PTPmu-targeted nanoparticles label invasive pediatric and adult glioblastoma

Nanomedicine facilitated cell signaling blockade: difficulties and strategies to overcome glioblastoma

Glioblastoma (GBM) is a highly aggressive and lethal type of brain tumor with complex and diverse molecular signaling pathways involved that are in its development and progression. Despite numerous attempts to develop effective treatments, the survival rate remains low. Therefore, understanding the molecular mechanisms of these pathways can aid in the development of targeted therapies for the treatment of glioblastoma. Nanomedicines have shown potential in targeting and blocking signaling pathways involved in glioblastoma. Nanomedicines can be engineered to specifically target tumor sites, bypass the blood-brain barrier (BBB), and release drugs over an extended period. However, current nanomedicine strategies also face limitations, including poor stability, toxicity, and low therapeutic efficacy. Therefore, novel and advanced nanomedicine-based strategies must be developed for enhanced drug delivery. In this review, we highlight risk factors and chemotherapeutics for the treatment of glioblastoma. Further, we discuss different nanoformulations fabricated using synthetic and natural materials for treatment and diagnosis to selectively target signaling pathways involved in GBM. Furthermore, we discuss current clinical strategies and the role of artificial intelligence in the field of nanomedicine for targeting GBM.

Diagnostic and Dosimetry Features of [64Cu]CuCl2 in High-Grade Paediatric Infiltrative Gliomas

PURPOSE OF THE REPORT

Paediatric diffuse high-grade gliomas (PDHGG) are rare central nervous system neoplasms lacking effective therapeutic options. Molecular imaging of tumour metabolism might identify novel diagnostic/therapeutic targets. In this study, we evaluated the distribution and the dosimetry aspects of [⁶⁴Cu]CuCl₂ in PDHGG subjects, as copper is a key element in cellular metabolism whose turnover may be increased in tumour cells.

MATERIAL AND METHODS

Paediatric patients with PDHGG were prospectively recruited. [⁶⁴Cu]CuCl₂ PET/CT was performed 1 h after tracer injection; if the scan was positive, it was repeated 24 and 72 h later. Lesion standardised uptake value (SUV) and target-to-background ratio (TBR) were calculated. Tumour and organ dosimetry were computed using the MIRD algorithm. Each patient underwent an MRI scan, including FLAIR, T2-weighted and post-contrast T1-weighted imaging.

RESULTS

Ten patients were enrolled (median age 9, range 6-16 years, 6 females). Diagnoses were diffuse midline gliomas (n = 8, 5 of which with H3K27 alterations) and diffuse hemispheric gliomas (n = 2). Six patients had visible tracer uptake (SUV: 1.0 ± 0.6 TBR: 5 ± 3.1). [⁶⁴Cu]CuCl₂ accumulation was always concordant with MRI contrast enhancement and was higher in the presence of radiological signs of necrosis. SUV and TBR progressively increased on the 24- and 72-h acquisitions (p < 0.05 and p < 0.01, respectively). The liver and the abdominal organs received the highest non-target dose.

CONCLUSIONS

[⁶⁴Cu]CuCl₂ is a well-tolerated radiotracer with reasonably favourable dosimetric properties, showing selective uptake in tumour areas with visible contrast enhancement and necrosis, thus suggesting that blood-brain barrier damage is a pre-requisite for its distribution to the intracranial structures. Moreover, tracer uptake showed an accumulating trend over time. These characteristics could deserve further analysis, to determine whether this radiopharmaceutical might have a possible therapeutic role as well.

Artificial Intelligence-Based Computational Screening and Functional Assays Identify Candidate Small Molecule Antagonists of PTPmu-Dependent Adhesion

PTPmu (PTPµ) is a member of the receptor protein tyrosine phosphatase IIb family that participates in cell-cell adhesion and signaling. PTPmu is proteolytically downregulated in glioblastoma (glioma), and the resulting extracellular and intracellular fragments are believed to stimulate cancer cell growth and/or migration. Therefore, drugs targeting these fragments may have therapeutic potential. Here, we used the AtomNet^® platform, the first deep learning neural network for drug design and discovery, to screen a molecular library of several million compounds and identified 76 candidates predicted to interact with a groove between the MAM and Ig extracellular domains required for PTPmu-mediated cell adhesion. These candidates were screened in two cell-based assays: PTPmu-dependent aggregation of Sf9 cells and a tumor growth assay where glioma cells grow in three-dimensional spheres. Four compounds inhibited PTPmu-mediated aggregation of Sf9 cells, six compounds inhibited glioma sphere formation/growth, while two priority compounds were effective in both assays. The stronger of these two compounds inhibited PTPmu aggregation in Sf9 cells and inhibited glioma sphere formation down to 25 micromolar. Additionally, this compound was able to inhibit the aggregation of beads coated with an extracellular fragment of PTPmu, directly demonstrating an interaction. This compound presents an interesting starting point for the development of PTPmu-targeting agents for treating cancer including glioblastoma.

Comparison of Near-Infrared Imaging Agents Targeting the PTPmu Tumor Biomarker

PURPOSE

Maximal, safe resection of solid tumors is considered a critical first step in successful cancer treatment. The advent of fluorescence image-guided surgery (FIGS) using non-specific agents has improved patient outcomes, particularly in the case of glioblastoma. Molecularly targeted agents that recognize specific tumor biomarkers have the potential to augment these gains. Identification of the optimal combination of targeting moiety and fluorophore is needed prior to initiating clinical trials.

PROCEDURES

A 20-amino acid peptide (SBK2) recognizing the receptor protein-tyrosine phosphatase mu (PTPmu)-derived tumor-specific biomarker, with or without a linker, was conjugated to three different near-infrared fluorophores: indocyanine green (ICG), IRDye® 800CW, and Tide Fluor™ 8WS. The in vivo specificity, time course, and biodistribution were evaluated for each using mice with heterotopic human glioma tumors that express the PTPmu biomarker to identify component combinations with optimal properties for FIGS.

RESULTS

SBK2 conjugated to ICG demonstrated excellent specificity for gliomas in heterotopic tumors. SBK2-ICG showed significantly higher in vivo tumor labeling compared to the Scram-ICG control from 10 min to 24 h, p < 0.01 at all timepoints, following injection, as well as a significantly higher ex vivo tumor signal at 24 h, p < 0.001. Inserting a six-amino acid linker between the targeting peptide and ICG increased the clearance rate and resulted in significantly higher in vivo tumor signal relative to its linker-containing Scrambled control from 10 min to 8 h, p < 0.05 at all timepoints, after dosing. Agents made with the more hydrophilic IRDye® 800CW and Tide Fluor™ 8WS showed no specific tumor labeling relative to the controls. The IRDye 800CW-conjugated agents cleared within 1 h, while the non-specific fluorescent tumor signal generated by the Tide Fluor 8WS-conjugated agents persists beyond 24 h.

CONCLUSIONS

The SBK2 PTPmu-targeting peptide conjugated to ICG specifically labels heterotopic human gliomas grown in mice between 10 min and 24 h following injection. Similar molecules constructed with more hydrophilic dyes demonstrated no specificity. These studies present a promising candidate for use in FIGS of PTPmu biomarker-expressing tumors.

Recent development of contrast agents for magnetic resonance and multimodal imaging of glioblastoma

Glioblastoma (GBM) as the most common primary malignant brain tumor exhibits a high incidence and degree of malignancy as well as poor prognosis. Due to the existence of formidable blood–brain barrier (BBB) and the aggressive growth and infiltrating nature of GBM, timely diagnosis and treatment of GBM is still very challenging. Among different imaging modalities, magnetic resonance imaging (MRI) with merits including high soft tissue resolution, non-invasiveness and non-limited penetration depth has become the preferred tool for GBM diagnosis. Furthermore, multimodal imaging with combination of MRI and other imaging modalities would not only synergistically integrate the pros, but also overcome the certain limitation in each imaging modality, offering more accurate morphological and pathophysiological information of brain tumors. Since contrast agents contribute to amplify imaging signal output for unambiguous pin-pointing of tumors, tremendous efforts have been devoted to advances of contrast agents for MRI and multimodal imaging. Herein, we put special focus on summary of the most recent advances of not only MRI contrast agents including iron oxide-, manganese (Mn)-, gadolinium (Gd)-, ¹⁹F- and copper (Cu)-incorporated nanoplatforms for GBM imaging, but also dual-modal or triple-modal nanoprobes. Furthermore, potential obstacles and perspectives for future research and clinical translation of these contrast agents are discussed. We hope this review provides insights for scientists and students with interest in this area.

A review of recent advances in magnetic nanoparticle-based theranostics of glioblastoma

Rapid vascular growth, infiltrative cells and high tumor heterogenicity are some glioblastoma multiforme (GBM) characteristics, making it the most lethal form of brain cancer. Low efficacy of the conventional treatment modalities leads to rampant disease progression and a median survival of 15 months. Magnetic nanoparticles (MNPs), due to their unique physical features/inherent abilities, have emerged as a suitable theranostic platform for targeted GBM treatment. Thus, new strategies are being designed to enhance the efficiency of existing therapeutic techniques such as chemotherapy, radiotherapy, and so on, using MNPs. Herein, the limitations of the current therapeutic strategies, the role of MNPs in mitigating those inadequacies, recent advances in the MNP-based theranostics of GBM and possible future directions are discussed.

Advances in magnetic resonance imaging contrast agents for glioblastoma-targeting theranostics

Glioblastoma (GBM) is the most aggressive malignant brain tumour, with a median survival of 3 months without treatment and 15 months with treatment. Early GBM diagnosis can significantly improve patient survival due to early treatment and management procedures. Magnetic resonance imaging (MRI) using contrast agents is the preferred method for the preoperative detection of GBM tumours. However, commercially available clinical contrast agents do not accurately distinguish between GBM, surrounding normal tissue and other cancer types due to their limited ability to cross the blood–brain barrier, their low relaxivity and their potential toxicity. New GBM-specific contrast agents are urgently needed to overcome the limitations of current contrast agents. Recent advances in nanotechnology have produced alternative GBM-targeting contrast agents. The surfaces of nanoparticles (NPs) can be modified with multimodal contrast imaging agents and ligands that can specifically enhance the accumulation of NPs at GBM sites. Using advanced imaging technology, multimodal NP-based contrast agents have been used to obtain accurate GBM diagnoses in addition to an increased amount of clinical diagnostic information. NPs can also serve as drug delivery systems for GBM treatments. This review focuses on the research progress for GBM-targeting MRI contrast agents as well as MRI-guided GBM therapy.

Quantitative analysis of metastatic breast cancer in mice using deep learning on cryo-image data

Cryo-imaging sections and images a whole mouse and provides ~ 120-GBytes of microscopic 3D color anatomy and fluorescence images, making fully manual analysis of metastases an onerous task. A convolutional neural network (CNN)-based metastases segmentation algorithm included three steps: candidate segmentation, candidate classification, and semi-automatic correction of the classification result. The candidate segmentation generated > 5000 candidates in each of the breast cancer-bearing mice. Random forest classifier with multi-scale CNN features and hand-crafted intensity and morphology features achieved 0.8645 ± 0.0858, 0.9738 ± 0.0074, and 0.9709 ± 0.0182 sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic (ROC), with fourfold cross validation. Classification results guided manual correction by an expert with our in-house MATLAB software. Finally, 225, 148, 165, and 344 metastases were identified in the four cancer mice. With CNN-based segmentation, the human intervention time was reduced from > 12 to ~ 2 h. We demonstrated that 4T1 breast cancer metastases spread to the lung, liver, bone, and brain. Assessing the size and distribution of metastases proves the usefulness and robustness of cryo-imaging and our software for evaluating new cancer imaging and therapeutics technologies. Application of the method with only minor modification to a pancreatic metastatic cancer model demonstrated generalizability to other tumor models.

Stimuli-Responsive Iron Oxide Nanotheranostics: A Versatile and Powerful Approach for Cancer Therapy

Recent advancements in unravelling elements of cancer biology involved in disease progression and treatment resistance have highlighted the need for a holistic approach to effectively tackle cancer. Stimuli-responsive nanotheranostics based on iron oxide nanoparticles are an emerging class of versatile nanomedicines with powerful capabilities to "seek, sense, and attack" multiple components of solid tumors. In this work, the rationale for using iron oxide nanoparticles and the basic physical principles that impact their function in biomedical applications are reviewed. Subsequently, recent advances in the integration of iron oxide nanoparticles with various stimulus mechanisms to facilitate the development of stimuli-responsive nanotheranostics for application in cancer therapy are summarized. The integration of an iron oxide core with various surface coating mechanisms results in the generation of hybrid nanoconstructs with capabilities to codeliver a wide variety of highly potent anticancer therapeutics and immune modulators. Finally, emerging future directions and considerations for their clinical translation are touched upon.