Morphological analysis of CDC2 and glycogen synthase kinase 3β phosphorylation as markers of g2 → m transition in glioma.

G2 → M transition is a strategic target for glioma chemotherapy. Key players in G2 → M transition include CDC2 and glycogen synthase kinase 3β (GSK3β), which are highly regulated by posttranslational phosphorylation. This report is a morphological analysis of CDC2 and GSK3β phosphorylation using immunohistochemistry in gliomas with different biological properties. GBM showed a 2.8-fold and 5.6-fold increase in number of cells positive for pThr161CDC2 and a 4.2- and 6.9-fold increase in number of cells positive for pTyr15CDC2 relative to oligodendroglioma and ependymoma, respectively. Elevated labeling for inhibited phospho-CDC2 (pTyr15CDC) correlates with elevated levels of phosphorylated glycogen synthase kinase 3β (GSK3β). 71% of the GBM cases showed intermediate to high intensity staining for pSer9SGK3β 53% of oligodendroglioma, and 73% of ependymoma showed low intensity staining. CDC2 gene amplification correlates with increased survival in glioblastoma multiforme (GBM) and astrocytoma WHO grades II-III, but not in oligodendroglioma WHO grades II-III

Machine Learning Decision Tree Models for Differentiation of Posterior Fossa Tumors Using Diffusion Histogram Analysis and Structural MRI Findings.

We applied machine learning algorithms for differentiation of posterior fossa tumors using apparent diffusion coefficient (ADC) histogram analysis and structural MRI findings. A total of 256 patients with intra-axial posterior fossa tumors were identified, of whom 248 were included in machine learning analysis, with at least 6 representative subjects per each tumor pathology. The ADC histograms of solid components of tumors, structural MRI findings, and patients' age were applied to construct decision models using Classification and Regression Tree analysis. We also compared different machine learning classification algorithms (i.e., naïve Bayes, random forest, neural networks, support vector machine with linear and polynomial kernel) for dichotomized differentiation of the 5 most common tumors in our cohort: metastasis (n = 65), hemangioblastoma (n = 44), pilocytic astrocytoma (n = 43), ependymoma (n = 27), and medulloblastoma (n = 26). The decision tree model could differentiate seven tumor histopathologies with terminal nodes yielding up to 90% accurate classification rates. In receiver operating characteristics (ROC) analysis, the decision tree model achieved greater area under the curve (AUC) for differentiation of pilocytic astrocytoma (p = 0.020); and atypical teratoid/rhabdoid tumor ATRT (p = 0.001) from other types of neoplasms compared to the official clinical report. However, neuroradiologists' interpretations had greater accuracy in differentiating metastases (p = 0.001). Among different machine learning algorithms, random forest models yielded the highest accuracy in dichotomized classification of the 5 most common tumor types; and in multiclass differentiation of all tumor types random forest yielded an averaged AUC of 0.961 in training datasets, and 0.873 in validation samples. Our study demonstrates the potential application of machine learning algorithms and decision trees for accurate differentiation of brain tumors based on pretreatment MRI. Using easy to apply and understandable imaging metrics, the proposed decision tree model can help radiologists with differentiation of posterior fossa tumors, especially in tumors with similar qualitative imaging characteristics. In particular, our decision tree model provided more accurate differentiation of pilocytic astrocytomas from ATRT than by neuroradiologists in clinical reads

Pathological perspectives in pilocytic astrocytomas: Extent of resection as the sole critical factor for recurrence-free survival, and the challenge of evaluating conclusions derived from limited data

Introduction: Pilocytic astrocytoma (PA) is one of the most common primary intracranial neoplasms in childhood with an overall favorable prognosis. Despite decades of experience, there are still diagnostic and treatment challenges and unresolved issues regarding risk factors associated with recurrence, most often due to conclusions of publications with limited data. We analyzed 499 patients with PA diagnosed in a single institution over 30 years in order to provide answers to some of the unresolved issues. Materials and Methods: We identified pilocytic astrocytomas diagnosed at the University of California, San Francisco, between 1989 and 2019, confirmed the diagnoses using the WHO 2021 essential and desirable criteria, and performed a retrospective review of the demographic and clinical features of the patients and the radiological, pathologic and molecular features of the tumors. Results: Among the patients identified from pathology archives, 499 cases fulfilled the inclusion criteria. Median age at presentation was 12 years (range 3.5 months – 73 years) and the median follow-up was 78.5 months. Tumors were predominantly located in the posterior fossa (52.6%). There were six deaths, but there were confounding factors that prevented a clear association of death to tumor progression. Extent of resection was the only significant factor for recurrence-free survival. Recurrence-free survival time was 321.0 months for gross total resection, compared to 160.9 months for subtotal resection (log rank, p <0.001). Conclusion: Multivariate analysis was able to identify extent of resection as the only significant variable to influence recurrence-free survival. We did not find a statistically significant association between age, NF1 status, tumor location, molecular alterations, and outcome. Smaller series with apparently significant results may have suffered from limited sample size, limited variables, acceptance of univariate analysis findings as well as a larger p value for biological significance. PA still remains a predominantly surgical disease and every attempt should be made to achieve gross total resection since this appears to be the most reliable predictor of recurrence-free survival

The hypoxic response of tumors is dependent on their microenvironment

AbstractTo reveal the functional significance of hypoxia and angiogenesis in astrocytoma progression, we created genetically engineered transformed astrocytes from murine primary astrocytes and deleted the hypoxia-responsive transcription factor HIF-1α or its target gene, the angiogenic factor VEGF. Growth of HIF-1α- and VEGF-deficient transformed astrocytes in the vessel-poor subcutaneous environment results in severe necrosis, reduced growth, and vessel density, whereas when the same cells are placed in the vascular-rich brain parenchyma, the growth of HIF-1α knockout, but not VEGF knockout tumors, is reversed: tumors deficient in HIF-1α grow faster, and penetrate the brain more rapidly and extensively. These results demonstrate that HIF-1α has differential roles in tumor progression, which are greatly dependent on the extant microenvironment of the tumor

Pathological perspectives in pilocytic astrocytomas: Extent of resection as the sole critical factor for recurrence-free survival, and the challenge of evaluating conclusions derived from limited data

Introduction: Pilocytic astrocytoma (PA) is one of the most common primary intracranial neoplasms in childhood with an overall favorable prognosis. Despite decades of experience, there are still diagnostic and treatment challenges and unresolved issues regarding risk factors associated with recurrence, most often due to conclusions of publications with limited data. We analyzed 499 patients with PA diagnosed in a single institution over 30 years in order to provide answers to some of the unresolved issues. Materials and Methods: We identified pilocytic astrocytomas diagnosed at the University of California, San Francisco, between 1989 and 2019, confirmed the diagnoses using the WHO 2021 essential and desirable criteria, and performed a retrospective review of the demographic and clinical features of the patients and the radiological, pathologic and molecular features of the tumors. Results: Among the patients identified from pathology archives, 499 cases fulfilled the inclusion criteria. Median age at presentation was 12 years (range 3.5 months – 73 years) and the median follow-up was 78.5 months. Tumors were predominantly located in the posterior fossa (52.6%). There were six deaths, but there were confounding factors that prevented a clear association of death to tumor progression. Extent of resection was the only significant factor for recurrence-free survival. Recurrence-free survival time was 321.0 months for gross total resection, compared to 160.9 months for subtotal resection (log rank, p <0.001). Conclusion: Multivariate analysis was able to identify extent of resection as the only significant variable to influence recurrence-free survival. We did not find a statistically significant association between age, NF1 status, tumor location, molecular alterations, and outcome. Smaller series with apparently significant results may have suffered from limited sample size, limited variables, acceptance of univariate analysis findings as well as a larger p value for biological significance. PA still remains a predominantly surgical disease and every attempt should be made to achieve gross total resection since this appears to be the most reliable predictor of recurrence-free survival

Using a preclinical mouse model of high-grade astrocytoma to optimize p53 restoration therapy

Based on clinical presentation, glioblastoma (GBM) is stratified into primary and secondary types. The protein 53 (p53) pathway is functionally incapacitated in most GBMs by distinctive type-specific mechanisms. To model human gliomagenesis, we used a GFAP-HRas(V12) mouse model crossed into the p53ER(TAM) background, such that either one or both copies of endogenous p53 is replaced by a conditional p53ER(TAM) allele. The p53ER(TAM) protein can be toggled reversibly in vivo between wild-type and inactive conformations by administration or withdrawal of 4-hydroxytamoxifen (4-OHT), respectively. Surprisingly, gliomas that develop in GFAP-HRas(V12);p53(+/KI) mice abrogate the p53 pathway by mutating p19(ARF)/MDM2 while retaining wild-type p53 allele. Consequently, such tumors are unaffected by restoration of their p53ER(TAM) allele. By contrast, gliomas arising in GFAP-HRas(V12);p53(KI/KI) mice develop in the absence of functional p53. Such tumors retain a functional p19(ARF)/MDM2-signaling pathway, and restoration of p53ER(TAM) allele triggers p53-tumor–suppressor activity. Congruently, growth inhibition upon normalization of mutant p53 by a small molecule, Prima-1, in human GBM cultures also requires p14(ARF)/MDM2 functionality. Notably, the antitumoral efficacy of p53 restoration in tumor-bearing GFAP-HRas(V12);p53(KI/KI) animals depends on the duration and frequency of p53 restoration. Thus, intermittent exposure to p53ER(TAM) activity mitigated the selective pressure to inactivate the p19(ARF)/MDM2/p53 pathway as a means of resistance, extending progression-free survival. Our results suggest that intermittent dosing regimes of drugs that restore wild-type tumor-suppressor function onto mutant, inactive p53 proteins will prove to be more efficacious than traditional chronic dosing by similarly reducing adaptive resistance

Clinical outcome and prognostic factors for central neurocytoma: twenty year institutional experience

Central neurocytomas are uncommon intraventricular neoplasms whose optimal management remains controversial due to their rarity. We assessed outcomes for a historical cohort of neurocytoma patients and evaluated effects of tumor atypia, size, resection extent, and adjuvant radiotherapy. Progression-free survival (PFS) was measured by Kaplan-Meier and Cox proportional hazards methods. A total of 28 patients (15 males, 13 females) were treated between 1995 and 2014, with a median age at diagnosis of 26 years (range 5-61). Median follow-up was 62.2 months and 3 patients were lost to follow-up postoperatively. Thirteen patients experienced recurrent/progressive disease and 2-year PFS was 75% (95% CI 53-88%). Two-year PFS was 48% for MIB-1 labeling >4% versus 90% for ≤4% (HR 5.4, CI 2.2-27.8, p = 0.0026). Nine patients (32%) had gross total resections (GTR) and 19 (68%) had subtotal resections (STR). PFS for >80% resection was 83 versus 67% for ≤80% resection (HR 0.67, CI 0.23-2.0, p = 0.47). Three STR patients (16%) received adjuvant radiation which significantly improved overall PFS (p = 0.049). Estimated 5-year PFS was 67% for STR with radiotherapy versus 53% for STR without radiotherapy. Salvage therapy regimens were diverse and resulted in stable disease for 54% of patients and additional progression for 38 %. Two patients with neuropathology-confirmed atypical neurocytomas died at 4.3 and 113.4 months after initial surgery. For central neurocytomas, MIB-1 labeling index >4% is predictive of poorer outcome and our data suggest that adjuvant radiotherapy after STR may improve PFS. Most patients requiring salvage therapy will be stabilized and multiple modalities can be effectively utilized

SNPLogic: an interactive single nucleotide polymorphism selection, annotation, and prioritization system

SNPLogic (http://www.snplogic.org) brings together single nucleotide polymorphism (SNP) information from numerous sources to provide a comprehensive SNP selection, annotation and prioritization system for design and analysis of genotyping projects. SNPLogic integrates information about the genetic context of SNPs (gene, chromosomal region, functional location, haplotypes tags and overlap with transcription factor binding sites, splicing sites, miRNAs and evolutionarily conserved regions), genotypic data (allele frequencies per population and validation method), coverage of commercial arrays (ParAllele, Affymetrix and Illumina), functional predictions (modeled on structure and sequence) and connections or established associations (biological pathways, gene ontology terms and OMIM disease terms). The SNPLogic web interface facilitates construction and annotation of user-defined SNP lists that can be saved, shared and exported. Thus, SNPLogic can be used to identify and prioritize candidate SNPs, assess custom and commercial arrays panels and annotate new SNP data with publicly available information. We have found integration of SNP annotation in the context of pathway information and functional prediction scores to be a powerful approach to the analysis and interpretation of SNP-disease association data