Search Results (93)

Glioblastoma (GBM), the most common primary malignant brain tumor in adults, has a median survival of 14–15 months despite aggressive treatment. Monitoring relies on MRI, but differentiating tumor progression from pseudo-progression or radiation necrosis remains difficult. Plasma extracellular vesicles (EVs) are emerging as promising non-invasive biomarkers due to their molecular cargos and accessibility. This review evaluates studies that specifically isolated plasma EVs for molecular profiling in GBM diagnosis and monitoring. Biomarkers (miRNA, RNA, DNA, proteins), EV characterization methods, and advancements in enriching tumor-derived EV subpopulations and assessing their diagnostic and prognostic potential are highlighted. Plasma EVs carry diverse cargos, including miRNAs (e.g., miR-21, miR-15b-3p), mRNAs (e.g., EGFRvIII), circRNAs, and proteins (e.g., CD44, GFAP). Composite molecular signatures have achieved sensitivities of 87–100% and specificities of 73–100% for GBM diagnosis. Tumor-derived EVs, enriched using techniques like SEC-CD44 immunoprecipitation, microfluidic platforms, or 5-ALA-induced PpIX fluorescence, enhance biomarker detection. Non-tumor-derived EVs may also reflect GBM’s systemic effects. Challenges include EV heterogeneity, non-EV contamination, and variable biomarker expression across studies. Plasma-EV-based liquid biopsies offer significant potential for GBM monitoring, with advanced enrichment methods improving tumor-specific biomarker detection. Standardizing isolation protocols and validating biomarkers in larger cohorts are critical for clinical translation. Full article

Background: Assessing the efficacy of combination therapies in hepatocellular carcinoma (HCC) requires both accurate tumor delineation and biologically validated prediction of therapeutic response. Conventional MRI-based criteria, which rely primarily on tumor size, often fail to capture treatment efficacy due to tumor heterogeneity and pseudo-progression. This study aimed to develop and biologically validate a multi-task deep learning model that simultaneously segments HCC tumors and predicts treatment outcomes using clinically relevant multi-parametric MRI in a preclinical rat model. Methods: Orthotopic HCC tumors were induced in rats assigned to Control, Sorafenib, NK cell immunotherapy, and combination treatment groups. Multi-parametric MRI (T1w, T2w, and contrast enhanced MRI) scans were performed weekly. We developed a U-Net++ architecture incorporating a pre-trained EfficientNet-B0 encoder, enabling simultaneous segmentation and classification tasks. Model performance was evaluated through Dice coefficients and area under the receiver operator characteristic curve (AUROC) scores, and histological validation (H&E for viability, TUNEL for apoptosis) assessed biological correlations using linear regression analysis. Results: The multi-task model achieved precise tumor segmentation (Dice coefficient = 0.92, intersection over union (IoU) = 0.86) and reliably predicted therapeutic outcomes (AUROC = 0.97, accuracy = 85.0%). MRI-derived deep learning biomarkers correlated strongly with histological markers of tumor viability and apoptosis (root mean squared error (RMSE): viability = 0.1069, apoptosis = 0.013), demonstrating that the model captures biologically relevant imaging features associated with treatment-induced histological changes. Conclusions: This multi-task deep learning framework, validated against histology, demonstrates the feasibility of leveraging widely available clinical MRI sequences for non-invasive monitoring of therapeutic response in HCC. By linking imaging features with underlying tumor biology, the model highlights a translational pathway toward more clinically applicable strategies for evaluating treatment efficacy. Full article

Background/Objectives: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide. Immune checkpoint inhibitors (ICIs) have transformed treatment paradigms, but assessing response remains challenging due to atypical patterns such as pseudoprogression, hyperprogression and dissociated response. Conventional evaluation criteria, such as RECIST 1.1, may not fully capture these patterns, leading to potential misclassification and premature therapy discontinuation. This review explores the role of 18F-FDG PET/CT in assessing immunotherapy response and highlights novel imaging criteria to enhance clinical decision-making. Methods: A systematic literature review was conducted across PubMed, Web of Science, Scopus, and Cochrane Library, selecting relevant studies published between 2013 and 2024. The review focuses on the strengths and limitations of PET-based imaging in monitoring NSCLC immunotherapy outcomes. Specific attention was given to evolving evaluation frameworks, including iRECIST, PERCIST, imPERCIST, and iPERCIST, as well as metabolic biomarkers such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Results: Compared with anatomical-based assessment, metabolic imaging using 18F-FDG PET/CT may offer deeper insights into tumor behavior during immunotherapy. PET-derived parameters seem to improve the detection of immune-related response patterns, providing a more refined approach to differentiate true progression from pseudoprogression. Emerging evidence indicates that metabolic biomarkers such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) could serve as useful predictors of therapeutic efficacy and support treatment adaptation. Nevertheless, current findings are mainly based on small, heterogeneous, and predominantly retrospective studies, with variable PET timing and threshold definitions that limit the generalizability of these results. Conclusions: 18F-FDG PET/CT represents a promising complementary tool for assessing immunotherapy response in NSCLC. Its integration with advanced imaging criteria and metabolic tumor biomarkers may enhance response evaluation and assist clinical decision-making. Nonetheless, the current evidence remains preliminary, and further standardization and large prospective validation studies are required before its routine implementation in clinical practice. Full article

Background: Deficient mismatch repair rectal cancer represents approximately 10% of rectal malignancies and demonstrates exceptional responsiveness to immune checkpoint inhibitors, achieving unprecedented complete response rates approaching 100%. This creates a novel clinical dilemma: should patients achieving complete response undergo standard surgical resection or pursue organ preservation through watch-and-wait management? Methods: We conducted a comprehensive literature review of clinical trials and retrospective studies published through 2025, focusing on response assessment strategies, decision-making frameworks, oncological outcomes, and quality of life assessments. Results: Landmark studies demonstrated remarkable efficacy with dostarlimab achieving 100% clinical complete response, while surgical cohorts achieved 68–92% pathological complete response rates. Response assessment challenges included pseudoprogression and pseudoresidue phenomena that complicated conventional imaging interpretation and required specialised multimodal evaluation protocols. Comparative analyses suggest equivalent oncological outcomes between surgical and non-surgical approaches in complete responders, achieving 100% disease-free survival at 2–3 years across multiple studies. The watch-and-wait approach offered significant advantages by preserving organ integrity and avoiding surgical morbidity, including permanent colostomy (15.4%) and perioperative complications (19.3%). Conversely, surgical management provided distinct benefits through definitive tissue confirmation and anxiety relief from intensive surveillance requirements and potential recurrence concerns. Conclusions: The surgery versus watch-and-wait dilemma represents a choice between equally effective oncological approaches with different quality of life implications. Evidence supports individualised decision-making weighing functional preservation benefits against patient preferences and institutional capabilities in this evolving therapeutic landscape. Full article

Glioblastoma multiforme (GBM), the most aggressive primary brain tumor in adults, has a poor prognosis due to rapid recurrence and treatment resistance. This review examines the evolution of radiotherapy (RT) for GBM management, from whole-brain RT to modern techniques like intensity-modulated RT (IMRT) and volumetric modulated arc therapy (VMAT), guided by 2023 European Society for Radiotherapy and Oncology (ESTRO)-European Association of Neuro-Oncology (EANO) and 2025 American Society for Radiation Oncology (ASTRO) recommendations. The standard Stupp protocol (60 Gy/30 fractions with temozolomide [TMZ]) improves overall survival (OS) to 14.6 months, with greater benefits in O6-methylguanine-DNA methyltransferase (MGMT)-methylated tumors (21.7 months). Tumor Treating Fields (TTFields) extend median overall survival (mOS) to 31.6 months in MGMT-methylated patients and 20.9 months overall in supratentorial GBM (EF-14 trial). However, 80–90% of recurrences occur within 2 cm of the irradiated field due to tumor infiltration and radioresistance driven by epidermal growth factor receptor (EGFR) amplification, phosphatase and tensin homolog (PTEN) mutations, cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) deletions, tumor hypoxia, and tumor stem cells. Pseudoprogression, distinguished using Response Assessment in Neuro-Oncology (RANO) criteria and positron emission tomography (PET), complicates response evaluation. Targeted therapies (e.g., bevacizumab; PARP inhibitors) and immunotherapies (e.g., pembrolizumab; oncolytic viruses), alongside advanced imaging (multiparametric magnetic resonance imaging [MRI], amino acid PET), support personalized RT. Ongoing trials evaluating reirradiation, hypofractionation, stereotactic radiosurgery, neoadjuvant therapies, proton therapy (PT), boron neutron capture therapy (BNCT), and AI-driven planning aim to enhance efficacy for GBM IDH-wildtype, but phase III trials are needed to improve survival and quality of life. Full article

Background: Pseudoprogression is known to occur after immune-checkpoint inhibitor (ICI) therapy in brain metastasis and can complicate clinical decision-making. Still, its incidence, timing, and clinical presentation remain unclear. A retrospective cohort study in melanoma and non-small cell lung cancer brain metastasis patients was conducted to address this. Materials and Methods: Brain metastasis patients showing progression on MRI according to response assessment in neuro-oncology brain metastases criteria after starting ICI therapy were included, irrespective of prior irradiation. Lesions were classified as tumour progression (TP) or pseudoprogression based on three-month radiological follow-up or histopathology. TP was assigned if progression was again shown at three months. Pseudoprogression was assigned if lesions showed stability, partial, or complete response at three months. ‘Non-classified’ lesions were those with new or changed treatment during follow-up. Results: A cohort of 98 patients with 233 lesions was included over a 13-year period; 170 lesions were considered non-classified, and 41 and 22 lesions were classified as TP and pseudoprogression respectively. This resulted in a lesion- and patient-specific incidence for pseudoprogression of 9.4% and 17.3% respectively. Due to the large number of lesions that could not be classified, as is the case in clinical practice, the reported incidence in this study is likely an underestimation and can be seen as a ‘minimum’ incidence rate. Ten pseudoprogression (45.5%) and 13 (31.7%) TP lesions were previously irradiated. Pseudoprogression occurred at a median of 2.7 months after starting ICI therapy. The only clinical feature distinguishing patients with TP from pseudoprogression was that TP patients were more likely to need dexamethasone for neurological symptoms. Conclusions: Pseudoprogression has a lesion-specific incidence rate of at least 9.4% and occurs at a median of 2.7 months after starting ICI therapy. Severe neurological symptoms requiring dexamethasone may be a clinical feature typical for TP. Full article

Over recent decades, significant advancements have been made in the treatment and imaging of gliomas. Conventional imaging techniques, such as MRI and CT, play critical roles in glioma diagnosis and treatment but often fail to distinguish between tumor pseudoprogression (Psp) and radiation necrosis (RN) versus true progression (TP). Emerging fields like radiomics and radiogenomics are addressing these challenges by extracting quantitative features from medical images and correlating them with genomic data, respectively. This article will discuss several studies that show how radiomic features (RFs) can aid in better patient stratification and prognosis. Radiogenomics, particularly in predicting biomarkers such as MGMT promoter methylation and 1p/19q codeletion, shows potential in non-invasive diagnostics. Radiomics also offers tools for predicting tumor recurrence (rBT), essential for treatment management. Further research is needed to standardize these methods and integrate them into clinical practice. This review underscores radiomics and radiogenomics’ potential to revolutionize glioma management, marking a significant shift towards precision neuro-oncology. Full article

Background: Pediatric high-grade glioma (pHGG) is a highly aggressive cancer with unique biology distinct from adult high-grade glioma, limiting the effectiveness of standard treatment protocols derived from adult research. Objective: The purpose of this report is to present preliminary results from an ongoing pilot study integrating spectroscopic magnetic resonance imaging (sMRI) to guide proton beam therapy and longitudinal imaging analysis in pediatric patients with high-grade glioma (pHGG). Methods: Thirteen pediatric patients under 21 years old with supratentorial WHO grade III-IV glioma underwent baseline and serial whole-brain spectroscopic MRI alongside standard structural MRIs. Radiation targets were defined using T1-weighted contrast enhanced, T2-FLAIR, and Cho/NAA ≥ 2X maps. Longitudinal analyses included voxel-level metabolic change maps and spatial overlap metrics comparing pre-proton therapy and post-. Results: Six patients had sufficient longitudinal data; five received sMRI-guided PBT. Significant positive correlation (R² = 0.89, p < 0.0001) was observed between T2-FLAIR and Cho/NAA ≥ 2X volumes. Voxel-level difference maps of Cho/NAA and Choline revealed dynamic metabolic changes across follow-up scans. Analyzing Cho/NAA and Cho changes over time allowed differentiation between true progression and pseudoprogression, which conventional MRI alone struggles to achieve. Conclusions: Longitudinal sMRI enhanced metabolic tracking in pHGG, detects early tumor changes, and refines RT targeting beyond structural imaging. This first in-kind study highlights the potential of sMRI biomarkers in tracking treatment effects and emphasizes the complementary roles of metabolic and radiographic metrics in evaluating therapy response in pHGG. Full article

Background and Objectives: This study aimed to investigate the prognostic value of the hemoglobin–albumin–lymphocyte–platelet (HALP) score—a marker reflecting both inflammatory and nutritional status—in patients with metastatic non-small cell lung cancer (NSCLC) undergoing immunotherapy. We also sought to determine whether dynamic changes in the HALP score during treatment could predict therapeutic success and help distinguish between pseudoprogression and hyperprogression. Materials and Methods: A retrospective analysis was conducted on 160 patients diagnosed with metastatic NSCLC and treated with immunotherapy at the Ankara Atatürk Sanatorium Training and Research Hospital. Chemotherapy regimens, metastatic sites, baseline and third-month hemograms and biochemistry parameters, and survival data were recorded. Survival outcomes were analyzed using the Kaplan–Meier method with the log-rank test and the Cox proportional hazards regression model using IBM SPSS Statistics. Results: The median overall survival (OS) for the entire cohort was 15 months (95% CI: 11.88–18.12). HALP1 score (p = 0.048), HALP2 score (p = 0.026), and hyperprogression (p < 0.001) were statistically significant predictors of OS. Regarding progression-free survival (PFS), the HALP2 score (p = 0.031), line of immunotherapy (p = 0.046), and hyperprogression (p < 0.001) were found to be significant. When comparing patients with increasing versus decreasing HALP scores, those with increasing HALP scores demonstrated significantly better outcomes for both OS (p = 0.034) and PFS (p = 0.007). Conclusions: In patients with metastatic NSCLC undergoing immunotherapy, the HALP score and its dynamic alterations during treatment appear to be non-invasive, easily calculable biomarkers that may predict both OS and PFS. Full article

Background/Objectives: Immunotherapy is an essential part of metastatic bladder cancer treatment. Our main objective was to study the prognostic value of FDG-PET/CT in early assessment of response to Pembrolizumab in metastatic bladder cancers using PERCIST5, imPERCIST5, and PERCIMT criteria. Methods: A total of 42 patients were evaluated with FDG-PET/CT at baseline and after 3–4 cycles of Pembrolizumab. Treatment response was blindly assessed with PERCIST5, imPERCIST5, and PERCIMT. Imaging and clinical data were collected. Progression was defined clinically using oncologist reports. Results: A total of 37 patients were evaluable with the PERCIST5 and imPERCIST5 criteria and included in the analysis. Median disease-specific progression-free survival (PFS) and overall survival (OS) were 152 and 363 days, respectively. All response criteria were significantly associated with PFS. When response was dichotomized in responders versus non-responders all scores were significantly associated with OS. When response was dichotomized in progressors versus non-progressors, only PERCIST5 (hazard ratio (HR) 2.2) and PERCIMT (HR 2.6) were significantly associated with OS, while imPERCIST was not (HR 1.6). Two patients had pseudoprogression (5%), both being adequately classified as non-progressors with PERCIMT criteria. Conclusions: Early response to immunotherapy as assessed with FDG-PET is a strong prognostic factor in bladder cancer patients, especially using the PERCIST5 or PERCIMT criteria. The latter seems clinically useful as it is simple to perform and its specific definition of metabolic progression correctly ruled-out patients with significant clinical benefit of Pembrolizumab in our study. Full article

Glioblastoma (GBM) is the most prevalent and aggressive primary central nervous system (CNS) tumor in adults. GBMs exhibit genetic and epigenetic heterogeneity, posing difficulties in surveillance and being associated with high rates of recurrence and mortality. Nevertheless, due to the high infiltrating ability of glioblastoma cells, and regardless of the considerable progress made in radiotherapeutic, chemotherapeutic, and surgical protocols, the treatment of GBM is still inefficient. Conventional diagnostic approaches, such as neuroimaging techniques and tissue biopsies, which are invasive maneuvers, present certain challenges and limitations in providing real-time information, and are incapable of differentiating pseudo-progression related to treatment from real tumor progression. Liquid biopsy, the analysis of biomarkers such as nucleic acids (DNA/RNA), circulating tumor cells (CTCs), extracellular vesicles (EVs), or tumor-educated platelets (TEPs) that are present in body fluids, provides a minimally invasive and dynamic method of diagnosis and continuous monitoring for GBM. It represents a new preferred approach that enables a superior manner to obtain data on possible tumor risk, prognosis, and recurrence assessment. This article is a literature review that aims to provide updated information about GBM biomarkers in body fluids and to analyze their clinical efficiency. Full article

Background/Objectives: Tumor interactions with their surrounding environment, particularly in the case of peritumoral edema, play a significant role in tumor behavior and progression. While most studies focus on the radiomic features of the tumor core, this work investigates whether peritumoral edema exhibits distinct radiomic fingerprints specific to glioma (GLI), meningioma (MEN), and metastasis (MET). By analyzing these patterns, we aim to deepen our understanding of the tumor microenvironment’s role in tumor development and progression. Methods: Radiomic features were extracted from peritumoral edema regions in T1-weighted (T1), post-gadolinium T1-weighted (T1-c), T2-weighted (T2), and T2 Fluid-Attenuated Inversion Recovery (T2-FLAIR) sequences. Three classification tasks using those features were then conducted: differentiating between Low-Grade Glioma (LGG) and High-Grade Glioma (HGG), distinguishing GLI from MET and MEN, and examining all four tumor types, i.e., LGG, HGG, MET, and MEN, to observe how tumor-specific signatures manifest in peritumoral edema. Model performance was assessed using balanced accuracy derived from 10-fold cross-validation. Results: The radiomic fingerprints specific to tumor types were more distinct in the peritumoral regions of T1-c images compared to other modalities. The best models, utilizing all features extracted from the peritumoral regions of T1-c images, achieved balanced accuracies of 0.86, 0.81, and 0.76 for the LGG-HGG, GLI-MET-MEN, and LGG-HGG-MET-MEN tasks, respectively. Conclusions: This study demonstrates that peritumoral edema, as characterized by radiomic features extracted from MRIs, contains fingerprints specific to tumor type, providing a non-invasive approach to understanding tumor-brain interactions. The results of this study hold the potential for predicting recurrence, distinguishing progression from pseudo-progression, and assessing treatment-induced changes, particularly in gliomas. Full article

Purpose: Early treatment response assessments are crucial, and the results are known to better correlate with prognosis and survival outcomes. The present study was conducted to differentiate true progression (TP) from pseudoprogression (PsP) in long-term-surviving glioblastoma patients using our previously established multiparametric MRI-based predictive model, as well as to identify clinical factors impacting survival outcomes in these patients. Methods: We report six patients with glioblastoma that had an overall survival longer than 5 years. When tumor specimens were available from second-stage surgery, histopathological analyses were used to classify between TP (>25% characteristics of malignant neoplasms; n = 2) and PsP (<25% characteristics of malignant neoplasms; n = 2). In the absence of histopathology, modified RANO criteria were assessed to determine the presence of TP (n = 1) or PsP (n = 1). The predictive probabilities (PPs) of tumor progression were measured from contrast-enhancing regions of neoplasms using a multiparametric MRI-based prediction model. Subsequently, these PP values were used to define each lesion as TP (PP ≥ 50%) or PsP (PP < 50%). Additionally, detailed clinical information was collected. Results: Our predictive model correctly identified all patients with TP (n = 3) and PsP (n = 3) cases, reflecting a significant concordance between histopathology/modified RANO criteria and PP values. The overall survival varied from 5.1 to 12.3 years. Five of the six glioblastoma patients were MGMT promoter methylated. All patients were female, with a median age of 56 years. Moreover, all six patients had a good functional status (KPS ≥ 70), underwent near-total/complete resection, and received alternative therapies. Conclusions: Multiparametric MRI can aid in assessing treatment response in long-term-surviving glioblastoma patients. Full article

Advances in neuro-oncology have transformed the diagnosis and management of brain tumors, which are among the most challenging malignancies due to their high mortality rates and complex neurological effects. Despite advancements in surgery and chemoradiotherapy, the prognosis for glioblastoma multiforme (GBM) and brain metastases remains poor, underscoring the need for innovative diagnostic strategies. This review highlights recent advancements in imaging techniques, liquid biopsies, and artificial intelligence (AI) applications addressing current diagnostic challenges. Advanced imaging techniques, including diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS), improve the differentiation of tumor progression from treatment-related changes. Additionally, novel positron emission tomography (PET) radiotracers, such as ¹⁸F-fluoropivalate, ¹⁸F-fluoroethyltyrosine, and ¹⁸F-fluluciclovine, facilitate metabolic profiling of high-grade gliomas. Liquid biopsy, a minimally invasive technique, enables real-time monitoring of biomarkers such as circulating tumor DNA (ctDNA), extracellular vesicles (EVs), circulating tumor cells (CTCs), and tumor-educated platelets (TEPs), enhancing diagnostic precision. AI-driven algorithms, such as convolutional neural networks, integrate diagnostic tools to improve accuracy, reduce interobserver variability, and accelerate clinical decision-making. These innovations advance personalized neuro-oncological care, offering new opportunities to improve outcomes for patients with central nervous system tumors. We advocate for future research integrating these tools into clinical workflows, addressing accessibility challenges, and standardizing methodologies to ensure broad applicability in neuro-oncology. Full article

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults, with a median overall survival (OS) of 15–18 months despite standard treatments. Approximately 8% of GBM cases exhibit genomic alterations in fibroblast growth factor receptors (FGFRs), particularly FGFR1 and FGFR3. Next-generation sequencing techniques have identified various FGFR3 fusions in GBM. This report presents a novel FGFR3 fusion with fatty acid synthase (FASN) in a 41-year-old male diagnosed with GBM. The patient presented with a persistent headache, and imaging revealed a right frontal lobe lesion. Surgical resection and subsequent histopathology confirmed GBM. Initial NGS analysis showed no mutations in the IDH1, IDH2 or H3F3 genes, but revealed a TERT promoter mutation and CDKN2A/2B and PTEN deletions. Postoperative treatment included radiotherapy and temozolomide. Despite initial management, recurrence occurred four months post-diagnosis, confirmed by MRI and histology. A second surgery identified a novel FGFR3-FASN fusion, alongside increased Ki67 expression. The recurrence was managed with regorafenib and bevacizumab, though complications like hand–foot syndrome and radiation necrosis arose. Despite initial improvement, the patient died 15 months after diagnosis. This case underscores the importance of understanding GBM’s molecular landscape for effective treatment strategies. The novel FGFR3-FASN fusion suggests potential implications for GBM recurrence and lipid metabolism. Further studies are warranted to explore FGFR3-FASN’s role in GBM and its therapeutic targeting. Full article