1
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Tang C, Chen L, Xu Y, Huang L, Zeng Z. Prediction of TERT mutation status in gliomas using conventional MRI radiogenomic features. Front Neurol 2024; 15:1439598. [PMID: 39131044 PMCID: PMC11310134 DOI: 10.3389/fneur.2024.1439598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Accepted: 07/15/2024] [Indexed: 08/13/2024] Open
Abstract
Objective Telomerase reverse transcriptase (TERT) promoter mutation status in gliomas is a key determinant of treatment strategy and prognosis. This study aimed to analyze the radiogenomic features and construct radiogenomic models utilizing medical imaging techniques to predict the TERT promoter mutation status in gliomas. Methods This was a retrospective study of 304 patients with gliomas. T1-weighted contrast-enhanced, apparent diffusion coefficient, and diffusion-weighted imaging MRI sequences were used for radiomic feature extraction. A total of 3,948 features were extracted from MRI images using the FAE software. These included 14 shape features, 18 histogram features, 24 gray level run length matrix, 14 gray level dependence matrix, 16 gray level run length matrix, 16 gray level size zone matrix (GLSZM), 5 neighboring gray tone difference matrix, and 744 wavelet transforms. The dataset was randomly divided into training and testing sets in a ratio of 7:3. Three feature selection methods and six classification algorithms were used to model the selected features. Predictive performance was evaluated using receiver operating characteristic curve analysis. Results Among the evaluated classification algorithms, the combination model of recursive feature elimination (RFE) with linear regression (LR) using six features showed the best diagnostic performance (area under the curve: 0.733, 0.562, and 0.633 in the training, validation, and testing sets, respectively). The next best-performing models were naive Bayes, linear discriminant analysis, autoencoder, and support vector machine. Regarding the three feature selection algorithms, RFE showed the most consistent performance, followed by relief and ANOVA. T1-enhanced entropy and GLSZM derived from T1-enhanced images were identified as the most critical radiomics features for distinguishing TERT promoter mutation status. Conclusion The LR and LRLasso models, mainly based on T1-enhanced entropy and GLSZM, showed good predictive ability for TERT promoter mutations in gliomas using radiomics models.
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Affiliation(s)
| | | | | | | | - Zisan Zeng
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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2
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Ali TE, Rodoshi ZN, Salcedo YE, Patel VK, Khan I. Optimizing Glioma Resection Outcomes: A Systematic Review of Intraoperative Magnetic Resonance Imaging Guidance in Neurosurgery. Cureus 2024; 16:e64697. [PMID: 39156414 PMCID: PMC11327550 DOI: 10.7759/cureus.64697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/16/2024] [Indexed: 08/20/2024] Open
Abstract
This systematic review evaluates the efficacy of intraoperative magnetic resonance imaging (iMRI) in enhancing glioma resection outcomes within neurosurgical procedures. Given the complexity and variability of gliomas, achieving precise and safe resections is challenging, necessitating the use of advanced imaging techniques like iMRI. This technology provides real-time, high-resolution insights during surgery, allowing for adaptations based on surgical dynamics and brain shifts. Our comprehensive search across multiple databases selected five significant studies that collectively demonstrate the beneficial impact of iMRI. These studies highlight its role in significantly improving the extent of tumor resection and suggest potential enhancements in both immediate and long-term patient outcomes. The findings indicate that iMRI facilitates more aggressive yet safe resections, particularly in high-risk glioma cases. However, the implementation of iMRI in clinical practice requires careful consideration of training, resource allocation, and the potential variability in outcomes due to study design heterogeneity. Future research should focus on randomized controlled trials to better understand the cost-effectiveness and long-term benefits of iMRI, promoting its wider adoption in neurosurgical settings.
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Affiliation(s)
- Thowaiba E Ali
- Medicine and Surgery, University of Khartoum, Khartoum, SDN
- Healthcare Administration, University of Tennessee at Chattanooga, Chattanooga, USA
| | | | | | | | - Ismail Khan
- Internal Medicine, Nishtar Medical University, Multan, PAK
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3
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Quadrado RFN, Silvestri S, de Souza JF, Iglesias BA, Fajardo AR. Advances in porphyrins and chlorins associated with polysaccharides and polysaccharides-based materials for biomedical and pharmaceutical applications. Carbohydr Polym 2024; 334:122017. [PMID: 38553216 DOI: 10.1016/j.carbpol.2024.122017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 02/26/2024] [Accepted: 03/01/2024] [Indexed: 04/02/2024]
Abstract
Over the last decade, the convergence of advanced materials and innovative applications has fostered notable scientific progress within the biomedical and pharmaceutical fields. Porphyrins and their derivatives, distinguished by an extended conjugated π-electron system, have a relevant role in propelling these advancements, especially in drug delivery systems, photodynamic therapy, wound healing, and (bio)sensing. However, despite their promise, the practical clinical application of these macrocycles is hindered by their inherent challenges of low solubility and instability under physiological conditions. To address this limitation, researchers have exploited the synergistic association of porphyrins and chlorins with polysaccharides by engineering conjugated systems and composite/hybrid materials. This review compiles the principal advances in this growing research field, elucidating fundamental principles and critically examining the applications of such materials within biomedical and pharmaceutical contexts. Additionally, the review addresses the eventual challenges and outlines future perspectives for this poignant research field. It is expected that this review will serve as a comprehensive guide for students and researchers dedicated to exploring state-of-the-art materials for contemporary medicine and pharmaceutical applications.
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Affiliation(s)
- Rafael F N Quadrado
- Laboratório de Tecnologia e Desenvolvimento de Compósitos e Materiais Poliméricos (LaCoPol), Universidade Federal de Pelotas (UFPel), Campus Capão do Leão s/n, 96010-900 Pelotas, RS, Brazil
| | - Siara Silvestri
- Laboratório de Tecnologia e Desenvolvimento de Compósitos e Materiais Poliméricos (LaCoPol), Universidade Federal de Pelotas (UFPel), Campus Capão do Leão s/n, 96010-900 Pelotas, RS, Brazil; Laboratório de Engenharia de Meio Ambiente (LEMA), Universidade Federal de Santa Maria (UFSM), Campus Camobi, 97105-900 Santa Maria, RS, Brazil
| | - Jaqueline F de Souza
- Laboratório de Bioinorgânica e Materiais Porfirínicos, Universidade Federal de Santa Maria (UFSM), Campus Camobi, 97105-900, Santa Maria, RS, Brazil
| | - Bernardo A Iglesias
- Laboratório de Bioinorgânica e Materiais Porfirínicos, Universidade Federal de Santa Maria (UFSM), Campus Camobi, 97105-900, Santa Maria, RS, Brazil.
| | - André R Fajardo
- Laboratório de Tecnologia e Desenvolvimento de Compósitos e Materiais Poliméricos (LaCoPol), Universidade Federal de Pelotas (UFPel), Campus Capão do Leão s/n, 96010-900 Pelotas, RS, Brazil.
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4
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Das N, Vikas, Kumar A, Soni S, Rayavarapu RG. Gold nanomakura: nanoarchitectonics and their photothermal response in association with carrageenan hydrogels. BEILSTEIN JOURNAL OF NANOTECHNOLOGY 2024; 15:678-693. [PMID: 38887524 PMCID: PMC11181249 DOI: 10.3762/bjnano.15.56] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 05/16/2024] [Indexed: 06/20/2024]
Abstract
Photothermal conversion of light into heat energy is an intrinsic optical property of metal nanoparticles when irradiated using near-infrared radiation. However, the impact of size and shape on the photothermal behaviour of gold nanomakura particles possessing optical absorption within 600-700 nm as well as on incorporation in hydrogels is not well reported. In this study, nanomakura-shaped anisotropic gold nanoparticles (AuNMs) were synthesized via a surfactant-assisted seed-mediated protocol. Quaternary cationic surfactants having variable carbon tail length (n = 16, 14, 12) were used as capping for tuning the plasmon peak of gold nanomakura within a 600-700 nm wavelength. The aspect ratio as well as anisotropy of synthesized gold nanomakura can influence photothermal response upon near-infrared irradiation. The role of carbon tail length was evident via absorption peaks obtained from longitudinal surface plasmon resonance analysis at 670, 650, and 630 nm in CTAB-AuNM, MTAB-AuNM, and DTAB-AuNM, respectively. Furthermore, the impact of morphology and surrounding milieu of the synthesized nanomakuras on photothermal conversion is investigated owing to their retention of plasmonic stability. Interestingly, we found that photothermal conversion was exclusively assigned to morphological features (i.e., nanoparticles of higher aspect ratio showed higher temperature change and vice versa irrespective of the surfactant used). To enable biofunctionality and stability, we used kappa-carrageenan- (k-CG) based hydrogels for incorporating the nanomakuras and further assessed their photothermal response. Nanomakura particles in association with k-CG were also able to show photothermal conversion, depicting their ability to interact with light without hindrance. The CTAB-AuNM, MTAB-AuNM, and DTAB-AuNM after incorporation into hydrogel beads attained up to ≈17.2, ≈17.2, and ≈15.7 °C, respectively. On the other hand, gold nanorods after incorporation into k-CG did not yield much photothermal response as compared to that of AuNMs. The results showed a promising platform to utilize nanomakura particles along with kappa-carrageenan hydrogels for enabling usage on nanophotonic, photothermal, and bio-imaging applications.
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Affiliation(s)
- Nabojit Das
- Nanomaterial Toxicology Laboratory, Drug and Chemical Toxicology Group, Food, Drug & Chemical, Environment and Systems Toxicology (FEST) Division, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31 Mahatma Gandhi Marg, Lucknow 226001, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Vikas
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Biomedical Applications Group, CSIR-Central Scientific Instruments Organisation, Sector 30C, Chandigarh 160030, India
| | - Akash Kumar
- Nanomaterial Toxicology Laboratory, Drug and Chemical Toxicology Group, Food, Drug & Chemical, Environment and Systems Toxicology (FEST) Division, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31 Mahatma Gandhi Marg, Lucknow 226001, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Sanjeev Soni
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Biomedical Applications Group, CSIR-Central Scientific Instruments Organisation, Sector 30C, Chandigarh 160030, India
| | - Raja Gopal Rayavarapu
- Nanomaterial Toxicology Laboratory, Drug and Chemical Toxicology Group, Food, Drug & Chemical, Environment and Systems Toxicology (FEST) Division, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31 Mahatma Gandhi Marg, Lucknow 226001, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
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Khan MK, Raza M, Shahbaz M, Hussain I, Khan MF, Xie Z, Shah SSA, Tareen AK, Bashir Z, Khan K. The recent advances in the approach of artificial intelligence (AI) towards drug discovery. Front Chem 2024; 12:1408740. [PMID: 38882215 PMCID: PMC11176507 DOI: 10.3389/fchem.2024.1408740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 04/26/2024] [Indexed: 06/18/2024] Open
Abstract
Artificial intelligence (AI) has recently emerged as a unique developmental influence that is playing an important role in the development of medicine. The AI medium is showing the potential in unprecedented advancements in truth and efficiency. The intersection of AI has the potential to revolutionize drug discovery. However, AI also has limitations and experts should be aware of these data access and ethical issues. The use of AI techniques for drug discovery applications has increased considerably over the past few years, including combinatorial QSAR and QSPR, virtual screening, and denovo drug design. The purpose of this survey is to give a general overview of drug discovery based on artificial intelligence, and associated applications. We also highlighted the gaps present in the traditional method for drug designing. In addition, potential strategies and approaches to overcome current challenges are discussed to address the constraints of AI within this field. We hope that this survey plays a comprehensive role in understanding the potential of AI in drug discovery.
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Affiliation(s)
- Mahroza Kanwal Khan
- College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, China
| | - Mohsin Raza
- Additive Manufacturing Institute, Shenzhen University, Shenzhen, China
| | - Muhammad Shahbaz
- Additive Manufacturing Institute, Shenzhen University, Shenzhen, China
| | - Iftikhar Hussain
- Department of Mechanical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, China
- A. J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA, United States
| | - Muhammad Farooq Khan
- Department of Electrical Engineering, Sejong University, Seoul, Republic of Korea
| | - Zhongjian Xie
- Shenzhen Children's Hospital, Clinical Medical College of Southern University of Science and Technology, Shenzhen, China
| | - Syed Shoaib Ahmad Shah
- Department of Chemistry, School of Natural Sciences, National University of Sciences and Technology, Islamabad, Pakistan
| | - Ayesha Khan Tareen
- School of Mechanical Engineering, Dongguan University of Technology, Dongguan, China
| | - Zoobia Bashir
- College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, China
| | - Karim Khan
- Additive Manufacturing Institute, Shenzhen University, Shenzhen, China
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6
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Miceli A, Liberini V, Pepe G, Dondi F, Vento A, Jonghi Lavarini L, Celesti G, Gazzilli M, Serani F, Guglielmo P, Buschiazzo A, Filice R, Alongi P, Laudicella R, Santo G. Prostate-Specific Membrane Antigen Positron Emission Tomography Oncological Applications beyond Prostate Cancer in Comparison to Other Radiopharmaceuticals. Diagnostics (Basel) 2024; 14:1002. [PMID: 38786300 PMCID: PMC11119694 DOI: 10.3390/diagnostics14101002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 04/29/2024] [Accepted: 05/09/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Prostate-specific membrane antigen (PSMA) is a type II transmembrane glycoprotein overexpressed on the surface of tumor cells in most of the patients affected by prostate adenocarcinoma (PCa). However, PSMA expression has also been demonstrated in the endothelial cells of newly formed vessels of various solid tumors, suggesting a role for PSMA in neoangiogenesis. In this scenario, gallium-68 (68Ga) or fluoro-18 (18F)-labeled PSMA positron emission tomography (PET) may play a role in tumors other than PCa, generally evaluated employing other radiopharmaceuticals targeting different pathways. This review aims to investigate the detection rate of PSMA-PET compared to other radiopharmaceuticals (especially [18F]FDG) in non-prostate tumors to identify patients who may benefit from the use of such a theragnostic agent. METHODS We performed a bibliographic search on three different databases until February 2024 using the following terms: "positron emission tomography", "PET", "PET/CT", "Prostate-specific membrane antigen", "PSMA", "non-prostate", "not prostate cancer", "solid tumor", "FDG", "Fluorodeoxyglucose", "FAPi", "FET", "MET", "DOPA", "choline", "FCH", "FES", "DOTATOC", "DOTANOC", and "DOTATATE". Only original articles edited in English with at least 10 patients were included. RESULTS Out of a total of 120 articles, only 25 original articles comparing PSMA with other radiotracers were included in this study. The main evidence was demonstrated in renal cell carcinoma, where PSMA showed a higher detection rate compared to [18F]FDG PET/CT, with implications for patient management. PSMA PET may also improve the assessment of other entities, such as gliomas, in defining regions of early neoangiogenesis. Further data are needed to evaluate the potential role of PSMA-PET in triple-negative breast cancer as a novel therapeutic vascular target. Finally, unclear applications of PSMA-PET include thyroid and gastrointestinal tumors. CONCLUSIONS The present review shows the potential use of PSMA-labeled PET/CT in solid tumors beyond PCa, underlining its value over other radiopharmaceuticals (mainly [18F]FDG). Prospective clinical trials with larger sample sizes are crucial to further investigate these possible clinical applications.
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Affiliation(s)
- Alberto Miceli
- Nuclear Medicine Unit, Azienda Ospedaliero-Universitaria SS. Antonio e Biagio e Cesare Arrigo, 15121 Alessandria, Italy;
| | - Virginia Liberini
- Nuclear Medicine Unit, ASO S.Croce e Carle Cuneo, 12100 Cuneo, Italy; (V.L.); (A.B.)
| | - Giovanna Pepe
- Nuclear Medicine Unit, Fondazione IRCCS Policlinico San Matteo—Pavia V.le Camillo Golgi, 27100 Pavia, Italy;
| | - Francesco Dondi
- Nuclear Medicine Unit, ASST Spedali Civili di Brescia, 25123 Brescia, Italy;
| | - Antonio Vento
- Nuclear Medicine Unit, ASP 1—P.O. San Giovanni di Dio, 92100 Agrigento, Italy;
| | | | - Greta Celesti
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and of Morpho-Functional Imaging, University of Messina, 98122 Messina, Italy; (G.C.); (R.L.)
| | - Maria Gazzilli
- Nuclear Medicine Unit, ASL Bari—Di Venere Bari, 70131 Bari, Italy;
| | - Francesca Serani
- Nuclear Medicine Unit, Presidio Ospedaliero Santo Spirito, 65124 Pescara, Italy;
| | - Priscilla Guglielmo
- Nuclear Medicine Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy;
| | - Ambra Buschiazzo
- Nuclear Medicine Unit, ASO S.Croce e Carle Cuneo, 12100 Cuneo, Italy; (V.L.); (A.B.)
| | - Rossella Filice
- Nuclear Medicine Unit, University Hospital “Paolo Giaccone”, Via del Vespro 129, 90127 Palermo, Italy;
| | - Pierpaolo Alongi
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico, Di Cristina e Benfratelli, 90127 Palermo, Italy;
| | - Riccardo Laudicella
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and of Morpho-Functional Imaging, University of Messina, 98122 Messina, Italy; (G.C.); (R.L.)
| | - Giulia Santo
- Nuclear Medicine Unit, Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy
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7
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M MM, T R M, V VK, Guluwadi S. Enhancing brain tumor detection in MRI images through explainable AI using Grad-CAM with Resnet 50. BMC Med Imaging 2024; 24:107. [PMID: 38734629 PMCID: PMC11088067 DOI: 10.1186/s12880-024-01292-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Accepted: 05/06/2024] [Indexed: 05/13/2024] Open
Abstract
This study addresses the critical challenge of detecting brain tumors using MRI images, a pivotal task in medical diagnostics that demands high accuracy and interpretability. While deep learning has shown remarkable success in medical image analysis, there remains a substantial need for models that are not only accurate but also interpretable to healthcare professionals. The existing methodologies, predominantly deep learning-based, often act as black boxes, providing little insight into their decision-making process. This research introduces an integrated approach using ResNet50, a deep learning model, combined with Gradient-weighted Class Activation Mapping (Grad-CAM) to offer a transparent and explainable framework for brain tumor detection. We employed a dataset of MRI images, enhanced through data augmentation, to train and validate our model. The results demonstrate a significant improvement in model performance, with a testing accuracy of 98.52% and precision-recall metrics exceeding 98%, showcasing the model's effectiveness in distinguishing tumor presence. The application of Grad-CAM provides insightful visual explanations, illustrating the model's focus areas in making predictions. This fusion of high accuracy and explainability holds profound implications for medical diagnostics, offering a pathway towards more reliable and interpretable brain tumor detection tools.
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Affiliation(s)
| | - Mahesh T R
- Department of Computer Science and Engineering, JAIN (Deemed-to-be University), Bengaluru, 562112, India
| | - Vinoth Kumar V
- School of Computer Science Engineering and Information Systems, Vellore Institute of Technology University, Vellore, 632014, India
| | - Suresh Guluwadi
- Adama Science and Technology University, Adama, 302120, Ethiopia.
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8
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Thenuwara G, Javed B, Singh B, Tian F. Biosensor-Enhanced Organ-on-a-Chip Models for Investigating Glioblastoma Tumor Microenvironment Dynamics. SENSORS (BASEL, SWITZERLAND) 2024; 24:2865. [PMID: 38732975 PMCID: PMC11086276 DOI: 10.3390/s24092865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 04/19/2024] [Accepted: 04/27/2024] [Indexed: 05/13/2024]
Abstract
Glioblastoma, an aggressive primary brain tumor, poses a significant challenge owing to its dynamic and intricate tumor microenvironment. This review investigates the innovative integration of biosensor-enhanced organ-on-a-chip (OOC) models as a novel strategy for an in-depth exploration of glioblastoma tumor microenvironment dynamics. In recent years, the transformative approach of incorporating biosensors into OOC platforms has enabled real-time monitoring and analysis of cellular behaviors within a controlled microenvironment. Conventional in vitro and in vivo models exhibit inherent limitations in accurately replicating the complex nature of glioblastoma progression. This review addresses the existing research gap by pioneering the integration of biosensor-enhanced OOC models, providing a comprehensive platform for investigating glioblastoma tumor microenvironment dynamics. The applications of this combined approach in studying glioblastoma dynamics are critically scrutinized, emphasizing its potential to bridge the gap between simplistic models and the intricate in vivo conditions. Furthermore, the article discusses the implications of biosensor-enhanced OOC models in elucidating the dynamic features of the tumor microenvironment, encompassing cell migration, proliferation, and interactions. By furnishing real-time insights, these models significantly contribute to unraveling the complex biology of glioblastoma, thereby influencing the development of more accurate diagnostic and therapeutic strategies.
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Affiliation(s)
- Gayathree Thenuwara
- School of Food Science and Environmental Health, Technological University Dublin, Grangegorman Lower, D07 H6K8 Dublin, Ireland; (G.T.); (B.J.)
- Institute of Biochemistry, Molecular Biology, and Biotechnology, University of Colombo, Colombo 00300, Sri Lanka
| | - Bilal Javed
- School of Food Science and Environmental Health, Technological University Dublin, Grangegorman Lower, D07 H6K8 Dublin, Ireland; (G.T.); (B.J.)
- Nanolab Research Centre, FOCAS Research Institute, Technological University Dublin, Camden Row, D08 CKP1 Dublin, Ireland
| | - Baljit Singh
- MiCRA Biodiagnostics Technology Gateway, Technological University Dublin (TU Dublin), D24 FKT9 Dublin, Ireland;
| | - Furong Tian
- School of Food Science and Environmental Health, Technological University Dublin, Grangegorman Lower, D07 H6K8 Dublin, Ireland; (G.T.); (B.J.)
- Nanolab Research Centre, FOCAS Research Institute, Technological University Dublin, Camden Row, D08 CKP1 Dublin, Ireland
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9
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Tosi U, Souweidane M. Diffuse Midline Gliomas: Challenges and New Strategies in a Changing Clinical Landscape. Cancers (Basel) 2024; 16:219. [PMID: 38201646 PMCID: PMC10778507 DOI: 10.3390/cancers16010219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 12/29/2023] [Accepted: 12/31/2023] [Indexed: 01/12/2024] Open
Abstract
Diffuse intrinsic pontine glioma (DIPG) was first described by Harvey Cushing, the father of modern neurosurgery, a century ago. Since then, the classification of this tumor changed significantly, as it is now part of the broader family of diffuse midline gliomas (DMGs), a heterogeneous group of tumors of midline structures encompassing the entire rostro-caudal space, from the thalamus to the spinal cord. DMGs are characterized by various epigenetic events that lead to chromatin remodeling similarities, as two decades of studies made possible by increased tissue availability showed. This new understanding of tumor (epi)biology is now driving novel clinical trials that rely on targeted agents, with finally real hopes for a change in an otherwise unforgiving prognosis. This biological discovery is being paralleled with equally exciting work in therapeutic drug delivery. Invasive and noninvasive platforms have been central to early phase clinical trials with a promising safety track record and anecdotal benefits in outcome.
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Affiliation(s)
- Umberto Tosi
- Department of Neurological Surgery, Weill Cornell Medicine, New York, NY 10021, USA
- Department of Neurological Surgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Mark Souweidane
- Department of Neurological Surgery, Weill Cornell Medicine, New York, NY 10021, USA
- Department of Neurological Surgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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10
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Jang P, Ser J, Cardenas K, Kim HJ, Hickey M, Jang J, Gladstone J, Bailey A, Dinh J, Nguyen V, DeMarco E, Srinivas S, Kang H, Kashiwagi S, Bao K, Yamashita A, Choi HS. HSA-ZW800-PEG for Enhanced Optophysical Stability and Tumor Targeting. Int J Mol Sci 2023; 25:559. [PMID: 38203730 PMCID: PMC10779243 DOI: 10.3390/ijms25010559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 12/21/2023] [Accepted: 12/28/2023] [Indexed: 01/12/2024] Open
Abstract
Small molecule fluorophores often face challenges such as short blood half-life, limited physicochemical and optical stability, and poor pharmacokinetics. To overcome these limitations, we conjugated the zwitterionic near-infrared fluorophore ZW800-PEG to human serum albumin (HSA), creating HSA-ZW800-PEG. This conjugation notably improves chemical, physical, and optical stability under physiological conditions, addressing issues commonly encountered with small molecules in biological applications. Additionally, the high molecular weight and extinction coefficient of HSA-ZW800-PEG enhances biodistribution and tumor targeting through the enhanced permeability and retention effect. The unique distribution and elimination dynamics, along with the significantly extended blood half-life of HSA-ZW800-PEG, contribute to improved tumor targetability in both subcutaneous and orthotopic xenograft tumor-bearing animal models. This modification not only influences the pharmacokinetic profile, affecting retention time and clearance patterns, but also enhances bioavailability for targeting tissues. Our study guides further development and optimization of targeted imaging agents and drug-delivery systems.
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Affiliation(s)
- Paul Jang
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Jinhui Ser
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
- School of Materials Science & Engineering, Chonnam National University, Gwangju 61186, Republic of Korea
| | - Kevin Cardenas
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Hajin Joanne Kim
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Morgan Hickey
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Jiseon Jang
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Jason Gladstone
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Aisha Bailey
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Jason Dinh
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Vy Nguyen
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Emma DeMarco
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Surbhi Srinivas
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Homan Kang
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Satoshi Kashiwagi
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Kai Bao
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Atsushi Yamashita
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
| | - Hak Soo Choi
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02119, USA; (P.J.); (J.S.)
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