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Despite some evidence of a possible link between epileptogenesis and tumorigenesis in glioblastoma, the prognostic value of epilepsy at presentation has been debated over the years. We performed a systematic review and meta-analysis to summarize all published data evaluating the prognostic significance of seizures as a presenting manifestation of glioblastoma. A comprehensive search of five databases from inception to December 2023 was conducted. Included studies underwent meta-analysis, with subgroup analyses performed to identify sources of heterogeneity. Fifteen studies were included in the analysis. Seizures were considered a favorable prognostic factor in seven studies, while eight studies found no differences in overall survival between patients with seizures and those with other presenting symptoms. Eleven studies were included in the meta-analysis. The overall pooled analysis indicated a potentially favorable prognostic impact of seizures at the clinical onset of glioblastoma (HR 0.73; 95% CI 0.61–0.87). However, subgroup analysis within studies focusing on IDH-wild type cases showed no discernible impact from preoperative seizures. Retrospective design, poor quality in reporting results, and heterogeneity in tumor characteristics and therapies are the main limitations of included studies. Future prospective studies on large, homogeneous cohorts of patients with IDH-wild type glioblastoma are warranted. Overall, these findings suggest that while seizures may hold some prognostic value, further research is essential to clarify their role. Understanding the true prognostic role of seizures at clinical onset may enhance our ability to predict patient outcomes and guide clinical decision-making.

Gliomas are the most common malignant primary brain tumors in adults, yet their prognosis remains poor despite advances in treatment. Radiotherapy is a cornerstone of glioma management; however, its efficacy is often limited by tumor radioresistance. Understanding the molecular mechanisms underlying this resistance is critical for improving therapeutic outcomes. Recent research has identified key biomarkers and molecular pathways, including immune modulation, hypoxia, cell cycle regulation, apoptosis, and stress responses that influence tumor radiosensitivity and prognosis. This review explores predictive molecular biomarkers for radiosensitivity in gliomas, highlighting the latest advancements in preclinical studies and available clinical data, as well as their potential to inform future personalized radiotherapy strategies. Incorporating these biomarkers into clinical decision-making may facilitate patient stratification, guide combined modality approaches, and improve treatment precision and outcomes in glioma care.

Background Craniopharyngioma consistently represents one of the most challenging diseases encountered by neurosurgeons and has a high recurrence rate. Currently, there is still no consensus on the surgical approach for recurrent craniopharyngioma. The purpose of this study was to compare the surgical outcomes and prognoses of endoscopic endonasal surgery (EES) with those of transcranial surgery (TCS) for recurrent craniopharyngioma. Methods A retrospective study was conducted on patients with craniopharyngioma who underwent surgical resection at Tangdu Hospital, Air Force Medical University, between January 2013 and December 2023. Patients who did not undergo surgery or who underwent primary surgery were excluded. Patients were separated into two groups based on the surgical approach. Specifically, one group underwent EES, and the other cohort underwent TCS. Patient demographic data, presenting symptoms, postoperative complications, and prognostic data were collected and analyzed. Student’s t test and the chi-square test were used to evaluate differences in patient demographics, tumor characteristics, and surgical outcomes between the two cohorts. A Kaplan-Meier curve was used to compare progression-free survival (PFS) and overall survival (OS) after reoperation between the two groups. Results A total of 399 patients who were diagnosed with craniopharyngioma were identified, 91 of whom had recurrent craniopharyngioma and met the inclusion criteria. Among these patients, 57 patients underwent TCS, whereas 34 patients received EES. Postoperatively, comparisons of the extent of tumor resection, intraoperative blood transfusion volume, postoperative hospital stay length, incidence of diabetes insipidus, and in-hospital mortality rate revealed no statistically significant differences. However, the EES group exhibited a greater incidence of postoperative cerebrospinal fluid (CSF) leakage than did the TCS group (14.71% vs. 0%,respectively; p  = 0.006). Conversely, the EES group exhibited a greater rate of improvement in visual field defects (82.35% vs. 42.11%, p  = 0.001), a shorter operative time (3.99 ± 1.97 hours vs. 4.86 ± 1.85 hours, p  = 0.037), and a lower incidence of new onset of hypopituitarism (14.71% vs. 36.84%, p  = 0.031). The average follow-up duration was 33.5 months (ranging from 4 to 51 months). There were no statistically significant differences observed in the PFS or OS between the TCS and EES groups. Conclusions Both EES and TCS are effective methods for the resection of recurrent craniopharyngioma. Although the degree of resection, PFS and OS after the second surgery were comparable between the two surgical approaches, the EES group demonstrated several advantages compared with the TCS group, although a high risk of CSF leakage was noted with EES. Therefore, the endoscopic transnasal approach is a safe and effective surgical approach for the removal of recurrent craniopharyngioma, achieving equivalent resection outcomes while minimizing complications.

Background Accurate diagnosis and therapeutic response to secondary central nervous system lymphoma (SCNSL) are challenges that need to be addressed. We assessed the value of cerebrospinal fluid (CSF) cytokine levels for diagnosis and post–therapeutic prognosis in patients with SCNSL. Methods This retrospective study included 234 patients with non-Hodgkin lymphoma (NHL), including the SCNSL group ( n  = 57) and the non-SCNSL group ( n  = 177). The Mann–Whitney U test was used to compare the cytokine profiles between SCNSL and non-SCNSL group. Receiver operating characteristic curve was used to determine the diagnostic ability of CSF cytokine levels for SCNSL. The predictive value of CSF cytokine concentrations for progression free survival of patients with SCNSL was evaluated using a log-rank test. Results CSF IL-6 and IL-10 levels in SCNSL group were significantly elevated compared with those in the other two groups. ROC curve showed that the cutoff values of IL-6 and IL-10 in CSF were 10.13 pg/ml and 7.82pg/ml, which yielded the diagnostic sensitivity were 62.34% and 76.23%, specificity were 87.57% and 88.31%, respectively. Furthermore, combining CSF IL-6 and IL-10 levels significantly improved the diagnostic efficacy. CSF IL-6 and IL-10 levels in SCNSL patients in complete remission under chemotherapy were significantly reduced. In addition, poor progression free survival (PFS) in patients with SCNSL was related to increased CSF IL-10 levels at diagnosis, but not with increased CSF IL-6 levels. Conclusion CSF IL-6 and IL-10 levels are promising biomarkers for diagnosis and predictors of response for SCNSL.

Background Intracranial radiation in combination with EGFR targeted therapy demonstrated signals of superiority to EGFR targeted therapy alone based on several observational studies. The timing based on specific criteria is not clear, and we evaluated the efficacy of intervention timing of craniocerebral radiotherapy (RT) combined with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) on prognosis of patients with EGFR mutant lung adenocarcinoma complicated with brain metastasis. Methods In total, 603 patients with advanced non-small cell lung cancer (NSCLC) harboring EGFR mutations were enrolled in this retrospective study between March 2008—September 2023. Propensity score matching (PSM) was conducted to adjust for demographic and clinical covariates and to compare survival differences between the EGFR-TKI plus craniocerebral RT group and the EGFR-TKI only group. Patients were divided into upfront group and delayed group according to timing of craniocerebral RT interventions and analyses. Graded prognostic assessment for lung cancer using molecular markers (Lung molGPA), overall survival (OS), and intracranial progression-free survival (iPFS) were calculated. Kaplan–Meier was used to compare iPFS and OS in different groups. Results In our study, the median overall survival (OS) was 48.8 months, and the median intracranial progression-free survival (iPFS) was 14.2 months before PSM. After PSM, the median OS of EGFR-TKIs + craniocerebral RT group and EGFR-TKI only group was 52.0 months and 43.2 months, respectively ( p  = 0.0363). In total of 417 patients who underwent craniocerebral RT, were enrolled subsequently and divided into groups A (Lung-molGPA 1–2) and B (Lung-molGPA 2.5–4) according to the lung-molGPA score. For group A, the median OS of upfront-group and delay-group was 27 and 42.1 months, respectively ( p  = 0.0019). For patients in group B, there was no significant difference in OS between the two groups ( p  = 0.9642). Conclusion For patients with craniocerebral metastases of EGFR-mutant lung adenocarcinoma, combination of EGFR-TKIs and craniocerebral RT confers enhanced survival benefits. In patients with lower Lung-molGPA scores, delayed administration of craniocerebral RT is recommended to improve both iPFS and OS.

The purpose of the current study was to analyze and validate the existing gap in knowledge, by conducting a differential expression analysis and validation of NEK6, NEK7, and NEK9 in breast, cervical, and glioblastoma cancer and targeting these proteins through development of novel site specific inhibitor with favorable pharmacokinetic and safety profile, using open-source databases. The analysis revealed that the targeted kinases were overexpressed in all three types of cancer. Their expression was significantly linked to overall survival rates, which suggests that they play a major role in the development and progression of these cancers. After, having the prognostic importance of These findings provided a rationale for synthesizing novel compound i.e., dimethyl 2,2’-((methylenebis(2-(2 H -benzo[d][1,2,3]triazol-2-yl)-4-(2,4,4-trimethylpentan-2-yl)-6,1phenylene))bis(oxy))diacetate (TAJ4)), capable of effectively targeting these proteins using in-vitro cytotoxicity assays and comprehensive computational approaches. Then the inhibitory potential of TAJ4 was evaluated against cell lines of the respective cancers (HeLa cells, MCF-7 cells, and Vero cells). The growth inhibitory values (GI 50 ) suggested that TAJ4 exhibited strong inhibitory potential towards MCF-7 cells (GI 50  = 3.18 ± 0.11 µM) in comparison to the HeLa cell line (GI 50  = 8.12 ± 0.43 µM), surpassing that of standard drugs. Furthermore, in-silico investigations, including density functional theory (DFT) calculations and molecular docking studies, revealed a substantial reactivity profile of TAJ4, with promising molecular interactions against NEK7, NEK9, TP53, NF-KAPPA-B, and caspase-3 proteins. Further investigation using in-vitro and in-vivo approaches is recommended to fully establish the therapeutic efficacy and safety profile of TAJ4.

Background The purpose of this study was to evaluate the utility of fluorine-18-fibroblast activation protein inhibitor ( 18 F-FAPI) PET/CT for detecting brain metastasis (BM) in different pathological types of lung cancer using craniocerebral MRI as the standard. Methods From December 2020 to October 2021, patients with pathologically confirmed lung cancer and suspected BM were prospectively enrolled and underwent paired 18 F-FAPI PET/CT and MRI. The number of BMs and maximum tumor diameter were measured by MRI. The maximum and peak standardized uptake values (SUVmax and SUVpeak, respectively) and tumor-to-background ratio (TBR) on 18 F‐FAPI PET/CT in BMs were evaluated. Results A total of 76 BM lesions from 18 patients (11 males and 7 females) were evaluated. Among these, 23 lesions were detected by 18 F-FAPI PET/CT. The detection rate of BM in adenocarcinoma was 48.28%, which was significantly higher than that in large cell carcinoma (16.67%, P  = 0.016) and small cell carcinoma (0%, P  = 0.009), but showed no significant difference from that in squamous carcinoma (35.71%, P  = 0.437). The detection rate in squamous carcinoma was significantly higher than that in small cell carcinoma ( P  = 0.043), while no significant differences were observed between large cell carcinoma and small cell carcinoma ( P  = 0.183), or between large cell carcinoma and squamous carcinoma ( P  = 0.191). Conclusions This study revealed differences in the detection rates of BM in lung cancer types by 18 F-FAPI PET/CT, with the highest and lowest detection rates in adenocarcinoma and small cell carcinoma, respectively, which may be valuable for predicting the prognosis of lung cancer patients with BM. Trial registration Institutional review board approval NO. SDZLEC2021-112-02.

Background To establish and validate the utility of computed tomography (CT) radiomics for the prognosis of patients with non-small cell lung cancer (NSCLC). Materials and methods Overall, 215 patients with pathologic diagnosis of NSCLC were included, chest CT images and clinical data were collected before treatment, and follow-up was conducted to assess brain metastasis and survival. Radiomics characteristics were extracted from the chest CT lung window images of each patient, key characteristics were screened, the radiomics score (Radscore) was calculated, and radiomics, clinical, and combined models were constructed using clinically independent predictive factors. A nomogram was constructed based on the final joint model to visualize prediction results. Predictive efficacy was evaluated using the concordance index (C-index), and survival (Kaplan-Meier) and calibration curves were drawn to further evaluate predictive efficacy. Results The training set included 151 patients (43 with brain metastasis and 108 without brain metastasis) and 64 patients (18 with brain metastasis and 46 without). Multivariate analysis revealed that lymph node metastasis, lymphocyte percentage, and neuron-specific enolase (NSE) were independent predictors of brain metastasis in patients with NSCLC. The area under the curve (AUC) of the these models were 0.733, 0.836, and 0.849, respectively, in the training set and were 0.739, 0.779, and 0.816, respectively, in the validation set. Multivariate Cox regression analysis revealed that the number of brain metastases, distant metastases elsewhere, and C-reactive protein levels were independent predictors of postoperative survival in patients with brain metastases ( P  < 0.05). The calibration curve exhibited that the predicted values of the prognostic prediction model agreed well with the actual values. Conclusion The model based on CT radiomics characteristics can effectively predict NSCLC brain metastasis and its prognosis and provide guidance for individualized treatment of NSCLC patients.

Background Pancreatic cancer is one of the most aggressive and lethal malignancies of the digestive system and is characterized by an extremely low five-year survival rate. The perineural invasion (PNI) status in patients with pancreatic cancer is positively correlated with adverse prognoses, including overall survival and recurrence-free survival. Emerging radiomic methods can reveal subtle variations in tumor structure by analyzing preoperative contrast-enhanced computed tomography (CECT) imaging data. Therefore, we propose the development of a preoperative CECT-based radiomic model to predict the risk of PNI in patients with pancreatic cancer. Patients and methods This study enrolled patients with pancreatic malignancies who underwent radical resection. Computerized tools were employed to extract radiomic features from tumor regions of interest (ROIs). The optimal radiomic features associated with PNI were selected to construct a radiomic score (RadScore). The model’s reliability was comprehensively evaluated by integrating clinical and follow-up information, with SHapley Additive exPlanations (SHAP)-based visualization to interpret the decision-making processes. Results A total of 167 patients with pancreatic malignancies were included. From the CECT images, 851 radiomic features were extracted, 22 of which were identified as most strongly correlated with PNI. These 22 features were evaluated using seven machine learning methods. We ultimately selected the Gaussian naive Bayes model, which demonstrated robust predictive performance in both the training and validation cohorts, and achieved area under the ROC curve (AUC) values of 0.899 and 0.813, respectively. Among the clinical features, maximum tumor diameter, CA-199 level, blood glucose concentration, and lymph node metastasis were found to be independent risk factors for PNI. The integrated model yielded AUCs of 0.945 (training cohort) and 0.881 (validation cohort). Decision curve analysis confirmed the clinical utility of the ensemble model to predict perineural invasion. Conclusion The combined model integrating clinical and radiomic features exhibited excellent performance in predicting the probability of perineural invasion in patients with pancreatic cancer. This approach has significant potential to optimize therapeutic decision-making and prognostic evaluation in patients with PNI.