Pediatric-Like Brain Tumors in Adults.

Pediatric brain tumors are different to those found in adults in pathological type, anatomical site, molecular signature, and probable tumor drivers. Although these tumors usually occur in childhood, they also rarely present in adult patients, either as a de novo diagnosis or as a delayed recurrence of a pediatric tumor in the setting of a patient that has transitioned into adult services.Due to the rarity of pediatric-like tumors in adults, the literature on these tumor types in adults is often limited to small case series, and treatment decisions are often based on the management plans taken from pediatric studies. However, the biology of these tumors is often different from the same tumors found in children. Likewise, adult patients are often unable to tolerate the side effects of the aggressive treatments used in children-for which there is little or no evidence of efficacy in adults. In this chapter, we review the literature and summarize the clinical, pathological, molecular profile, and response to treatment for the following pediatric tumor types-medulloblastoma, ependymoma, craniopharyngioma, pilocytic astrocytoma, subependymal giant cell astrocytoma, germ cell tumors, choroid plexus tumors, midline glioma, and pleomorphic xanthoastrocytoma-with emphasis on the differences to the adult population.

Headache in Brain Tumors.

The prevalence of brain tumors in patients with headache is very low; however, 48% to 71% of patients with brain tumors experience headache. The clinical presentation of headache in brain tumors varies according to age; intracranial pressure; tumor location, type, and progression; headache history; and treatment. Brain tumor-associated headaches can be caused by local and distant traction on pain-sensitive cranial structures, mass effect caused by the enlarging tumor and cerebral edema, infarction, hemorrhage, hydrocephalus, and tumor secretion. This article reviews the current findings related to epidemiologic details, clinical manifestations, mechanisms, diagnostic approaches, and management of headache in association with brain tumors.

Advancing glioblastoma treatment by targeting metabolism.

Alterations in cellular metabolism are important hallmarks of glioblastoma(GBM). Metabolic reprogramming is a critical feature as it meets the higher nutritional demand of tumor cells, including proliferation, growth, and survival. Many genes, proteins, and metabolites associated with GBM metabolism reprogramming have been found to be aberrantly expressed, which may provide potential targets for cancer treatment. Therefore, it is becoming increasingly important to explore the role of internal and external factors in metabolic regulation in order to identify more precise therapeutic targets and diagnostic markers for GBM. In this review, we define the metabolic characteristics of GBM, investigate metabolic specificities such as targetable vulnerabilities and therapeutic resistance, as well as present current efforts to target GBM metabolism to improve the standard of care.

Chat-GPT on brain tumors: An examination of Artificial Intelligence/Machine Learning's ability to provide diagnoses and treatment plans for example neuro-oncology cases.

OBJECTIVE: Assess the capabilities of ChatGPT-3.5 and 4 to provide accurate diagnoses, treatment options, and treatment plans for brain tumors in example neuro-oncology cases. METHODS: ChatGPT-3.5 and 4 were provided with twenty example neuro-oncology cases of brain tumors, all selected from medical textbooks. The artificial intelligence programs were asked to give a diagnosis, treatment option, and treatment plan for each of these twenty example cases. Team members first determined in which cases ChatGPT-3.5 and 4 provided the correct diagnosis or treatment plan. Twenty neurosurgeons from the researchers' institution then independently rated the diagnoses, treatment options, and treatment plans provided by both artificial intelligence programs for each of the twenty example cases, on a scale of one to ten, with ten being the highest score. To determine whether the difference between the scores of ChatGPT-3.5 and 4 was statistically significant, a paired t-test was conducted for the average scores given to the programs for each example case. RESULTS: In the initial analysis of correct responses, ChatGPT-4 had an accuracy of 85% for its diagnoses of example brain tumors and an accuracy of 75% for its provided treatment plans, while ChatGPT-3.5 only had an accuracy of 65% and 10%, respectively. The average scores given by the twenty independent neurosurgeons to ChatGPT-4 for its accuracy of diagnosis, provided treatment options, and provided treatment plan were 8.3, 8.4, and 8.5 out of 10, respectively, while ChatGPT-3.5's average scores for these categories of assessment were 5.9, 5.7, and 5.7. These differences in average score are statistically significant on a paired t-test, with a p-value of less than 0.001 for each difference. CONCLUSIONS: ChatGPT-4 demonstrates great promise as a diagnostic tool for brain tumors in neuro-oncology, as attested to by the program's performance in this study and its assessment by surveyed neurosurgeon reviewers.

Identification and Validation of a PEX5-Dependent Signature for Prognostic Prediction in Glioma.

Gliomas, the most prevalent and lethal form of brain cancer, are known to exhibit metabolic alterations that facilitate tumor growth, invasion, and resistance to therapies. Peroxisomes, essential organelles responsible for fatty acid oxidation and reactive oxygen species (ROS) homeostasis, rely on the receptor PEX5 for the import of metabolic enzymes into their matrix. However, the prognostic significance of peroxisomal enzymes for glioma patients remains unclear. In this study, we elucidate that PEX5 is indispensable for the cell growth, migration, and invasion of glioma cells. We establish a robust prognosis model based on the expression of peroxisomal enzymes, whose localization relies on PEX5. This PEX5-dependent signature not only serves as a robust prognosis model capable of accurately predicting outcomes for glioma patients, but also effectively distinguishes several clinicopathological features, including the grade, isocitrate dehydrogenase (IDH) mutation, and 1p19q codeletion status. Furthermore, we developed a nomogram that integrates the prognostic model with other clinicopathological factors, demonstrating highly accurate performance in estimating patient survival. Patients classified into the high-risk group based on our prognostic model exhibited an immunosuppressive microenvironment. Finally, our validation reveals that the elevated expression of GSTK1, an antioxidant enzyme within the signature, promotes the cell growth and migration of glioma cells, with this effect dependent on the peroxisomal targeting signal recognized by PEX5. These findings identify the PEX5-dependent signature as a promising prognostic tool for gliomas.

Clinical diagnosis and management of multiple cerebral ring-enhancing lesions-study of 50 patients at a tertiary healthcare center.

AIM OF THE STUDY: Multiple ring-enhancing lesions are commonly experienced group of brain pathologies which we come across in day-to-day practice. Clinical symptoms in these lesions are quite non-specific, and hence, it is difficult to reach a final diagnosis. However, these lesions have a varied group of differential diagnosis and it is sometimes difficult to have an accurate diagnosis on conventional MRI. This article was written with the objective of discussing the demographical study and etiology, clinical diagnosis and management for these patients. MATERIALS AND METHODS: It is a prospective study carried out at the Department of Neurosurgery, Dr. D Y Patil Medical College and Hospital, Pune, from September 2019 to August 2022 and included 50 patients who presented to us multiple ring-enhancing brain lesions. RESULTS: In our study, 50 patients between age (1-70 years) with multiple ring-enhancing lesions were analyzed. Majority of the patients were between age group 30-39 years. Males (76%) were majority in our study than females (24%). Most common pathology was primary neoplasm (glioma) and metastasis, followed by nine patients of pyogenic abscess and tuberculosis each. Neurocysticercosis was seen in eight patients and three patients were diagnosed with CNS lymphoma. Most of our patients presented with headache (38 patients) and a subset of patients had associated seizures (28 patients). Two patients with primary neoplasm were diagnosed to have WHO grade 3 glioma and seven patients were diagnosed to have WHO grade 4 glioma. Glioblastoma multiforme presented as multifocal and multicentric lesions. Among the patients with primary neoplasm, three patients underwent stereotactic biopsy for diagnosis and the rest of seven patients underwent maximum safe resection followed by chemotherapy and radiotherapy. Ten patients were diagnosed with metastatic lesions, among them six patients underwent stereotactic biopsy for histopathological diagnosis and immunohistochemistry, and rest of the patients were managed on the basis of the primary lesion. Five patients were immune-compromised, among them two patients presented with abscess and three patients presented with primary neoplastic lesion. Thirty-six patients underwent biopsy, among them seven patients underwent frameless, seven patients underwent frame stereotactic biopsy, and the rest 22 patients underwent excision biopsy. CONCLUSION: Multiple ring-enhancing lesions of brain pose a challenge in terms of achieving an accurate diagnosis and planning further treatment. It is of utmost importance to have a diagnosis in mind based on radiological investigations, so that surgical intervention can be planned accordingly be it by invasive or minimal invasive techniques. An idea toward the diagnosis also helps in prognosticating these patients which could avoid costly whole-body scans and unnecessary surgical intervention.

Intraoperative Touch Imprint Cytology of Brain Neoplasms: A Useful High-Diagnostic Tool in 93 Consecutive Cases; Differential Diagnoses, Pitfalls, and Traps.

Introduction: Intraoperative cytological examination of central nervous system (CNS) lesions was first introduced in 1920 by Eisenhardt and Cushing for rapid evaluation of neurosurgical specimens and to guide surgical treatment. It is recognized that this method not only confirms the adequacy of biopsy in CNS samples but also indicates the presence and preliminary diagnosis of lesional tissue. Methods: A total of 93 patients who underwent touch imprint cytology (TIC) for CNS tumors or lesions between 2018 and 2023 were included in the study. All cases were correlated with the final histopathological diagnosis, and pitfalls and difficulties encountered with discrepancies were noted. Result: The most common primary CNS tumors were gliomas and meningiomas, while secondary (metastatic) tumors were predominantly lung, breast, and gastrointestinal system carcinomas. Sensitivity, specificity, positive predictive value, and negative predictive value for diagnosis with TIC were 94.1%, 100%, and 61.5%, respectively. Final histopathological diagnosis by TIC was made in 88 cases (94.6%) and the discrepancy was found in 5 cases (5.37%). Three of the five discrepancies (3.2%) were haematolymphoid malignancies (two lymphomas and one plasma cell neoplasia), one glioblastoma, and one hemangioblastoma case. Conclusion: TIC is a fast, safe, and inexpensive diagnostic tool used during intraoperative neuropathology consultation. Awareness of the pitfalls of using this method during intraoperative consultation will enable high-diagnostic accuracy.

Real-time glioblastoma tumor microenvironment assessment by SpiderMass for improved patient management.

Glioblastoma is a highly heterogeneous and infiltrative form of brain cancer associated with a poor outcome and limited therapeutic effectiveness. The extent of the surgery is related to survival. Reaching an accurate diagnosis and prognosis assessment by the time of the initial surgery is therefore paramount in the management of glioblastoma. To this end, we are studying the performance of SpiderMass, an ambient ionization mass spectrometry technology that can be used in vivo without invasiveness, coupled to our recently established artificial intelligence pipeline. We demonstrate that we can both stratify isocitrate dehydrogenase (IDH)-wild-type glioblastoma patients into molecular sub-groups and achieve an accurate diagnosis with over 90% accuracy after cross-validation. Interestingly, the developed method offers the same accuracy for prognosis. In addition, we are testing the potential of an immunoscoring strategy based on SpiderMass fingerprints, showing the association between prognosis and immune cell infiltration, to predict patient outcome.

Diagnostic yield of postmortem brain examination following premortem brain biopsy for neoplastic and nonneoplastic disease.

Medical autopsies have decreased in frequency due in part to advances in radiological techniques and increased availability of molecular and other ancillary testing. However, premortem diagnosis of CNS disease remains challenging; while ∼90% of brain tumor biopsies are diagnostic, only 20%-70% of biopsies for presumed nonneoplastic disease result in a specific diagnosis. The added benefits of performing an autopsy following surgical brain biopsy are not well defined. A retrospective analysis was performed of patients who underwent brain biopsy and autopsy at Brigham and Women's Hospital from 2003 to 2022. A total of 135 cases were identified, including 95 (70%) patients with primary CNS neoplasms, 16 (12%) with metastatic tumors, and 24 (18%) with nonneoplastic neurological disease. Diagnostic concordance between biopsy and autopsy diagnosis was excellent both for primary CNS neoplasms (98%) and metastatic tumors (94%). Conversely, patients with nonneoplastic disease received definitive premortem diagnoses in 7/24 (29%) cases. Five (21%) additional patients received conclusive diagnoses following autopsy; 8 (33%) received a more specific differential diagnosis compared to the biopsy. Overall, autopsy confirmed premortem diagnoses or provided new diagnostic information in 131/135 (97%) cases, highlighting the value in performing postmortem brain examination in patients with both neoplastic and nonneoplastic diseases.

The development of a custom RNA-sequencing panel for the identification of predictive and diagnostic biomarkers in glioma.

PURPOSE: Various molecular profiles are needed to classify malignant brain tumors, including gliomas, based on the latest classification criteria of the World Health Organization, and their poor prognosis necessitates new therapeutic targets. The Todai OncoPanel 2 RNA Panel (TOP2-RNA) is a custom-target RNA-sequencing (RNA-seq) using the junction capture method to maximize the sensitivity of detecting 455 fusion gene transcripts and analyze the expression profiles of 1,390 genes. This study aimed to classify gliomas and identify their molecular targets using TOP2-RNA. METHODS: A total of 124 frozen samples of malignant gliomas were subjected to TOP2-RNA for classification based on their molecular profiles and the identification of molecular targets. RESULTS: Among 55 glioblastoma cases, gene fusions were detected in 11 cases (20%), including novel MET fusions. Seven tyrosine kinase genes were found to be overexpressed in 15 cases (27.3%). In contrast to isocitrate dehydrogenase (IDH) wild-type glioblastoma, IDH-mutant tumors, including astrocytomas and oligodendrogliomas, barely harbor fusion genes or gene overexpression. Of the 34 overexpressed tyrosine kinase genes, MDM2 and CDK4 in glioblastoma, 22 copy number amplifications (64.7%) were observed. When comparing astrocytomas and oligodendrogliomas in gene set enrichment analysis, the gene sets related to 1p36 and 19q were highly enriched in astrocytomas, suggesting that regional genomic DNA copy number alterations can be evaluated by gene expression analysis. CONCLUSIONS: TOP2-RNA is a highly sensitive assay for detecting fusion genes, exon skipping, and aberrant gene expression. Alterations in targetable driver genes were identified in more than 50% of glioblastoma. Molecular profiling by TOP2-RNA provides ample predictive, prognostic, and diagnostic biomarkers that may not be identified by conventional assays and, therefore, is expected to increase treatment options for individual patients with glioma.

Novel insights on genetics and epigenetics as clinical targets for paediatric astrocytoma.

Paediatric and adult astrocytomas are notably different, where clinical treatments used for adults are not as effective on children with the same form of cancer and these treatments lead to adverse long-term health concerns. Integrative omics-based studies have shown the pathology and fundamental molecular characteristics differ significantly and cannot be extrapolated from the more widely studied adult disease. Recent clinical advances in our understanding of paediatric astrocytomas, with the aid of next-generation sequencing and epigenome-wide profiling, have led to the identification of key canonical mutations that vary based on the tumour location and age of onset. These driver mutations, in particular the identification of the recurrent histone H3 mutations in high-grade tumours, have confirmed the important role epigenetic dysregulations play in cancer progression. This review summarises the current updates of the classification, epidemiology, pathogenesis and clinical management of paediatric astrocytoma based on their grades and the ongoing clinical trials. It also provides novel insights on genetic and epigenetic alterations as diagnostic biomarkers, highlighting the potential of targeting these pathways as therapeutics for this devastating childhood cancer.

The diagnostic efficiency of integration of 2HG MRS and IVIM versus individual parameters for predicting IDH mutation status in gliomas in clinical scenarios: A retrospective study.

PURPOSE: Currently, there remains a scarcity of established preoperative tests to accurately predict the isocitrate dehydrogenase (IDH) mutation status in clinical scenarios, with limited research has explored the potential synergistic diagnostic performance among metabolite, perfusion, and diffusion parameters. To address this issue, we aimed to develop an imaging protocol that integrated 2-hydroxyglutarate (2HG) magnetic resonance spectroscopy (MRS) and intravoxel incoherent motion (IVIM) by comprehensively assessing metabolic, cellular, and angiogenic changes caused by IDH mutations, and explored the diagnostic efficiency of this imaging protocol for predicting IDH mutation status in clinical scenarios. METHODS: Patients who met the inclusion criteria were categorized into two groups: IDH-wild type (IDH-WT) group and IDH-mutant (IDH-MT) group. Subsequently, we quantified the 2HG concentration, the relative apparent diffusion coefficient (rADC), the relative true diffusion coefficient value (rD), the relative pseudo-diffusion coefficient (rD*) and the relative perfusion fraction value (rf). Intergroup differences were estimated using t-test and Mann-Whitney U test. Finally, we performed receiver operating characteristic (ROC) curve and DeLong's test to evaluate and compare the diagnostic performance of individual parameters and their combinations. RESULTS: 64 patients (female, 21; male, 43; age, 47.0 ± 13.7 years) were enrolled. Compared with IDH-WT gliomas, IDH-MT gliomas had higher 2HG concentration, rADC and rD (P < 0.001), and lower rD* (P = 0.013). The ROC curve demonstrated that 2HG + rD + rD* exhibited the highest areas under curve (AUC) value (0.967, 95%CI 0.889-0.996) for discriminating IDH mutation status. Compared with each individual parameter, the predictive efficiency of 2HG + rADC + rD* and 2HG + rD + rD* shows a statistically significant enhancement (DeLong's test: P < 0.05). CONCLUSIONS: The integration of 2HG MRS and IVIM significantly improves the diagnostic efficiency for predicting IDH mutation status in clinical scenarios.

FT-Raman spectra in combination with machine learning and multivariate analyses as a diagnostic tool in brain tumors.

Brain tumors are one of the most dangerous, because the position of these are in the organ that governs all life processes. Moreover, a lot of brain tumor types were observed, but only one main diagnostic method was used - histopathology, for which preparation of sample was long. Consequently, a new, quicker diagnostic method is needed. In this paper, FT-Raman spectra of brain tissues were analyzed by Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), four different machine learning (ML) algorithms to show possibility of differentiating between glioblastoma G4 and meningiomas, as well as two different types of meningiomas (atypical and angiomatous). Obtained results showed that in meningiomas additional peak around 1503 cm-1 and higher level of amides was noticed in comparison with glioblastoma G4. In the case of meningiomas differentiation, in angiomatous meningiomas tissues lower level of lipids and polysaccharides were visible than in atypical meningiomas. Moreover, PCA analyses showed higher distinction between glioblastoma G4 and meningiomas in the FT-Raman range between 800 cm-1 and 1800 cm-1 and between two types of meningiomas in the range between 2700 cm-1 and 3000 cm-1. Decision trees showed, that the most important peaks to differentiate glioblastoma and meningiomas were at 1151 cm-1 and 2836 cm-1 while for angiomatous and atypical meningiomas - 1514 cm-1 and 2875 cm-1. Furthermore, the accuracy of obtained results for glioblastoma G4 and meningiomas was 88 %, while for meningiomas - 92 %. Consequently, obtained data showed possibility of using FT-Raman spectroscopy in diagnosis of different types of brain tumors.

Evaluation of Pathway to Diagnosis of Pediatric Brain Tumors in Tamil Nadu, India.

PURPOSE: Delayed diagnosis and poor awareness are significant barriers to the early intervention of pediatric brain tumors. This multicenter observational study aimed to evaluate the baseline routes and time to diagnosis for pediatric brain tumors in Tamil Nadu (TN), with the goal of promoting early diagnosis and timely referrals in the future. METHODS: A standard proforma was used to retrospectively collect information on demographics, diagnosis, referral pathways, and symptoms of incident pediatric brain tumor cases between January 2018 and October 2020 across eight tertiary hospitals in TN. Dates of symptom onset, first presentation of health care, and diagnosis were used to calculate total diagnostic interval (TDI), patient interval (PI), and diagnostic interval (DI). RESULTS: A total of 144 cases (mean age, 6.64 years; range, 0-15.1 years) were included in the analysis. Among those, 94% (135/144) were from city/district areas, 40% (55/144) were self-referred, and 90% (129/144) had one to three health care professional visits before diagnosis. Median TDI, PI, and DI were 3.5 (IQR, 1-9.3), 0.6 (IQR, 0.1-4.6), and 0.6 (IQR, 0-3.3) weeks, respectively. Low-grade gliomas had the longest median TDI (6.6 weeks), followed by medulloblastomas (4.6 weeks) and high-grade gliomas (3.3 weeks). Average number of symptoms recorded was 1.7 at symptom onset and 1.9 at diagnosis. CONCLUSION: Although there are some similarities with data from the United Kingdom, many low-grade and optic pathway tumors were unaccounted for in our study. DIs were relatively short, which suggests that infrastructure may not be a problem in this cohort. Increased training and establishment of proper cancer registries, combined with proper referral pathways, could enhance early diagnosis for these children.

Distinguishing brain tumors by Label-free confocal micro-Raman spectroscopy.

BACKGROUND: Brain tumors have serious adverse effects on public health and social economy. Accurate detection of brain tumor types is critical for effective and proactive treatment, and thus improve the survival of patients. METHODS: Four types of brain tumor tissue sections were detected by Raman spectroscopy. Principal component analysis (PCA) has been used to reduce the dimensionality of the Raman spectra data. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) methods were utilized to discriminate different types of brain tumors. RESULTS: Raman spectra were collected from 40 brain tumors. Variations in intensity and shift were observed in the Raman spectra positioned at 721, 854, 1004, 1032, 1128, 1248, 1449 cm-1 for different brain tumor tissues. The PCA results indicated that glioma, pituitary adenoma, and meningioma are difficult to differentiate from each other, whereas acoustic neuroma is clearly distinguished from the other three tumors. Multivariate analysis including QDA and LDA methods showed the classification accuracy rate of the QDA model was 99.47 %, better than the rate of LDA model was 95.07 %. CONCLUSIONS: Raman spectroscopy could be used to extract valuable fingerprint-type molecular and chemical information of biological samples. The demonstrated technique has the potential to be developed to a rapid, label-free, and intelligent approach to distinguish brain tumor types with high accuracy.

Unraveling the Impact of miRNA-17 in Glial Tumors and Cerebral Metastases: A Step Towards Enhanced Diagnosis and Prognosis.

BACKGROUND/AIM: MicroRNAs (miRNAs) have been identified as key regulators in various cancer types, including brain tumors. This study aimed to investigate the differential expression of miRNA-17 in glial tumors, cerebral metastases, and normal glial tissues. MATERIALS AND METHODS: A total of 42 patients were included in this cross-sectional study. Tissue samples were obtained from patients with glial tumors or cerebral metastases and from normal glial tissues. miRNA-17 expression levels were computed by using real-time polymerase chain reaction. Receiver operating characteristics analysis was used to determine the predictive potential of miRNA-17. RESULTS: In this study, we demonstrated a statistically significant difference in miRNA-17 expression levels between glial tumors and the control group (p=0.001), with higher miRNA-17 expression observed in glial tumors. Similarly, there was statistically higher miRNA-17 expression in metastatic cases compared with the control group (p=0.007). CONCLUSION: These findings suggest miRNA-17 might be a potential biomarker for differentiating glial tumors and cerebral metastases from normal glial tissue, although further research is necessary to validate these findings and investigate the potential role of miRNA-17 in the pathogenesis of these brain tumors.

Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation.

BACKGROUND: Glioma is a primary brain tumor and the assessment of its molecular profile in a minimally invasive manner is important in determining treatment strategies. Among the molecular abnormalities of gliomas, mutations in the isocitrate dehydrogenase (IDH) gene are strong predictors of treatment sensitivity and prognosis. In this study, we attempted to non-invasively diagnose glioma development and the presence of IDH mutations using multivariate analysis of the plasma mid-infrared absorption spectra for a comprehensive and sensitive view of changes in blood components associated with the disease and genetic mutations. These component changes are discussed in terms of absorption wavenumbers that contribute to differentiation. METHODS: Plasma samples were collected at our institutes from 84 patients with glioma (13 oligodendrogliomas, 17 IDH-mutant astrocytoma, 7 IDH wild-type diffuse glioma, and 47 glioblastomas) before treatment initiation and 72 healthy participants. FTIR-ATR spectra were obtained for each plasma sample, and PLS discriminant analysis was performed using the absorbance of each wavenumber in the fingerprint region of biomolecules as the explanatory variable. This data was used to distinguish patients with glioma from healthy participants and diagnose the presence of IDH mutations. RESULTS: The derived classification algorithm distinguished the patients with glioma from healthy participants with 83% accuracy (area under the curve (AUC) in receiver operating characteristic (ROC) = 0.908) and diagnosed the presence of IDH mutation with 75% accuracy (AUC = 0.752 in ROC) in cross-validation using 30% of the total test data. The characteristic changes in the absorption spectra suggest an increase in the ratio of ß-sheet structures in the conformational composition of blood proteins of patients with glioma. Furthermore, these changes were more pronounced in patients with IDH-mutant gliomas. CONCLUSIONS: The plasma infrared absorption spectra could be used to diagnose gliomas and the presence of IDH mutations in gliomas with a high degree of accuracy. The spectral shape of the protein absorption band showed that the ratio of ß-sheet structures in blood proteins was significantly higher in patients with glioma than in healthy participants, and protein aggregation was a distinct feature in patients with glioma with IDH mutations.

PBX3 as a biomarker for the early diagnosis and prediction of prognosis of glioma.

BACKGROUND: Increasing evidence have elucidated that PBX3 played a crucial role in cancer initiation and progression. PBX3 was differentially expressed in many cancer types. However, PBX3 potential involvement in gliomas remains to be explored. METHODS: The expression level of PBX3 in glioma tissues and glioma cells, and its correlation with clinical features were analyzed by data from TCGA, GEPIA, CGGA and CCLE. Univariable survival and Multivariate Cox analysis was used to compare several clinical characteristics with survival. We also analyzed the correlation between PBX3 expression level and survival outcome and survival time of LGG and GBM patients by using linear regression equation. GSEA was used to generate an ordered list of all genes related to PBX3 expression and screening of genes co-expressed with PBX3 mRNA by "limma" package. RESULTS: The results showed that PBX3 was highly expressed in gliomas and its expression increased with the increase of malignancy. Survival analysis found that PBX3 is more valuable in predicting the OS and PFI of LGG patients than that of GBM. For further study, TCGA and CGGA data were downloaded for univariate Cox analysis and multivariate Cox analysis which showed that the expression of PBX3 was independent influencing factors for poor prognosis of LGG patients. Meanwhile, Receiver operating characteristic (ROC) curve showed that PBX3 was a predictor of overall survival rate and progression-free survival rate of LGG. Linear regression model analysis indicated that the higher expression of PBX3 the higher the risk of death of LGG patients, and the higher expression of PBX3 the higher the risk of disease progression of LGG patients. Next, TCGA data were downloaded for GSEA and Co-expression analyses, which was performed to study the function of PBX3. CONCLUSION: PBX3 may be involved in the occurrence and development of glioma, and has potential reference value for the early diagnosis and prediction of prognosis of glioma.

Prognostic factors analysis of diffuse midline glioma.

PURPOSE: This study retrospectively analyzes cases of diffuse midline glioma treated with radiotherapy, with the aim of investigating the prognosis of the tumor and its influencing factors. METHODS: From January 2018 to November 2022, we treated 64 patients who were pathologically diagnosed with diffuse midline glioma. Among them, 41 underwent surgical resection, and 23 underwent biopsy procedures. All patients received postoperative radiotherapy. We followed up with the patients to determine the overall survival rate and conducted univariate and multivariate analyses on relevant indicators. RESULTS: The median survival time for the entire patient group was 33.3 months, with overall survival rates of 92.9%, 75.4%, and 45.0% at 1 year, 2 years, and 3 years, respectively. Univariate and multivariate analyses indicated that older patients had a better prognosis. CONCLUSION: Patient age is an independent prognostic factor for patients with diffuse midline glioma undergoing radiation therapy.