New Perspectives in the Management of Central Nervous System (CNS) Tumors

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Therapy".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 1662

Special Issue Editors


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Guest Editor
Department of Neuro-Oncology, University and City of Health and Science Hospital, Via Cherasco 15, 10126 Turin, Italy
Interests: brain metastases; leptomeningeal metastases; liquid biopsy; clinical trials

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Guest Editor
Division of Neuro-Oncology, Department Neuroscience, University and City of Health and Science Hospital, 10126 Turin, Italy
Interests: gliomas

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Guest Editor
Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy
Interests: brain tumors; spinal surgery; deep brain stimulation
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Special Issue Information

Dear Colleagues,

Neuro-oncology is rapidly growing, posing new challenges in terms of diagnosis and therapeutic options.

The WHO Classification of Central Nervous System Tumors of 2021 identified different entities based on the integration of histological and molecular biomarkers, aiming to select patients for tailoring treatments and identify subgroups with different outcomes. Moreover, the WHO Classification recognizes some rare/ultra-rare entities, where management in clinical settings is based only on case-reports or small retrospective cohorts with limited evidence-based significance.

Surgery is the mainstay treatment for most brain tumors to achieve a histological diagnosis and reduce the burden of disease and neurological symptoms. However, not all patients are fit for surgical resection; thus, different intraoperative techniques should be used to improve the extent of resection and the neurological outcome of patients, alongside the employment of prognostic scales which are increasingly being used to select patients for surgery or adjuvant treatments. Furthermore, novel medical devices are under evaluation to improve the penetration of compounds through the blood–brain barrier in patients with glioblastoma and brain metastases.

For those patients in whom surgery is not feasible, the investigation of novel tools, including spectroscopy and radiomics, is underway. Similarly, the role of CSF liquid biopsy in primary brain tumors, as well as brain and leptomeningeal metastases, is considered a hot topic. In this regard, the integration of CSF liquid biopsies in the diagnostic flowchart may lead to several advantages in the management of CNS metastases, including diagnosis in cases of negative or “atypical” CSF cytology, the monitoring of tumor response following targeted therapy or immunotherapy, the early detection of CNS recurrence and the development of resistant mutations, the early identification of subgroups of patients with a higher risk of CNS recurrence, and the correlation of CNS burden with survival.

Finally, novel targeted therapies and immunotherapies have changed the survival of patients with CNS tumors. In primary brain tumors, patients with IDH mutant low-grade gliomas have benefitted from the IDH inhibitor vorasidenib, while glioblastomas, ependymomas, and many other brain tumors still lack targeted therapies. Similarly, immunotherapy confers modest benefit in such entities; therefore, many efforts are underway to investigate potential druggable pathways or the microenvironment in preclinical settings. Conversely, targeted therapies, including small-molecule and/or antibody drug conjugated ones, have prolonged the intracranial response, progression free survival, and overall survival of patients with metastatic CNS and different solid tumors, especially in non-small-cell lung cancer and breast cancer. However, further insights are required to improve the outcomes, find the optimal timing and combinations of these compounds (alone or in association with radiotherapy or systemic therapies), and impact patients’ quality of life.

This Special Issue welcomes both original articles and reviews on new pathways in the growth of primary or secondary CNS tumors with potential impacts of translational research and applications in clinical settings, surgery techniques, and outcomes in such populations, alongside registry/prospective real-life studies or clinical trials investigating the impact of drugs. Furthermore, studies on neuroradiological tools or liquid biopsies for diagnosing and monitoring CNS diseases are strongly encouraged. Post hoc analyses or retrospective studies evaluating the predictive and prognostic role of clinical and molecular markers in primary brain tumors or brain and leptomeningeal metastases will also be considered. Last, reviews or small cohorts with deep analyses of correlations between histology, molecular features, radiological findings, clinical course, and treatment of CNS ultra-rare entities could also be an interesting topic for this Special Issue.

Dr. Alessia Pellerino
Dr. Francesco Bruno
Dr. Teresa Somma
Guest Editors

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Keywords

  • gliomas
  • brain metastases
  • leptomeningeal metastases
  • liquid biopsy
  • neuroradiological tools
  • brain surgery
  • targeted therapy
  • immunotherapy
  • clinical trials
  • molecular factors

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Published Papers (2 papers)

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Research

12 pages, 7608 KiB  
Article
Proton Craniospinal Irradiation for Patients with Solid Tumor Leptomeningeal Disease: Real-World Feasibility, Toxicity, and Outcome Analysis
by Omer Gal, Alonso La Rosa, Matthew D. Hall, Robert H. Press, Zachary Fellows, Andrew J. Wroe, Alonso N. Gutierrez, Yazmin Odia, Minesh P. Mehta and Rupesh Kotecha
Cancers 2025, 17(6), 1046; https://doi.org/10.3390/cancers17061046 - 20 Mar 2025
Viewed by 423
Abstract
Leptomeningeal disease (LMD) is a devastating clinical scenario in patients with metastatic cancer [...] Full article
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17 pages, 2164 KiB  
Article
Development of Clinical-Radiomics Nomogram for Predicting Post-Surgery Functional Improvement in High-Grade Glioma Patients
by Tamara Ius, Maurizio Polano, Michele Dal Bo, Daniele Bagatto, Valeria Bertani, Davide Gentilini, Giuseppe Lombardi, Serena D’agostini, Miran Skrap and Giuseppe Toffoli
Cancers 2025, 17(5), 758; https://doi.org/10.3390/cancers17050758 - 23 Feb 2025
Viewed by 662
Abstract
Introduction: Glioma Grade 4 (GG4) tumors, which include both IDH-mutated and IDH wild-type astrocytomas, are the most prevalent and aggressive form of primary brain tumor. Radiomics is gaining ground in neuro-oncology. The integration of this data into machine learning models has the potential [...] Read more.
Introduction: Glioma Grade 4 (GG4) tumors, which include both IDH-mutated and IDH wild-type astrocytomas, are the most prevalent and aggressive form of primary brain tumor. Radiomics is gaining ground in neuro-oncology. The integration of this data into machine learning models has the potential to improve the accuracy of prognostic models for GG4 patients. Karnofsky Performance Status (KPS), an established preoperative prognostic factor for survival, is commonly used in these patients. In this study, we developed a nomogram to identify patients with improved functional performance as indicated by an increase in KPS after surgery by analyzing radiomic features from preoperative 3D MRI scans. Methods: Quantitative imaging features were extracted from the -3D T1 GRE sequence of 157 patients from a single center and were used to develop the machine learning (ML) model. To improve applicability and create a nomogram, multivariable logistic regression analysis was performed to build a model incorporating clinical characteristics and radiomics features. Results: We labeled 55 cases in which KPS was improved after surgery (35%, KPS-flag = 1). The resulting model was evaluated according to test series results. The best model was obtained by XGBoost using the features extracted by pyradiomics, with a Matthew coefficient score (MCC) of 0.339 (95% CI: 0.330–0.3483) in cross-validation. The out-of-sample evaluation on the test set yielded an MCC of 0.302. A nomogram evaluating the improvement of KPS post-surgery was built based on statistically significant variables from multivariate logistic regression including clinical and radiomics data (c-index = 0.760, test set). Conclusions: MRI radiomic analysis represents a powerful tool to predict postoperative functional outcomes, as evaluated by KPS. Full article
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