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Object: Magnetic resonance fingerprinting (MRF) allows rapid, simultaneous mapping of T1 and T2 relaxation times and may be an important diagnostic tool to measure tissue characteristics in pediatric brain tumors. We examined children and young adults with primary brain tumors to determine whether MRF can discriminate tumor from normal-appearing white matter and distinguish tumor grade. Methods: MRF was performed in 23 patients (14 children and 9 young adults) with brain tumors (19 low-grade glioma, 4 high-grade tumors). T1 and T2 values were recorded in regions of solid tumor (ST), peritumoral white matter (PWM), and contralateral white matter (CWM). Nonparametric tests were used for comparison between groups and regions. Results: Median scan time for MRF and a sequence for tumor localization was 11 min. MRF-derived T1 and T2 values distinguished ST from CWM (T1: 1,444 ± 254 ms vs. 938 ± 96 ms, p = 0.0002; T2: 61 ± 22 ms vs. 38 ± 9 ms, p = 0.0003) and separated high-grade tumors from low-grade tumors (T1: 1,863 ± 70 ms vs. 1,355 ± 187 ms, p = 0.007; T2: 90 ± 13 ms vs. 56 ± 19 ms, p = 0.013). PWM was distinct from CWM (T1: 1,261 ± 359 ms vs. 933 ± 104 ms, p = 0.0008; T2: 65 ± 51 ms vs. 38 ± 8 ms, p = 0.008), as well as from tumor (T1: 1,261 ± 371 ms vs. 1,462 ± 248 ms, p = 0.047). Conclusions: MRF is a fast sequence that can rapidly distinguish important tissue components in pediatric brain tumor patients. MRF-derived T1 and T2 distinguished tumor from normal-appearing white matter, differentiated tumor grade, and found abnormalities in peritumoral regions. MRF may be useful for rapid quantitative measurement of tissue characteristics and distinguish tumor grade in children and young adults with brain tumors.

The evolutionary processes that drive universal therapeutic resistance in adult patients with diffuse glioma remain unclear1,2. Here we analysed temporally separated DNA-sequencing data and matched clinical annotation from 222 adult patients with glioma. By analysing mutations and copy numbers across the three major subtypes of diffuse glioma, we found that driver genes detected at the initial stage of disease were retained at recurrence, whereas there was little evidence of recurrence-specific gene alterations. Treatment with alkylating agents resulted in a hypermutator phenotype at different rates across the glioma subtypes, and hypermutation was not associated with differences in overall survival. Acquired aneuploidy was frequently detected in recurrent gliomas and was characterized by IDH mutation but without co-deletion of chromosome arms 1p/19q, and further converged with acquired alterations in the cell cycle and poor outcomes. The clonal architecture of each tumour remained similar over time, but the presence of subclonal selection was associated with decreased survival. Finally, there were no differences in the levels of immunoediting between initial and recurrent gliomas. Collectively, our results suggest that the strongest selective pressures occur during early glioma development and that current therapies shape this evolution in a largely stochastic manner.

The National Cancer Institute Comprehensive Oncology Network Evaluating Rare CNS Tumors (NCI-CONNECT) program focuses on improving approaches to care and treatment for 12 rare CNS tumors, each with < 2,000 diagnoses per year. To reach this rare population, the primary objective was to develop a website to share educational resources that provide patients direct access to clinical care and trials. METHODS: The NCI-CONNECT website uses the Drupal platform within NCI’s framework and the content is free to syndicate. A multidisciplinary team developed tumor-specific content in English and Spanish, clinical trial information, and survivorship resources using evidence-based sources. The Central Brain Tumor Registry of the United States provided statistics on incidence and prevalence of rare tumors. Population reach was calculated using Adobe Experience Cloud website analytics. NCI-CONNECT referrals and study participation data were collected prospectively. RESULTS: The English website launched in September 2018 and visits have increased 2,384%. The Spanish website launched in March 2020 and visits have increased 1,137%. From April 2020 to March 2021, top website page views by English page views / Spanish page views / people living with this disease include oligodendroglioma (43,859 / 8,241 / 11,757), ependymoma (31,579 / 12,684 / 13,294), meningioma (30,261 / 19,507 / 2,692), medulloblastoma (28,487 / 9,999 / 3,840), diffuse midline gliomas (23,064 / 3,851 / 6,033), and pineal region tumors (19,939 / 9,973 / 1,297). Referral rates and participation have accelerated – 45% of patients visiting the Neuro-Oncology Clinic at NIH have a rare CNS tumor and 409 patients enrolled in an NCI-CONNECT study. CONCLUSION: Patient-focused websites can provide guidance to those affected by rare cancers outside of in-person health care visits. The NCI-CONNECT website is an educational and clinical resource for patients and families affected by rare CNS tumors and was created to raise awareness and improve patient outcomes.

PURPOSE Multi-parametric MRI and artificial intelligence (AI) methods were previously used to predict peritumoral neoplastic cell infiltration and risk of future recurrence in glioblastoma, in single-institution studies. We hypothesize that important characteristics of peritumoral tissue heterogeneity captured, engineered/selected, and quantified by these methods relate to predictions generalizable in the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium. METHODS To support further development, generalization, and clinical translation of our proposed method, we trained the AI model on a retrospective cohort of 29 de novo glioblastoma patients from the Hospital of the University of Pennsylvania (UPenn) (Male/Female:20/9, age:22-78 years) followed by evaluation on a prospective multi-institutional cohort of 84 glioblastoma patients (Male/Female:51/33, age:34-89 years) from Case Western Reserve University/University Hospitals (CWRU/UH, 25), New York University (NYU, 13), Ohio State University (OSU, 13), University Hospital Río Hortega (RH, 2), and UPenn (31). Features extracted from pre-resection MRI (T1, T1-Gd, T2, T2-FLAIR, ADC) were used to build our model predicting the spatial pattern of subsequent tumor recurrence. These predictions were evaluated against regions of pathology-confirmed post-resection recurrence. RESULTS Our model predicted the locations that later harbored tumor recurrence with sensitivity 83%, AUC 0.83 (99% CI, 0.73-0.93), and odds ratio 7.23 (99% CI, 7.09-7.37) in the prospective cohort. Odds ratio (99% CI)/AUC(99% CI) per institute were: CWRU/UH, 7.8(7.6-8.1)/0.82(0.75-0.89); NYU, 3.5(3.3-3.6)/0.84(074-0.93); OSU, 7.9(7.6-8.3)/0.8(0.67-0.94); RH, 22.7(20-25.1)/0.94(0.27-1); UPenn, 7.1(6.8-7.3)/0.83(0.76-0.91). CONCLUSION This is the first study that provides relatively extensive multi-institutional validated evidence that AI can provide good predictions of peritumoral neoplastic cell infiltration and future recurrence, by dissecting the MRI signal heterogeneity in peritumoral tissue. Our analyses leveraged the unique dataset of the ReSPOND consortium, which aims to develop and evaluate AI-based biomarkers for individualized prediction and prognostication, by moving from single-institution studies to generalizable, well-validated multi-institutional predictive biomarkers.

PURPOSE: Glioma is the most common type of primary malignant brain tumor, and incidence is 25% lower in U.S. Hispanics than White non-Hispanics. Though often pooled in epidemiological analyses, the U.S. Hispanic population is very diverse, and registry-based analyses may mask incidence and survival differences associated with geographic/ancestral origins. METHODS: County-level glioma incidence data in U.S. Hispanics from 2000-2017 were retrieved from the Central Brain Tumor Registry of the United States, and survival data from the CDC’s National Program of Cancer Registries was obtained for 2001-2017. American Community Survey data were used to determine county-level proportion of the Hispanic population of Mexican/Central-American origin and of Caribbean origin (Puerto Rican, Cuban, Dominican). State-level estimates of European and African admixture in Hispanics were obtained from published 23andMe data. Incidence rate ratios (IRRs) quantified the glioma incidence differences across groups. County-level incidence was modeled using linear regression to control for potential confounding factors (e.g., county size, median socioeconomic status), and Cox proportional hazards models were used to assess associations between individual-level survival, county-level origin percentages, and state-level admixture. RESULTS: Compared to Hispanics living in predominantly Caribbean-origin counties, Hispanics from predominantly Mexican/Central-American-origin counties had lower age-adjusted risks of glioma (IRR=0.83; P CONCLUSIONS: Glioma incidence and outcomes differ in association with the geographic origins of the Hispanic community, with residents of predominantly Mexican/Central-American-origin counties at significantly reduced risk and those of Caribbean-origin counties at comparatively greater risk. Although typically classified as a single ethnic group in registry data, appreciating the cultural, socioeconomic, and genetic diversity of U.S. Hispanics will help advance cancer disparities research. Citation Format: Kyle M. Walsh, Corey Neff, Melissa L. Bondy, Carol Kruchko, Jason T. Huse, Christopher I. Amos, Jill S. Barnholtz-Sloan, Quinn T. Ostrom. Influence of geographic/ancestral origin on glioma incidence and outcomes in US Hispanics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 26.

Lung cancer is the leading cause of cancer-related death and the second most often diagnosed malignancy worldwide. Males have higher incidence of lung cancer and higher mortality. It is hypothesized that the sex differences in survival are primarily driven by a better response of females to treatment. The primary objective of this work is to analyze and describe outcome differences between males and females diagnosed with having lung cancer.Data were obtained from a large hybrid academic-community practice institution and validated with Surveillance, Epidemiology, and End Results (SEER). The initial cohort included patients aged more than or equal to 18 years diagnosed with having primary malignant lung cancer. Patients were excluded from the analysis if they had an unknown diagnosis date, were missing sex, or had prior history of cancer. Chi-square,A total of 8909 patients from our institution and 725,018 in SEER were analyzed. Male-to-female ratio was 1.0. Females were more likely to undergo surgery and less likely to be treated with immunotherapy. Females had higher rates of documented psychological affections, depression, anxiety, urinary tract infection, hypothyroidism, and hyperthyroidism, while displaying lower rates of acute kidney injury, myocardial infarction, and myocarditis. Paired multivariable models revealed a lower risk of death for females in SEER (hazard ratio for females = 0.84, confidence interval: 0.69-1.02,Female sex was associated with higher surgical rates, lower immunotherapy use rates, higher rates of endocrinologic complications after immunotherapy use, and higher rates of psychological disorders.

Glioblastomas (GBMs) are the most aggressive primary brain tumors, with an average survival of less than 15 months. Therefore, there is a critical need to develop novel therapeutic strategies for GBM. This study aimed to assess the prognostic value of miR-4516 and investigate its oncogenic functions and the underlying cellular and molecular mechanisms in GBM. To determine the correlation between miR-4516 expression and overall survival of patients with GBM, total RNAs were isolated from 268 FFPE tumor samples, miR expression was assayed (simultaneously) using the nCounter human miRNA v3a assay followed by univariable and multivariable survival analyses. Further, in vitro and in vivo studies were conducted to define the role of miR-4516 in GBM tumorigenesis and the underlying molecular mechanisms. Upon multivariable analysis, miR-4516 was correlated with poor prognosis in GBM patients (HR = 1.49, 95%CI: 1.12-1.99, P = 0.01). Interestingly, the significance of miR-4516 was retained including MGMT methylation status. Overexpression of miR-4516 significantly enhanced cell proliferation and invasion of GBM cells both in vitro and in vivo. While conducting downstream targeting studies, we found that the tumor-promoting function of miR-4516, in part, was mediated by direct targeting of PTPN14 (protein tyrosine phosphatase, non-receptor type 14) which, in turn, regulated the Hippo pathway in GBM. Taken together, our data suggest that miR-4516 represents an independent negative prognostic factor in GBM patients and acts as a novel oncogene in GBM, which regulates the PTPN14/Hippo pathway. Thus, this newly identified miR-4516 may serve as a new potential therapeutic target for GBM treatment.

BACKGROUND: The goal of this study was to provide up-to-date and comprehensive statistics on incidence, survival, and prevalence rates for selected malignant brain and other CNS tumors in adults. METHODS: The current study used data from the Central Brain Tumor Registry of the United States, provided by the Centers for Disease Control and Prevention, to examine incidence and data from the Surveillance, Epidemiology, and End Results program to examine survival and prevalence in 16 distinct malignant brain and other CNS histologies in adults (aged 20 y and older at diagnosis) from 2000–2014 overall and by sex, age group, race, and ethnicity. RESULTS: Glioblastoma had the highest incidence (4.40 per 100000) and prevalence (9.23 per 100000). Ependymal tumors had the highest 5- and 10-year relative survivals (87.8% and 84.5%, respectively), while glioblastoma had the lowest 5- and 10-year relative survivals (5.4% and 2.7%, respectively). Females generally had better survival and lower prevalence than males. Younger adults tended to have better survival than older adults, and prevalence varied greatly by age and histology. While survival did not vary significantly by race, white adults had higher prevalence than the other race groups. Hispanics generally had better survival rates and lower prevalence than non-Hispanics. CONCLUSIONS: Survival varied greatly by age and ethnicity. Prevalence differed by sex, age, race, and ethnicity.

The ClinGen PTEN Expert Panel was organized by the ClinGen Hereditary Cancer Clinical Domain Working Group to assemble clinicians, researchers, and molecular diagnosticians with PTEN expertise to develop specifications to the 2015 ACMG/AMP Sequence Variant Interpretation Guidelines for PTEN variant interpretation. We describe finalized PTEN-specific variant classification criteria and outcomes from pilot testing of 42 variants with benign/likely benign (BEN/LBEN), pathogenic/likely pathogenic (PATH/LPATH), uncertain significance (VUS), and conflicting (CONF) ClinVar assertions. Utilizing these rules, classifications concordant with ClinVar assertions were achieved for 14/15 (93.3%) BEN/LBEN and 16/16 (100%) PATH/LPATH ClinVar consensus variants for an overall concordance of 96.8% (30/31). The variant where agreement was not reached was a synonymous variant near a splice donor with non-canonical sequence for which in silico models cannot predict the native site. Applying these rules to six VUS and five CONF variants, adding shared internal laboratory data enabled one VUS to be classified as LBEN and two CONF variants to be as classified as PATH and LPATH. This study highlights the benefit of gene-specific criteria and the value of sharing internal laboratory data for variant interpretation. Our PTEN-specific criteria and expertly reviewed assertions should prove helpful for laboratories and others curating PTEN variants.

Objectives To develop nomograms predicting overall survival (OS), freedom from locoregional recurrence (FFLR), and freedom from distant metastasis (FFDM) for patients receiving chemoradiation for laryngeal squamous cell carcinoma (LSCC). Material and methods Clinical and treatment data for patients with LSCC enrolled on NRG Oncology/RTOG 0129 and 0522 were extracted from the RTOG database. The dataset was partitioned into 70% training and 30% independent validation datasets. Significant predictors of OS, FFLR, and FFDM were obtained using univariate analysis on the training dataset. Nomograms were built using multivariate analysis with four a priori variables (age, gender, T-stage, and N-stage) and significant predictors from the univariate analyses. These nomograms were internally and externally validated using c-statistics (c) on the training and validation datasets, respectively. Results The OS nomogram included age, gender, T stage, N stage, and number of cisplatin cycles. The FFLR nomogram included age, gender, T-stage, N-stage, and time-equivalent biologically effective dose. The FFDM nomogram included age, gender, N-stage, and number of cisplatin cycles. Internal validation of the OS nomogram, FFLR nomogram, and FFDM nomogram yielded c = 0.66, c = 0.66 and c = 0.73, respectively. External validation of these nomograms yielded c = 0.59, c = 0.70, and c = 0.73, respectively. Using nomogram score cutoffs, three risk groups were separated for each outcome. Conclusions We have developed and validated easy-to-use nomograms for LSCC outcomes using prospective cooperative group trial data.

Background Gliomas represent a biologically heterogeneous group of primary brain tumors with uncontrolled cellular proliferation and diffuse infiltration that renders them almost incurable, thereby leading to a grim prognosis. Recent comprehensive genomic profiling has greatly elucidated the molecular hallmarks of gliomas, including the mutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), loss of chromosomes 1p and 19q (1p/19q), and epidermal growth factor receptor variant III (EGFRvIII). Detection of these molecular alterations is based on ex vivo analysis of surgically resected tissue specimen that sometimes is not adequate for testing and/or does not capture the spatial tumor heterogeneity of the neoplasm. Methods We developed a method for noninvasive detection of radiogenomic markers of IDH both in lower-grade gliomas (WHO grade II and III tumors) and glioblastoma (WHO grade IV), 1p/19q in IDH-mutant lower-grade gliomas, and EGFRvIII in glioblastoma. Preoperative MRIs of 473 glioma patients from 3 of the studies participating in the ReSPOND consortium (collection I: Hospital of the University of Pennsylvania [HUP: n = 248], collection II: The Cancer Imaging Archive [TCIA; n = 192], and collection III: Ohio Brain Tumor Study [OBTS, n = 33]) were collected. Neuro-Cancer Imaging Phenomics Toolkit (neuro-CaPTk), a modular platform available for cancer imaging analytics and machine learning, was leveraged to extract histogram, shape, anatomical, and texture features from delineated tumor subregions and to integrate these features using support vector machine to generate models predictive of IDH, 1p/19q, and EGFRvIII. The models were validated using 3 configurations: (1) 70–30% training–testing splits or 10-fold cross-validation within individual collections, (2) 70–30% training–testing splits within merged collections, and (3) training on one collection and testing on another. Results These models achieved a classification accuracy of 86.74% (HUP), 85.45% (TCIA), and 75.15% (TCIA) in identifying EGFRvIII, IDH, and 1p/19q, respectively, in configuration I. The model, when applied on combined data in configuration II, yielded a classification success rate of 82.50% in predicting IDH mutation (HUP + TCIA + OBTS). The model when trained on TCIA dataset yielded classification accuracy of 84.88% in predicting IDH in HUP dataset. Conclusions Using machine learning algorithms, high accuracy was achieved in the prediction of IDH, 1p/19q, and EGFRvIII mutation. Neuro-CaPTk encompasses all the pipelines required to replicate these analyses in multi-institutional settings and could also be used for other radio(geno)mic analyses.

BackgroundGliomas are the most common type of primary malignant brain tumor in adults, representing one third of all primary and central nervous system (CNS) tumors and 80% of malignant tumors diagnosed in the Western world. Epidemiological data indicate that the overall incidence and mortality of cancer is higher in males, while females have a better prognosis. The goal of this study is to determine whether there are sex differences in the time to treat and clinical outcomes in patients with gliomaMethodsGlioblastoma (GB) and Lower Grade Glioma (LGG) patients were defined per the Central Brain Tumor Registry of the United States (CBTRUS) from the National Cancer Database (NCDB) for diagnosis years 2004 to 2016. Associations between sex and time to treatment variables as well as associations between sex and multiple clinical outcomes were assessed using univariable and multivariable models.ResultsA total of 176,100 patients were used for analysis (124,502 GBM and 51,598 LGG). Males had a statistically significant association with >7 days to surgery (OR = 1.09, CI 1.05–1.13, p < 0.001) but this association was not observed in the multivariable model (OR = 1.05, CI 0.96–1.16, p = 0.25). After adjustment for key variables including time to treat variables, males with GB and LGG had a higher risk of death (HR = 1.11, CI 1.09–1.13, p < 0.001, HR = 1.09, CI 1.03–1.15, p < 0.001; respectfully). Sex differences in 90-day mortality for GBM were not found after adjustment (OR for males = 0.99, CI 0.91–1.08, p = 0.93). For LGG, both the univariable and multivariable logistic regression models showed no sex differences in 90-day mortality (OR for males = 1.03, CI 0.94–1.12, p = 0.45; multivariable OR for males = 0.81, CI 0.62–1.06, p = 0.13).ConclusionsBased on NCDB data, there were no statistically significant differences in time to treatment between males and females, however males had a higher proportion of GB and LGG as well as a higher risk of death compared to females.

Craniopharyngiomas are rare benign brain tumors originating from errors in differentiation during embryogenesis. Given current interest in treatments that target genetic and molecular signatures of specific craniopharyngioma subtypes, updated and comprehensive epidemiologic data of these subtypes are necessary to inform and direct resources.We utilized data from the Central Brain Tumor Registry of the United States (CBTRUS), which represents 100% of the US population. Incidence by demographics was calculated only for histologically-confirmed cases. Age-adjusted annual incidence was calculated and is reported per 100,000 persons. Annual percent change (APC) in incidence rates from 2004 to 2016 was calculated to assess trends.From 2004 to 2016, 7441 craniopharyngiomas were diagnosed in the United States, representing approximately 620 new cases each year. The incidence for histologically-confirmed cases was 0.16 per 100,000 persons. The age distribution was bimodal, with one peak in 5- to 9-year-olds and another in 55- to 69-year-olds. Compared with adamantinomatous tumors, papillary craniopharyngiomas only represented 5.5% of the histologically diagnosed craniopharyngiomas in 0- to 29-year-olds, 30.6% in 30- to 59-year-olds, and 30.4% in 60 + year-olds. Incidence was highest amongst Blacks (0.22), followed by Whites (0.15), Asians or Pacific Islanders (0.14), and American Indians/Alaska Natives (0.10). No significant difference was discovered in incidence rates between males and females or Hispanic and non-Hispanic ethnicities.Craniopharyngiomas are rare tumors with a bimodal age distribution and an equal male-to-female incidence. Black patients had the highest incidence, and adamantinomatous craniopharyngiomas were significantly more common than papillary tumors in adolescent, adult, and elderly populations.

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment. Wang et al. perform integrated proteogenomic analysis of adult glioblastoma (GBM), including metabolomics, lipidomics, and single nuclei RNA-Seq, revealing insights into the immune landscape of GBM, cell-specific nature of EMT signatures, histone acetylation in classical GBM, and the existence of signaling hubs which could provide therapeutic vulnerabilities.

BackgroundThe functions of most glioma risk alleles are unknown. Very few studies had evaluated expression quantitative trait loci (eQTL), and insights of susceptibility genes were limited due to scarcity of available brain tissues. Moreover, no prior study had examined the effect of glioma risk alleles on alternative RNA splicing.ObjectiveThis study explored splicing quantitative trait loci (sQTL) as molecular QTL and improved the power of QTL mapping through meta-analyses of both cis eQTL and sQTL.MethodsWe first evaluated eQTLs and sQTLs of the CommonMind Consortium (CMC) and Genotype-Tissue Expression Project (GTEx) using genotyping, or whole-genome sequencing and RNA-seq data. Alternative splicing events were characterized using an annotation-free method that detected intron excision events. Then, we conducted meta-analyses by pooling the eQTL and sQTL results of CMC and GTEx using the inverse variance-weighted model. Afterward, we integrated QTL meta-analysis results (Q < 0.05) with the Glioma International Case Control Study (GICC) GWAS meta-analysis (case:12,496, control:18,190), using a summary statistics-based mendelian randomization (SMR) method.ResultsBetween CMC and GTEx, we combined the QTL data of 354 unique individuals of European ancestry. SMR analyses revealed 15 eQTLs in 11 loci and 32 sQTLs in 9 loci relevant to glioma risk. Two loci only harbored sQTLs (1q44 and 16p13.3). In seven loci, both eQTL and sQTL coexisted (2q33.3, 7p11.2, 11q23.3 15q24.2, 16p12.1, 20q13.33, and 22q13.1), but the target genes were different for five of these seven loci. Three eQTL loci (9p21.3, 20q13.33, and 22q13.1) and 4 sQTL loci (11q23.3, 16p13.3, 16q12.1, and 20q13.33) harbored multiple target genes. Eight target genes of sQTLs (C2orf80, SEC61G, TMEM25, PHLDB1, RP11-161M6.2, HEATR3, RTEL1-TNFRSF6B, and LIME1) had multiple alternatively spliced transcripts.ConclusionOur study revealed that the regulation of transcriptome by glioma risk alleles is complex, with the potential for eQTL and sQTL jointly affecting gliomagenesis in risk loci. QTLs of many loci involved multiple target genes, some of which were specific to alternative splicing. Therefore, quantitative trait loci that evaluate only total gene expression will miss many important target genes.

Rapid tumor growth, widespread brain-invasion, and therapeutic resistance critically contribute to glioblastoma (GBM) recurrence and dismal patient outcomes. Although GBM stem cells (GSC) are shown to play key roles in these processes, the molecular pathways governing the GSC phenotype (GBM-stemness) remain poorly defined. Here, we show that epigenetic silencing of miR-146a significantly correlated with worse patient outcome and importantly, miR-146a level was significantly lower in recurrent tumors compared with primary ones. Further, miR-146a overexpression significantly inhibited the proliferation and invasion of GBM patient-derived primary cells and increased their response to temozolomide (TMZ), both in vitro and in vivo. Mechanistically, miR-146a directly silenced POU3F2 and SMARCA5, two transcription factors that mutually regulated each other, significantly compromising GBM-stemness and increasing TMZ response. Collectively, our data show that miR-146a–POU3F2/SMARCA5 pathway plays a critical role in suppressing GBM-stemness and increasing TMZ-response, suggesting that POU3F2 and SMARCA5 may serve as novel therapeutic targets in GBM. Implications: miR-146a predicts favorable prognosis and the miR-146a–POU3F2/SMARCA5 pathway is important for the suppression of stemness in GBM.

Race/ethnicity have been previously shown to significantly affect survival after diagnosis with glioblastoma, but the cause of this survival difference is not known. The aim of this study was to examine variation in treatment pattern and time to treatment by race/ethnicity, and the extent to which this affects survival.Data were obtained from the National Cancer Database (NCDB) for adults ≥ 40 with glioblastoma from 2004 to 2016 (N = 68,979). Treatment patterns and time to treatment by race/ethnicity were compared using univariable and multivariable logistic and linear regression models, respectively, and adjusted for known prognostic factors and factors potentially affecting health care access.Black non-Hispanics (BNH) and Hispanics were less likely to receive radiation and less likely to receive chemotherapy as compared to White non-Hispanics (WNH). Time to radiation initiation was ~ 2 days longer and time to chemotherapy initiation was ~ 4 days longer in both groups in comparison to WNH.Both race/ethnicity and treatment timing significantly affected survival time, and this association remained after adjustment for known prognostic factors. Additional research is necessary to disentangle the specific causal factors, and the mechanism with which they affect survival.

Background There are over 100 histologically distinct types of primary malignant and nonmalignant brain and other central nervous system (CNS) tumors. Our study presents recent trends in the incidence of these tumors using an updated histology recode that incorporates major diagnostic categories listed in the 2016 World Health Organization Classification of Tumours of the CNS. Methods We used data from the SEER-21 registries for patients of all ages diagnosed in 2000–2017. We calculated age-adjusted incidence rates and fitted a joinpoint regression to the observed data to estimate the Annual Percent Change and 95% confidence intervals over the period 2000–2017. Results There were 315,184 new malignant (34.2%; 107,890) and nonmalignant (65.8%; 207,294) brain tumor cases during 2004–2017. Nonmalignant meningioma represented 46.5% (146,498) of all brain tumors (malignant and nonmalignant), while glioblastoma represented 50.8% (54,832) of all malignant tumors. Temporal trends were stable or declining except for nonmalignant meningioma (0.7% per year during 2004–2017). Several subtypes presented decreases in trends in the most recent period (2013–2017): diffuse/anaplastic astrocytoma (−1.3% per year, oligodendroglioma (−2.6%), pilocytic astrocytoma (−3.8%), and malignant meningioma (−5.9%). Conclusions Declining trends observed in our study may be attributable to recent changes in diagnostic classification and the coding practices stemming from those changes. The recode used in this study enables histology reporting to reflect the changes. It also provides a first step toward the reporting of malignant and nonmalignant brain and other CNS tumors in the Surveillance, Epidemiology, and End Results (SEER) Program by clinically relevant histology groupings.

When the COVID-19 pandemic began, formal frameworks to collect data about affected patients were lacking. The COVID-19 and Cancer Consortium (CCC19) was formed to collect granular data on patients with cancer and COVID-19 at scale and as rapidly as possible. CCC19 has grown from five initial institutions to 125 institutions with >400 collaborators. More than 5,000 cases with complete baseline data have been accrued. Future directions include increased electronic health record integration for direct data ingestion, expansion to additional domestic and international sites, more intentional patient involvement, and granular analyses of still-unanswered questions related to cancer subtypes and treatments.

BackgroundVestibular schwannomas (VS) are nonmalignant tumors of the eighth cranial nerve and are the most common nonmalignant nerve sheath tumor. This study provides the most comprehensive and current analysis of VS epidemiology in the United States.MethodsIncidence data were obtained from the Central Brain Tumor Registry of the United States, from 2004 to 2016 for VS. Age-adjusted incidence rates (AAIRs), rate ratios (AAIRRs), and prevalence ratios (AAPRs) per 100 000 were analyzed by age, sex, race and ethnicity, and laterality. Additional analyses were performed to assess differences in treatment, laterality, and diagnostic confirmation.ResultsIncidence of VS was highest among adults (aged 65–74 years, AAIR: 3.18, 95% confidence interval [CI]: 3.15–3.25). However, there was a much higher distribution of bilateral tumors compared to unilateral in children aged 0–19 years (28.5% vs 1.0%, P < .001). VS incidence was highest among white non-Hispanics (AAIR:1.30, 95% CI: 1.29–1. 31) and lowest among black non-Hispanics. Incidence of radiographically confirmed VS increased from 2004 to 2016 (annual percent change: 1.64, 95% CI: 0.15–3.16, P = .03). For treatment, 40.1% received surgery, while only 23.7% received radiation. There were an estimated 44 762 prevalent cases of VS in 2016 (AAPR: 12.17, 95% CI: 12.06–12.29).ConclusionsVS incidence and prevalence are highest among adults and white non-Hispanics. Bilateral VS was more common among children. There was an increase of radiographically confirmed VS over time. A higher proportion of patients received surgical treatment than radiotherapy. Population-based statistics provide healthcare professionals with vital information regarding disease burden and help improve patient care.

Glioblastoma (GBM) is recognized as one of the deadliest forms of cancer, despite aggressive therapy consisting of maximal surgical resection followed by concurrent radiation and chemotherapy, the median survival remains ~12 months. Glioma stem cells (GSCs) possess potent tumor-initiating properties and comprise a cellular hierarchy that is responsible for treatment resistance and progression. Specifically targeting GSCs has been considered a promising therapeutic approach, however no clear method has been identified. Histologically, it is known that GSCs are found in perivascular and pseudsopalisading regions of GBM. Similarly, platelet aggregates are often found in pseudsopalisading necrotic regions, suggesting a potential interaction between platelets and GSCs due to their spatial locations. High platelet counts have been associated with poor clinical outcome in many cancers including ovarian and endometrial cancer. While platelets are known to affect progression of other tumors, mechanisms by which platelets influence GBM oncogenesis are unknown. Our work aimed to understand the crosstalk between GSCs and platelets within GBM solid tumors that work to enhance disease progression and treatment resistance. Our clinical studies suggest elevated platelet counts positively correlate with tumor growth and negatively correlate to overall patient survival. We found platelets and GSC co-localization in GBM solid tissue; platelet exposure to GSCs results in increased proliferation of GSCs specifically, by increasing the self-renewing capacity of GSCs in a dose dependent manner, and resulted in an increased “Stem-like” transcriptional pattern. Inhibiting the GSC-platelet interaction results in a decrease in GSC renewal and stemness. These results introduce a novel interaction between GSCs and platelets and elucidate a novel therapeutic approach specifically targeting GSCs by disrupting the GSC-platelet interaction.

Brain metastases (BM) are typically treated with systemic chemotherapy and stereotactic radiosurgery (SRS). Population-level studies exploring SRS use in different patient populations and its impact on chemotherapy treatment patterns are needed. This study examines data from Surveillance, Epidemiology, and End-Results (SEER) from 2010–2012 and Medicare claims from 2008–2014 to identify the utility of SRS and associated chemotherapy treatment patterns in the breast cancer BM patient population. 25,954 breast cancer patients were identified, of which 6,657 (26%) received SRS. Chi-square and Fisher’s exact tests were used for initial univariate analyses. Univariable logistic regression models were fit for each predictor and multivariable models were selected using LASSO. Compared to patients without SRS, patients who received SRS were older, diagnosed at later disease stages, and less likely to have the Her2-/HR+ subtype. Patients with SRS most commonly received aromatase inhibitors (53.5%), followed by selective estrogen receptor modulators (SERM; 31.7%), taxanes (27.2%), alkylating agents (21.2%), monoclonal antibodies (22.2%), antimetabolite drugs (18.3%), anthracyclines (11.4%), and platinating agents (6.8%). Increased odds of SRS were associated with drug classes including taxanes (aOR: 1.29), monoclonal antibodies (aOR: 1.67), antimetabolites (aOR: 1.77), anthracyclines (aOR: 1.32), and topoisomerase-II inhibitors (aOR: 3.16). Aromatase inhibitors were associated with decreased odds of SRS use (aOR: 0.84). Alkylating agents, platinating agents, and SERM had no such associations. Our findings suggest that use of many chemotherapeutic agents increases with SRS regardless of ability to penetrate the blood-brain-barrier and parallels standard systemic breast cancer treatments. Because large-scale studies on the impact of SRS on breast cancer BM patients are lacking, it is important to identify differences in treatment usage and patterns. Important clinical implications regarding drug usage frequency, adherence to treatment guidelines, and use of different agents across SRS patients may arise by analyzing differences amongst and between populations of patients with and without SRS.

BACKGROUND Population-based data on the various causes of death among Primary Brain and CNS tumor patients are lacking. We evaluated the causes of death for all eligible patients using the National Program of Cancer Registries (NPCR) data. METHODS The population-based cancer survival data collected by the Centers for Disease Control and Prevention’s National Program of Cancer Registries (NPCR) were used to analyze the causes of death for patients of all ages with primary brain and CNS tumors diagnosed between 2001 and 2016. Patients for whom the cause of death was not listed on the death certificate or whose state death certificate was not available were excluded. Additional analyses to identify factors associated with brain tumor-specific mortality for the most common malignant (Glioblastoma) and non-malignant (Meningioma) were performed using univariable and multivariable logistic regression analysis. RESULTS Major cause of death for patients with malignant tumors was death due to brain and other CNS tumors (49.29%), and for non-malignant tumors were other benign and malignant tumors (31.5%) and heart disease (17.9%). Overall mortality was 36.4% (n=331,953) in patients with Primary Brain and CNS Tumors during the study period. Specifically, 163,621 (49.29%) patients died due to brain and other CNS tumors. A significant proportion of patients with malignant tumors had brain tumor-specific mortality compared to non-malignant tumors (75.4% in malignant vs 4.2% in non-malignant). The factors associated with brain specific mortality in Glioblastoma patients were Age (p< 0.001), Race (p< 0.001) and Primary Site (p< 0.001). Further, the factors associated with brain specific mortality in Non-malignant Meningioma patients were Age (p< 0.001), Sex (p< 0.001), Race (p< 0.001) and Primary Site (P< 0.001). CONCLUSION Cause of death attributed to the brain tumor was significantly higher in malignant brain tumors compared to non-malignant brain tumors.

The tumor microenvironment in glioblastoma provides cancer cells with favorable conditions to proliferate and invade surrounding tissues. Macrophages comprise a large portion of the glioblastoma tumor microenvironment (TME) both in terms of volume and function. These cells have been reported to influence tumor progression by modulating immune responses, remodeling extracellular matrix, and providing nutrients to cancer cells among numerous other functions. Radiation therapy forms one of the pillars of glioblastoma management along with surgical resection and chemotherapy. Here we investigated the effects of radiation on macrophage iron metabolism. Using mouse bone-marrow-derived macrophages (BMDMs) we performed in-vitro 59Fe radiotracer assays to study how radiation exposure modified iron trafficking in these cells. We found that low dose radiation at 0.25, 0.5, or 2 Gy from a 60Co source stimulated iron release from the BMDMs with maximal release occurring at 0.5 Gy. Moreover, we observed that iron release was dependent on the amount of serum present in culture media with cells cultured in 20% fetal bovine serum (FBS) showing reduced iron release profiles compared to those cultured in 10% or 1% FBS. Since glioblastoma patients exhibit sexually dimorphic survival outcomes, we investigated whether these radiation-induced responses occurred in a sexually dimorphic pattern. At radiation doses of 0.25 Gy we observed that male macrophages tended to release more iron than female macrophages despite no differences in iron uptake between the sexes – raising the question as to whether differential iron trafficking in response to treatment contributes to the poorer survival outcomes observed in males. Our data suggest that delineating how supporting cells such as macrophages respond to glioblastoma treatment regimens may provide insights into addressing mechanisms of treatment resistance and further our understanding of the sexual dimorphism observed in patient outcomes.

AI-based methods have shown great promise in a variety of biomedical research fields, including neurooncologic imaging. For example, machine learning methods have offered informative predictions of overall survival (OS) and progression-free survival (PFS), differentiation between pseudoprogression (PsP) and progressive disease (PD), and estimation of mutational status from imaging data. Despite their promise, AI, and especially the emerging deep learning (DL) methods, are challenged by several factors, including imaging heterogeneity across scanners and lack of sufficiently large and diverse training datasets, which limits their reproducibility and general acceptance. These challenges prompted the development of the ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium on glioblastoma, a growing effort to bring together a community of researchers sharing imaging, demographic, clinical and (currently) limited molecular data in order to address the following aims: 1) pool and harmonize data across diverse hospitals and patient populations worldwide; 2) derive robust and generalizable AI models for prediction of (initially) OS, PFS, PsP vs. PD, and recurrence; 3) test these predictive models across multiple sites. In its first phase, ReSPOND aims to pool together approximately 3,000MRI scans (from 10institutions plus TCIA), along with demographics, KPS, and (for a subset) MGMT/IDH1 status. We present initial results testing the generalization of a previously trained model of OS on 505Penn datasets to 2independent cohorts from Case Western Reserve University and University Hospitals (N=44), and Penn (N=67). The results indicate good generalization, with correlation coefficients between OS/predicted-OS between 0.25 to 0.5, depending on variable availability, which is comparable to cross-validated accuracy previously obtained from the training set itself (N=505). Additional preliminary studies evaluating prediction of future recurrence from baseline pre-operative scans in de novo patients (Penn model applied to CWR) indicated potential for guiding targeted dose escalation and supra-total resection (excellent predictions in 6/12 patients, modest in 1/12, and poor in 5/12).

Glioblastoma (GBM) is recognized as one of the deadliest forms of cancer, despite aggressive therapy consisting of maximal surgical resection followed by concurrent radiation and chemotherapy, the median survival remains ~15 months. Glioma stem cells (GSCs) possess potent tumor-initiating properties and comprise a cellular hierarchy that is responsible for treatment resistance and progression. Specifically targeting GSCs has been considered a promising therapeutic approach, however no clear method has been identified. Histologically, it is known that GSCs are found in perivascular and pseudsopalisading regions of GBM. Similarly, platelet aggregates are often found in pseudsopalisading necrotic regions, suggesting a potential interaction between platelets and GSCs due to their spatial locations. High platelet counts have been associated with poor clinical outcome in many cancers including ovarian and endometrial cancer. While platelets are known to affect progression of other tumors, mechanisms by which platelets influence GBM oncogenesis are unknown. Our work aimed to understand the crosstalk between GSCs and platelets within GBM solid tumors that work to enhance disease progression and treatment resistance. Our clinical studies suggest elevated platelet counts positively correlate with tumor growth and negatively correlate to overall patient survival. We found platelets and GSC co-localization in GBM solid tissue; platelet exposure to GSCs results in increased proliferation of GSCs specifically, by increasing the self-renewing capacity of GSCs in a dose dependent manner, and resulted in an increased “Stem-like” transcriptional pattern. Consequently, inhibiting the GSC-platelet interaction results in a decrease in GSC renewal and stemness. These results introduce a novel interaction between GSCs and platelets and elucidate a novel therapeutic approach specifically targeting GSCs by disrupting the GSC-platelet interaction.

Glioblastoma (GBM) is the most aggressive brain cancer. Sex differences in incidence and clinical outcomes have been reported, however, our knowledge of contributing mechanisms is limited. Iron acquisition is key to robust tumor growth. Upregulation of Transferrin (Tf, iron transport protein)/Transferrin receptor (TfR) is found in multiple different cancers. We have identified H-ferritin (FTH1) as involved in iron transport and explore its uptake in GBM in this study. We interrogated iron uptake in a syngeneic orthotopic mouse model (GL261 cells) using male and female mice. After the tumors were established, radioactive 125I labeled Tf and FTH1 proteins were injected retro-orbitally in the mice. After 24 hours, tumors were removed, homogenized and analyzed for Tf and FTH1 uptake. There was a significant difference in Tf uptake into the tumor versus matched non-tumor tissue in both males and females and the uptake in the tumors was 1.5-fold higher in males than females. There was no significant difference in FTH1 uptake between male and female tumors nor between tumor and matched non-tumor brain tissue. Binding analyses were performed on homogenized samples of human male and female GBM tissue samples using 125I labeled Tf and FTH1. Tumors from males had increased binding of both proteins compared to tumors from females. We next queried the TCGA database and found in females, high TfR expression was associated with poor survival but not in males. TCGA database revealed a robust expression of Tim1, a putative receptor for FTH1, but its expression did not relate to survival. In summary, this study demonstrates FTH1 binding to GBMs and sexual dimorphism in iron acquisition via Tf and survival.

Background Immune checkpoint inhibitors (ICIs) can cause unique, high-grade immune-related adverse events. Although rare, ICI related stroke events can have high morbidity and mortality. Neurological monitoring is not routinely performed in patients on ICI treatment, thus risk factors remain unknown. Characterisation of such rare, but fatal adverse events requires integration of real-world data. Methods U.S claims data (IBM MarketScan) of over 30 million commercially insured individuals was leveraged to identify 2,687,301 cancer patients between 2011–2018. Patients ≥18 years of age, treated with ICIs (targeting CTLA4 (ipilimumab) and/or the PD1 (nivolumab, pembrolizumab)/PDL1 (atezolizumab, avelumab, durvalumab) alone or in combination with ICI and/or chemotherapy were identified and followed until disenrollment. All strokes (ischemic or haemorrhagic), comorbidities, and treatment details were identified using diagnosis and billing codes. Patients from the ICI cohort were matched 1:1 to those in the chemotherapy cohort according to age, gender, NCI comorbidity score, and primary cancer as presented in the study design (figure 1). The matched cohorts were split by the specific type of chemotherapy (targeted or cytotoxic) used in the control patients. This yielded a total of 2,177 pairs of matched patients where the control arm received targeted chemotherapy, and 3,550 pairs of matched patients where the control arm received cytotoxic chemotherapy. Analyses included descriptive statistics and Cox proportional hazards regression. Results A total of 16,574 patients received at least one dose of ICI therapy for any advanced cancer. Overall 9,496 patients who were treated with ICI met the study eligibility criteria. Stroke was identified in 489 (5.14%) patients. Mean age (±standard deviation, SD) was 60 (±12), male 62%, mean (±SD) NCI comorbidity index 2.3 (±2.12), median time to stroke was 168 days. 51.3% patients received anti-PD1 monotherapy, 37.6% received anti-CTLA4, 3.3.% anti-PD-L1 and 7.8% received combination therapy (anti-PD1 plus anti-CTLA4). One-year cumulative incidence (CI) in the matched ICI vs. targeted and ICI vs. cytotoxic chemotherapy were 6.3% vs. 5.7% (p=0.07) and 4.95% vs. 4.08% (p=0.90) respectively (table 1). Within the ICI cohort, CI of stroke events with anti-CTLA4 monotherapy vs. anti-PD1/PD-L1 and anti-CTLA-4 plus anti-PD-1 combination vs. PD1/PD-L1 monotherapy were 9.89% vs. 4.54% and 6.69% vs. 3.73%, respectively (table 2). On multivariable regression analyses, patients with malignant melanoma, and those receiving anti-CTLA-4 monotherapy were associated with higher risk of stroke events, while the risk was lower in patients with head and neck cancer and those who received anti-PD-1 monotherapy (table 3 and 4). Conclusions To the best of our knowledge, this is the largest and comprehensive real-world longitudinal study for stroke events in advanced cancer patients treated with ICI. Cumulative incidence of stroke was significantly higher in patients on anti-CTLA-4 monotherapy and anti-CTLA-4 plus anti-PD-1 combination therapy in comparison to anti-PD-1/PD-L1 monotherapy. Malignant melanoma and anti CTLA-4 therapy were independent risk factors for stroke. Acknowledgements This work was funded by pilot award in Big Data/Cancer Informatics to Prantesh Jain, MD from University Hospitals Research & Education Institute Ethics Approval The IBM MarketScan national database contains de-identified linked inpatient, outpatient, and pharmacy claims data. University Hospitals’ Institutional Review Board determined this study to be exempt from review and requirement of an informed consent.

The Central Brain Tumor Registry of the United States (CBTRUS), in collaboration with the Centers for Disease Control (CDC) and National Cancer Institute (NCI), is the largest population-based registry focused exclusively on primary brain and other central nervous system (CNS) tumors in the United States (US) and represents the entire US population. This report contains the most up-to-date population-based data on primary brain tumors (malignant and non-malignant) and supersedes all previous CBTRUS reports in terms of completeness and accuracy. All rates (incidence and mortality) are age-adjusted using the 2000 US standard population and presented per 100,000 population. The average annual age-adjusted incidence rate (AAAIR) of all malignant and non-malignant brain and other CNS tumors was 23.79 (Malignant AAAIR=7.08, non-Malignant AAAIR=16.71). This rate was higher in females compared to males (26.31 versus 21.09), Blacks compared to Whites (23.88 versus 23.83), and non-Hispanics compared to Hispanics (24.23 versus 21.48). The most commonly occurring malignant brain and other CNS tumor was glioblastoma (14.5% of all tumors), and the most common non-malignant tumor was meningioma (38.3% of all tumors). Glioblastoma was more common in males, and meningioma was more common in females. In children and adolescents (age 0-19 years), the incidence rate of all primary brain and other CNS tumors was 6.14. An estimated 83,830 new cases of malignant and non-malignant brain and other CNS tumors are expected to be diagnosed in the US in 2020 (24,970 malignant and 58,860 non-malignant). There were 81,246 deaths attributed to malignant brain and other CNS tumors between 2013 and 2017. This represents an average annual mortality rate of 4.42. The 5-year relative survival rate following diagnosis of a malignant brain and other CNS tumor was 23.5% and for a non-malignant brain and other CNS tumor was 82.4%.

The use of magnetic resonance imaging (MRI) in healthcare and the emergence of radiology as a practice are both relatively new compared with the classical specialties in medicine. Having its naissance in the 1970s and later adoption in the 1980s, the use of MRI has grown exponentially, consequently engendering exciting new areas of research. One such development is the use of computational techniques to analyze MRI images much like the way a radiologist would. With the advent of affordable, powerful computing hardware and parallel developments in computer vision, MRI image analysis has also witnessed unprecedented growth. Due to the interdisciplinary and complex nature of this subfield, it is important to survey the current landscape and examine the current approaches for analysis and trend trends moving forward.

Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence., In cancer many gene variants may contribute to disease etiology, but the impact of a given gene variant may have varied effect size. Here, the authors analyse summary statistics of genome-wide association studies from fourteen cancers, and show the utility of polygenic risk scores may vary depending on cancer type.

Background Glioblastoma (GB) is the most common and most lethal primary malignant brain tumor. Extent of surgical resection is one of the most important prognostic factors associated with improved survival. Historically, patients living in nonmetropolitan counties in the United States have limited access to optimal treatment and health care services. The aim of this study is to determine whether there is an association between urbanicity and surgical treatment patterns among US patients with primary GB. Methods Cases with histologically confirmed, primary GB diagnosed between 2005 and 2015 were obtained from the Central Brain Tumor Registry of the United States (CBTRUS) in collaboration with the Centers for Disease Control and Prevention, and the National Cancer Institute. Multivariable logistic regression models were constructed to assess the association between urbanicity and receipt of surgical treatment (gross total resection [GTR]/subtotal resection [STR] vs biopsy only/none) and extent of resection (GTR vs STR), adjusted for age at diagnosis, sex, race, US regional division, and primary tumor site. Results Patients residing in nonmetropolitan counties were 7% less likely to receive surgical treatment (odds ratio [OR] = 0.93, 95% CI: 0.89-0.96, P < .0001). Among those who received surgical treatment, metropolitan status was not significantly associated with receiving GTR vs STR (OR = 0.99, 95% CI: 0.94-1.04, P = .620). Conclusions Among US patients with GB, urbanicity is associated with receipt of surgical treatment, but among patients who receive surgery, urbanicity is not associated with extent of resection. These results point to potential differences in access to health care for those in nonmetropolitan areas that warrant further exploration.

This is a radiomics study investigating the ability of texture analysis of MRF maps to improve differentiation between intra-axial adult brain tumors and to predict survival in the glioblastoma cohort.Magnetic resonance fingerprinting (MRF) acquisition was performed on 31 patients across 3 groups: 17 glioblastomas, 6 low-grade gliomas, and 8 metastases. Using regions of interest for the solid tumor and peritumoral white matter on T1 and T2 maps, second-order texture features were calculated from gray-level co-occurrence matrices and gray-level run length matrices. Selected features were compared across the three tumor groups using Wilcoxon rank-sum test. Receiver operating characteristic curve analysis was performed for each feature. Kaplan-Meier method was used for survival analysis with log rank tests.Low-grade gliomas and glioblastomas had significantly higher run percentage, run entropy, and information measure of correlation 1 on T1 than metastases (p 0.017). The best separation of all three tumor types was seen utilizing inverse difference normalized and homogeneity values for peritumoral white matter in both T1 and T2 maps (p 0.017). In solid tumor T2 maps, lower values in entropy and higher values of maximum probability and high-gray run emphasis were associated with longer survival in glioblastoma patients (p 0.05). Several texture features were associated with longer survival in glioblastoma patients on peritumoral white matter T1 maps (p 0.05).Texture analysis of MRF-derived maps can improve our ability to differentiate common adult brain tumors by characterizing tumor heterogeneity, and may have a role in predicting outcomes in patients with glioblastoma.

PURPOSE The Electronic Medical Record Search Engine (EMERSE) is a software tool built to aid research spanning cohort discovery, population health, and data abstraction for clinical trials. EMERSE is now live at three academic medical centers, with additional sites currently working on implementation. In this report, we describe how EMERSE has been used to support cancer research based on a variety of metrics. METHODS We identified peer-reviewed publications that used EMERSE through online searches as well as through direct e-mails to users based on audit logs. These logs were also used to summarize use at each of the three sites. Search terms for two of the sites were characterized using the natural language processing tool MetaMap to determine to which semantic types the terms could be mapped. RESULTS We identified a total of 326 peer-reviewed publications that used EMERSE through August 2019, although this is likely an underestimation of the true total based on the use log analysis. Oncology-related research comprised nearly one third (n = 105; 32.2%) of all research output. The use logs showed that EMERSE had been used by multiple people at each site (nearly 3,500 across all three) who had collectively logged into the system > 100,000 times. Many user-entered search queries could not be mapped to a semantic type, but the most common semantic type for terms that did match was “disease or syndrome,” followed by “pharmacologic substance.” CONCLUSION EMERSE has been shown to be a valuable tool for supporting cancer research. It has been successfully deployed at other sites, despite some implementation challenges unique to each deployment environment.

Modeling of genomic profiles from the Cancer Genome Atlas (TCGA) by using recently developed mathematical frameworks has associated a genome-wide pattern of DNA copy-number alterations with a shorter, roughly one-year, median survival time in glioblastoma (GBM) patients. Here, to experimentally test this relationship, we whole-genome sequenced DNA from tumor samples of patients. We show that the patients represent the U.S. adult GBM population in terms of most normal and disease phenotypes. Intratumor heterogeneity affects ≈ 11 % and profiling technology and reference human genome specifics affect 30%. With a 2.25-year Kaplan–Meier median survival difference, a 3.5 univariate Cox hazard ratio, and a 0.78 concordance index, i.e., accuracy, the pattern predicts survival better than and independent of age at diagnosis, which has been the best indicator since 1950. The prognostic classification by the pattern may, therefore, help to manage GBM pseudoprogression. The diagnostic classification may help drugs progress to regulatory approval. The therapeutic predictions, of previously unrecognized targets that are correlated with survival, may lead to new drugs. Other methods missed this relationship in the roughly 3B-nucleotide genomes of the small, order of magnitude of 100, patient cohorts, e.g., from TCGA. Previous attempts to associate GBM genotypes with patient phenotypes were unsuccessful. This is a proof of principle that the frameworks are uniquely suitable for discovering clinically actionable genotype–phenotype relationships.

Background Studies that have examined the association between cardiovascular comorbidities and epithelial ovarian cancer (EOC) have yielded inconsistent results. It remains unknown whether cardiometabolic disease is associated with EOC in African American (AA) women, who have a higher prevalence of cardiovascular disease and lower risk of EOC than White women. Here, we estimate the effect of cardiovascular comorbid conditions and EOC risk among AA women. Methods Data were available from 593 ovarian carcinoma patients and 752 controls enrolled in the African American Cancer Epidemiology Study (AACES). Participants were asked to self-report a history of hypertension, hyperlipidemia, and diabetes and any current medication use. The relationship between hypertension, hyperlipidemia, diabetes, and medications taken for these conditions was determined using multivariate logistic regression. Results Hypertension was associated with an increased risk (adjusted odds ratio (aOR) = 1.32, 95% confidence interval (CI) = 1.01, 1.73), whereas diabetes and hyperlipidemia were associated with a decreased risk (aOR = 0.67, 95% CI = 0.49, 0.91 and aOR = 0.61, 95% CI = 0.47, 0.80, respectively) of EOC. Use of anti-diabetic medication was inversely associated with EOC risk, as was use of lipid lowering medications (in the overall study population), which were predominantly statins. Among women with hypertension, use of anti-hypertensive medications was inversely associated with EOC risk, with associations that were most pronounced for diuretics, ARBs and ACE inhibitors. Conclusion Hypertension was associated with an increased EOC risk in this patient population, whereas an inverse association was observed for diabetes and hyperlipidemia. The decreased risk of EOC identified with use of anti-hypertensive, anti-diabetes or lipid-lowering medications could have implications for risk reduction strategies.

Glioblastomas are the most common form of malignant primary brain tumor and an important cause of morbidity and mortality. In recent years there have been important advances in understanding the molecular pathogenesis and biology of these tumors, but this has not translated into significantly improved outcomes for patients. In this consensus review from the Society for Neuro-Oncology (SNO) and the European Association of Neuro-Oncology (EANO), the current management of isocitrate dehydrogenase wildtype (IDHwt) glioblastomas will be discussed. In addition, novel therapies such as targeted molecular therapies, agents targeting DNA damage response and metabolism, immunotherapies, and viral therapies will be reviewed, as well as the current challenges and future directions for research.

Background Metabolic syndrome is identified as a risk factor for the development of several systemic cancers, but its frequency among patients with glioblastoma and its association with clinical outcomes have yet to be determined. The aim of this study was to investigate metabolic syndrome as a risk factor for and affecting survival in glioblastoma patients. Methods A retrospective cohort study, consisting of patients with diagnoses at a single institution between 2007 and 2013, was conducted. Clinical records were reviewed, and clinical and laboratory data pertaining to 5 metabolic criteria were extrapolated. Overall survival was determined by time from initial surgical diagnosis to date of death or last follow-up. Results The frequency of metabolic syndrome among patients diagnosed with glioblastoma was slightly greater than the frequency of metabolic syndrome among the general population. Within a subset of patients (n = 91) receiving the full schedule of concurrent radiation and temozolomide and adjuvant temozolomide, median overall survival was significantly shorter for patients with metabolic syndrome compared with those without. In addition, the presence of all 5 elements of the metabolic syndrome resulted in significantly decreased median survival in these patients. Conclusions We identified the metabolic syndrome at a slightly higher frequency in patients with diagnosed glioblastoma compared with the general population. In addition, metabolic syndrome with each of its individual components is associated with an overall worse prognosis in patients receiving the standard schedule of radiation and temozolomide after adjustment for age.

Chordomas account for 1% to 4% of all bone malignancies and 0.5% of all primary intracranial central nervous system tumors. Prior epidemiologic literature is based on limited population data. The purpose of this study is to provide the largest and most inclusive population based study of the descriptive epidemiology of chordomas. The Centers for Disease Control and Prevention and National Program of Cancer Registries were queried for chordoma in all locations. Age-adjusted incidence per 100,000 persons was calculated by age, sex, race, and ethnicity. Annual percentage change was calculated using Joinpoint. From 2004 to 2014, a total of 3670 chordomas were diagnosed in the US. The most common location was cranial (38.7%), followed by sacral (34.3%) and spinal (27.0%). The average age-adjusted incidence rate was 0.088 per 100,000 persons per year (95% CI 0.086–0.091), with an annual percentage change of 1.29% (95% CI 0.31–2.28%). For all chordomas, the incidence peaks in the 75–84 year age group. The male-to-female incidence rate ratio is 1.54 (p

Importance Per the World Health Organization 2016 integrative classification, newly diagnosed glioblastomas are separated into isocitrate dehydrogenase gene 1 or 2 (IDH)–wild-type andIDH-mutant subtypes, with median patient survival of 1.2 and 3.6 years, respectively. Although maximal resection of contrast-enhanced (CE) tumor is associated with longer survival, the prognostic importance of maximal resection within molecular subgroups and the potential importance of resection of non–contrast-enhanced (NCE) disease is poorly understood. Objective To assess the association of resection of CE and NCE tumors in conjunction with molecular and clinical information to develop a new road map for cytoreductive surgery. Design, Setting, and Participants This retrospective, multicenter cohort study included a development cohort from the University of California, San Francisco (761 patients diagnosed from January 1, 1997, through December 31, 2017, with 9.6 years of follow-up) and validation cohorts from the Mayo Clinic (107 patients diagnosed from January 1, 2004, through December 31, 2014, with 5.7 years of follow-up) and the Ohio Brain Tumor Study (99 patients with data collected from January 1, 2008, through December 31, 2011, with a median follow-up of 10.9 months). Image accessors were blinded to patient groupings. Eligible patients underwent surgical resection for newly diagnosed glioblastoma and had available survival, molecular, and clinical data and preoperative and postoperative magnetic resonance images. Data were analyzed from November 15, 2018, to March 15, 2019. Main Outcomes and Measures Overall survival. Results Among the 761 patients included in the development cohort (468 [61.5%] men; median age, 60 [interquartile range, 51.6-67.7] years), younger patients withIDH–wild-type tumors and aggressive resection of CE and NCE tumors had survival similar to that of patients withIDH-mutant tumors (median overall survival [OS], 37.3 [95% CI, 31.6-70.7] months). Younger patients withIDH–wild-type tumors and reduction of CE tumor but residual NCE tumors fared worse (median OS, 16.5 [95% CI, 14.7-18.3] months). Older patients withIDH–wild-type tumors benefited from reduction of CE tumor (median OS, 12.4 [95% CI, 11.4-14.0] months). The results were validated in the 2 external cohorts. The association between aggressive CE and NCE in patients withIDH–wild-type tumors was not attenuated by the methylation status of the promoter region of the DNA repair enzyme O6-methylguanine-DNA methyltransferase. Conclusions and Relevance This study confirms an association between maximal resection of CE tumor and OS in patients with glioblastoma across all subgroups. In addition, maximal resection of NCE tumor was associated with longer OS in younger patients, regardless ofIDHstatus, and among patients withIDH–wild-type glioblastoma regardless of the methylation status of the promoter region of the DNA repair enzyme O6-methylguanine-DNA methyltransferase. These conclusions may help reassess surgical strategies for individual patients with newly diagnosed glioblastoma.

Background:. Autologous fat transfer—also referred to as fat grafting—has been reported to provide beneficial effects to overlying scar and skin. Despite procedural frequency, there is a paucity of high-level evidence guiding the surgeon in technique, patient selection, and efficacy. Methods:. A multicenter, double-blinded, randomized, internally placebo-controlled trial was performed with an aim to qualitatively and quantitatively evaluate the impact of autologous fat transfer on the quality of overlying scar tissue. Fat-grafted scars were evaluated and compared with paired, saline-injected “control” scars. Subjective and objective metrics were evaluated in treated sites for 12 months after treatment. Results:. Blinded qualitative results demonstrated a statistically significant improvement in scar quality over time in fat-grafted scars. However, these improvements were not found to be statistically different from changes noted in scars treated with saline. In addition, objective metrics did not statistically differ between saline-injected and autologous fat-grafted scars. Conclusions:. Our results demonstrate that autologous fat grafting can improve the qualitative profile of a scar from both the patient and observer perspectives. However, there was no difference in improvement when compared with scars that were treated with saline in a randomized and blinded fashion. These results demonstrate that any improvements in scar quality related to fat grafting are also achieved using saline and suggest that mechanisms other than cell activity may be at play. Additional randomized, blinded, placebo-controlled trials are required to either corroborate or contest the putative beneficial effect(s) of adipose tissue on scar remodeling.

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute–funded cancer centers. Although each of the participating cancer centers is structured differently, and leaders’ titles vary, we know firsthand there are similarities in both the issues we face and the solutions we achieve. As a consortium, we have initiated a dedicated listserv, an open-initiatives program, and targeted biannual face-to-face meetings. These meetings are a place to review our priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues we, as informatics leaders, individually face at our respective institutions and cancer centers. Here we provide a brief history of the CI4CC organization and meeting highlights from the latest CI4CC meeting that took place in Napa, California from October 14-16, 2019. The focus of this meeting was “intersections between informatics, data science, and population science.” We conclude with a discussion on “hot topics” on the horizon for cancer informatics.

Background Gliomas are the most common type of primary brain tumor and one of many cancers where males are diagnosed with greater frequency than females. However, little is known about the sex-based molecular differences in glioblastomas (GBMs) or lower grade glioma (non-GBM) subtypes. DNA methylation is an epigenetic mechanism involved in regulating gene transcription. In glioma and other cancers, hypermethylation of specific gene promoters downregulates transcription and may have a profound effect on patient outcome. The purpose of this study was to determine if sex-based methylation differences exist in different glioma subtypes. Methods Molecular and clinical data from glioma patients were obtained from The Cancer Genome Atlas and grouped according to tumor grade and molecular subtype (IDH1/2 mutation and 1p/19q chromosomal deletion). Sex-specific differentially methylated probes (DMPs) were identified in each subtype and further analyzed to determine if they were part of differentially methylated regions (DMRs) or associated with differentially methylated DNA transcription regulatory binding motifs. Results Analysis of methylation data in 4 glioma subtypes revealed unique sets of both sex-specific DMPs and DMRs in each subtype. Motif analysis based on DMP position also identified distinct sex-based sets of DNA-binding motifs that varied according to glioma subtype. Downstream targets of 2 of the GBM-specific transcription binding sites, NFAT5 and KLF6, showed differential gene expression consistent with increased methylation mediating downregulation. Conclusion DNA methylation differences between males and females in 4 glioma molecular subtypes suggest an important, sex-specific role for DNA methylation in epigenetic regulation of gliomagenesis.

Background The median survival for patients with glioblastoma (GBM), the most common primary malignant brain tumor in adults, has remained approximately 1 year for more than 2 decades. Recent advances in the field have identified GBM as a sexually dimorphic disease. It is less prevalent in females and they have better survival compared to males. The molecular mechanism of this difference has not yet been established. Iron is essential for many biological processes supporting tumor growth and its regulation is impacted by sex. Therefore, we interrogated the expression of a key component of cellular iron regulation, the HFE (homeostatic iron regulatory) gene, on sexually dimorphic survival in GBM. Methods We analyzed TCGA microarray gene expression and clinical data of all primary GBM patients (IDH-wild type) to compare tumor mRNA expression of HFE with overall survival, stratified by sex. Results In low HFE expressing tumors (below median expression, n = 220), survival is modulated by both sex and MGMT status, with the combination of female sex and MGMT methylation resulting in over a 10-month survival advantage (P < .0001) over the other groups. Alternatively, expression of HFE above the median (high HFE, n = 240) is associated with significantly worse overall survival in GBM, regardless of MGMT methylation status or patient sex. Gene expression analysis uncovered a correlation between high HFE expression and expression of genes associated with immune function. Conclusions The level of HFE expression in GBM has a sexually dimorphic impact on survival. Whereas HFE expression below the median imparts a survival benefit to females, high HFE expression is associated with significantly worse overall survival regardless of established prognostic factors such as sex or MGMT methylation.

Glioblastoma (GBM) is the most common malignant brain tumor in the United States. Incidence of GBM increases with age, and younger age-at-diagnosis is significantly associated with improved prognosis. While the relationship between candidate GBM risk SNPs and age-at-diagnosis has been explored, genome-wide association studies (GWAS) have not previously been stratified by age. Potential age-specific genetic effects were assessed in autosomal SNPs for GBM patients using data from four previous GWAS. Using age distribution tertiles (18–53, 54–64, 65+) datasets were analyzed using age-stratified logistic regression to generate p values, odds ratios (OR), and 95% confidence intervals (95%CI), and then combined using meta-analysis. There were 4,512 total GBM cases, and 10,582 controls used for analysis. Significant associations were detected at two previously identified SNPs in 7p11.2 (rs723527 [p(54–63)=1.50×10(−9), OR(54–63)=1.28, 95%CI(54–63)=1.18–1.39; p(64+)=2.14×10(−11), OR(64+)=1.32, 95%CI(64+)=1.21–1.43] and rs11979158 [p(54–63)=6.13×10(−8), OR(54–63)=1.35, 95%CI(54–63)=1.21–1.50; p(64+)=2.18×10(−10), OR(64+)=1.42, 95%CI(64+)=1.27–1.58]) but only in persons >54. There was also a significant association at the previously identified lower grade glioma (LGG) risk locus at 8q24.21 (rs55705857) in persons ages 18–53 (p(18–53)=9.30×10(−11), OR(18–53)=1.76, 95%CI(18–53)=1.49–2.10). Within The Cancer Genome Atlas (TCGA) there was higher prevalence of ‘LGG’-like tumor characteristics in GBM samples in those 18–53, with IDH1/2 mutation frequency of 15%, as compared to 2.1% [54–63] and 0.8% [64+] (p=0.0005). Age-specific differences in cancer susceptibility can provide important clues to etiology. The association of a SNP known to confer risk for IDH1/2 mutant glioma and higher prevalence of IDH1/2 mutation within younger individuals 18–53 suggests that more younger individuals may present initially with ‘secondary glioblastoma.’

Dysregulated iron transport and a compromised blood-brain barrier are implicated in HIV-associated neurocognitive disorders (HAND). We quantified the levels of proteins involved in iron transport and/or angiogenesis-ceruloplasmin, haptoglobin, and vascular endothelial growth factor (VEGF)-as well as biomarkers of neuroinflammation, in cerebrospinal fluid (CSF) from 405 individuals with HIV infection and comprehensive neuropsychiatric assessments. Associations with HAND [defined by a Global Deficit Score (GDS) ≥ 0.5, GDS as a continuous measure (cGDS), or by Frascati criteria] were evaluated for the highest versus lowest tertile of each biomarker, adjusting for potential confounders. Higher CSF VEGF was associated with GDS-defined impairment [odds ratio (OR) 2.17, p= 0.006] and cGDS in unadjusted analyses and remained associated with GDS impairment after adjustment (p= 0.018). GDS impairment was also associated with higher CSF ceruloplasmin (p= 0.047) and with higher ceruloplasmin and haptoglobin in persons with minimal comorbidities (ORs 2.37 and 2.13, respectively; both p= 0.043). In persons with minimal comorbidities, higher ceruloplasmin and haptoglobin were associated with HAND by Frascati criteria (both p&nbsp