Precision Neuro-Oncology in Glioblastoma: AI-Guided CRISPR Editing and Real-Time Multi-Omics for Genomic Brain Surgery
Abstract
1. Introduction
1.1. Background
1.2. Importance in Neurosurgery
1.3. Objectives of the Review
- Describe how genomic profiling will change our conceptualization and management of patients with brain tumors, neurodegenerative diseases, and epilepsy while also facilitating our uptake of that molecular knowledge into an actionable evidence-based standard of care.
- Describe innovative technologies such as intraoperative genomic sequencing, transcriptomics, and CRISPR-mediated gene editing to improve precision or treatment effects in surgery.
- Discuss how molecular imaging modalities (e.g., PET, molecular MRI) might work with genomic knowledge to improve preoperative planning and intraoperative decision making.
- Explore the use of artificial intelligence to merge genomic, radiological, and clinical datasets to develop predictive models that can lead to the individualization of care in neurosurgery.
- Address the ethical and societal ramifications of this research agenda such as genetic privacy, equitable access, and regulatory concerns regarding the use of genomic technology in surgical practice.
- Offer ideas for next steps to push this research agenda toward the future of precision neurosurgery; specifically, to stimulate creative and cross-discipline collaboration for the purpose of expediting the ambition of integration of genomic medicine into the clinical neurosurgical workflow.
2. Evolution of Neurosurgery in the Genomic Era
2.1. Traditional Neurosurgical Approaches
2.2. Shift Toward Precision Neurosurgery
3. Genomic Medicine: An Overview
3.1. Fundamentals of Genomics
3.2. Technological Advances
3.3. Genomic Profiling
4. Integrating Genomic Insights into Neurosurgical Practices
4.1. Genomic Profiling in Brain Tumors
4.1.1. Gliomas
4.1.2. Meningiomas
4.1.3. Other Brain Tumors
4.2. Personalized Surgical Planning
4.3. Intraoperative Genomic Applications
4.4. Limitations, Barriers, and Ethical Considerations
5. Genomics and Emerging Neurological Diseases
5.1. Neurodegenerative Diseases
5.1.1. Alzheimer’s Disease
5.1.2. Parkinson’s Disease
5.2. Epilepsy
5.3. Other Neurological Conditions
6. Personalized Treatment Strategies
6.1. Targeted Therapies
6.2. Gene Editing and Gene Therapies
6.3. Immunotherapies
7. Technological Innovations Enabling Precision Neurosurgery
7.1. Artificial Intelligence in Neurosurgery
7.2. Molecular Imaging for Precision Interventions
7.3. Bioinformatics: Transforming Data into Actionable Insights
7.4. Emerging Technologies in Neurosurgery
8. Future Directions in Precision Neurosurgery
8.1. Expanding the Scope of Genomics in Neurosurgery
8.2. Integrating Multi-Omics Data into Clinical Practice
8.3. Advancing Technological Infrastructure
8.4. Enhancing Global Collaboration and Data Sharing
8.5. Bridging Research and Clinical Practice
9. Ethical and Regulatory Challenges in Precision Neurosurgery
9.1. Ethical Considerations in Genomic and Multi-Omics Integration
9.2. Equity and Access to Precision Neurosurgery
9.3. Ethical Implications of Genetic Editing
9.4. Regulatory Challenges in Precision Neurosurgery
9.5. Building Public Trust and Ethical Literacy
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Karin, J.; Mintz, R.; Raveh, B.; Nitzan, M. Interpreting single-cell and spatial omics data using deep neural network training dynamics. Nat. Comput. Sci. 2024, 4, 941–954. [Google Scholar] [CrossRef] [PubMed]
- Hainsworth, A.H.; Blackburn, T.P.; Bradshaw, E.M.; Elahi, F.M.; Gorelick, P.B.; Isaacs, J.D.; Wallin, A.; Williams, S.C. The promise of molecular science in brain health. What breakthroughs are anticipated in the next 20 years? Cereb. Circ.-Cogn. Behav. 2024, 7, 100364. [Google Scholar] [CrossRef] [PubMed]
- Song, M.; Zhou, X.; Sigdel, M.; Hou, R.; Han, X.; Liu, Y.; Xu, K.; Jiao, D. Clinical application of intravascular forceps biopsy in the diagnosis of vascular obstructive diseases: A pilot study. Quant. Imaging Med. Surg. 2024, 14, 85260–85860. [Google Scholar] [CrossRef]
- Zaidi, S.; Park, J.; Chan, J.M.; Roudier, M.P.; Zhao, J.L.; Gopalan, A.; Wadosky, K.M.; Patel, R.A.; Sayar, E.; Karthaus, W.R.; et al. Single-cell analysis of treatment-resistant prostate cancer: Implications of cell state changes for cell surface antigen–targeted therapies. Proc. Natl. Acad. Sci. USA 2024, 121, e2322203121. [Google Scholar] [CrossRef]
- Sussman, J.H.; Xu, J.; Amankulor, N.; Tan, K. Dissecting the tumor microenvironment of epigenetically driven gliomas: Opportunities for single-cell and spatial multiomics. Neuro-Oncol. Adv. 2023, 5, vdad101. [Google Scholar] [CrossRef] [PubMed]
- Johnston, K.G.; Berackey, B.T.; Tran, K.M.; Gelber, A.; Yu, Z.; MacGregor, G.R.; Mukamel, E.A.; Tan, Z.; Green, K.N.; Xu, X. Single-cell spatial transcriptomics reveals distinct patterns of dysregulation in non-neuronal and neuronal cells induced by the Trem2R47H Alzheimer’s risk gene mutation. Mol. Psychiatry 2024, 30, 461–477. [Google Scholar] [CrossRef]
- Rymuza, J.; Kober, P.; Rusetska, N.; Mossakowska, B.J.; Maksymowicz, M.; Nyc, A.; Baluszek, S.; Zieliński, G.; Kunicki, J.; Bujko, M. Transcriptomic Classification of Pituitary Neuroendocrine Tumors Causing Acromegaly. Cells 2022, 11, 3846. [Google Scholar] [CrossRef]
- Varachev, V.; Susova, O.; Mitrofanov, A.; Naskhletashvili, D.; Krasnov, G.; Ikonnikova, A.; Bezhanova, S.; Semenova, V.; Sevyan, N.; Prozorenko, E.; et al. Genomic Profiling in Glioma Patients to Explore Clinically Relevant Markers. Int. J. Mol. Sci. 2024, 25, 13004. [Google Scholar] [CrossRef]
- Lee, Y.; Park, C.-K.; Park, S.-H. Prognostic Impact of TERT Promoter Mutations in Adult-Type Diffuse Gliomas Based on WHO2021 Criteria. Cancers 2024, 16, 2032. [Google Scholar] [CrossRef]
- Zhang, J.; Sun, R.; Lyu, Y.; Liu, C.; Liu, Y.; Feng, Y.; Fu, M.; Wong, P.J.C.; Du, Z.; Qiu, T.; et al. Proteomic profiling of gliomas unveils immune and metabolism-driven subtypes with implications for anti-nucleotide metabolism therapy. Nat. Commun. 2024, 15, 10005. [Google Scholar] [CrossRef]
- Zheng, Q.; Wang, X. Alzheimer’s disease: Insights into pathology, molecular mechanisms, and therapy. Protein Cell 2024, 16, pwae026. [Google Scholar] [CrossRef]
- Toader, C.; Covache-Busuioc, R.-A.; Rădoi, P.M.; Covlea, C.-A.; Popa, A.A.; Dumitrascu, D.-I.; Ciurea, A.V. Gerstmann Syndrome in an Elderly Patient: A Case Report Presented with a Complete Tetrad of Symptoms. Medicina 2024, 60, 1640. [Google Scholar] [CrossRef]
- Komine, O.; Ohnuma, S.; Hinohara, K.; Hara, Y.; Shimada, M.; Akashi, T.; Watanabe, S.; Sobue, A.; Kawade, N.; Ogi, T.; et al. Genetic background variation impacts microglial heterogeneity and disease progression in amyotrophic lateral sclerosis model mice. iScience 2024, 27, 108872. [Google Scholar] [CrossRef]
- Navarro, E.; Efthymiou, A.G.; Parks, M.; Riboldi, G.M.; Vialle, R.A.; Udine, E.; Muller, B.Z.; Humphrey, J.; Allan, A.; Argyrou, C.C.; et al. LRRK2 G2019S variant is associated with transcriptional changes in Parkinson’s disease human myeloid cells under proinflammatory environment. BioRxiv Prepr. Serv. Biol. 2024. [Google Scholar] [CrossRef]
- Salunkhe, M.; Agarwal, A.; Faruq, M.; Srivastava, A.K. Genetic Testing in Neurology: What Every Neurologist Must Know. Ann. Indian. Acad. Neurol. 2022, 25, 350–353. [Google Scholar] [CrossRef] [PubMed]
- Veltra, D.; Theodorou, V.; Katsalouli, M.; Vorgia, P.; Niotakis, G.; Tsaprouni, T.; Pons, R.; Kosma, K.; Kampouraki, A.; Tsoutsou, I.; et al. SCN1A Channels a Wide Range of Epileptic Phenotypes: Report of Novel and Known Variants with Variable Presentations. Int. J. Mol. Sci. 2024, 25, 5644. [Google Scholar] [CrossRef] [PubMed]
- Miguel Sanz, C.; Martinez Navarro, M.; Caballero Diaz, D.; Sanchez-Elexpuru, G.; Di Donato, V. Toward the use of novel alternative methods in epilepsy modeling and drug discovery. Front. Neurol. 2023, 14, 1213969. [Google Scholar] [CrossRef]
- Kong, X.; Dai, G.; Zeng, Z.; Zhang, Y.; Gu, J.; Ma, T.; Wang, N.; Gu, J.; Wang, Y. Integrating Proteomics and Transcriptomics Reveals the Potential Pathways of Hippocampal Neuron Apoptosis in Dravet Syndrome Model Mice. Int. J. Mol. Sci. 2024, 25, 4457. [Google Scholar] [CrossRef] [PubMed]
- Syu, Y.M.; Lee, I.; Lu, J.-F.; Hung, P.-L.; Hong, S.-Y.; Yang, M.-T.; Liang, J.-S. Insights into clinical phenotypes and treatment responses in a Small cohort of Taiwanese patients with SCN1A variants: A Preliminary study. Pediatr. Neonatol. 2024, 66, 223–229. [Google Scholar] [CrossRef] [PubMed]
- Dmello, C.; Zhao, J.; Chen, L.; Gould, A.; Castro, B.; Arrieta, V.A.; Zhang, D.Y.; Kim, K.-S.; Kanojia, D.; Zhang, P.; et al. Checkpoint kinase 1/2 inhibition potentiates anti-tumoral immune response and sensitizes gliomas to immune checkpoint blockade. Nat. Commun. 2023, 14, 1566. [Google Scholar] [CrossRef] [PubMed]
- Zhao, Y.; Qin, J.; Yu, D.; Liu, Y.; Song, D.; Tian, K.; Chen, H.; Ye, Q.; Wang, X.; Xu, T.; et al. Polymer-locking fusogenic liposomes for glioblastoma-targeted siRNA delivery and CRISPR–Cas gene editing. Nat. Nanotechnol. 2024, 19, 1869–1879. [Google Scholar] [CrossRef] [PubMed]
- Rocha-Júnior, E.; Pêgo-Fernandes, P.M. Three-dimensional computed tomography reconstruction in the era of digital personalized medicine. São Paulo Med. J. 2022, 141, 1–3. [Google Scholar] [CrossRef] [PubMed]
- Takamiya, S.; Malvea, A.; Ishaque, A.H.; Pedro, K.; Fehlings, M.G. Advances in imaging modalities for spinal tumors. Neuro-Oncol. Adv. 2024, 6, iii13–iii27. [Google Scholar] [CrossRef]
- Toader, C.; Radoi, M.P.; Ilie, M.-M.; Covache-Busuioc, R.-A.; Buica, V.; Glavan, L.-A.; Covlea, C.-A.; Corlatescu, A.D.; Costin, H.-P.; Crivoi, C.; et al. Clinical Presentations and Treatment Approaches in a Retrospective Analysis of 128 Intracranial Arteriovenous Malformation Cases. Brain Sci. 2024, 14, 1136. [Google Scholar] [CrossRef]
- Guibourd de Luzinais, M.; Engelhardt, J.; Ollivier, M.; Planchon, C.; Gallice, T.; Michel, V.; de Montaudouin, M.; Aupy, J.; Penchet, G. Awake surgery with mapping-based resection to treat focal epilepsy in eloquent brain areas. Acta Neurochir. 2024, 166, 430. [Google Scholar] [CrossRef]
- Moretto, M.; Luciani, B.F.; Zigiotto, L.; Saviola, F.; Tambalo, S.; Cabalo, D.G.; Annicchiarico, L.; Venturini, M.; Jovicich, J.; Sarubbo, S. Resting State Functional Networks in Gliomas: Validation With Direct Electric Stimulation Using a New Tool for Planning Brain Resections. Neurosurgery 2024, 95, 1358. [Google Scholar] [CrossRef]
- Duraj, T.; Kalamian, M.; Zuccoli, G.; Maroon, J.C.; D’Agostino, D.P.; Scheck, A.C.; Poff, A.; Winter, S.F.; Hu, J.; Klement, R.J.; et al. Clinical research framework proposal for ketogenic metabolic therapy in glioblastoma. BMC Med. 2024, 22, 578. [Google Scholar] [CrossRef]
- Onciul, R.; Brehar, F.-M.; Toader, C.; Covache-Busuioc, R.-A.; Glavan, L.-A.; Bratu, B.-G.; Costin, H.P.; Dumitrascu, D.-I.; Serban, M.; Ciurea, A.V. Deciphering Glioblastoma: Fundamental and Novel Insights into the Biology and Therapeutic Strategies of Gliomas. Curr. Issues Mol. Biol. 2024, 46, 2402–2443. [Google Scholar] [CrossRef]
- Chi, X.; Lu, J.; Guo, Z.; Wang, J.; Liu, G.; Jin, Z.; Wang, Y.; Zhang, Q.; Sun, T.; Ji, N.; et al. Susceptibility to preoperative seizures in glioma patients with elevated homocysteine levels. Epilepsia Open 2023, 8, 1350–1361. [Google Scholar] [CrossRef]
- Xue, W.; Li, H.; Xu, J.; Yu, X.; Liu, L.; Liu, H.; Zhao, R.; Shao, Z. Effective cryopreservation of human brain tissue and neural organoids. Cell Rep. Methods 2024, 4, 100777. [Google Scholar] [CrossRef] [PubMed]
- Hussen, B.M.; Taheri, M.; Yashooa, R.K.; Abdullah, G.H.; Abdullah, S.R.; Kheder, R.K.; Mustafa, S.A. Revolutionizing medicine: Recent developments and future prospects in stem-cell therapy. Int. J. Surg. 2024, 110, 8002–8024. [Google Scholar] [CrossRef]
- Khalifa, M.; Albadawy, M. Artificial Intelligence for Clinical Prediction: Exploring Key Domains and Essential Functions. Comput. Methods Programs Biomed. Update 2024, 5, 100148. [Google Scholar] [CrossRef]
- D’Alessandris, Q.G.; Offi, M.; Lauretti, L.; Pallini, R. Personalized Medicine in Brain Tumors. J. Pers. Med. 2024, 14, 413. [Google Scholar] [CrossRef] [PubMed]
- Lost, J.; Ashraf, N.; Jekel, L.; von Reppert, M.; Tillmanns, N.; Willms, K.; Merkaj, S.; Petersen, G.C.; Avesta, A.; Ramakrishnan, D.; et al. Enhancing clinical decision-making: An externally validated machine learning model for predicting isocitrate dehydrogenase mutation in gliomas using radiomics from presurgical magnetic resonance imaging. Neuro-Oncol. Adv. 2024, 6, vdae157. [Google Scholar] [CrossRef]
- Toader, C.; Serban, M.; Eva, L.; Costea, D.; Covache-Busuioc, R.-A.; Radoi, M.P.; Ciurea, A.V.; Dumitru, A.V. Large Pontine Cavernoma with Hemorrhage: Case Report on Surgical Approach and Recovery. J. Clin. Med. 2025, 14, 2358. [Google Scholar] [CrossRef]
- Slota, J.A.; Lamoureux, L.; Frost, K.L.; Sajesh, B.V.; Booth, S.A. Single-cell transcriptomics unveils molecular signatures of neuronal vulnerability in a mouse model of prion disease that overlap with Alzheimer’s disease. Nat. Commun. 2024, 15, 10174. [Google Scholar] [CrossRef]
- Kumari, S.; Gupta, S.; Sukhija, R.; Gurjar, S.; Dubey, S.K.; Taliyan, R. Neuroprotective potential of Epigenetic modulators, its regulation and therapeutic approaches for the management of Parkinson’s disease. Eur. J. Pharmacol. 2024, 985, 177123. [Google Scholar] [CrossRef]
- Ye, L.-J.; Xu, K.-M.; Bai, G.; Yuan, J.; Ran, F.-M. SRSF1 induces glioma progression and has a potential diagnostic application in grading primary glioma. Oncol. Lett. 2023, 26, 348. [Google Scholar] [CrossRef]
- Balakumar, S.; Pai, R.; Chacko, A.G.; Patel, B.; Nancy, R.; Balakrishnan, R.; Sarkar, S.; Sampath, G.; Chacko, G. Telomerase Reverse Transcriptase Promoter Mutations in A Cohort of Adult Gliomas-Clinicopathological Correlates. Neurol. India 2022, 70, 953–959. [Google Scholar] [CrossRef]
- Lee, K.; Kim, S.-I.; Kim, E.E.; Shim, Y.-M.; Won, J.-K.; Park, C.-K.; Choi, S.H.; Yun, H.; Lee, H.; Park, S.-H. Genomic profiles of IDH-mutant gliomas: MYCN-amplified IDH-mutant astrocytoma had the worst prognosis. Sci. Rep. 2023, 13, 6761. [Google Scholar] [CrossRef] [PubMed]
- Nussbaumer, G.; Benesch, M.; Grabovska, Y.; Mackay, A.; Castel, D.; Grill, J.; Alonso, M.M.; Antonelli, M.; Bailey, S.; Baugh, J.N.; et al. Gliomatosis cerebri in children: A poor prognostic phenotype of diffuse gliomas with a distinct molecular profile. Neuro-Oncology 2024, 26, 1723–1737. [Google Scholar] [CrossRef]
- Halder, A.; Biswas, D.; Chauhan, A.; Saha, A.; Auromahima, S.; Yadav, D.; Nissa, M.U.; Iyer, G.; Parihari, S.; Sharma, G.; et al. A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors. Clin. Proteom. 2023, 20, 41. [Google Scholar] [CrossRef] [PubMed]
- Toader, C.; Rădoi, P.M.; Ilie, M.-M.; Covache-Busuioc, R.-A.; Buica, V.; Glavan, L.-A.; Serban, M.; Corlatescu, A.D.; Crivoi, C.; Gorgan, R.M. Clinical Presentation, Treatment Outcomes, and Demographic Trends in Vestibular Schwannomas: A 135-Case Retrospective Study. J. Clin. Med. 2025, 14, 482. [Google Scholar] [CrossRef] [PubMed]
- Wang, J.Z.; Patil, V.; Landry, A.P.; Gui, C.; Ajisebutu, A.; Liu, J.; Saarela, O.; Pugh, S.L.; Won, M.; Patel, Z.; et al. Molecular classification to refine surgical and radiotherapeutic decision-making in meningioma. Nat. Med. 2024, 30, 3173–3183. [Google Scholar] [CrossRef]
- Toader, C.; Radoi, M.P.; Glavan, L.-A.; Covache-Busuioc, R.-A.; Ilie, M.M.; Popa, M.; Dumitru, A.; Toader, C.; Radoi, M.P.; Glavan, L.-A.; et al. Giant Chondromyxoid Fibroma Associated with Epileptic Seizures: A Case Report. Cureus 2024, 16, e70950. [Google Scholar] [CrossRef]
- Ren, L.; Xie, Q.; Deng, J.; Chen, J.; Yu, J.; Wang, D.; Wakimoto, H.; Gong, Y.; Hua, L. Association of frequent NF2 mutations with spinal location predominance and worse outcomes in psammomatous meningiomas. J. Neurosurg. 2024, 141, 593–601. [Google Scholar] [CrossRef]
- Alkazemi, M.; Lo, Y.T.; Hussein, H.; Mammi, M.; Saleh, S.; Araujo-Lama, L.; Mommsen, S.; Pisano, A.; Lamba, N.; Bunevicius, A.; et al. Laser Interstitial Thermal Therapy for the Treatment of Primary and Metastatic Brain Tumors: A Systematic Review and Meta-Analysis. World Neurosurg. 2023, 171, e654–e671. [Google Scholar] [CrossRef]
- El Ganainy, S.O.; Cijsouw, T.; Ali, M.A.; Schoch, S.; Hanafy, A.S. Stereotaxic-assisted gene therapy in Alzheimer’s and Parkinson’s diseases: Therapeutic potentials and clinical frontiers. Expert. Rev. Neurother. 2022, 22, 319–335. [Google Scholar] [CrossRef]
- Toader, C.; Tataru, C.P.; Munteanu, O.; Covache-Busuioc, R.-A.; Serban, M.; Ciurea, A.V.; Enyedi, M. Revolutionizing Neuroimmunology: Unraveling Immune Dynamics and Therapeutic Innovations in CNS Disorders. Int. J. Mol. Sci. 2024, 25, 13614. [Google Scholar] [CrossRef] [PubMed]
- Gerritsen, J.K.W.; Broekman, M.L.D.; De Vleeschouwer, S.; Schucht, P.; Nahed, B.V.; Berger, M.S.; Vincent, A.J.P.E. Safe surgery for glioblastoma: Recent advances and modern challenges. Neuro-Oncol. Pract. 2022, 9, 364–379. [Google Scholar] [CrossRef]
- Zirem, Y.; Ledoux, L.; Roussel, L.; Maurage, C.A.; Tirilly, P.; Le Rhun, É.; Meresse, B.; Yagnik, G.; Lim, M.J.; Rothschild, K.J.; et al. Real-time glioblastoma tumor microenvironment assessment by SpiderMass for improved patient management. Cell Rep. Med. 2024, 5, 101482. [Google Scholar] [CrossRef]
- Bedics, G.; Szőke, P.; Bátai, B.; Nagy, T.; Papp, G.; Kránitz, N.; Rajnai, H.; Reiniger, L.; Bödör, C.; Scheich, B. Novel, clinically relevant genomic patterns identified by comprehensive genomic profiling in ATRX-deficient IDH-wildtype adult high-grade gliomas. Sci. Rep. 2023, 13, 18436. [Google Scholar] [CrossRef]
- Moškon, M.; Režen, T. Integration and Analysis of Omics Data Using Genome-Scale Metabolic Models. Metabolites 2024, 14, 595. [Google Scholar] [CrossRef]
- Paverd, H.; Zormpas-Petridis, K.; Clayton, H.; Burge, S.; Crispin-Ortuzar, M. Radiology and multi-scale data integration for precision oncology. Npj Precis. Oncol. 2024, 8, 1–9. [Google Scholar] [CrossRef]
- Nejo, T.; Krishna, S.; Yamamichi, A.; Jimenez, C.; Young, J.S.; Lakshmanachetty, S.; Chen, T.; Phyu, S.; Watchmaker, P.; Choudhury, A.; et al. 956 Glioma-neuronal circuit remodeling induces regional immunosuppression. J. Immunother. Cancer 2023, 11. [Google Scholar] [CrossRef]
- Toader, C.; Eva, L.; Costea, D.; Corlatescu, A.D.; Covache-Busuioc, R.-A.; Bratu, B.-G.; Glavan, L.A.; Costin, H.P.; Popa, A.A.; Ciurea, A.V. Low-Grade Gliomas: Histological Subtypes, Molecular Mechanisms, and Treatment Strategies. Brain Sci. 2023, 13, 1700. [Google Scholar] [CrossRef]
- Lin, J.-C.; Liu, Y.-L.; Hsiao, W.W.-W.; Fan, C.-T. Integrating population-based biobanks: Catalyst for advances in precision health. Comput. Struct. Biotechnol. J. 2024, 24, 690–698. [Google Scholar] [CrossRef] [PubMed]
- Marek, S.; Tervo-Clemmens, B.; Calabro, F.J.; Montez, D.F.; Kay, B.P.; Hatoum, A.S.; Donohue, M.R.; Foran, W.; Miller, R.L.; Hendrickson, T.J.; et al. Reproducible brain-wide association studies require thousands of individuals. Nature 2022, 603, 654–660. [Google Scholar] [CrossRef] [PubMed]
- Sánchez-Rivera, F.J.; Jacks, T. Applications of the CRISPR-Cas9 system in cancer biology. Nat. Rev. Cancer 2015, 15, 387–395. [Google Scholar] [CrossRef]
- Huang, Q.; Chen, A.T.; Chan, K.Y.; Sorensen, H.; Barry, A.J.; Azari, B.; Zheng, Q.; Beddow, T.; Zhao, B.; Tobey, I.G.; et al. Targeting AAV vectors to the central nervous system by engineering capsid-receptor interactions that enable crossing of the blood-brain barrier. PLoS Biol. 2023, 21, e3002112. [Google Scholar] [CrossRef] [PubMed]
- Park, J.H.; Kim, C.W.; Kim, H.-J.; Kim, H.J.; Lee, J.H.; Lee, H.K. Protocol to analyze antitumor immunity of orthotopic injection and spontaneous murine high-grade glioma models using flow cytometry and single-cell RNA sequencing. STAR Protoc. 2022, 3, 101607. [Google Scholar] [CrossRef]
- Garcia-Diaz, C.; Pöysti, A.; Mereu, E.; Clements, M.P.; Brooks, L.J.; Galvez-Cancino, F.; Castillo, S.P.; Tang, W.; Beattie, G.; Courtot, L.; et al. Glioblastoma cell fate is differentially regulated by the microenvironments of the tumor bulk and infiltrative margin. Cell Rep. 2023, 42, 112472. [Google Scholar] [CrossRef]
- Nojadeh, J.N.; Eryilmaz, N.S.B.; Ergüder, B.I. CRISPR/Cas9 genome editing for neurodegenerative diseases. EXCLI J. 2023, 22, 567. [Google Scholar] [CrossRef]
- Toader, C.; Brehar, F.M.; Radoi, M.P.; Covache-Busuioc, R.A.; Serban, M.; Ciurea, A.V.; Dobrin, N. Challenging Management of a Rare Complex Cerebral Arteriovenous Malformation in the Corpus Callosum and Post-Central Gyrus: A Case Study of a 41-Year-Old Female. J. Clin. Med. 2024, 13, 7494. [Google Scholar] [CrossRef] [PubMed]
- Seidinger, A.L.; Silva, F.L.T.; Euzébio, M.F.; Krieger, A.C.; Meidanis, J.; Gutierrez, J.M.; Bezerra, T.M.S.; Queiroz, L.; Silva, A.A.R.; Hoffmann, I.L.; et al. Tumor-Promoted Changes in Pediatric Brain Histology Can Be Distinguished from Normal Parenchyma by Desorption Electrospray Ionization Mass Spectrometry Imaging. Biomedicines 2024, 12, 2593. [Google Scholar] [CrossRef] [PubMed]
- Pirro, V.; Alfaro, C.M.; Jarmusch, A.K.; Hattab, E.M.; Cohen-Gadol, A.A.; Cooks, R.G. Intraoperative assessment of tumor margins during glioma resection by desorption electrospray ionization-mass spectrometry. Proc. Natl. Acad. Sci. USA 2017, 114, 6700–6705. [Google Scholar] [CrossRef] [PubMed]
- Songkai, W.A.G.; Yuchen, Z.O.; Shipeng, S.U.; Zhiye, Y.A.; Weiwei, T.A.G.; Ping, L.I.; Bin, L.I. Recent advances in mass spectrometry imaging and its application in drug research. J. China Pharm. Univ. 2023, 54, 653–661. [Google Scholar] [CrossRef]
- Liu, J.; Hu, W.; Han, Y.; Nie, H. Recent advances in mass spectrometry imaging of single cells. Anal. Bioanal. Chem. 2023, 415, 4093–4110. [Google Scholar] [CrossRef]
- Que, Z.; Olivero-Acosta, M.I.; Robinson, M.; Chen, I.; Zhang, J.; Wettschurack, K.; Wu, J.; Xiao, T.; Otterbacher, C.M.; Shankar, V.; et al. Human iPSC-derived microglia sense and dampen hyperexcitability of cortical neurons carrying the epilepsy-associated SCN2A-L1342P mutation. J. Neurosci. Off. J. Soc. Neurosci. 2024, 45, e2027232024. [Google Scholar] [CrossRef]
- Toader, C.; Serban, M.; Covache-Busuioc, R.-A.; Radoi, M.P.; Aljboor, G.S.R.; Glavan, L.-A.; Corlatescu, A.D.; Ilie, M.-M.; Gorgan, R.M. Navigating the Rare and Dangerous: Successful Clipping of a Superior Cerebellar Artery Aneurysm Against the Odds of Uncontrolled Hypertension. J. Clin. Med. 2024, 13, 7430. [Google Scholar] [CrossRef]
- Huang, H.-H.; Li, J.; Cho, W.C. Editorial: Integrative analysis for complex disease biomarker discovery. Front. Bioeng. Biotechnol. 2023, 11, 1273084. [Google Scholar] [CrossRef] [PubMed]
- Toader, C.; Serban, M.; Dobrin, N.; Covache-Busuioc, R.-A.; Radoi, M.P.; Ciurea, A.V.; Munteanu, O. Complex Anatomy, Advanced Techniques: Microsurgical Clipping of a Ruptured Hypophyseal Artery Aneurysm. J. Clin. Med. 2025, 14, 2361. [Google Scholar] [CrossRef]
- Hertler, C.; Felsberg, J.; Gramatzki, D.; Rhun, E.L.; Clarke, J.; Soffietti, R.; Wick, W.; Chinot, O.; Ducray, F.; Roth, P.; et al. Long-term survival with IDH wildtype glioblastoma: First results from the ETERNITY Brain Tumor Funders’ Collaborative Consortium (EORTC 1419). Eur. J. Cancer 2023, 189, 112913. [Google Scholar] [CrossRef]
- Tang, F.; Chen, X.; Liu, J.-S.; Liu, Z.-Y.; Yang, J.-Z.; Wang, Z.-F.; Li, Z.-Q. TERT mutations-associated alterations in clinical characteristics, immune environment and therapy response in glioblastomas. Discov. Oncol. 2023, 14, 148. [Google Scholar] [CrossRef]
- Guo, G.; Gong, K.; Beckley, N.; Zhang, Y.; Yang, X.; Chkheidze, R.; Hatanpaa, K.J.; Garzon-Muvdi, T.; Koduru, P.; Nayab, A.; et al. EGFR ligand shifts the role of EGFR from oncogene to tumour suppressor in EGFR-amplified glioblastoma by suppressing invasion through BIN3 upregulation. Nat. Cell Biol. 2022, 24, 1291–1305. [Google Scholar] [CrossRef]
- Thapa, R.; Afzal, M.; Goyal, A.; Gupta, G.; Bhat, A.A.; Almalki, W.H.; Kazmi, I.; Alzarea, S.I.; Shahwan, M.; Kukreti, N.; et al. Exploring ncRNA-mediated regulation of EGFR signalling in glioblastoma: From mechanisms to therapeutics. Life Sci. 2024, 345, 122613. [Google Scholar] [CrossRef] [PubMed]
- Kaynar, A.; Kim, W.; Ceyhan, A.B.; Zhang, C.; Uhlén, M.; Turkez, H.; Shoaie, S.; Mardinoglu, A. Unveiling the Molecular Mechanisms of Glioblastoma through an Integrated Network-Based Approach. Biomedicines 2024, 12, 2237. [Google Scholar] [CrossRef]
- Demetriou, A.N.; Chow, F.; Craig, D.W.; Webb, M.G.; Ormond, D.R.; Battiste, J.; Chakravarti, A.; Colman, H.; Villano, J.L.; Schneider, B.P.; et al. Profiling the molecular and clinical landscape of glioblastoma utilizing the Oncology Research Information Exchange Network brain cancer database. Neuro-Oncol. Adv. 2024, 6, vdae046. [Google Scholar] [CrossRef] [PubMed]
- Uno, M.; Oba-Shinjo, S.M.; Camargo, A.A.; Moura, R.P.; de Aguiar, P.H.; Cabrera, H.N.; Begnami, M.; Rosemberg, S.; Teixeira, M.J.; Marie, S.K.N. Correlation of MGMT promoter methylation status with gene and protein expression levels in glioblastoma. Clinics 2011, 66, 1747–1755. [Google Scholar] [CrossRef]
- Shapiro, J.A.; Gaonkar, K.S.; Spielman, S.J.; Savonen, C.L.; Bethell, C.J.; Jin, R.; Rathi, K.S.; Zhu, Y.; Egolf, L.E.; Farrow, B.K.; et al. OpenPBTA: The Open Pediatric Brain Tumor Atlas. Cell Genom. 2023, 3, 100340. [Google Scholar] [CrossRef]
- Bouffet, E.; Hansford, J.R.; Garrè, M.L.; Hara, J.; Plant-Fox, A.; Aerts, I.; Locatelli, F.; van der Lugt, J.; Papusha, L.; Sahm, F.; et al. Dabrafenib plus Trametinib in Pediatric Glioma with BRAF V600 Mutations. N. Engl. J. Med. 2023, 389, 1108–1120. [Google Scholar] [CrossRef] [PubMed]
- Wu, H.; Guo, C.; Wang, C.; Xu, J.; Zheng, S.; Duan, J.; Li, Y.; Bai, H.; Xu, Q.; Ning, F.; et al. Single-cell RNA sequencing reveals tumor heterogeneity, microenvironment, and drug-resistance mechanisms of recurrent glioblastoma. Cancer Sci. 2023, 114, 2609–2621. [Google Scholar] [CrossRef]
- Cao, L.; Lu, X.; Wang, X.; Wu, H.; Miao, X. From single-cell to spatial transcriptomics: Decoding the glioma stem cell niche and its clinical implications. Front. Immunol. 2024, 15, 1475235. [Google Scholar] [CrossRef]
- Ren, Y.; Huang, Z.; Zhou, L.; Xiao, P.; Song, J.; He, P.; Xie, C.; Zhou, R.; Li, M.; Dong, X.; et al. Spatial transcriptomics reveals niche-specific enrichment and vulnerabilities of radial glial stem-like cells in malignant gliomas. Nat. Commun. 2023, 14, 1028. [Google Scholar] [CrossRef]
- Kang, X.; Wang, Y.; Liu, P.; Huang, B.; Zhou, B.; Lu, S.; Geng, W.; Tang, H. Progresses, Challenges, and Prospects of CRISPR/Cas9 Gene-Editing in Glioma Studies. Cancers 2023, 15, 396. [Google Scholar] [CrossRef] [PubMed]
- Ozyerli-Goknar, E.; Kala, E.Y.; Aksu, A.C.; Bulut, I.; Cingöz, A.; Nizamuddin, S.; Biniossek, M.; Seker-Polat, F.; Morova, T.; Aztekin, C.; et al. Epigenetic-focused CRISPR/Cas9 screen identifies (absent, small, or homeotic)2-like protein (ASH2L) as a regulator of glioblastoma cell survival. Cell Commun. Signal. 2023, 21, 328. [Google Scholar] [CrossRef]
- Tsung, K.; Liu, K.Q.; Han, J.S.; Deshpande, K.; Doan, T.; Loh, Y.-H.E.; Ding, L.; Yang, W.; Neman, J.; Dou, Y.; et al. CRISPRi screen of long non-coding RNAs identifies LINC03045 regulating glioblastoma invasion. PLoS Genet. 2024, 20, e1011314. [Google Scholar] [CrossRef]
- Schloissnig, S.; Pani, S.; Rodriguez-Martin, B.; Ebler, J.; Hain, C.; Tsapalou, V.; Söylev, A.; Hüther, P.; Ashraf, H.; Prodanov, T.; et al. Long-read sequencing and structural variant characterization in 1,019 samples from the 1000 Genomes Project. BioRxiv Prepr. Serv. Biol. 2024. [Google Scholar] [CrossRef]
- Blobner, J.; Dengler, L.; Blobner, S.; Eberle, C.; Weller, J.; Teske, N.; Karschnia, P.; Rühlmann, K.; Heinrich, K.; Ziemann, F.; et al. Significance of molecular diagnostics for therapeutic decision-making in recurrent glioma. Neuro-Oncol. Adv. 2023, 5, vdad060. [Google Scholar] [CrossRef]
- Zeng, B.; Zhang, H.; Lu, Q.; Fu, Q.; Yan, Y.; Lu, W.; Ma, P.; Feng, C.; Qin, J.; Luo, L.; et al. Identification of five novel SCN1A variants. Front. Behav. Neurosci. 2023, 17, 1272748. [Google Scholar] [CrossRef]
- Haag, N.; Bremer, J.; Zempel, H. Understanding genetics, sex and signaling: Implications of sex-dependent APOE4-neutrophil-microglia interactions for Alzheimer’s and tauopathies. Signal Transduct. Target. Ther. 2024, 9, 1–3. [Google Scholar] [CrossRef] [PubMed]
- Liu, H.-Q.; Li, W.-X.; An, Y.-W.; Wu, T.; Jiang, G.-Y.; Dong, Y.; Chen, W.-X.; Wang, J.-C.; Wang, C.; Song, S. Integrated analysis of the genomic and transcriptional profile of gliomas with isocitrate dehydrogenase-1 and tumor protein 53 mutations. Int. J. Immunopathol. Pharmacol. 2022, 36, 03946320221139262. [Google Scholar] [CrossRef]
- Onciul, R.; Brehar, F.-M.; Dumitru, A.V.; Crivoi, C.; Covache-Busuioc, R.-A.; Serban, M.; Radoi, P.M.; Toader, C. Predicting overall survival in glioblastoma patients using machine learning: An analysis of treatment efficacy and patient prognosis. Front. Oncol. 2025, 15, 1539845. [Google Scholar] [CrossRef]
- Chen, A.-Q.; Jiang, Q.-X.; Zhu, Y.-J.; Wang, Q.-W. Transcriptomic profiling identifies a nucleotide metabolism-related signature with prognostic power in gliomas. Transl. Oncol. 2024, 49, 102068. [Google Scholar] [CrossRef]
- Poon, M.T.C.; Keni, S.; Vimalan, V.; Ip, C.; Smith, C.; Erridge, S.; Weir, C.J.; Brennan, P.M. Extent of MGMT promoter methylation modifies the effect of temozolomide on overall survival in patients with glioblastoma: A regional cohort study. Neuro-Oncol. Adv. 2021, 3, vdab171. [Google Scholar] [CrossRef]
- Steininger, J.; Buszello, C.; Oertel, R.; Meinhardt, M.; Schmid, S.; Engellandt, K.; Herold, S.; Stasik, S.; Ebrahimi, A.; Renner, B.; et al. Efficacy of BRAF/MEK-inhibitor therapy for epithelioid glioblastoma with a novel BRAFV600 mutation. Acta Neuropathol. Commun. 2024, 12, 124. [Google Scholar] [CrossRef] [PubMed]
- Kantor, B.; O’Donovan, B.; Rittiner, J.; Hodgson, D.; Lindner, N.; Guerrero, S.; Dong, W.; Zhang, A.; Chiba-Falek, O. The therapeutic implications of all-in-one AAV-delivered epigenome-editing platform in neurodegenerative disorders. Nat. Commun. 2024, 15, 7259. [Google Scholar] [CrossRef] [PubMed]
- Mabika, M.; Agbogba, K.; Côté, S.; Lippé, S.; Riou, É.; Cieuta, C.; Lepage, J.-F. Neurophysiological assessment of cortical activity in DEPDC5- and NPRL3-related epileptic mTORopathies. Orphanet J. Rare Dis. 2023, 18, 11. [Google Scholar] [CrossRef]
- Kino, S.; Kanamori, M.; Shimoda, Y.; Niizuma, K.; Endo, H.; Matsuura, Y. Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation. BMC Cancer 2024, 24, 222. [Google Scholar] [CrossRef]
- Mellinghoff, I.K.; Bent, M.J.v.D.; Blumenthal, D.T.; Touat, M.; Peters, K.B.; Clarke, J.; Mendez, J.; Yust-Katz, S.; Welsh, L.; Mason, W.P.; et al. Vorasidenib in IDH1- or IDH2-Mutant Low-Grade Glioma. N. Engl. J. Med. 2023, 389, 589–601. [Google Scholar] [CrossRef]
- Yousefi, Y.; Nejati, R.; Eslahi, A.; Alizadeh, F.; Farrokhi, S.; Asoodeh, A.; Mojarrad, M. Enhancing Temozolomide (TMZ) chemosensitivity using CRISPR-dCas9-mediated downregulation of O6-methylguanine DNA methyltransferase (MGMT). J. Neurooncol. 2024, 169, 129–135. [Google Scholar] [CrossRef] [PubMed]
- Wang, X.; Sun, Q.; Wang, W.; Liu, B.; Gu, Y.; Chen, L. Decoding key cell sub-populations and molecular alterations in glioblastoma at recurrence by single-cell analysis. Acta Neuropathol. Commun. 2023, 11, 125. [Google Scholar] [CrossRef]
- Herrgott, G.A.; Snyder, J.M.; She, R.; Malta, T.M.; Sabedot, T.S.; Lee, I.Y.; Pawloski, J.; Podolsky-Gondim, G.G.; Asmaro, K.P.; Zhang, J.; et al. Detection of diagnostic and prognostic methylation-based signatures in liquid biopsy specimens from patients with meningiomas. Nat. Commun. 2023, 14, 5669. [Google Scholar] [CrossRef]
- Toader, C.; Brehar, F.M.; Radoi, M.P.; Serban, M.; Covache-Busuioc, R.-A.; Aljboor, G.S.; Gorgan, R.M. The Management of a Giant Convexity en Plaque Anaplastic Meningioma with Gerstmann Syndrome: A Case Report of Surgical Outcomes in a 76-Year-Old Male. Diagnostics 2024, 14, 2566. [Google Scholar] [CrossRef]
- Ruchiy, Y.; Tsea, I.; Preka, E.; Verhoeven, B.M.; Olsen, T.K.; Mei, S.; Sinha, I.; Blomgren, K.; Carlson, L.-M.; Dyberg, C.; et al. Genomic tumor evolution dictates human medulloblastoma progression. Neuro-Oncol. Adv. 2024, 6, vdae172. [Google Scholar] [CrossRef] [PubMed]
- Rubio-San-Simón, A.; Ritzmann, T.A.; Obrecht-Sturm, D.; Benesch, M.; Timmermann, B.; Leblond, P.; Kilday, J.-P.; Poggi, G.; Thorp, N.; Massimino, M.; et al. European standard clinical practice recommendations for newly diagnosed ependymoma of childhood and adolescence. EJC Paediatr. Oncol. 2025, 5, 100227. [Google Scholar] [CrossRef]
- Pesaresi, A.; La Cava, P.; Bonada, M.; Zeppa, P.; Melcarne, A.; Cofano, F.; Fiaschi, P.; Garbossa, D.; Bianconi, A. Combined Fluorescence-Guided Surgery with 5-Aminolevulinic Acid and Fluorescein in Glioblastoma: Technical Description and Report of 100 Cases. Cancers 2024, 16, 2771. [Google Scholar] [CrossRef]
- Song, S.; Shan, Y.; Wang, L.; Cheng, Y.; Yang, H.; Zhao, G.; Wang, Z.; Lu, J. MGMT promoter methylation status shows no effect on [18F]FET uptake and CBF in gliomas: A stereotactic image-based histological validation study. Eur. Radiol. 2022, 32, 5577–5587. [Google Scholar] [CrossRef] [PubMed]
- López-Rivera, J.A.; Leu, C.; Macnee, M.; Khoury, J.; Hoffmann, L.; Coras, R.; Kobow, K.; Bhattarai, N.; Pérez-Palma, E.; Hamer, H.; et al. The genomic landscape across 474 surgically accessible epileptogenic human brain lesions. Brain 2022, 146, 1342–1356. [Google Scholar] [CrossRef]
- Sheikh, K.; Miller, D.; Blake, R.; Smith, L.; Conrad, S.; Sokol, D.; Obeid, M.; Radhakrishnan, R.; Schultheis, A.; Raskin, J. Using magnetic resonance-guided laser interstitial thermal therapy corpus callosotomy to lateralize a seizure focus for staged surgical approach. Explor. Neurosci. 2024, 3, 198–206. [Google Scholar] [CrossRef]
- Xie, Y.; Zhao, C.; Zhang, X.; Shen, C.; Qi, Z.; Tang, Q.; Guo, W.; Shi, Z.; Ding, H.; Yang, B.; et al. Intraoperative Real-Time IDH Diagnosis for Glioma Based on Automatic Analysis of Contrast-Enhanced Ultrasound Video. Ultrasound Med. Biol. 2024, 51, 484–493. [Google Scholar] [CrossRef]
- Vermeulen, C.; Pagès-Gallego, M.; Kester, L.; Kranendonk, M.E.G.; Wesseling, P.; Verburg, N.; de Witt Hamer, P.; Kooi, E.J.; Dankmeijer, L.; van der Lugt, J.; et al. Ultra-fast deep-learned CNS tumour classification during surgery. Nature 2023, 622, 842–849. [Google Scholar] [CrossRef] [PubMed]
- Shahi, M.; Pringle, S.; Morris, M.; Garcia, D.M.; Quiñones-Hinojosa, A.; Cooks, R.G. Detection of IDH mutation in glioma by desorption electrospray ionization (DESI) tandem mass spectrometry. Sci. Rep. 2024, 14, 26865. [Google Scholar] [CrossRef]
- Oudin, A.; Moreno-Sanchez, P.M.; Baus, V.; Niclou, S.P.; Golebiewska, A. Magnetic resonance imaging-guided intracranial resection of glioblastoma tumors in patient-derived orthotopic xenografts leads to clinically relevant tumor recurrence. BMC Cancer 2024, 24, 3. [Google Scholar] [CrossRef]
- Feng, Z.; Kong, D.; Jin, W.; He, K.; Zhao, J.; Liu, B.; Xu, H.; Yu, X.; Feng, S. Rapid detection of isocitrate dehydrogenase 1 mutation status in glioma based on Crispr-Cas12a. Sci. Rep. 2023, 13, 5748. [Google Scholar] [CrossRef]
- Toader, C.; Serban, M.; Covache-Busuioc, R.-A.; Radoi, M.P.; Ciurea, A.V.; Dobrin, N. Comprehensive Management of a Giant Left Frontal AVM Coexisting with a Bilobed PComA Aneurysm: A Case Report Highlighting Multidisciplinary Strategies and Advanced Neurosurgical Techniques. J. Clin. Med. 2025, 14, 1232. [Google Scholar] [CrossRef]
- Fernandez, E.G.; Mai, W.X.; Song, K.; Bayley, N.A.; Kim, J.; Zhu, H.; Pioso, M.; Young, P.; Andrasz, C.L.; Cadet, D.; et al. Integrated molecular and functional characterization of the intrinsic apoptotic machinery identifies therapeutic vulnerabilities in glioma. Nat. Commun. 2024, 15, 10089. [Google Scholar] [CrossRef]
- Van Hese, L.; De Vleeschouwer, S.; Theys, T.; Larivière, E.; Solie, L.; Sciot, R.; Siegel, T.P.; Rex, S.; Heeren, R.M.A.; Cuypers, E. Towards real-time intraoperative tissue interrogation for REIMS-guided glioma surgery. J. Mass. Spectrom. Adv. Clin. Lab. 2022, 24, 80–89. [Google Scholar] [CrossRef] [PubMed]
- Mani, S.; Lalani, S.R.; Pammi, M. Genomics and multiomics in the age of precision medicine. Pediatr. Res. 2025, 97, 1399–1410. [Google Scholar] [CrossRef]
- Onciul, R.; Tataru, C.-I.; Dumitru, A.V.; Crivoi, C.; Serban, M.; Covache-Busuioc, R.-A.; Radoi, M.P.; Toader, C. Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications. J. Clin. Med. 2025, 14, 550. [Google Scholar] [CrossRef]
- Knudsen, J.E.; Ghaffar, U.; Ma, R.; Hung, A.J. Clinical applications of artificial intelligence in robotic surgery. J. Robot. Surg. 2024, 18, 102. [Google Scholar] [CrossRef] [PubMed]
- Nussinov, R.; Zhang, M.; Liu, Y.; Jang, H. AlphaFold, Artificial Intelligence (AI), and Allostery. J. Phys. Chem. B 2022, 126, 6372–6383. [Google Scholar] [CrossRef]
- Hachmeriyan, M.; Levkova, M.; Yahya, D.; Stoyanova, M.; Dimitrova, E. Ethical and Psychosocial Issues Associated with Genetic Testing for Hereditary Tumor Predisposition Syndromes. Healthcare 2025, 13, 880. [Google Scholar] [CrossRef]
- Kohabir, K.A.V.; Sistermans, E.A.; Wolthuis, R.M.F. Recent advances in CRISPR-based single-nucleotide fidelity diagnostics. Commun. Med. 2025, 5, 252. [Google Scholar] [CrossRef] [PubMed]
- Chen, Y.; Zhong, N.-N.; Cao, L.-M.; Liu, B.; Bu, L.-L. Surgical margins in head and neck squamous cell carcinoma: A narrative review. Int. J. Surg. Lond. Engl. 2024, 110, 3680–3700. [Google Scholar] [CrossRef]
- Valerio, J.E.; Ramirez-Velandia, F.; Fernandez-Gomez, M.P.; Rea, N.S.; Alvarez-Pinzon, A.M. Bridging the Global Technology Gap in Neurosurgery: Disparities in Access to Advanced Tools for Brain Tumor Resection. Neurosurg. Pract. 2024, 5, e00090. [Google Scholar] [CrossRef] [PubMed]
- Li, J.-P.O.; Liu, H.; Ting, D.S.J.; Jeon, S.; Chan, R.V.P.; Kim, J.E.; Sim, D.A.; Thomas, P.B.M.; Lin, H.; Chen, Y.; et al. Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective. Prog. Retin. Eye Res. 2021, 82, 100900. [Google Scholar] [CrossRef] [PubMed]
- Long, H.; Simmons, A.; Mayorga, A.; Burgess, B.; Nguyen, T.; Budda, B.; Rychkova, A.; Rhinn, H.; Tassi, I.; Ward, M.; et al. Preclinical and first-in-human evaluation of AL002, a novel TREM2 agonistic antibody for Alzheimer’s disease. Alzheimers Res. Ther. 2024, 16, 235. [Google Scholar] [CrossRef]
- Thierry, M.; Ponce, J.; Martà-Ariza, M.; Askenazi, M.; Faustin, A.; Leitner, D.; Pires, G.; Kanshin, E.; Drummond, E.; Ueberheide, B.; et al. The influence of APOEε4 on the pTau interactome in sporadic Alzheimer’s disease. Acta Neuropathol. 2024, 147, 91. [Google Scholar] [CrossRef]
- Agnello, L.; Gambino, C.M.; Ciaccio, A.M.; Piccoli, T.; Blandino, V.; Scazzone, C.; Lo Sasso, B.; Del Ben, F.; Ciaccio, M. Exploring the effect of APOE ε4 on biomarkers of neurodegeneration in Alzheimer’s disease. Clin. Chim. Acta 2024, 562, 119876. [Google Scholar] [CrossRef]
- Toader, C.; Serban, M.; Munteanu, O.; Covache-Busuioc, R.-A.; Enyedi, M.; Ciurea, A.V.; Tataru, C.P. From Synaptic Plasticity to Neurodegeneration: BDNF as a Transformative Target in Medicine. Int. J. Mol. Sci. 2025, 26, 4271. [Google Scholar] [CrossRef]
- Ramakrishnan, A.; Piehl, N.; Simonton, B.; Parikh, M.; Zhang, Z.; Teregulova, V.; van Olst, L.; Gate, D. Epigenetic dysregulation in Alzheimer’s disease peripheral immunity. Neuron 2024, 112, 1235–1248.e5. [Google Scholar] [CrossRef]
- Jennings, D.; Huntwork-Rodriguez, S.; Vissers, M.F.J.M.; Daryani, V.M.; Diaz, D.; Goo, M.S.; Chen, J.J.; Maciuca, R.; Fraser, K.; Mabrouk, O.S.; et al. LRRK2 Inhibition by BIIB122 in Healthy Participants and Patients with Parkinson’s Disease. Mov. Disord. 2023, 38, 386–398. [Google Scholar] [CrossRef]
- Ilieva, N.M.; Hoffman, E.K.; Ghalib, M.A.; Greenamyre, J.T.; De Miranda, B.R. LRRK2 kinase inhibition protects against Parkinson’s disease-associated environmental toxicants. Neurobiol. Dis. 2024, 196, 106522. [Google Scholar] [CrossRef]
- Abeliovich, A.; Hefti, F.; Sevigny, J. Gene Therapy for Parkinson’s Disease Associated with GBA1 Mutations. J. Park. Dis. 2021, 11, S183–S188. [Google Scholar] [CrossRef]
- Senkevich, K.A.; Kopytova, A.E.; Usenko, T.S.; Emelyanov, A.K.; Pchelina, S.N. Parkinson’s Disease Associated with GBA Gene Mutations: Molecular Aspects and Potential Treatment Approaches. Acta Naturae 2021, 13, 70–78. [Google Scholar] [CrossRef]
- Fernández-Vidal, J.M.; Aracil-Bolaños, I.; García-Sánchez, C.; Campolongo, A.; Curell, M.; Rodríguez-Rodriguez, R.; Aibar-Duran, J.Á.; Kulisevsky, J.; Pascual-Sedano, B. Cognitive phenotyping of GBA1-Parkinson’s disease: A study on deep brain stimulation outcomes. Park. Relat. Disord. 2024, 128, 107127. [Google Scholar] [CrossRef]
- Zagare, A.; Preciat, G.; Nickels, S.L.; Luo, X.; Monzel, A.S.; Gomez-Giro, G.; Robertson, G.; Jaeger, C.; Sharif, J.; Koseki, H.; et al. Omics data integration suggests a potential idiopathic Parkinson’s disease signature. Commun. Biol. 2023, 6, 1–14. [Google Scholar] [CrossRef] [PubMed]
- Strzelczyk, A.; Schubert-Bast, S. A Practical Guide to the Treatment of Dravet Syndrome with Anti-Seizure Medication. CNS Drugs 2022, 36, 217–237. [Google Scholar] [CrossRef] [PubMed]
- Toader, C.; Brehar, F.-M.; Radoi, M.P.; Serban, M.; Covache-Busuioc, R.-A.; Glavan, L.-A.; Ciurea, A.V.; Dobrin, N. The Microsurgical Resection of an Arteriovenous Malformation in a Patient with Thrombophilia: A Case Report and Literature Review. Diagnostics 2024, 14, 2613. [Google Scholar] [CrossRef] [PubMed]
- Miller, T.M.; Cudkowicz, M.E.; Genge, A.; Shaw, P.J.; Sobue, G.; Bucelli, R.C.; Chiò, A.; Damme, P.V.; Ludolph, A.C.; Glass, J.D.; et al. Trial of Antisense Oligonucleotide Tofersen for SOD1 ALS. N. Engl. J. Med. 2022, 387, 1099–1110. [Google Scholar] [CrossRef]
- Rothstein, J.D.; Baskerville, V.; Rapuri, S.; Mehlhop, E.; Jafar-Nejad, P.; Rigo, F.; Bennett, F.; Mizielinska, S.; Isaacs, A.; Coyne, A.N. G2C4 targeting antisense oligonucleotides potently mitigate TDP-43 dysfunction in human C9orf72 ALS/FTD induced pluripotent stem cell derived neurons. Acta Neuropathol. 2023, 147, 1. [Google Scholar] [CrossRef]
- Cammack, A.J.; Balendra, R.; Isaacs, A.M. Failure of C9orf72 sense repeat-targeting antisense oligonucleotides: Lessons learned and the path forward. Brain 2024, 147, 2607–2609. [Google Scholar] [CrossRef] [PubMed]
- Rook, M.E.; Southwell, A.L. Antisense Oligonucleotide Therapy: From Design to the Huntington Disease Clinic. BioDrugs 2022, 36, 105–119. [Google Scholar] [CrossRef] [PubMed]
- Moriyama, H.; Yokota, T. Recent Progress of Antisense Oligonucleotide Therapy for Superoxide-Dismutase-1-Mutated Amyotrophic Lateral Sclerosis: Focus on Tofersen. Genes 2024, 15, 1342. [Google Scholar] [CrossRef]
- Kairuz, D.; Samudh, N.; Ely, A.; Arbuthnot, P.; Bloom, K. Advancing mRNA technologies for therapies and vaccines: An African context. Front. Immunol. 2022, 13, 1018961. [Google Scholar] [CrossRef]
- Jacob, E.M.; Huang, J.; Chen, M. Lipid nanoparticle-based mRNA vaccines: A new frontier in precision oncology. Precis. Clin. Med. 2024, 7, pbae017. [Google Scholar] [CrossRef]
- Ding, S.; Khan, A.I.; Cai, X.; Song, Y.; Lyu, Z.; Du, D.; Dutta, P.; Lin, Y. Overcoming blood-brain barrier transport: Advances in nanoparticle-based drug delivery strategies. Mater. Today Kidlington Engl. 2020, 37, 112–125. [Google Scholar] [CrossRef] [PubMed]
- Miclăuș, M.; Balmus, G. CRISPR-Cas9-directed gene therapy for spinocerebellar ataxia type 1. Mol. Ther. Nucleic Acids 2024, 35, 102377. [Google Scholar] [CrossRef]
- Wasielewska, J.M.; Chaves, J.C.S.; Cabral-da-Silva, M.C.; Pecoraro, M.; Viljoen, S.J.; Nguyen, T.H.; Bella, V.L.; Oikari, L.E.; Ooi, L.; White, A.R. A patient-derived amyotrophic lateral sclerosis blood-brain barrier model for focused ultrasound-mediated anti-TDP-43 antibody delivery. Fluids Barriers CNS 2024, 21, 65. [Google Scholar] [CrossRef]
- Toader, C.; Corlatescu, A.-D.; Dobrin, N.; Covache-Busuioc, R.-A.; Costin, H.P.; Ciurea, A.V. Surgical Approach and Considerations for Compressive Thoracic Intraspinal Osteochondroma in Familial Hereditary Multiple Exostosis. Diseases 2024, 12, 165. [Google Scholar] [CrossRef]
- Misra, S.K.; Rosenholm, J.M.; Pathak, K. Functionalized and Nonfunctionalized Nanosystems for Mitochondrial Drug Delivery with Metallic Nanoparticles. Molecules 2023, 28, 4701. [Google Scholar] [CrossRef]
- Boros, B.D.; Schoch, K.M.; Kreple, C.J.; Miller, T.M. Antisense Oligonucleotides for the Study and Treatment of ALS. Neurotherapeutics 2022, 19, 1145–1158. [Google Scholar] [CrossRef]
- Priesterbach-Ackley, L.P.; Cordier, F.; de Witt Hamer, P.; Snijders, T.J.; Robe, P.A.; Küsters, B.; de Leng, W.W.J.; den Dunnen, W.F.A.; Brandsma, D.; Jansen, C.; et al. Diffuse, IDH-wildtype gliomas in adults with minimal histological change and isolated TERT promoter mutation: Not simply CNS WHO grade 4. Acta Neuropathol. 2024, 148, 12. [Google Scholar] [CrossRef]
- Zheng, L.; Luthra, R.; Alvarez, H.A.; San Lucas, F.A.; Duose, D.Y.; Wistuba, I.I.; Fuller, G.N.; Ballester, L.Y.; Roy-Chowdhuri, S.; Sweeney, K.J.; et al. Intragenic EGFR::EGFR.E1E8 Fusion (EGFRvIII) in 4331 Solid Tumors. Cancers 2023, 16, 6. [Google Scholar] [CrossRef] [PubMed]
- Bae, H.; Lee, B.; Hwang, S.; Lee, J.; Kim, H.-S.; Suh, Y.-L. Clinicopathological and Molecular Characteristics of IDH-Wildtype Glioblastoma with FGFR3::TACC3 Fusion. Biomedicines 2024, 12, 150. [Google Scholar] [CrossRef] [PubMed]
- Farooq, S.; Zeches, B.A.; Boyer, P.; Lee, S.; Jo, J. Bihemispheric IDH-Wildtype Glioblastoma with Unilateral FGFR3-TACC3 Fusion in Patient with Breast Cancer History: A Case Report and Literature Review. Am. J. Clin. Pathol. 2024, 162, S133–S134. [Google Scholar] [CrossRef]
- Cavirani, B.; Spagnoli, C.; Caraffi, S.G.; Cavalli, A.; Cesaroni, C.A.; Cutillo, G.; De Giorgis, V.; Frattini, D.; Marchetti, G.B.; Masnada, S.; et al. Genetic Epilepsies and Developmental Epileptic Encephalopathies with Early Onset: A Multicenter Study. Int. J. Mol. Sci. 2024, 25, 1248. [Google Scholar] [CrossRef] [PubMed]
- Moloney, P.B.; Cavalleri, G.L.; Delanty, N. Epilepsy in the mTORopathies: Opportunities for precision medicine. Brain Commun. 2021, 3, fcab222. [Google Scholar] [CrossRef]
- Buerki, S.E.; Haas, C.; Neubauer, J. Exome analysis focusing on epilepsy-related genes in children and adults with sudden unexplained death. Seizure 2023, 113, 66–75. [Google Scholar] [CrossRef]
- Pang, D.; Yu, Y.; Zhao, B.; Huang, J.; Cui, Y.; Li, T.; Li, C.; Shang, H. The Long Non-Coding RNA NR3C2-8:1 Promotes p53-Mediated Apoptosis through the miR-129-5p/USP10 Axis in Amyotrophic Lateral Sclerosis. Mol. Neurobiol. 2024, 61, 7466–7480. [Google Scholar] [CrossRef]
- Riva, N.; Domi, T.; Pozzi, L.; Lunetta, C.; Schito, P.; Spinelli, E.G.; Cabras, S.; Matteoni, E.; Consonni, M.; Bella, E.D.; et al. Update on recent advances in amyotrophic lateral sclerosis. J. Neurol. 2024, 271, 4693–4723. [Google Scholar] [CrossRef] [PubMed]
- Nguyen, L. Updates on Disease Mechanisms and Therapeutics for Amyotrophic Lateral Sclerosis. Cells 2024, 13, 888. [Google Scholar] [CrossRef]
- Rattay, T.W.; Völker, M.; Rautenberg, M.; Kessler, C.; Wurster, I.; Winter, N.; Haack, T.B.; Lindig, T.; Hengel, H.; Synofzik, M.; et al. The prodromal phase of hereditary spastic paraplegia type 4: The preSPG4 cohort study. Brain J. Neurol. 2023, 146, 1093–1102. [Google Scholar] [CrossRef]
- Ferese, R.; Scala, S.; Suppa, A.; Campopiano, R.; Asci, F.; Zampogna, A.; Chiaravalloti, M.A.; Griguoli, A.; Storto, M.; Pardo, A.D.; et al. Cohort analysis of novel SPAST variants in SPG4 patients and implementation of in vitro and in vivo studies to identify the pathogenic mechanism caused by splicing mutations. Front. Neurol. 2023, 14, 1296924. [Google Scholar] [CrossRef]
- Wang, X.-C.; Liu, R.-H.; Wang, T.; Wang, Y.; Jiang, Y.; Chen, D.-D.; Wang, X.-Y.; Hou, T.-S.; Kong, Q.-X. A novel missense mutation in SPAST causes hereditary spastic paraplegia in male members of a family: A case report. Mol. Med. Rep. 2023, 27, 79. [Google Scholar] [CrossRef]
- Prasad, V.K.; Verma, A.; Bhattacharya, P.; Shah, S.; Chowdhury, S.; Bhavsar, M.; Aslam, S.; Ashraf, N. Revolutionizing healthcare: A comparative insight into deep learning’s role in medical imaging. Sci. Rep. 2024, 14, 30273. [Google Scholar] [CrossRef]
- Ghorbani, F.; de Boer, E.N.; Benjamins-Stok, M.; Verschuuren-Bemelmans, C.C.; Knapper, J.; de Boer-Bergsma, J.; de Vries, J.J.; Sikkema-Raddatz, B.; Verbeek, D.S.; Westers, H.; et al. Copy Number Variant Analysis of Spinocerebellar Ataxia Genes in a Cohort of Dutch Patients With Cerebellar Ataxia. Neurol. Genet. 2023, 9, e200050. [Google Scholar] [CrossRef]
- Peng, Y.; Tu, Q.; Han, Y.; Gao, L.; Wan, C. Incidence of different pressure patterns of spinal cerebellar ataxia and analysis of imaging and genetic diagnosis. Open Life Sci. 2023, 18, 20220762. [Google Scholar] [CrossRef]
- Yang, Y.; Bagyinszky, E.; An, S.S.A. Patient with PSEN1 Glu318Gly and Other Possible Disease Risk Mutations, Diagnosed with Early Onset Alzheimer’s Disease. Int. J. Mol. Sci. 2023, 24, 15461. [Google Scholar] [CrossRef] [PubMed]
- Bae, H.; Shim, K.H.; Yoo, J.; Yang, Y.-S.; An, S.S.A.; Kang, M.-J. Double Mutations in a Patient with Early-Onset Alzheimer’s Disease in Korea: An APP Val551Met and a PSEN2 His169Asn. Int. J. Mol. Sci. 2023, 24, 7446. [Google Scholar] [CrossRef] [PubMed]
- Zholdasbekova, G.; Kaiyrlykyzy, A.; Kassenova, A.; Alzhanova, D.; Klyuev, D.; Askarova, S. ApoE Gene Polymorphism and Clinical, Biochemical, and Sociodemographic Characteristics of Alzheimer’s Disease Patients From Northern and Southern Regions of Kazakhstan. Int. J. Geriatr. Psychiatry 2024, 39, e70019. [Google Scholar] [CrossRef]
- Okobi, Q.; Cadet, D.; Urner, L.; Jung, M.; Cloughesy, T.; Nathanson, D. DDDR-43. ERAS-801 IS A SELECTIVE BRAIN-PENETRANT EGFR INHIBITOR WITH IMPROVED ACTIVITY AGAINST EGFR EXTRACELLULAR DOMAIN-MUTANT GLIOBLASTOMA. Neuro-Oncology 2024, 26, viii135. [Google Scholar] [CrossRef]
- Urian, F.I.; Toader, C.; Busuioc, R.-A.C.; Glavan, L.-A.; Corlatescu, A.D.; Iacob, G.; Ciurea, A.V. Evaluating the Efficacy of Vagus Nerve Stimulation across ‘Minor’ and ‘Major’ Seizure Types: A Retrospective Analysis of Clinical Outcomes in Pharmacoresistant Epilepsy. J. Clin. Med. 2024, 13, 4114. [Google Scholar] [CrossRef] [PubMed]
- Cockerell, I.; Christensen, J.; Hoei-Hansen, C.E.; Holst, L.; Grenaa Frederiksen, M.; Issa-Epe, A.I.; Nedregaard, B.; Solhoff, R.; Heimdal, K.; Johannessen Landmark, C.; et al. Effectiveness and safety of everolimus treatment in patients with tuberous sclerosis complex in real-world clinical practice. Orphanet J. Rare Dis. 2023, 18, 377. [Google Scholar] [CrossRef] [PubMed]
- Kovačević, M.; Janković, M.; Branković, M.; Milićević, O.; Novaković, I.; Sokić, D.; Ristić, A.; Shamsani, J.; Vojvodić, N. Novel GATOR1 variants in focal epilepsy. Epilepsy Behav. 2023, 141, 109139. [Google Scholar] [CrossRef]
- Barbato, M.I.; Nashed, J.; Bradford, D.; Ren, Y.; Khasar, S.; Miller, C.P.; Zolnik, B.S.; Zhao, H.; Li, Y.; Bi, Y.; et al. FDA Approval Summary: Dabrafenib in Combination with Trametinib for BRAFV600E Mutation-Positive Low-Grade Glioma. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2024, 30, 263–268. [Google Scholar] [CrossRef]
- Picca, A.; Di Stefano, A.L.; Savatovsky, J.; Ducray, F.; Chinot, O.; Moyal, E.C.-J.; Augereau, P.; Le Rhun, E.; Schmitt, Y.; Rousseaux, N.; et al. TARGET: A phase I/II open-label multicenter study to assess safety and efficacy of fexagratinib in patients with relapsed/refractory FGFR fusion-positive glioma. Neuro-Oncol. Adv. 2024, 6, vdae068. [Google Scholar] [CrossRef] [PubMed]
- Kakinen, A.; Jiang, Y.; Davis, T.P.; Teesalu, T.; Saarma, M. Brain Targeting Nanomedicines: Pitfalls and Promise. Int. J. Nanomed. 2024, 19, 4857–4875. [Google Scholar] [CrossRef]
- Wong, S.C.; Kamarudin, M.N.A.; Naidu, R. Anticancer Mechanism of Flavonoids on High-Grade Adult-Type Diffuse Gliomas. Nutrients 2023, 15, 797. [Google Scholar] [CrossRef]
- Ljubimova, J.Y.; Holler, E.; Black, K.L.; Ljubimov, A.V. Nanoparticles crossing blood-brain barrier need specific design for normal, neurodegenerative or cancerous brain conditions. Nanomed. 2024, 19, 1863–1866. [Google Scholar] [CrossRef]
- Asadpour, A.; Yahaya, B.H.; Bicknell, K.; Cottrell, G.S.; Widera, D. Uncovering the gray zone: Mapping the global landscape of direct-to-consumer businesses offering interventions based on secretomes, extracellular vesicles, and exosomes. Stem Cell Res. Ther. 2023, 14, 111. [Google Scholar] [CrossRef]
- Li, J.; Han, S.; Yu, F.; Li, T.; Liao, B.; Liu, F. Mapping the landscape of PSC-CM research through bibliometric analysis. Front. Cardiovasc. Med. 2024, 11, 1435874. [Google Scholar] [CrossRef]
- Song, J.; Zhan, K.; Li, J.; Cheng, S.; Li, X.; Yu, L. Bibliometric and visual analyses of research on the links between stroke and exosomes from 2008 to 2023. Medicine 2024, 103, e39498. [Google Scholar] [CrossRef] [PubMed]
- Guo, W.; Shu, Q.; Gao, L.; Gao, N.; Wang, Z.; Wei, W.; Zhang, Y.; Huyan, T.; Li, Q. A bibliometric analysis of extracellular vesicles as drug delivery vehicles in disease treatment (2010–2024). Extracell. Vesicle 2024, 4, 100051. [Google Scholar] [CrossRef]
- Kathad, U.; Biyani, N.; Peru YColón De Portugal, R.L.; Zhou, J.; Kochat, H.; Bhatia, K.; Kathad, U.; Biyani, N.; Peru YColón De Portugal, R.L.; Zhou, J.; et al. Expanding the repertoire of Antibody Drug Conjugate (ADC) targets with improved tumor selectivity and range of potent payloads through in-silico analysis. PLoS ONE 2024, 19, E0308604. [Google Scholar] [CrossRef]
- Jain, S.; Griffith, J.I.; Porath, K.A.; Rathi, S.; Le, J.; Pasa, T.I.; Decker, P.A.; Gupta, S.K.; Hu, Z.; Carlson, B.L.; et al. Bystander Effects, Pharmacokinetics, and Linker-Payload Stability of EGFR-Targeting Antibody-Drug Conjugates Losatuxizumab Vedotin and Depatux-M in Glioblastoma Models. Clin. Cancer Res. 2024, 30, 3287–3297. [Google Scholar] [CrossRef]
- Porath, K.A.; Regan, M.S.; Griffith, J.I.; Jain, S.; Stopka, S.A.; Burgenske, D.M.; Bakken, K.K.; Carlson, B.L.; Decker, P.A.; Vaubel, R.A.; et al. Convection enhanced delivery of EGFR targeting antibody-drug conjugates Serclutamab talirine and Depatux-M in glioblastoma patient-derived xenografts. Neuro-Oncol. Adv. 2022, 4, vdac130. [Google Scholar] [CrossRef] [PubMed]
- He, C.; Wu, Z.; Zhuang, M.; Li, X.; Xue, S.; Xu, S.; Xu, J.; Wu, Z.; Lu, M. Focused ultrasound-mediated blood-brain barrier opening combined with magnetic targeting cytomembrane based biomimetic microbubbles for glioblastoma therapy. J. Nanobiotechnol. 2023, 21, 297. [Google Scholar] [CrossRef]
- Wei, H.-J.; Upadhyayula, P.S.; Pouliopoulos, A.N.; Englander, Z.K.; Zhang, X.; Jan, C.-I.; Guo, J.; Mela, A.; Zhang, Z.; Wang, T.J.C.; et al. Focused Ultrasound-Mediated Blood-Brain Barrier Opening Increases Delivery and Efficacy of Etoposide for Glioblastoma Treatment. Int. J. Radiat. Oncol. Biol. Phys. 2021, 110, 539–550. [Google Scholar] [CrossRef] [PubMed]
- Rehman, G.; Shafiq, M.M.; Qadri, H.M.; Khan, Z.M.; Bashir, A. Focused ultrasound: A Trojan horse to deliver chemotherapeutics across blood-tumor barrier. Neurosurg. Rev. 2024, 47, 537. [Google Scholar] [CrossRef]
- Zhang, T.; Ding, J.; Lv, Q.; Zhao, M.; Liu, Y.; Wang, Q.; Chen, Y.; Zhao, H.; Ren, H.; Jiang, W.; et al. Strategies for organic nanoparticles delivering CRISPR/Cas9 for cancer therapy: Challenges and breakthroughs. Mater. Des. 2024, 244, 113097. [Google Scholar] [CrossRef]
- Ahmad, I. CRISPR/Cas9—A Promising Therapeutic Tool to Cure Blindness: Current Scenario and Future Prospects. Int. J. Mol. Sci. 2022, 23, 11482. [Google Scholar] [CrossRef] [PubMed]
- Foss, D.V.; Muldoon, J.J.; Nguyen, D.N.; Carr, D.; Sahu, S.U.; Hunsinger, J.M.; Wyman, S.K.; Krishnappa, N.; Mendonsa, R.; Schanzer, E.V.; et al. Peptide-mediated delivery of CRISPR enzymes for the efficient editing of primary human lymphocytes. Nat. Biomed. Eng. 2023, 7, 647–660. [Google Scholar] [CrossRef] [PubMed]
- El Moukhtari, S.H.; Garbayo, E.; Amundarain, A.; Pascual-Gil, S.; Carrasco-León, A.; Prosper, F.; Agirre, X.; Blanco-Prieto, M.J. Lipid nanoparticles for siRNA delivery in cancer treatment. J. Control. Release 2023, 361, 130–146. [Google Scholar] [CrossRef]
- Scuteri, D.; Pierobon, D.; Pagliaro, M.; Hamamura, K.; Hayashi, T.; Pignolo, L.; Nicotera, P.; Bagetta, G.; Corasaniti, M.T. Clinical and Market Analysis of NanoBEO: A Public-Worth, Innovative Therapy for Behavioral and Psychological Symptoms of Dementia (BPSD)—Emerging Evidence and Its Implications for a Health Technology Assessment (HTA) and Decision-Making in National Health Systems. Pharmaceutics 2024, 16, 1253. [Google Scholar] [CrossRef]
- Baig, M.S.; Karade, S.K.; Ahmad, A.; Khan, M.A.; Haque, A.; Webster, T.J.; Faiyazuddin, M.; Al-Qahtani, N.H. Lipid-based nanoparticles: Innovations in ocular drug delivery. Front. Mol. Biosci. 2024, 11, 1421959. [Google Scholar] [CrossRef]
- Yu, W.; Hill, S.F.; Huang, Y.; Zhu, L.; Demetriou, Y.; Ziobro, J.; Reger, F.; Jia, X.; Mattis, J.; Meisler, M.H. Allele-Specific Editing of a Dominant Epilepsy Variant Protects against Seizures and Lethality in a Murine Model. Ann. Neurol. 2024, 96, 958–969. [Google Scholar] [CrossRef]
- Begagić, E.; Bečulić, H.; Đuzić, N.; Džidić-Krivić, A.; Pugonja, R.; Muharemović, A.; Jaganjac, B.; Salković, N.; Sefo, H.; Pojskić, M. CRISPR/Cas9-Mediated Gene Therapy for Glioblastoma: A Scoping Review. Biomedicines 2024, 12, 238. [Google Scholar] [CrossRef]
- Marshall, M.S.; Issa, Y.; Heller, G.; Nguyen, D.; Bongarzone, E.R. AAV-Mediated GALC Gene Therapy Rescues Alpha-Synucleinopathy in the Spinal Cord of a Leukodystrophic Lysosomal Storage Disease Mouse Model. Front. Cell. Neurosci. 2020, 14. [Google Scholar] [CrossRef]
- Gao, T.; Huo, J.; Xin, C.; Yang, J.; Liu, Q.; Dong, H.; Li, R.; Liu, Y. Protective effects of intrathecal injection of AAV9-RabGGTB-GFP+ in SOD1G93A mice. Front. Aging Neurosci. 2023, 15, 1092607. [Google Scholar] [CrossRef]
- Daci, R.; Flotte, T.R. Delivery of Adeno-Associated Virus Vectors to the Central Nervous System for Correction of Single Gene Disorders. Int. J. Mol. Sci. 2024, 25, 1050. [Google Scholar] [CrossRef]
- Filipoiu, F.-M.; Badea, G.-T.; Enyedi, M.; Oprea, Ș.; Filipoiu, Z.-F.; Mutu, D.-E.G. Mesopancreas—Anatomical Insights and Its Implications for Diagnosis and Clinical and Surgical Practice. Diagnostics 2025, 15, 914. [Google Scholar] [CrossRef]
- Yang, T.; Kong, Z.; Ma, W. PD-1/PD-L1 immune checkpoint inhibitors in glioblastoma: Clinical studies, challenges and potential. Hum. Vaccines Immunother. 2020, 17, 546. [Google Scholar] [CrossRef]
- Han, J.; Chitu, V.; Stanley, E.R.; Wszolek, Z.K.; Karrenbauer, V.D.; Harris, R.A. Inhibition of colony stimulating factor-1 receptor (CSF-1R) as a potential therapeutic strategy for neurodegenerative diseases: Opportunities and challenges. Cell. Mol. Life Sci. 2022, 79, 219. [Google Scholar] [CrossRef] [PubMed]
- Luksik, A.S.; Yazigi, E.; Shah, P.; Jackson, C.M. CAR T Cell Therapy in Glioblastoma: Overcoming Challenges Related to Antigen Expression. Cancers 2023, 15, 1414. [Google Scholar] [CrossRef] [PubMed]
- Fan, H.; Luo, Y.; Gu, F.; Tian, B.; Xiong, Y.; Wu, G.; Nie, X.; Yu, J.; Tong, J.; Liao, X. Artificial intelligence-based MRI radiomics and radiogenomics in glioma. Cancer Imaging 2024, 24, 36. [Google Scholar] [CrossRef]
- Khayari, A.E.; Bouchmaa, N.; Taib, B.; Wei, Z.; Zeng, A.; Fatimy, R.E. Metabolic Rewiring in Glioblastoma Cancer: EGFR, IDH and Beyond. Front. Oncol. 2022, 12, 901951. [Google Scholar] [CrossRef] [PubMed]
- Shmelev, M.E.; Pilnik, A.A.; Shved, N.A.; Penkova, A.O.; Gulaia, V.S.; Kumeiko, V.V. IDH1 R132H and TP53 R248Q Mutations Modulate Glioma Cell Migration and Adhesion on Different ECM Components. Int. J. Mol. Sci. 2024, 25, 12178. [Google Scholar] [CrossRef]
- Broti, N.M.; Iwasaki, M.; Ono, Y. Machine learning detection of epileptic seizure onset zone from iEEG. Biomed. Eng. Lett. 2025, 15, 677–692. [Google Scholar] [CrossRef]
- Daly, S.R.; Soto, J.M.; Gonzalez, S.M.; Ankrah, N.; Gogineni, E.; Andraos, T.Y.; Skalina, K.A.; Fekrmandi, F.; Quinn, A.E.; Romanelli, P.; et al. Stereotactic radiosurgery for medically refractory non-lesional epilepsy: A case-based Radiosurgery Society (RSS) practice review. Clin. Neurol. Neurosurg. 2024, 246, 108550. [Google Scholar] [CrossRef]
- Shao, W.; Liu, L.; Gu, J.; Yang, Y.; Wu, Y.; Zhang, Z.; Xu, Q.; Wang, Y.; Shen, Y.; Gu, L.; et al. Spotlight on mechanism of sudden unexpected death in epilepsy in Dravet syndrome. Transl. Psychiatry 2025, 15, 84. [Google Scholar] [CrossRef]
- Hollunder, B.; Rajamani, N.; Siddiqi, S.H.; Finke, C.; Kühn, A.A.; Mayberg, H.S.; Fox, M.D.; Neudorfer, C.; Horn, A. Toward personalized medicine in connectomic deep brain stimulation. Prog. Neurobiol. 2022, 210, 102211. [Google Scholar] [CrossRef]
- Vetchinova, A.S.; Kapkaeva, M.R.; Ivanov, M.V.; Kutukova, K.A.; Mudzhiri, N.M.; Frumkina, L.E.; Brydun, A.V.; Sukhorukov, V.S.; Illarioshkin, S.N. Mitochondrial Dysfunction in Dopaminergic Neurons Derived from Patients with LRRK2- and SNCA-Associated Genetic Forms of Parkinson’s Disease. Curr. Issues Mol. Biol. 2023, 45, 8395–8411. [Google Scholar] [CrossRef]
- Cousins, O.; Schubert, J.J.; Chandra, A.; Veronese, M.; Valkimadi, P.; Creese, B.; Khan, Z.; Arathimos, R.; Hampshire, A.; Rosenzweig, I.; et al. Microglial activation, tau and amyloid deposition in TREM2 p.R47H carriers and mild cognitive impairment patients: A multi-modal/multi-tracer PET/MRI imaging study with influenza vaccine immune challenge. J. Neuroinflammation 2023, 20, 272. [Google Scholar] [CrossRef]
- Șovrea, A.S.; Boșca, A.B.; Dronca, E.; Constantin, A.-M.; Crintea, A.; Suflețel, R.; Ștefan, R.A.; Ștefan, P.A.; Onofrei, M.M.; Tschall, C.; et al. Non-Drug and Non-Invasive Therapeutic Options in Alzheimer’s Disease. Biomedicines 2025, 13, 84. [Google Scholar] [CrossRef] [PubMed]
- Zheng, M.; Bao, N.; Wang, Z.; Song, C.; Jin, Y. Alternative splicing in autism spectrum disorder: Recent insights from mechanisms to therapy. Asian J. Psychiatry 2025, 108, 104501. [Google Scholar] [CrossRef] [PubMed]
- Tsekrekou, M.; Giannakou, M.; Papanikolopoulou, K.; Skretas, G. Protein aggregation and therapeutic strategies in SOD1- and TDP-43- linked ALS. Front. Mol. Biosci. 2024, 11, 1383453. [Google Scholar] [CrossRef]
- Nguyen, L.H.; Xu, Y.; Nair, M.; Bordey, A. The mTOR pathway genes mTOR, Rheb, Depdc5, Pten, and Tsc1 have convergent and divergent impacts on cortical neuron development and function. eLife 2024, 12, RP91010. [Google Scholar] [CrossRef] [PubMed]
- Boff, M.O.; Xavier, F.A.C.; Diz, F.M.; Gonçalves, J.B.; Ferreira, L.M.; Zambeli, J.; Pazzin, D.B.; Previato, T.T.R.; Erwig, H.S.; Gonçalves, J.I.B.; et al. mTORopathies in Epilepsy and Neurodevelopmental Disorders: The Future of Therapeutics and the Role of Gene Editing. Cells 2025, 14, 662. [Google Scholar] [CrossRef]
- Wang, L.; Vaios, E.J.; Yang, Z.; Zhao, J.; Yin, F.F.; Reitman, Z.J.; Wang, C. A Radiogenomic Machine Learning Model for Glioblastoma Post-Resection Overall Survival Group Prediction. Int. J. Radiat. Oncol. 2023, 117, S156. [Google Scholar] [CrossRef]
- Zhang, W.; Dang, R.; Liu, H.; Dai, L.; Liu, H.; Adegboro, A.A.; Zhang, Y.; Li, W.; Peng, K.; Hong, J.; et al. Machine learning-based investigation of regulated cell death for predicting prognosis and immunotherapy response in glioma patients. Sci. Rep. 2024, 14, 4173. [Google Scholar] [CrossRef]
- Kons, Z.; Hadanny, A.; Bush, A.; Nanda, P.; Herrington, T.M.; Richardson, R.M. Accurate Deep Brain Stimulation Lead Placement Concurrent With Research Electrocorticography. Oper. Neurosurg. 2023, 24, 524–532. [Google Scholar] [CrossRef]
- Sadjadi, S.M.; Ebrahimzadeh, E.; Shams, M.; Seraji, M.; Soltanian-Zadeh, H. Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data. Front. Neurol. 2021, 12. [Google Scholar] [CrossRef]
- Kazemzadeh, K.; Akhlaghdoust, M.; Zali, A. Advances in artificial intelligence, robotics, augmented and virtual reality in neurosurgery. Front. Surg. 2023, 10, 1241923. [Google Scholar] [CrossRef]
- Pandey, S.; Choudhari, J.K.; Tripathi, A.; Singh, A.; Antony, A.; Chouhan, U. Artificial Intelligence-Based Genome Editing in CRISPR/Cas9. Methods Mol. Biol. Clifton NJ 2025, 2952, 273–282. [Google Scholar] [CrossRef]
- Dixit, S.; Kumar, A.; Srinivasan, K.; Vincent, P.M.D.R.; Ramu Krishnan, N. Advancing genome editing with artificial intelligence: Opportunities, challenges, and future directions. Front. Bioeng. Biotechnol. 2024, 11, 1335901. [Google Scholar] [CrossRef] [PubMed]
- Abbasi, A.F.; Asim, M.N.; Dengel, A. Transitioning from wet lab to artificial intelligence: A systematic review of AI predictors in CRISPR. J. Transl. Med. 2025, 23, 153. [Google Scholar] [CrossRef]
- Grandi, F.C.; Modi, H.; Kampman, L.; Corces, M.R. Chromatin accessibility profiling by ATAC-seq. Nat. Protoc. 2022, 17, 1518–1552. [Google Scholar] [CrossRef]
- Kolanu, N.D. CRISPR–Cas9 Gene Editing: Curing Genetic Diseases by Inherited Epigenetic Modifications. Glob. Med. Genet. 2024, 11, 113–122. [Google Scholar] [CrossRef] [PubMed]
- Morabito, A.; De Simone, G.; Pastorelli, R.; Brunelli, L.; Ferrario, M. Algorithms and tools for data-driven omics integration to achieve multilayer biological insights: A narrative review. J. Transl. Med. 2025, 23, 425. [Google Scholar] [CrossRef]
- Pan, W.; Long, F.; Pan, J. ScInfoVAE: Interpretable dimensional reduction of single cell transcription data with variational autoencoders and extended mutual information regularization. BioData Min. 2023, 16, 17. [Google Scholar] [CrossRef]
- Ritter, M.; Blume, C.; Tang, Y.; Patel, A.; Patel, B.; Berghaus, N.; Kada Benotmane, J.; Kueckelhaus, J.; Yabo, Y.; Zhang, J.; et al. Spatially resolved transcriptomics and graph-based deep learning improve accuracy of routine CNS tumor diagnostics. Nat. Cancer 2025, 6, 292–306. [Google Scholar] [CrossRef]
- Wang, H.; Zhang, J.; Xie, N.; Liu, J. Visualized knowledge map of robot application in surgical field: A bibliometric analysis. J. Robot. Surg. 2025, 19, 350. [Google Scholar] [CrossRef] [PubMed]
- Zhu, R.; Pan, W.; Liu, J.; Shang, J. Epileptic seizure prediction via multidimensional transformer and recurrent neural network fusion. J. Transl. Med. 2024, 22, 895. [Google Scholar] [CrossRef] [PubMed]
- Ghosh, S.; Sindhujaa, P.; Kesavan, D.K.; Gulyás, B.; Máthé, D. Brain-Computer Interfaces and AI Segmentation in Neurosurgery: A Systematic Review of Integrated Precision Approaches. Surgeries 2025, 6, 50. [Google Scholar] [CrossRef]
- Cascella, M.; Scarpati, G.; Bignami, E.G.; Cuomo, A.; Vittori, A.; Di Gennaro, P.; Crispo, A.; Coluccia, S. Utilizing an artificial intelligence framework (conditional generative adversarial network) to enhance telemedicine strategies for cancer pain management. J. Anesth. Analg. Crit. Care 2023, 3, 19. [Google Scholar] [CrossRef] [PubMed]
- Bhat, A.A.; Nisar, S.; Mukherjee, S.; Saha, N.; Yarravarapu, N.; Lone, S.N.; Masoodi, T.; Chauhan, R.; Maacha, S.; Bagga, P.; et al. Integration of CRISPR/Cas9 with artificial intelligence for improved cancer therapeutics. J. Transl. Med. 2022, 20, 534. [Google Scholar] [CrossRef]
- Rončević, A.; Koruga, N.; Soldo Koruga, A.; Rončević, R. Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment. Chin. Neurosurg. J. 2025, 11, 10. [Google Scholar] [CrossRef]
- Guo, Y.; Zhao, S.; Wang, G.G. Polycomb gene silencing mechanisms: PRC2 chromatin targeting, H3K27me3 “readout” and phase separation-based compaction. Trends Genet. TIG 2021, 37, 547–565. [Google Scholar] [CrossRef]
- Tang, Q.; Ratnayake, R.; Seabra, G.; Jiang, Z.; Fang, R.; Cui, L.; Ding, Y.; Kahveci, T.; Bian, J.; Li, C.; et al. Morphological profiling for drug discovery in the era of deep learning. Brief. Bioinform. 2024, 25, bbae284. [Google Scholar] [CrossRef]
- Binan, L.; Jiang, A.; Danquah, S.A.; Valakh, V.; Simonton, B.; Bezney, J.; Manguso, R.T.; Yates, K.B.; Nehme, R.; Cleary, B.; et al. Simultaneous CRISPR screening and spatial transcriptomics reveal intracellular, intercellular, and functional transcriptional circuits. Cell 2025, 188, 2141–2158.e18. [Google Scholar] [CrossRef]
- Moon, H.H.; Jeong, J.; Park, J.E.; Kim, N.; Choi, C.; Kim, Y.-H.; Song, S.W.; Hong, C.-K.; Kim, J.H.; Kim, H.S. Generative AI in glioma: Ensuring diversity in training image phenotypes to improve diagnostic performance for IDH mutation prediction. Neuro-Oncology 2024, 26, 1124–1135. [Google Scholar] [CrossRef]
- Shen, S.; Qi, W.; Liu, X.; Zeng, J.; Li, S.; Zhu, X.; Dong, C.; Wang, B.; Shi, Y.; Yao, J.; et al. From virtual to reality: Innovative practices of digital twins in tumor therapy. J. Transl. Med. 2025, 23, 348. [Google Scholar] [CrossRef]
- Whitelaw, B.S.; Stoessel, M.B.; Majewska, A.K. Movers and Shakers: Microglial dynamics and modulation of neural networks. Glia 2023, 71, 1575–1591. [Google Scholar] [CrossRef]
- Chakraborty, C.; Bhattacharya, M.; Pal, S.; Lee, S.-S. From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare. Curr. Res. Biotechnol. 2024, 7, 100164. [Google Scholar] [CrossRef]
- Chirizzi, C.; Pellegatta, S.; Gori, A.; Falco, J.; Rubiu, E.; Acerbi, F.; Bombelli, F.B. Next-generation agents for fluorescence-guided glioblastoma surgery. Bioeng. Transl. Med. 2024, 9, e10608. [Google Scholar] [CrossRef] [PubMed]
- Piscopo, L.; Zampella, E.; Klain, M. [18F]FET PET/MR and machine learning in the evaluation of glioma. Eur. J. Nucl. Med. Mol. Imaging 2024, 51, 797–799. [Google Scholar] [CrossRef] [PubMed]
- Gigante, E.; Cazier, H.; Albuquerque, M.; Laouirem, S.; Beaufrère, A.; Paradis, V. MALDI Imaging, a Powerful Multiplex Approach to Decipher Intratumoral Heterogeneity: Combined Hepato-Cholangiocarcinomas as Proof of Concept. Cancers 2023, 15, 2143. [Google Scholar] [CrossRef]
- Toader, C.; Serban, M.; Covache-Busuioc, R.-A.; Radoi, M.P.; Aljboor, G.S.R.; Costin, H.P.; Corlatescu, A.D.; Glavan, L.-A.; Gorgan, R.M. Cerebellar Cavernoma Resection: Case Report with Long-Term Follow-Up. J. Clin. Med. 2024, 13, 7525. [Google Scholar] [CrossRef]
- Toader, C.; Brehar, F.-M.; Radoi, M.P.; Serban, M.; Covache-Busuioc, R.-A.; Aljboor, G.S.; Gorgan, R.M. Stroke and Pulmonary Thromboembolism Complicating a Kissing Aneurysm in the M1 Segment of the Right MCA. J. Clin. Med. 2025, 14, 564. [Google Scholar] [CrossRef]
- Yoganathan, K.; Malek, N.; Torzillo, E.; Paranathala, M.; Greene, J. Neurological update: Structural and functional imaging in epilepsy surgery. J. Neurol. 2023, 270, 2798–2808. [Google Scholar] [CrossRef]
- Toader, C.; Tataru, C.P.; Munteanu, O.; Serban, M.; Covache-Busuioc, R.-A.; Ciurea, A.V.; Enyedi, M. Decoding Neurodegeneration: A Review of Molecular Mechanisms and Therapeutic Advances in Alzheimer’s, Parkinson’s, and ALS. Int. J. Mol. Sci. 2024, 25, 12613. [Google Scholar] [CrossRef]
- Iba, M.; Lee, Y.-J.; Horan-Portelance, L.; Chang, K.; Szabo, M.; Rissman, R.A.; You, S.; Masliah, E.; Kim, C. Microglial and neuronal fates following inhibition of CSF-1R in synucleinopathy mouse model. Brain. Behav. Immun. 2025, 123, 254–269. [Google Scholar] [CrossRef] [PubMed]
- Shimoda, Y.; Beppu, K.; Ikoma, Y.; Morizawa, Y.M.; Zuguchi, S.; Hino, U.; Yano, R.; Sugiura, Y.; Moritoh, S.; Fukazawa, Y.; et al. Optogenetic stimulus-triggered acquisition of seizure resistance. Neurobiol. Dis. 2022, 163, 105602. [Google Scholar] [CrossRef] [PubMed]
- Karlsson, J.; Luly, K.M.; Tzeng, S.Y.; Green, J.J. Nanoparticle designs for delivery of nucleic acid therapeutics as brain cancer therapies. Adv. Drug Deliv. Rev. 2021, 179, 113999. [Google Scholar] [CrossRef] [PubMed]
- Toader, C.; Radoi, M.P.; Brehar, F.-M.; Serban, M.; Glavan, L.-A.; Covache-Busuioc, R.-A.; Ciurea, A.V.; Dobrin, N. Mirror Aneurysms of the Pericallosal Artery Clipped During a Single Surgical Procedure: Case Report and Literature Review. J. Clin. Med. 2024, 13, 6719. [Google Scholar] [CrossRef]
- Toader, C.; Kakucs, C.; Dobrin, N.; Covache-Busuioc, R.-A.; Bratu, B.-G.; Popa, A.A.; Glavan, L.-A.; Corlatescu, A.-D.; Grama, M.G.N.; Costin, H.-P.; et al. Cerebral Aneurysm Characteristics and Surgical Outcomes: An In-Depth Analysis of 346 Cases Operated Using Microsurgical Clipping. Cureus 2024, 16, e56933. [Google Scholar] [CrossRef]
- Merulla, A.E.; Stella, M.; Barbagallo, C.; Battaglia, R.; Caponnetto, A.; Broggi, G.; Altieri, R.; Certo, F.; Caltabiano, R.; Ragusa, M.; et al. circSMARCA5 Is an Upstream Regulator of the Expression of miR-126-3p, miR-515-5p, and Their mRNA Targets, Insulin-like Growth Factor Binding Protein 2 (IGFBP2) and NRAS Proto-Oncogene, GTPase (NRAS) in Glioblastoma. Int. J. Mol. Sci. 2022, 23, 13676. [Google Scholar] [CrossRef]
- Ahmad, F.; Sudesh, R.; Ahmed, A.T.; Haque, S. Roles of HOTAIR Long Non-coding RNA in Gliomas and Other CNS Disorders. Cell. Mol. Neurobiol. 2024, 44, 23. [Google Scholar] [CrossRef]
- Ma, J.-Q.; Wang, L.; Zhang, Y.; Bian, Y.-Q.; Qu, X.-P.; Song, L.-J.; Wang, C.; Gao, L.; Fang, Q.-X.; Zhao, D.-C.; et al. Single-nucleus RNA sequencing-based construction of a hippocampal neuron atlas in mice with epileptic cognitive impairment. iScience 2024, 27, 111065. [Google Scholar] [CrossRef]
- Barzegar Behrooz, A.; Latifi-Navid, H.; da Silva Rosa, S.C.; Swiat, M.; Wiechec, E.; Vitorino, C.; Vitorino, R.; Jamalpoor, Z.; Ghavami, S. Integrating Multi-Omics Analysis for Enhanced Diagnosis and Treatment of Glioblastoma: A Comprehensive Data-Driven Approach. Cancers 2023, 15, 3158. [Google Scholar] [CrossRef] [PubMed]
- Bernhard, C.; Reita, D.; Martin, S.; Entz-Werle, N.; Dontenwill, M. Glioblastoma Metabolism: Insights and Therapeutic Strategies. Int. J. Mol. Sci. 2023, 24, 9137. [Google Scholar] [CrossRef] [PubMed]
- Chong, D.; Jones, N.C.; Schittenhelm, R.B.; Anderson, A.; Casillas-Espinosa, P.M. Multi-omics integration and epilepsy: Towards a better understanding of biological mechanisms. Prog. Neurobiol. 2023, 227, 102480. [Google Scholar] [CrossRef]
- Ngadimon, I.W.; Seth, E.A.; Shaikh, M.F. Exploring the Neuroinflammatory Pathway in Epilepsy and Cognitive Impairment: Role of HMGB1 and Translational Challenges. Front. Biosci.-Landmark 2024, 29, 229. [Google Scholar] [CrossRef]
- Zhong, H.; Zhou, X.; Uhm, H.; Jiang, Y.; Cao, H.; Chen, Y.; Mak, T.T.W.; Lo, R.M.N.; Wong, B.W.Y.; Cheng, E.Y.L.; et al. Using blood transcriptome analysis for Alzheimer’s disease diagnosis and patient stratification. Alzheimers Dement. 2024, 20, 2469–2484. [Google Scholar] [CrossRef]
- Ling, A.L.; Solomon, I.H.; Landivar, A.M.; Nakashima, H.; Woods, J.K.; Santos, A.; Masud, N.; Fell, G.; Mo, X.; Yilmaz, A.S.; et al. Clinical trial links oncolytic immunoactivation to survival in glioblastoma. Nature 2023, 623, 157–166. [Google Scholar] [CrossRef]
- Alqahtani, S.M.; Altharawi, A.; Alabbas, A.; Ahmad, F.; Ayaz, H.; Nawaz, A.; Rahman, S.; Alossaimi, M.A. System biology approach to identify the novel biomarkers in glioblastoma multiforme tumors by using computational analysis. Front. Pharmacol. 2024, 15, 1364138. [Google Scholar] [CrossRef] [PubMed]
- Yang, Q.; Cai, Y.; Qiu, S.; Zhang, A. Integrated analysis of abnormal metabolic homeostasis for decoding tumor microenvironment. Front. Mol. Biosci. 2024, 11, 1443642. [Google Scholar] [CrossRef]
- Shaath, R.; Al-Maraghi, A.; Ali, H.; AlRayahi, J.; Kennedy, A.D.; DeBalsi, K.L.; Hussein, S.; Elbashir, N.; Padmajeya, S.S.; Palaniswamy, S.; et al. Integrating Genome Sequencing and Untargeted Metabolomics in Monozygotic Twins with a Rare Complex Neurological Disorder. Metabolites 2024, 14, 152. [Google Scholar] [CrossRef]
- Leitner, D.F.; Siu, Y.; Korman, A.; Lin, Z.; Kanshin, E.; Friedman, D.; Devore, S.; Ueberheide, B.; Tsirigos, A.; Jones, D.R.; et al. Metabolomic, proteomic, and transcriptomic changes in adults with epilepsy on modified Atkins diet. Epilepsia 2023, 64, 1046–1060. [Google Scholar] [CrossRef] [PubMed]
- Kadena, K.; Vlamos, P. Elucidating the Epigenetic and Protein Interaction Landscapes in Amyotrophic Lateral Sclerosis: An Integrated Bioinformatics Analysis. Sclerosis 2024, 2, 140–155. [Google Scholar] [CrossRef]
- Zhao, Y.; Li, X.; Wang, K.; Iyer, G.; Sakowski, S.A.; Zhao, L.; Teener, S.; Bakulski, K.M.; Dou, J.F.; Traynor, B.J.; et al. Epigenetic age acceleration is associated with occupational exposures, sex, and survival in amyotrophic lateral sclerosis. EBioMedicine 2024, 109, 105383. [Google Scholar] [CrossRef] [PubMed]
- Dareng, E.O.; Coetzee, S.G.; Tyrer, J.P.; Peng, P.-C.; Rosenow, W.; Chen, S.; Davis, B.D.; Dezem, F.S.; Seo, J.-H.; Nameki, R.; et al. Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions. Am. J. Hum. Genet. 2024, 111, 1061–1083. [Google Scholar] [CrossRef]
- Lee, W.-J.; Moon, J.; Jang, Y.; Shin, Y.-W.; Son, H.; Shin, S.; Jeon, D.; Han, D.; Lee, S.-T.; Park, K.-I.; et al. Nilotinib treatment outcomes in autosomal dominant spinocerebellar ataxia over one year. Sci. Rep. 2024, 14, 16303. [Google Scholar] [CrossRef] [PubMed]
- Kon, T.; Ichimata, S.; Di Luca, D.G.; Martinez-Valbuena, I.; Kim, A.; Yoshida, K.; Alruwaita, A.A.; Kleiner, G.; Strafella, A.P.; Forrest, S.L.; et al. Multiple system atrophy with amyloid-β-predominant Alzheimer’s disease neuropathologic change. Brain Commun. 2024, 6, fcae141. [Google Scholar] [CrossRef]
- Shen, X.-N.; Wu, K.-M.; Huang, Y.-Y.; Guo, Y.; Huang, S.-Y.; Zhang, Y.-R.; Chen, S.-F.; Wang, H.-F.; Zhang, W.; Cheng, W.; et al. Systematic assessment of plasma biomarkers in spinocerebellar ataxia. Neurobiol. Dis. 2023, 181, 106112. [Google Scholar] [CrossRef]
- Morikawa, T.; Takahashi, M.; Izumi, Y.; Bamba, T.; Moriyama, K.; Hattori, G.; Fujioka, R.; Miura, S.; Shibata, H. Oleic Acid-Containing Phosphatidylinositol Is a Blood Biomarker Candidate for SPG28. Biomedicines 2023, 11, 1092. [Google Scholar] [CrossRef]
- Christen, M.; Oevermann, A.; Rupp, S.; Vaz, F.M.; Wever, E.J.M.; Braus, B.K.; Jagannathan, V.; Kehl, A.; Hytönen, M.K.; Lohi, H.; et al. PCYT2 deficiency in Saarlooswolfdogs with progressive retinal, central, and peripheral neurodegeneration. Mol. Genet. Metab. 2024, 141, 108149. [Google Scholar] [CrossRef]
- Baggiani, M.; Santorelli, F.M.; Mero, S.; Privitera, F.; Damiani, D.; Tessa, A. Generation of a human induced pluripotent stem cell line (FSMi001-A) from fibroblasts of a patient carrying heterozygous mutation in the REEP1 gene. Stem Cell Res. 2024, 79, 103472. [Google Scholar] [CrossRef]
- Tang, A.S.; Rankin, K.P.; Cerono, G.; Miramontes, S.; Mills, H.; Roger, J.; Zeng, B.; Nelson, C.; Soman, K.; Woldemariam, S.; et al. Leveraging electronic health records and knowledge networks for Alzheimer’s disease prediction and sex-specific biological insights. Nat. Aging 2024, 4, 379–395. [Google Scholar] [CrossRef]
- Lu, L.; Kotowska, A.M.; Kern, S.; Fang, M.; Rudd, T.R.; Alexander, M.R.; Scurr, D.J.; Zhu, Z. Metabolomic and Proteomic Analysis of ApoE4-Carrying H4 Neuroglioma Cells in Alzheimer’s Disease Using OrbiSIMS and LC-MS/MS. Anal. Chem. 2024, 96, 11760–11770. [Google Scholar] [CrossRef]
- Panizza, E. DeepOmicsAE: Representing Signaling Modules in Alzheimer’s Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data. JoVE 2023, e65910. [Google Scholar] [CrossRef] [PubMed]
- Ledri, M.; Andersson, M.; Wickham, J.; Kokaia, M. Optogenetics for controlling seizure circuits for translational approaches. Neurobiol. Dis. 2023, 184, 106234. [Google Scholar] [CrossRef] [PubMed]
- Rouatbi, N.; Walters, A.A.; Costa, P.M.; Qin, Y.; Liam-Or, R.; Grant, V.; Pollard, S.M.; Wang, J.T.-W.; Al-Jamal, K.T. RNA lipid nanoparticles as efficient in vivo CRISPR-Cas9 gene editing tool for therapeutic target validation in glioblastoma cancer stem cells. J. Control. Release 2024, 375, 776–787. [Google Scholar] [CrossRef] [PubMed]
- Toader, C.; Dumitru, A.V.; Eva, L.; Serban, M.; Covache-Busuioc, R.-A.; Ciurea, A.V. Nanoparticle Strategies for Treating CNS Disorders: A Comprehensive Review of Drug Delivery and Theranostic Applications. Int. J. Mol. Sci. 2024, 25, 13302. [Google Scholar] [CrossRef]
- Liu, X.; Liu, F.; Jin, L.; Wu, J. Evolution of Neurosurgical Robots: Historical Progress and Future Direction. World Neurosurg. 2024, 191, 49–57. [Google Scholar] [CrossRef]
- Toader, C.; Brehar, F.-M.; Radoi, M.P.; Covache-Busuioc, R.-A.; Glavan, L.-A.; Grama, M.; Corlatescu, A.-D.; Costin, H.P.; Bratu, B.-G.; Popa, A.A.; et al. Machine Learning-Based Prediction of Clinical Outcomes in Microsurgical Clipping Treatments of Cerebral Aneurysms. Diagnostics 2024, 14, 2156. [Google Scholar] [CrossRef]
- Guo, P.; Yang, Y.; Wang, L.; Zhang, Y.; Zhang, B.; Cai, J.; de Melo, F.F.; Strickland, M.R.; Huang, M.; Liu, B. Development of a streamlined NGS-based TCGA classification scheme for gastric cancer and its implications for personalized therapy. J. Gastrointest. Oncol. 2024, 15, 2053–2066. [Google Scholar] [CrossRef]
- Li, W.; Zhang, Z.; Xie, B.; He, Y.; He, K.; Qiu, H.; Lu, Z.; Jiang, C.; Pan, X.; He, Y.; et al. HiOmics: A cloud-based one-stop platform for the comprehensive analysis of large-scale omics data. Comput. Struct. Biotechnol. J. 2024, 23, 659–668. [Google Scholar] [CrossRef]
- Kaizer, A.M.; Belli, H.M.; Ma, Z.; Nicklawsky, A.G.; Roberts, S.C.; Wild, J.; Wogu, A.F.; Xiao, M.; Sabo, R.T. Recent innovations in adaptive trial designs: A review of design opportunities in translational research. J. Clin. Transl. Sci. 2023, 7, e125. [Google Scholar] [CrossRef]
- Shlobin, N.A.; Ward, M.; Shah, H.A.; Brown, E.D.L.; Sciubba, D.M.; Langer, D.; D’Amico, R.S. Ethical Incorporation of Artificial Intelligence into Neurosurgery: A Generative Pretrained Transformer Chatbot-Based, Human-Modified Approach. World Neurosurg. 2024, 187, e769–e791. [Google Scholar] [CrossRef] [PubMed]
- Tafazoli, A.; Abbaszadegan, M.R.; Patrinos, G.P. Editorial: Integration of computational genomics into clinical pharmacogenomic tests: How bioinformatics may help primary care in precision medicine area. Front. Genet. 2023, 14, 1261876. [Google Scholar] [CrossRef]
- Gupta, S.; Gomez, M.G.; Johnston, J.M.; Park, K.B. Global Partnerships in Neurosurgery: Mapping the Need. Neurosurg. Clin. 2024, 35, 489–498. [Google Scholar] [CrossRef] [PubMed]
- Toader, C.; Serban, M.; Covache-Busuioc, R.-A.; Radoi, M.P.; Aljboor, G.S.R.; Costin, H.P.; Ilie, M.-M.; Popa, A.A.; Gorgan, R.M. Single-Stage Microsurgical Clipping of Multiple Intracranial Aneurysms in a Patient with Cerebral Atherosclerosis: A Case Report and Review of Surgical Management. J. Clin. Med. 2025, 14, 269. [Google Scholar] [CrossRef] [PubMed]
References | Disease | Key Mutations | Pathological Mechanism | Therapeutic Focus | Preclinical/Clinical Advancements | Challenges |
---|---|---|---|---|---|---|
[154,155,156,157] | Glioblastoma | EGFRvIII, IDH1, TERT | Tumor proliferation, disrupted metabolism | EGFR inhibitors, IDH inhibitors, CRISPR-based editing | Nanoparticle-based CRISPR delivery under development | Resistance due to tumor heterogeneity |
[158,159,160] | Epilepsy | SCN1A, SCN8A, DEPDC5 | Ion channel dysregulation, mTOR pathway activation | Cannabidiol (CBD), mTOR inhibitors | Gene-silencing therapies showing reduction in seizures | Incomplete seizure localization in non-lesional epilepsy |
[161,162,163] | ALS | C9orf72, SOD1, TARDBP | RNA toxicity, dipeptide protein accumulation | ASOs targeting toxic RNA, CRISPR excision | ASOs delivering uniform therapeutic effects via intrathecal routes | Long-term durability of CRISPR treatments |
[164,165,166] | HSP | SPAST, ATL1 | Impaired microtubule dynamics | Microtubule stabilizers, gene therapy | Structural modeling advancing small molecule design | Poor BBB penetration of therapeutic molecules |
[167,168,169] | SCAs | ATXN1, ATXN2, ATXN3 | Trinucleotide repeat expansions | Antisense oligonucleotides, HDAC inhibitors | Positive early-phase trials for HDAC inhibitors improving motor coordination | Need for specific delivery technologies |
[170,171,172] | Alzheimer’s Disease | APOE ε4, TREM2, PSEN1 | Amyloid-beta aggregation, tau hyperphosphorylation | Anti-amyloid antibodies, tau kinase inhibitors | Microglial-modulating therapies showing plaque clearance | BBB penetration remains limited |
References | Technology | Mechanism | Disease Applications | Key Findings | Advantages | Limitations |
---|---|---|---|---|---|---|
[179,180,181] | Nanoparticles | BBB penetration, receptor-targeted delivery | Glioblastoma, SCAs | Enhanced RNA delivery to cerebellum; improved survival in preclinical models | Highly specific delivery, reduced systemic effects | Complex manufacturing processes |
[182,183,184,185] | Exosome-based therapy | Natural vesicle-mediated RNA/protein transport | ALS, SCAs | High efficiency in delivering ASOs to motor neurons and cerebellar neurons | Biocompatibility, immune evasion | Limited scalability and yield |
[186,187,188] | Convection-Enhanced Delivery (CED) | Uniform regional drug distribution | SCAs, glioblastoma | Effective ASO delivery to cerebellum; improved motor outcomes in animal models | Avoids systemic exposure, bypasses BBB | Requires precise surgical techniques |
[189,190,191] | Focused Ultrasound (FUS) | Transient BBB disruption using microbubbles | ALS, glioblastoma | Improved localized delivery of monoclonal antibodies and neuroprotective agents | Non-invasive, high localization | Risk of local tissue damage |
[192,193,194] | Nanoparticles for CRISPR | BBB-penetrating CRISPR-carrying particles | Glioblastoma, HSP | Demonstrated precise gene editing and reduced tumor growth in preclinical trials | Enables direct gene editing | Long-term safety of CRISPR delivery remains unclear |
[195,196,197] | Lipid Nanoparticles (LNPs) | mRNA delivery | Alzheimer’s Disease, Parkinson’s Disease | Effective mRNA transport targeting microglia and neurons | Cost-effective, scalable | Risk of off-target effects |
References | Disease | Causative/Associated Genes | Functional Deficit or Pathological Defect | Surgical/Genomic Intervention Strategy | Role of AI |
---|---|---|---|---|---|
[207,208,209] | Glioblastoma | IDH1, EGFRvIII, TERT, TP53 | Uncontrolled proliferation, necrosis, metabolic rewiring | Tumor resection with intraoperative mapping; CRISPR knockout of EGFRvIII; IDH1-specific metabolic inhibition | AI-powered radiogenomics and subtype prediction (e.g., DeepGlioma) |
[210,211,212] | Epilepsy (non-lesional/refractory) | SCN1A, DEPDC5, PCDH19, KCNQ2 | Hyperexcitability, interneuron dysfunction, mTOR hyperactivation | Stereo-EEG guided laser ablation (LITT); CRISPR correction of SCN1A; responsive neurostimulation | AI fusion of iEEG + variant data for seizure zone prediction (e.g., EpileptorNet) |
[213,214] | Parkinson’s Disease | LRRK2, SNCA, GBA | Dopaminergic neuron degeneration, alpha-synuclein aggregation | Deep Brain Stimulation individualized by genotype; targeted SNCA knockdown | AI-based connectome mapping for electrode planning and symptom modeling |
[215,216] | Alzheimer’s Disease | APOE ε4, TREM2, PSEN1, BIN1 | Amyloid aggregation, tau propagation, synaptic failure | Focused ultrasound delivery of antibodies; future CRISPR APOE allele replacement | AI integration of PET/MRI and genomics for staging and target selection |
[217,218] | ALS | C9orf72, SOD1, TARDBP | Motor neuron degeneration, RNA toxicity, protein aggregates | Intrathecal delivery of ASOs or CRISPR constructs; exon skipping or repeat excision | AI stratification of progression trajectories and molecular timing of intervention |
[219,220] | Cortical Dysplasia/mTORopathies | MTOR, TSC1, TSC2, RHEB | Focal cortical thickening, epileptogenesis | Surgical resection or ablation of mTOR-active cortex; gene therapy suppression | AI segmentation of cortical lesions using MRI + genotype overlays |
Study/Author (Year) | Disease | Omics Approach | Key Insights | Clinical Implications | Novel Therapies | Challenges |
---|---|---|---|---|---|---|
[267,268,269] | Glioblastoma | Proteomics, transcriptomics | PI3K/AKT/mTOR pathway alterations | Guided development of combination therapies targeting genomic and protein-level vulnerabilities | mTOR inhibitors combined with EGFR inhibitors | Resistance due to clonal heterogeneity |
[264,270,271] | Epilepsy | Metabolomics, transcriptomics | Glycolysis and mitochondrial dysfunction in seizure zones | Development of metabolic modulators for seizure control | Anti-inflammatory metabolic modulators | Complex metabolic pathways |
[272,273,274] | ALS | Transcriptomics, epigenomics | Downstream effects of C9orf72 RNA toxicity | Informed design of ASO therapies addressing both primary and secondary mechanisms | RNA toxicity-focused ASOs | Long-term monitoring required |
[275,276,277] | SCAs | Transcriptomics, epigenomics | Histone hypoacetylation, mitochondrial dysfunction | Supported clinical trials of HDAC inhibitors and mitochondrial enhancers | Combination HDAC and mitochondrial therapies | Challenges in targeted delivery |
[278,279,280] | HSP | Metabolomics | Lipid metabolism alterations in corticospinal neurons | Targeted use of PPAR agonists and NAD+ precursors for neuroprotection | Microtubule-stabilizing compounds | Difficulties in axonal-targeted delivery |
[281,282,283] | Alzheimer’s Disease | Proteomics, metabolomics | Neuroinflammation and tau propagation | Anti-inflammatory and tau-focused therapies improving cognitive outcomes | Tau kinase inhibitors combined with microglial agonists | Lack of early biomarkers for intervention |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Șerban, M.; Toader, C.; Covache-Busuioc, R.-A. Precision Neuro-Oncology in Glioblastoma: AI-Guided CRISPR Editing and Real-Time Multi-Omics for Genomic Brain Surgery. Int. J. Mol. Sci. 2025, 26, 7364. https://doi.org/10.3390/ijms26157364
Șerban M, Toader C, Covache-Busuioc R-A. Precision Neuro-Oncology in Glioblastoma: AI-Guided CRISPR Editing and Real-Time Multi-Omics for Genomic Brain Surgery. International Journal of Molecular Sciences. 2025; 26(15):7364. https://doi.org/10.3390/ijms26157364
Chicago/Turabian StyleȘerban, Matei, Corneliu Toader, and Răzvan-Adrian Covache-Busuioc. 2025. "Precision Neuro-Oncology in Glioblastoma: AI-Guided CRISPR Editing and Real-Time Multi-Omics for Genomic Brain Surgery" International Journal of Molecular Sciences 26, no. 15: 7364. https://doi.org/10.3390/ijms26157364
APA StyleȘerban, M., Toader, C., & Covache-Busuioc, R.-A. (2025). Precision Neuro-Oncology in Glioblastoma: AI-Guided CRISPR Editing and Real-Time Multi-Omics for Genomic Brain Surgery. International Journal of Molecular Sciences, 26(15), 7364. https://doi.org/10.3390/ijms26157364