Imaging acute effects of bevacizumab on tumor vascular kinetics in a preclinical orthotopic model of U251 glioma

Extracellular volume fraction can predict the treatment response and survival outcome of colorectal cancer liver metastases

OBJECTIVE

To assess the prognostic value of pre- and post-therapeutic changes in extracellular volume (ECV) fraction of liver metastases (LMs) for treatment response (TR) and survival outcomes in colorectal cancer liver metastases (CRLM).

METHODS

186 LMs were confirmed by pathology or follow-up (Training: 130; Test: 56). We analyzed the changes in ECV fraction of LMs before and after 2 cycles of chemotherapy combined with bevacizumab. After 12 cycles, we evaluated the TR on LMs based on the RECIST v1.1. Relative changes in ECV fraction and Hounsfield Units (HU), defined as ΔECV and ΔHU, were associated with progression-free survival (PFS), overall survival (OS), and TR. We identified TR predictors with multivariate logistic regression and PFS, OS risk factors with COX analysis.

RESULTS

186 LMs were classified as TR lesions (TR+: 84) and non-TR lesions (TR-:102). ΔECV, ΔHUA-E, and texture could distinguish the TR of LMs in training and test set (P < 0.05). ΔECV [Odds ratio (OR): 1.03; 95% Confidence interval (CI): 1.02-1.05, P < 0.01] was an independent predictor of TR-. Area under the curve (AUC), sensitivity and specificity of TR model in training and test set were 0.87, 0.84, 90.14%, 90.32%, 72.88%, 64.00%, respectively. High CRD_score indicates that patients have shorter PFS [Hazard ratio (HR): 2.01; 95%CI: 1.02-3.98, P = 0.045)] and OS (HR: 1.89, 95%CI: 1.04-3.42, P = 0.038).

CONCLUSION

ΔECV can be used as an independent predictor of TR of CRLM chemotherapy combined with bevacizumab.

Biodistribution and pharmacokinetics of [89Zr]-anti-VEGF mAbs using PET in glioblastoma rat models

INTRODUCTION

Glioblastomas present intensive angiogenesis, thus anti-Vascular Endothelial Growth Factor (VEGF) antibodies (mAbs) have been proposed as promising therapies. However, the results of clinical trials reported moderate toxicity and limited effectiveness. This study evaluates the in vivo pharmacokinetics and biodistribution of these mAbs in a growing model of glioblastoma in rats using Positron Emission Tomography (PET).

MATERIAL

&Methods: mAbs were radiolabeled with zirconium-89. Four days after the model induction, animals were injected with 2.33 ± 1.3 MBq of [89Zr]-DFO-bevacizumab (n = 8) or 2.35 ± 0.26 MBq of [89Zr]-DFO-aflibercept (n = 6). PETs were performed at 0H, 48H, 168H, 240H, and 336H post-injection. Tumor induction was confirmed using [18F]-Fluorodeoxyglucose-PET and immunohistochemistry. Radiotracer uptake was estimated in all pre-defined Volumes-of-Interest.

RESULTS

Anti-VEGF mAbs showed 100 % Radiochemical-Purity. [89Zr]-DFO-bevacizumab showed a significantly higher bioavailability in whole-blood. A significant increase in the tumor uptake was detectable at 168H PET with [89Zr]-DFO-bevacizumab meanwhile with [89Zr]-DFO-aflibercept it was only detectable at 336H. [89Zr]-DFO-bevacizumab tumor uptake was significantly higher than that of [89Zr]-DFO-aflibercept in all the scans. Tumor induction was confirmed in all animal models.

CONCLUSION

MAbs detect VEGF-expression in glioblastoma models. Tumors were earlier targeted by Bevacizumab. The lower blood availability of aflibercept resulted in a lower tumor uptake than bevacizumab in all the scans.

Radiomics characterization of tissues in an animal brain tumor model imaged using dynamic contrast enhanced (DCE) MRI

Here, we investigate radiomics-based characterization of tumor vascular and microenvironmental properties in an orthotopic rat brain tumor model measured using dynamic-contrast-enhanced (DCE) MRI. Thirty-two immune compromised-RNU rats implanted with human U-251N cancer cells were imaged using DCE-MRI (7Tesla, Dual-Gradient-Echo). The aim was to perform pharmacokinetic analysis using a nested model (NM) selection technique to classify brain regions according to vasculature properties considered as the source of truth. A two-dimensional convolutional-based radiomics analysis was performed on the raw-DCE-MRI of the rat brains to generate dynamic radiomics maps. The raw-DCE-MRI and respective radiomics maps were used to build 28 unsupervised Kohonen self-organizing-maps (K-SOMs). A Silhouette-Coefficient (SC), k-fold Nested-Cross-Validation (k-fold-NCV), and feature engineering analyses were performed on the K-SOMs' feature spaces to quantify the distinction power of radiomics features compared to raw-DCE-MRI for classification of different Nested Models. Results showed that eight radiomics features outperformed respective raw-DCE-MRI in prediction of the three nested models. The average percent difference in SCs between radiomics features and raw-DCE-MRI was: 29.875% ± 12.922%, p < 0.001. This work establishes an important first step toward spatiotemporal characterization of brain regions using radiomics signatures, which is fundamental toward staging of tumors and evaluation of tumor response to different treatments.

Dynamic contrast enhanced (DCE) MRI estimation of vascular parameters using knowledge-based adaptive models

We introduce and validate four adaptive models (AMs) to perform a physiologically based Nested-Model-Selection (NMS) estimation of such microvascular parameters as forward volumetric transfer constant, Ktrans, plasma volume fraction, vp, and extravascular, extracellular space, ve, directly from Dynamic Contrast-Enhanced (DCE) MRI raw information without the need for an Arterial-Input Function (AIF). In sixty-six immune-compromised-RNU rats implanted with human U-251 cancer cells, DCE-MRI studies estimated pharmacokinetic (PK) parameters using a group-averaged radiological AIF and an extended Patlak-based NMS paradigm. One-hundred-ninety features extracted from raw DCE-MRI information were used to construct and validate (nested-cross-validation, NCV) four AMs for estimation of model-based regions and their three PK parameters. An NMS-based a priori knowledge was used to fine-tune the AMs to improve their performance. Compared to the conventional analysis, AMs produced stable maps of vascular parameters and nested-model regions less impacted by AIF-dispersion. The performance (Correlation coefficient and Adjusted R-squared for NCV test cohorts) of the AMs were: 0.914/0.834, 0.825/0.720, 0.938/0.880, and 0.890/0.792 for predictions of nested model regions, vp, Ktrans, and ve, respectively. This study demonstrates an application of AMs that quickens and improves DCE-MRI based quantification of microvasculature properties of tumors and normal tissues relative to conventional approaches.

LncRNA MIR4435-2HG functions as a ceRNA against miR-125a-5p and promotes neuroglioma development by upregulating TAZ

BACKGROUND

Expression of the TAZ gene is closely related to the prognosis of glioma patients. We hoped to find long noncoding RNAs (lncRNAs) related to TAZ and a new target for glioma treatment.

METHODS

TAZ-related genes were found by dual-luciferase reporter gene assay, and the correlation of each gene was analyzed by the Pearson method. Human glioma cell lines U87 MG and U251 and glioma rats were used for cytology assays, and the related genes were transfected. We conducted immunohistochemistry, RT-qPCR, Western blotting, CCK8 test, flow cytometry, transwell assays, clone formation analysis, and tumor weight measurements to verify the above relationship.

RESULTS

We found that miR-125a-5p was closely related to the TAZ gene, and the lncRNA MIR4435-2HG was closely related to miR-125a-5p. Both MIR4435-2HG-OE and TAZ increased the expression of the TAZ gene, activated the Wnt signaling pathway, inhibited apoptosis, and promoted migration and proliferation in glioma cells. Besides, it also increased the tumor volume of gliomas in a rat model subcutaneously inoculated with glioma cells. We also found miR-125a-5p could block the effect of MIR4435-2HG-OE and TAZ.

CONCLUSIONS

LncRNA MIR4435-2HG obstructs the functions of miR-125a-5p and promotes neuroglioma development by upregulating the TAZ gene.

Adaptation of laser interstitial thermal therapy for tumor ablation under MRI monitoring in a rat orthotopic model of glioblastoma

BACKGROUND

Laser interstitial thermal therapy (LITT) under magnetic resonance imaging (MRI) monitoring is being increasingly used in cytoreductive surgery of recurrent brain tumors and tumors located in eloquent brain areas. The objective of this study was to adapt this technique to an animal glioma model.

METHODS

A rat model of U251 glioblastoma (GBM) was employed. Tumor location and extent were determined by MRI and dynamic contrast-enhanced (DCE) MRI. A day after assessing tumor appearance, tumors were ablated during diffusion-weighted imaging (DWI)-MRI using a Visualase LITT system (n = 5). Brain images were obtained immediately after ablation and again at 24 h post-ablation to confirm the efficacy of tumor cytoablation. Untreated tumors served as controls (n = 3). Rats were injected with fluorescent isothiocyanate (FITC) dextran and Evans blue that circulated for 10 min after post-LITT MRI. The brains were then removed for fluorescence microscopy and histopathology evaluations using hematoxylin and eosin (H&E) and major histocompatibility complex (MHC) staining.

RESULTS

All rats showed a space-occupying tumor with T2 and T1 contrast-enhancement at pre-LITT imaging. The rats that underwent the LITT procedure showed a well-demarcated ablation zone with near-complete ablation of tumor tissue and with peri-ablation contrast enhancement at 24 h post-ablation. Tumor cytoreduction by ablation as seen on MRI was confirmed by H&E and MHC staining.

CONCLUSIONS

Data showed that tumor cytoablation using MRI-monitored LITT was possible in preclinical glioma models. Real-time MRI monitoring facilitated visualizing and controlling the area of ablation as it is otherwise performed in clinical applications.

A computational model of glioma reveals opposing, stiffness-sensitive effects of leaky vasculature and tumor growth on tissue mechanical stress and porosity

A biphasic computational model of a growing, vascularized glioma within brain tissue was developed to account for unique features of gliomas, including soft surrounding brain tissue, their low stiffness relative to brain tissue, and a lack of draining lymphatics. This model is the first to couple nonlinear tissue deformation with porosity and tissue hydraulic conductivity to study the mechanical interaction of leaky vasculature and solid growth in an embedded glioma. The present model showed that leaky vasculature and elevated interstitial fluid pressure produce tensile stress within the tumor in opposition to the compressive stress produced by tumor growth. This tensile effect was more pronounced in softer tissue and resulted in a compressive stress concentration at the tumor rim that increased when tumor was softer than host. Aside from generating solid stress, fluid pressure-driven tissue deformation decreased the effective stiffness of the tumor while growth increased it, potentially leading to elevated stiffness in the tumor rim. A novel prediction of reduced porosity at the tumor rim was corroborated by direct comparison with estimates from our in vivo imaging studies. Antiangiogenic and radiation therapy were simulated by varying vascular leakiness and tissue hydraulic conductivity. These led to greater solid compression and interstitial pressure in the tumor, respectively, the former of which may promote tumor infiltration of the host. Our findings suggest that vascular leakiness has an important influence on in vivo solid stress, stiffness, and porosity fields in gliomas given their unique mechanical microenvironment.