From Pediatric to Adult Brain Cancer: Exploring Histone H3 Mutations in Australian Brain Cancer Patients

Genetic histone variants have been implicated in cancer development and progression. Mutations affecting the histone 3 (H3) family, H3.1 (encoded by HIST1H3B and HIST1H3C) and H3.3 (encoded by H3F3A), are mainly associated with pediatric brain cancers. While considered poor prognostic brain cancer biomarkers in children, more recent studies have reported H3 alterations in adult brain cancer as well. Here, we established reliable droplet digital PCR based assays to detect three histone mutations (H3.3-K27M, H3.3-G34R, and H3.1-K27M) primarily linked to childhood brain cancer. We demonstrate the utility of our assays for sensitively detecting these mutations in cell-free DNA released from cultured diffuse intrinsic pontine glioma (DIPG) cells and in the cerebral spinal fluid of a pediatric patient with DIPG. We further screened tumor tissue DNA from 89 adult patients with glioma and 1 with diffuse hemispheric glioma from Southwestern Sydney, Australia, an ethnically diverse region, for these three mutations. No histone mutations were detected in adult glioma tissue, while H3.3-G34R presence was confirmed in the diffuse hemispheric glioma patient.

Predicting Histopathological Grading of Adult Gliomas Based On Preoperative Conventional Multimodal MRI Radiomics: A Machine Learning Model

PURPOSE

The accurate preoperative histopathological grade diagnosis of adult gliomas is of great significance for the formulation of a surgical plan and the implementation of a subsequent treatment. The aim of this study is to establish a predictive model for classifying adult gliomas into grades 2-4 based on preoperative conventional multimodal MRI radiomics.

PATIENTS AND METHODS

Patients with pathologically confirmed gliomas at Huashan Hospital, Fudan University, between February 2017 and July 2019 were retrospectively analyzed. Two regions of interest (ROIs), called the maximum anomaly region (ROI1) and the tumor region (ROI2), were delineated on the patients' preoperative MRIs utilizing the tool ITK-SNAP, and Pyradiomics 3.0 was applied to execute feature extraction. Feature selection was performed utilizing a least absolute shrinkage and selection operator (LASSO) filter. Six classifiers, including Gaussian naive Bayes (GNB), random forest (RF), K-nearest neighbor (KNN), support vector machine (SVM) with a linear kernel, adaptive boosting (AB), and multilayer perceptron (MLP) were used to establish predictive models, and the predictive performance of the six classifiers was evaluated through five-fold cross-validation. The performance of the predictive models was evaluated using the AUC and other metrics. After that, the model with the best predictive performance was tested using the external data from The Cancer Imaging Archive (TCIA).

RESULTS

According to the inclusion and exclusion criteria, 240 patients with gliomas were identified for inclusion in the study, including 106 grade 2, 68 grade 3, and 66 grade 4 gliomas. A total of 150 features was selected, and the MLP classifier had the best predictive performance among the six classifiers based on T2-FLAIR (mean AUC of 0.80 ± 0.07). The SVM classifier had the best predictive performance among the six classifiers based on DWI (mean AUC of 0.84 ± 0.05); the SVM classifier had the best predictive performance among the six classifiers based on CE-T1WI (mean AUC of 0.85 ± 0.06). Among the six classifiers, based on ROI1, the MLP classifier had the best prediction performance (mean AUC of 0.78 ± 0.07); among the six classifiers, based on ROI2, the SVM classifier had the best prediction performance (mean AUC of 0.82 ± 0.07). Among the six classifiers, based on the multimodal MRI of all the ROIs, the SVM classifier had the best prediction performance (average AUC of 0.85 ± 0.04). The SVM classifier, based on the multimodal MRI of all the ROIs, achieved an AUC of 0.81 using the external data from TCIA.

CONCLUSIONS

The prediction model, based on preoperative conventional multimodal MRI radiomics, established in this study can conveniently, accurately, and noninvasively classify adult gliomas into grades 2-4, providing certain assistance for the precise diagnosis and treatment of patients and optimizing their clinical management.

Antibodies to varicella-zoster virus and three other herpesviruses and survival in adults with glioma

BACKGROUND

Lifetime exposure to the varicella-zoster virus (VZV) has been consistently inversely associated with glioma risk, however, the relationship of VZV with survival in adults with glioma has not been investigated. In this study, we analyzed the survival of adults with glioma in relation to their antibody measurements to 4 common herpes viral infections, including VZV, measured post-diagnosis.

METHODS

We analyzed IgG antibody measurements to VZV, cytomegalovirus (CMV), herpes simplex virus 1/2 (HSV), and Epstein-Barr virus (EBV) collected from 1378 adults with glioma diagnosed between 1991 and 2010. Blood was obtained a median of 3 months after surgery. Associations of patient IgG levels with overall survival were estimated using Cox models adjusted for age, sex, self-reported race, surgery type, dexamethasone usage at blood draw, and tumor grade. Models were stratified by recruitment series and meta-analyzed to account for time-dependent treatment effects.

RESULTS

VZV antibody seropositivity was associated with improved survival outcomes in adults with glioma (Hazard ratio, HR = 0.70, 95% Confidence Interval 0.54-0.90, P = .006). Amongst cases who were seropositive for VZV antibodies, survival was significantly improved for those above the 25th percentile of continuous reactivity measurements versus those below (HR = 0.76, 0.66-0.88, P = .0003). Antibody seropositivity to EBV was separately associated with improved survival (HR = 0.71, 0.53-0.96, P = .028). Antibody positivity to 2 other common viruses (CMV, HSV) was not associated with altered survival.

CONCLUSIONS

Low levels of VZV or EBV antibodies are associated with poorer survival outcomes for adults with glioma. Differential immune response rather than viral exposure may explain these findings.

A systematic review and meta-analysis examining the effects of cannabis and its derivatives in adults with malignant CNS tumors

Background

Primary CNS tumors constitute a heterogeneous group of neoplasms that share a considerable morbidity and mortality rate. To help control tumor growth and clinical outcomes (overall survival, progression-free survival, quality of life) symptoms, patients often resort to alternative therapies, including the use of cannabis. Despite rapidly growing popularity, cannabis and its impact on patients with primary malignant CNS tumors is understudied.

Methods

To shed light on the lack of scientific evidence in this field, in November 2018 we conducted a search and examination of cannabis in neuro-oncology in major journal databases and bibliographies of selected articles, and through abstracts of annual meetings using prespecified criteria in line with the Cochrane Collaboration guidelines.

Results

We identified 45 publications, of which 9 were selected. Five studies were included. Publication dates ranged from 2004 to 2018 and included varying histologies of primary brain tumors. The average survival at 1 year was 56.09% (95% CI: 48.28-63.9). There was no difference in risk ratio (RR) for death at 1 year between groups (RR: 1.069 [95% CI: 0.139-8.25]). We found strong evidence of heterogeneity (Q = 74.0%; P = .021). We found no statistical evidence of publication bias (P = .117; SD = 1.91).

Conclusions

There was limited moderate-quality evidence that supports the use of cannabinoids as adjuvant to the standard of care in the treatment of brain and CNS tumors. There was very low-quality evidence suggesting that cannabinoids were associated with adult-onset gliomas. Further prospective clinical trials are necessary to adequately evaluate the impact of cannabinoids on CNS tumors, specifically on survival and quality of life.

Comparative Molecular Life History of Spontaneous Canine and Human Gliomas

Sporadic gliomas in companion dogs provide a window on the interaction between tumorigenic mechanisms and host environment. We compared the molecular profiles of canine gliomas with those of human pediatric and adult gliomas to characterize evolutionarily conserved mammalian mutational processes in gliomagenesis. Employing whole-genome, exome, transcriptome, and methylation sequencing of 83 canine gliomas, we found alterations shared between canine and human gliomas such as the receptor tyrosine kinases, TP53 and cell-cycle pathways, and IDH1 R132. Canine gliomas showed high similarity with human pediatric gliomas per robust aneuploidy, mutational rates, relative timing of mutations, and DNA-methylation patterns. Our cross-species comparative genomic analysis provides unique insights into glioma etiology and the chronology of glioma-causing somatic alterations.

Inherited variant on chromosome 11q23 increases susceptibility to IDH-mutated but not IDH-normal gliomas regardless of grade or histology

INTRODUCTION

Recent discoveries of inherited glioma risk loci and acquired IDH mutations are providing new insights into glioma etiology. IDH mutations are common in lower grade gliomas and secondary glioblastomas and uncommon in primary glioblastomas. Because the inherited variant in 11q23 has been associated with risk of lower grade glioma and not with glioblastomas, we hypothesized that this variant increases susceptibility to IDH-mutated gliomas, but not to IDH-wild-type gliomas.

METHODS

We tested this hypothesis in patients with glioma and controls from the San Francisco Adult Glioma Study, the Mayo Clinic, and Illumina controls (1102 total patients, 5299 total controls). Case-control additive associations of 11q23 risk alleles (rs498872, T allele) were calculated using logistic regression, stratified by tumor IDH status (mutated or wild-type) and by histology and grade. We also adjusted for the recently discovered 8q24 glioma risk locus rs55705857 G allele.

RESULTS

The 11q23 glioma risk locus was associated with increased risk of IDH-mutated gliomas of all histologies and grades (odds ratio [OR] = 1.50; 95% confidence interval [CI] = 1.29-1.74; P = 1.3X10(-7)) but not with IDH-wild-type gliomas of any histology or grade (OR = 0.91; 95% CI = 0.81-1.03; P = 0.14). The associations were independent of the rs55705857 G allele.

CONCLUSION

A variant at the 11q23 locus increases risk for IDH-mutated but not IDH-wild-type gliomas, regardless of grade or histology.