The development of tumour vascular networks

Biotechnological advances in 3D modeling of cancer initiation. Examples from pancreatic cancer research and beyond

In recent years, biofabrication technologies have garnered significant attention within the scientific community for their potential to create advancedin vitrocancer models. While these technologies have been predominantly applied to model advanced stages of cancer, there exists a pressing need to develop pertinent, reproducible, and sensitive 3D models that mimic cancer initiation lesions within their native tissue microenvironment. Such models hold profound relevance for comprehending the intricacies of cancer initiation, to devise novel strategies for early intervention, and/or to conduct sophisticated toxicology assessments of putative carcinogens. Here, we will explain the pivotal factors that must be faithfully recapitulated when constructing these models, with a specific focus on early pancreatic cancer lesions. By synthesizing the current state of research in this field, we will provide insights into recent advances and breakthroughs. Additionally, we will delineate the key technological and biological challenges that necessitate resolution in future endeavors, thereby paving the way for more accurate and insightfulin vitrocancer initiation models.

The in vitro dynamics of pseudo-vascular network formation

BACKGROUND/OBJECTIVES

Pseudo-vascular network formation in vitro is considered a key characteristic of vasculogenic mimicry. While many cancer cell lines form pseudo-vascular networks, little is known about the spatiotemporal dynamics of these formations.

METHODS

Here, we present a framework for monitoring and characterising the dynamic formation and dissolution of pseudo-vascular networks in vitro. The framework combines time-resolved optical microscopy with open-source image analysis for network feature extraction and statistical modelling. The framework is demonstrated by comparing diverse cancer cell lines associated with vasculogenic mimicry, then in detecting response to drug compounds proposed to affect formation of vasculogenic mimics. Dynamic datasets collected were analysed morphometrically and a descriptive statistical analysis model was developed in order to measure stability and dissimilarity characteristics of the pseudo-vascular networks formed.

RESULTS

Melanoma cells formed the most stable pseudo-vascular networks and were selected to evaluate the response of their pseudo-vascular networks to treatment with axitinib, brucine and tivantinib. Tivantinib has been found to inhibit the formation of the pseudo-vascular networks more effectively, even in dose an order of magnitude less than the two other agents.

CONCLUSIONS

Our framework is shown to enable quantitative analysis of both the capacity for network formation, linked vasculogenic mimicry, as well as dynamic responses to treatment.

Endogenous bystander killing mechanisms enhance the activity of novel FAP-specific CAR-T cells against glioblastoma

Objectives

CAR-T cells are being investigated as a novel immunotherapy for glioblastoma, but clinical success has been limited. We recently described fibroblast activation protein (FAP) as an ideal target antigen for glioblastoma immunotherapy, with expression on both tumor cells and tumor blood vessels. However, CAR-T cells targeting FAP have never been investigated as a therapy for glioblastoma.

Methods

We generated a novel FAP targeting CAR with CD3ζ and CD28 signalling domains and tested the resulting CAR-T cells for their lytic activity and cytokine secretion function in vitro (using real-time impedance, flow cytometry, imaging and bead-based cytokine assays), and in vivo (using a xenograft mimicking the natural heterogeneity of human glioblastoma).

Results

FAP-CAR-T cells exhibited target specificity against model cell lines and potent cytotoxicity against patient-derived glioma neural stem cells, even when only a subpopulation expressed FAP, indicating a bystander killing mechanism. Using co-culture assays, we confirmed FAP-CAR-T cells mediate bystander killing of antigen-negative tumor cells, but only after activation by FAP-positive target cells. This bystander killing was at least partially mediated by soluble factors and amplified by IL-2 which activated the non-transduced fraction of the CAR-T product. Finally, a low dose of intravenously administered FAP-CAR-T cells controlled, without overt toxicity, the growth of subcutaneous tumors created using a mixture of antigen-negative and antigen-positive glioblastoma cells.

Conclusions

Our findings advance FAP as a leading candidate for clinical CAR-T therapy of glioblastoma and highlight under-recognised antigen nonspecific mechanisms that may contribute meaningfully to the antitumor activity of CAR-T cells.

Incorporating temporal information during feature engineering bolsters emulation of spatio-temporal emergence

MOTIVATION

Emergent biological dynamics derive from the evolution of lower-level spatial and temporal processes. A long-standing challenge for scientists and engineers is identifying simple low-level rules that give rise to complex higher-level dynamics. High-resolution biological data acquisition enables this identification and has evolved at a rapid pace for both experimental and computational approaches. Simultaneously harnessing the resolution and managing the expense of emerging technologies-e.g. live cell imaging, scRNAseq, agent-based models-requires a deeper understanding of how spatial and temporal axes impact biological systems. Effective emulation is a promising solution to manage the expense of increasingly complex high-resolution computational models. In this research, we focus on the emulation of a tumor microenvironment agent-based model to examine the relationship between spatial and temporal environment features, and emergent tumor properties.

RESULTS

Despite significant feature engineering, we find limited predictive capacity of tumor properties from initial system representations. However, incorporating temporal information derived from intermediate simulation states dramatically improves the predictive performance of machine learning models. We train a deep-learning emulator on intermediate simulation states and observe promising enhancements over emulators trained solely on initial conditions. Our results underscore the importance of incorporating temporal information in the evaluation of spatio-temporal emergent behavior. Nevertheless, the emulators exhibit inconsistent performance, suggesting that the underlying model characterizes unique cell populations dynamics that are not easily replaced.

AVAILABILITY AND IMPLEMENTATION

All source codes for the agent-based model, emulation, and analyses are publicly available at the corresponding DOIs: 10.5281/zenodo.10622155, 10.5281/zenodo.10611675, 10.5281/zenodo.10621244, respectively.

Synthesis, Characterizations, and Quantum Chemical Investigations on Imidazo[1,2-a]pyrimidine-Schiff Base Derivative: (E)-2-Phenyl-N-(thiophen-2-ylmethylene)imidazo[1,2-a]pyrimidin-3-amine

In this study, (E)-2-phenyl-N-(thiophen-2-ylmethylene)imidazo[1,2-a]pyrimidin-3-amine (3) is synthesized, and detailed spectral characterizations using 1H NMR, 13C NMR, mass, and Fourier transform infrared (FT-IR) spectroscopy were performed. The optimized geometry was computed using the density functional theory method at the B3LYP/6-311++G(d,p) basis set. The theoretical FT-IR and NMR (1H and 13C) analysis are agreed to validate the structural assignment made for (3). Frontier molecular orbitals, molecular electrostatic potential, Mulliken atomic charge, electron localization function, localized orbital locator, natural bond orbital, nonlinear optical, Fukui functions, and quantum theory of atoms in molecules analyses are undertaken and meticulously interpreted, providing profound insights into the molecular nature and behaviors. In addition, ADMET and drug-likeness studies were carried out and investigated. Furthermore, molecular docking and molecular dynamics simulations have been studied, indicating that this is an ideal molecule to develop as a potential vascular endothelial growth factor receptor-2 inhibitor.

Nano-phototherapy: Favorable prospects for cancer treatment

Nanotechnology-based phototherapies have drawn interest in the fight against cancer because of its noninvasiveness, high flexibility, and precision in terms of cancer targeting and drug delivery based on its surface properties and size. Phototherapy has made remarkable development in recent decades. Approaches to phototherapy, which utilize nanomaterials or nanotechnology have emerged to contribute to advances around nanotechnologies in medicine, particularly for cancers. A brief overviews of the development of photodynamic therapy as well as its mechanism in cancer treatment is provided. We emphasize the design of novel nanoparticles utilized in photodynamic therapy while summarizing the representative progress during the recent years. Finally, to forecast important future research in this area, we examine the viability and promise of photodynamic therapy systems based on nanoparticles in clinical anticancer treatment applications and briefly make mention of the elimination of all reactive metabolites pertaining to nano formulations inside living organisms providing insight into clinical mechanistic processes. Future developments and therapeutic prospects for photodynamic treatments are anticipated. Our viewpoints might encourage scientists to create more potent phototherapy-based cancer therapeutic modalities. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

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.

Neovascularization, vascular mimicry and molecular exchange: The imaging of tumorous tissue aggressiveness based on tissue perfusion

Angiogenesis in healthy tissue and within malignant tumors differs on many levels, which may partly be explained by vascular mimicry formation resulting in altered contrast material or different radiopharmaceuticals distributions. Failed remodulation results in changes in the molecular exchange through the capillary wall and those consequences affect the behavior of contrast agents and radiopharmaceuticals. One of the most indicative signs of malignant tissue is the increased permeability and the faster molecular exchange that occurs between the extracellular and intravascular spaces. Dynamic imaging can help to assess the changed microenvironment. The fast-distribution of molecules reflects newly developed conditions in blood-flow redistribution inside a tumor and within the affected organ during the early stages of tumor formation. Tumor development, as well as aggressiveness, can be assessed based on the change to the vascular bed development, the level of molecular exchange within the tissue, and/or indicative distribution within the organ. The study of the vascular network organization and its impact on the distribution of molecules is important to our understanding of the image pattern in several imaging methods, which in turn influences our interpretation of the findings. A hybrid imaging approach (including PET/MRI) allows the quantification of vascularization and/or its pathophysiological impressions in structural and metabolic images. It might optimize the evaluation of the pretreatment imaging, as well as help assess the effect of therapy targeting neovascularization; antiVEGF drugs and embolization-based therapies, for example.

Overcoming the Fibrotic Fortress in Pancreatic Ductal Adenocarcinoma: Challenges and Opportunities

An overabundance of desmoplasia in the tumour microenvironment (TME) is one of the defining features that influences pancreatic ductal adenocarcinoma (PDAC) development, progression, metastasis, and treatment resistance. Desmoplasia is characterised by the recruitment and activation of fibroblasts, heightened extracellular matrix deposition (ECM) and reduced blood supply, as well as increased inflammation through an influx of inflammatory cells and cytokines, creating an intrinsically immunosuppressive TME with low immunogenic potential. Herein, we review the development of PDAC, the drivers that initiate and/or sustain the progression of the disease and the complex and interwoven nature of the cellular and acellular components that come together to make PDAC one of the most aggressive and difficult to treat cancers. We review the challenges in delivering drugs into the fortress of PDAC tumours in concentrations that are therapeutic due to the presence of a highly fibrotic and immunosuppressive TME. Taken together, we present further support for continued/renewed efforts focusing on aspects of the extremely dense and complex TME of PDAC to improve the efficacy of therapy for better patient outcomes.

Detection of Possible Symmetries in Vascular Networks by Computer-Assisted Image Analysis

The possible forms that vascular networks may assume are significantly constrained by complex demands in terms of efficient delivery of oxygen and resources throughout the entire body. Because of these constraints the search for systematic patterns in the structural features of vascular networks and of their correlation with physiological needs and pathological conditions (such as tumor angiogenesis) represents an important line of morphological research. In this context, symmetry properties of vascular trees received limited attention, although symmetry is a widespread phenomenon, visible in all forms and scales in natural environments, and represents a significant information to describe a shape. In the present chapter three, image analysis-based methods allowing for the detection of possible symmetry features exhibited by vascular trees will be detailed and discussed.

Hip osteoarthritis: A novel network analysis of subchondral trabecular bone structures

Hip osteoarthritis (HOA) is a degenerative joint disease that leads to the progressive destruction of subchondral bone and cartilage at the hip joint. Development of effective treatments for HOA remains an open problem, primarily due to the lack of knowledge of its pathogenesis and a typically late-stage diagnosis. We describe a novel network analysis methodology for microcomputed tomography (micro-CT) images of human trabecular bone. We explored differences between the trabecular bone microstructure of femoral heads with and without HOA. Large-scale automated extraction of the network formed by trabecular bone revealed significant network properties not previously reported for bone. Profound differences were discovered, particularly in the proximal third of the femoral head, where HOA networks demonstrated elevated numbers of edges, vertices, and graph components. When further differentiating healthy joint and HOA networks, the latter showed fewer small-world network properties, due to decreased clustering coefficient and increased characteristic path length. Furthermore, we found that HOA networks had reduced length of edges, indicating the formation of compressed trabecular structures. In order to assess our network approach, we developed a deep learning model for classifying HOA and control cases, and we fed it with two separate inputs: (i) micro-CT images of the trabecular bone, and (ii) the network extracted from them. The model with plain micro-CT images achieves 74.6% overall accuracy while the trained model with extracted networks attains 96.5% accuracy. We anticipate our findings to be a starting point for a novel description of bone microstructure in HOA, by considering the phenomenon from a graph theory viewpoint.

Metronomic Chemotherapy for Metastatic Breast Cancer Treatment: Clinical and Preclinical Data between Lights and Shadows

Metronomic chemotherapy (mCHT), defined as continuous administration of low-dose chemotherapeutic agents with no or short regular treatment-free intervals, was first introduced to the clinic in international guidelines in 2017, and, since then, has become one of the available strategies for the treatment of advanced breast cancer (ABC). Despite recent successes, many unsolved practical and theoretical issues remain to be addressed. The present review aims to identify the "lights and shadows" of mCHT in preclinical and clinical settings. In the preclinical setting, several findings indicate that one of the most noticeable effects of mCHT is on the tumor microenvironment, which, over the last twenty years, has been demonstrated to be pivotal in supporting tumor cell survival and proliferation. On the other hand, the direct effects on tumor cells have been less well-defined. In addition, critical items to be addressed are the lack of definition of an optimal biological dose (OBD), the method of administration of metronomic schedules, and the recognition and validation of predictive biomarkers. In the clinical context-where mCHT has mainly been used in a metastatic setting-low toxicity is the most well-recognised light of mCHT, whereas the type of study design, the absence of randomised trials and uncertainty in terms of doses and drugs remain among the shadows. In conclusion, growing evidence indicates that mCHT is a suitable treatment option for selected metastatic breast cancer (MBC) patients. Moreover, given its multimodal mechanisms of action, its addition to immunological and targeted therapies might represent a promising new approach to the treatment of MBC. More preclinical data are needed in this regard, which can only be obtained through support for translational research as the key link between basic science and patient care.

Pt(IV) Prodrugs with Non-Steroidal Anti-inflammatory Drugs in the Axial Position

We report herein the design, synthesis, and biological investigation of a series of novel Pt(IV) prodrugs with non-steroidal anti-inflammatory drugs naproxen, diclofenac, and flurbiprofen, as well as these with stearic acid in the axial position. Six Pt(IV) prodrugs 5-10 were designed, which showed superior antiproliferative activity compared to cisplatin as well as an ability to overcome tumor cell line resistance to cisplatin. By tuning the drug lipophilicity via variation of the axial ligands, the most potent Pt(IV) prodrug 7 was obtained, with an enhanced cellular accumulation of up to 153-fold that of cisplatin and nanomolar cytotoxicity both in 2D and 3D cell cultures. Pt²⁺ species were detected at different depths of MCF-7 spheroids after incubation with Pt(IV) prodrugs using a Pt-coated carbon nanoelectrode. Cisplatin accumulation in vivo in the murine mammary EMT6 tumor tissue of BALB/c mice after Pt(IV) prodrug injection was proved electrochemically as well. The drug tolerance study on BALB/c mice showed good tolerance of 7 in doses up to 8 mg/kg.

Confocal Laser Microscopy for VM Analysis with DAPI and Phalloidin Staining

Confocal laser scanning microscopy (CLSM) is one of the most prevalent fluorescence microscopy techniques for assessing the progression of cancer cells in three-dimensional structures, such as vasculogenic mimicry (VM). We show a basic approach for using DAPI and phalloidin dyes to detect the early stages of progression and VM of melanoma tumor cells grown in a 3D environment, as well as demonstrating how to acquire images and improve them by changing the software acquisition parameters.