=109) was prepared and examined similarly. For in vitro studies, the pancreatic stellate cell line RLT was co-cultivated either with isolated PMN, PMN-lysates, or recombinant azurocidin and characterized by Western blot, flow cytometry, and proteome profiler arrays.

Results: Tumors with high PMN density showed restricted water diffusion in DW-MRI and histologic apparent alterations of the tumor microarchitecture (microglandular, micropapillary, or overall poorly differentiated growth pattern) as opposed to tumors with scattered PMN. Areas with altered growth pattern lacked α-SMA-positive myofibroblastic cells. Tissue microarrays confirmed a close association of high PMN density with alterations of the tumor microarchitecture and revealed a significant association of high PMN density with poor histologic grade of differentiation (G3). In vitro experiments provided evidence for direct effects of PMN on stellate cells, where a change to a spindle shaped cell morphology in response to PMN and to PMN-derived azurocidin was seen. Azurocidin incorporated into stellate cells, where it associated with F-actin. Down-regulation of α-SMA was seen within hours, as was activation of the p38-cofilin axis, up-regulation of MMP9, and acquisition of intracellular lipid droplets, which together indicate a phenotype switch of the stellate cells.

Conclusion: In PDAC, PMN infiltrates are associated with alterations of the tumor microarchitecture. As a causal relationship, we propose a reprogramming of stellate cells by PMN-derived azurocidin towards a phenotype, which affects the microarchitecture of the tumor.

Dynamic contrast-enhanced MRI of the microenvironment of pancreatic adenocarcinoma xenografts

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with poor outcome. Resistance to treatment is associated with impaired vascularity, extensive hypoxia, and interstitial hypertension. In this study, the potential of dynamic contrast-enhanced (DCE)-MRI as a method for assessing the microvascular density (MVD), the fraction of hypoxic tissue, and the interstitial fluid pressure (IFP) of PDACs was investigated.

MATERIAL AND METHODS

Intramuscular BxPC-3, Capan-2, MIAPaCa-2, and Panc-1 PDAC xenografts were used as preclinical models of human PDACs. DCE-MRI with Gd-DOTA as contrast agent was conducted with a 7.05-T scanner, and the DCE-MRI series were analyzed voxelwise by using the Tofts pharmacokinetic model. Tumor MVD and hypoxia were measured in histological preparations by using pimonidazole as a hypoxia marker and CD31 as a marker of endothelial cells. IFP was measured with a Millar catheter.

RESULTS

K^trans (the volume transfer constant of Gd-DOTA) increased with increasing MVD and decreased with increasing hypoxic fraction, but was not associated with IFP. Any association between v_e (the fractional distribution volume of Gd-DOTA) and MVD, hypoxic fraction, or IFP could not be detected.

CONCLUSIONS

This study shows that DCE-MRI is a useful modality for assessing important features of the microenvironment of PDAC xenografts and thus provides the basis for future preclinical and clinical DCE-MRI investigations of PDAC.

Diffusion-weighted MRI-derived ADC values reflect collagen I content in PDX models of uterine cervical cancer

Apparent diffusion coefficient (ADC) values derived from diffusion-weighted magnetic resonance imaging (DW-MRI) are known to reflect the cellular environment of biological tissues. However, emerging evidence accentuates the influence of stromal elements on ADC values. The current study sought to elucidate whether a correlation exists between ADC and the fraction of collagen I-positive tissue across different tumor models of uterine cervical cancer. Early and late generation tumors of four patient-derived xenograft (PDX) models of squamous cell carcinoma (BK-12, ED-15, HL-16, and LA-19) were included. DW-MRI was performed with diffusion encoding constants (b) of 200, 400, 700, and 1000 s/mm2 and diffusion gradient sensitization in three orthogonal directions. The fraction of collagen I-positive connective tissue was determined by immunohistochemistry. Mono-exponential decay curves, from which the ADC value of tumor voxels was calculated, yielded good fits to the diffusion data. A significant inverse correlation was detected between median tumor ADC and collagen I fraction across the four PDX models, indicating that collagen fibers in the extracellular space have the ability to inhibit the movement of water molecules in these xenografts. The results encourage further exploration of DW-MRI as a non-invasive imaging method for characterizing the stromal microenvironment of tumors.

DCE-MRI of patient-derived xenograft models of uterine cervix carcinoma: associations with parameters of the tumor microenvironment

BACKGROUND

Abnormalities in the tumor microenvironment are associated with resistance to treatment, aggressive growth, and poor clinical outcome in patients with advanced cervical cancer. The potential of dynamic contrast-enhanced (DCE) MRI to assess the microvascular density (MVD), interstitial fluid pressure (IFP), and hypoxic fraction of patient-derived cervical cancer xenografts was investigated in the present study.

METHODS

Four patient-derived xenograft (PDX) models of squamous cell carcinoma of the uterine cervix (BK-12, ED-15, HL-16, and LA-19) were subjected to Gd-DOTA-based DCE-MRI using a 7.05 T preclinical scanner. Parametric images of the volume transfer constant (K ^trans) and the fractional distribution volume (v _e) of the contrast agent were produced by pharmacokinetic analyses utilizing the standard Tofts model. Whole tumor median values of the DCE-MRI parameters were compared with MVD and the fraction of hypoxic tumor tissue, as determined histologically, and IFP, as measured with a Millar catheter.

RESULTS

Both on the PDX model level and the single tumor level, a significant inverse correlation was found between K ^trans and hypoxic fraction. The extent of hypoxia was also associated with the fraction of voxels with unphysiological v _e values (v _e > 1.0). None of the DCE-MRI parameters were related to MVD or IFP.

CONCLUSIONS

DCE-MRI may provide valuable information on the hypoxic fraction of squamous cell carcinoma of the uterine cervix, and thereby facilitate individualized patient management.

Monitoring Tumor Volume in Patients With Prostate Cancer Undergoing Active Surveillance: Is MRI Apparent Diffusion Coefficient Indicative of Tumor Growth?

OBJECTIVE

The purpose of this study was to measure longitudinal change in tumor volume of the dominant intraprostatic lesion and determine whether baseline apparent diffusion coefficient (ADC) and change in ADC are indicative of tumor growth in patients with prostate cancer undergoing active surveillance.

SUBJECTS AND METHODS

The study group included 151 men (mean age, 68.1 ± 7.4 [SD] years; range, 50-83 years) undergoing active surveillance with 3D whole prostate, zonal, and tumor volumetric findings documented at endorectal MRI examinations performed at two time points (median interval, 1.9 years). Tumor (location confirmed at transrectal ultrasound or template biopsy) ADC was measured on the slice with the largest lesion. Twenty randomly selected patients had the measurements repeated by the same observer after a greater than 4-month interval, and the limits of agreement of measurements were calculated. Tumor volume increases greater than the upper limit of agreement were designated measurable growth, and their baseline ADCs and change in ADC were compared with those of tumors without measurable growth (independent-samples t test).

RESULTS

Fifty-two (34.4%) tumors increased measurably in volume. Baseline ADC and tumor volume were negatively correlated (r = -0.42, p = 0.001). Baseline ADC values did not differ between those with and those without measurable growth (p = 0.06), but change in ADC was significantly different (-6.8% ± 12.3% for those with measurable growth vs 0.23% ± 10.1% for those without, p = 0.0005). Percentage change in tumor volume and percentage change in ADC were negatively correlated (r = -0.31, p = 0.0001). A 5.8% reduction in ADC indicated a measurable increase in tumor volume with 54.9% sensitivity and 77.0% specificity (AUC, 0.67).

CONCLUSION

Tumor volume increased measurably in 34.4% of men after 2 years of active surveillance. Change in ADC may be used to identify tumors with measurable growth.

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

Pancreatic ductal adenocarcinoma (PDAC) patients develop lymph node metastases early and have a particularly poor prognosis. The poor prognosis has been shown to be associated with the physicochemical microenvironment of the tumor tissue, which is characterized by desmoplasia, abnormal microvasculature, extensive hypoxia, and highly elevated interstitial fluid pressure (IFP). In this study, we searched for associations between lymph node metastasis and features of the physicochemical microenvironment in an attempt to identify mechanisms leading to metastatic dissemination and growth. BxPC-3 and Capan-2 PDAC xenografts were used as preclinical models of human PDAC. In both models, lymph node metastasis was associated with high IFP rather than high fraction of hypoxic tissue or high microvascular density. Seven angiogenesis-related genes associated with high IFP-associated lymph node metastasis were detected by quantitative PCR in each of the models, and these genes were all up-regulated in high IFP/highly metastatic tumors. Three genes were mutual for the BxPC-3 and Capan-2 models: transforming growth factor beta, angiogenin, and insulin-like growth factor 1. Further comprehensive studies are needed to determine whether there is a causal relationship between the up-regulation of these genes and high IFP and/or high propensity for lymph node metastasis in PDAC.