Malignant gliomas are the most common and deadly brain tumors. Although their etiology remains elusive, recent studies have narrowed the search for genetic loci that influence risk. We examined variants implicated in recent cancer genome-wide association studies (GWAS) for associations with glioma risk in a US case–control study. Cases were identified from neurosurgical and neuro-oncology clinics at major academic centers in the Southeastern US. Controls were identified from the community or were friends or other associates of cases. We examined a total of 191 susceptibility variants in genes identified in published cancer GWAS including glioma. A total of 639 glioma cases and 649 controls, all Caucasian, were included in analysis. Cases were enrolled a median of 1 month following diagnosis. Among glioma GWAS-identified variants, we detected associations in CDKN2B, RTEL1, TERT and PHLDB1, whereas we did not find overall associations for CCDC26. Results showed clear heterogeneity according to histologic subtypes of glioma, with TERT and RTEL variants a feature of astrocytic tumors and glioblastoma (GBM), CCDC26 and PHLDB1 variants a feature of astrocytic and oligodendroglial tumors, and CDKN2B variants most prominent in GBM. No examined variant in other cancer GWAS was found to be related to risk after adjustment for multiple comparisons. These results suggest that GWAS-identified SNPs in glioma mark different molecular etiologies in glioma. Stratification by broad histological subgroups may shed light on molecular mechanisms and assist in the discovery of novel loci in future studies of genetic susceptibility variants in glioma.

This animal study suggests that nerve expansion seen on ultrasound during intraneural injection of clinically relevant volumes of LA results in histologic but not functional nerve injury.

MicroRNAs (miRNAs) are non-coding RNAs that function as post-transcriptional regulators of tumor suppressors and oncogenes. Single nucleotide polymorphisms (SNPs) in miRNAs may contribute to carcinogenesis by altering expression of miRNAs and their targets. A G>C polymorphism (rs2910164) in the miR-146a precursor sequence leads to a functional change associated with the risk for numerous malignancies. A role for this SNP in glioma pathogenesis has not yet been examined. We investigated whether rs2910164 genotypes influence glioma risk and prognosis in a multi-center case–control study comprised of 593 Caucasian glioma cases and 614 community-based controls. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for rs2910164 genotypes according to case status. Cox proportional hazards regression modeling was used to estimate hazards ratios (HR) and 95% CIs according to genotype among glioblastomas, the most lethal glioma subtype. An increased glioma risk was observed among rs2910164 minor allele (C) carriers (per allele OR (95% CI) = 1.22 (1.01–1.46, ptrend = 0.039)). The association was stronger among older subjects carrying at least one copy of the C allele (OR (95% CI) = 1.38 (1.04–1.83, P = 0.026). Mortality was increased among minor allele carriers (HR (95% CI) = 1.33 (1.03–1.72, P = 0.029)), with the association largely restricted to females (HR (95% CI) = 2.02 (1.28–3.17, P = 0.002)). We provide novel data suggesting rs2910164 genotype may contribute to glioma susceptibility and outcome. Future studies are warranted to replicate these findings and characterize mechanisms underlying these associations.

Purpose There is growing evidence that circadian disruption may alter risk and aggressiveness of cancer. We evaluated common genetic variants in the circadian gene pathway for associations with glioma risk and patient outcome in a US clinic-based case-control study. Methods Subjects were genotyped for 17 candidate single nucleotide polymorphisms (SNPs) in ARNTL, CRY1, CRY2, CSNK1E, KLHL30, NPAS2, PER1, PER3, CLOCK and MYRIP. Unconditional logistic regression was used to estimate age and gender-adjusted odds ratios (OR) and 95% confidence intervals (CI) for glioma risk under three inheritance models (additive, dominant and recessive). Proportional hazards regression was used to estimate hazard ratios (HR) for glioma-related death among 441 patients with high grade tumors. Survival associations were validated using a TCGA (The Cancer Genome Atlas) dataset. Results A variant in PER1 (rs2289591) was significantly associated with overall glioma risk (per variant allele OR: 0.80; 95% CI: 0.66–0.97; ptrend=0.027). The variant allele for CLOCK rs11133391 under a recessive model increased risk of oligodendroglioma (OR: 2.41; 95% CI: 1.31–4.42; p=0.005), though not other glioma subtypes (p for heterogeneity=0.0033). The association remained significant after FDR adjustment (p=0.008). Differential associations by gender were observed for MYRIP rs6599077 and CSNK1E rs1534891 though differences were not significant after adjustment for multiple testing. No consistent mortality associations were identified. Several of the examined genes exhibited differential expression in GBM versus normal brain in TCGA data (MYRIP, ARNTL, CRY1, KLHL30, PER1, CLOCK, PER3) and expression of NPAS2 was significantly associated with a poor patient outcome in TCGA patients. Conclusion This exploratory analysis provides some evidence supporting a role for circadian genes in the onset of glioma and possibly the outcome of glioma.

Introduction Greater adiposity has been linked to an increased risk and/or poorer survival in a variety of cancers. We examined whether prediagnostic body weight 1–5 years prior to diagnosis is associated with survival in patients with high grade glioma. Methods The analysis was based on a series of patients with high-grade glioma (N=853) enrolled in a US-based multicenter case-control study. Subjects reported height and weight 1–5 years prior to interview and at age 21. BMI was categorized according to WHO criteria as underweight (BMI<18.5kg/m2), normal weight (BMI 18.5–24.9kg/m2), overweight (BMI 25–29.9kg/m2) and obese (BMI≥30kg/m2). Proportional hazards regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CIs) for glioma-related death according to body mass index (BMI, kg/m2). Results Overall survival was reduced among patients underweight (median survival: 12.0 months) or obese (median: 13.6 months) when compared to patients of normal weight (median: 17.5 months) prior to glioma diagnosis (p=0.004). In a multivariate model controlling for other prognostic factors, an excess mortality was observed in patients reporting obese body weights 1–5 years prior to study interview when compared to patients with a normal BMI (HR=1.32; 95% CI:1.04–1.68). Consistent patterns of association with excess body weight were observed in men and women, and all findings were similar regardless of treatment for glioma. A lower than optimal body weight was associated with a nonsignificant excess mortality in multivariate analysis. Conclusions Premorbid obesity was significantly associated with a poor patient outcome independent of treatment and established prognostic factors. Excess body weight may be an adverse prognostic factor in glioma, a relationship observed across a spectrum of cancer types. The current findings linking prediagnostic body weight with mortality in high-grade glioma warrant further research.