The immunogenetics of viral antigen response is associated with subtype-specific glioma risk and survival.

Glioma is a highly fatal cancer with prognostically significant molecular subtypes and few known risk factors. Multiple studies have implicated infections in glioma susceptibility, but evidence remains inconsistent. Genetic variants in the human leukocyte antigen (HLA) region modulate host response to infection and have been linked to glioma risk. In this study, we leveraged genetic predictors of antibody response to 12 viral antigens to investigate the relationship with glioma risk and survival. Genetic reactivity scores (GRSs) for each antigen were derived from genome-wide-significant (p < 5 × 10-8) variants associated with immunoglobulin G antibody response in the UK Biobank cohort. We conducted parallel analyses of glioma risk and survival for each GRS and HLA alleles imputed at two-field resolution by using data from 3,418 glioma-affected individuals subtyped by somatic mutations and 8,156 controls. Genetic reactivity scores to Epstein-Barr virus (EBV) ZEBRA and EBNA antigens and Merkel cell polyomavirus (MCV) VP1 antigen were associated with glioma risk and survival (Bonferroni-corrected p < 0.01). GRSZEBRA and GRSMCV were associated in opposite directions with risk of IDH wild-type gliomas (ORZEBRA = 0.91, p = 0.0099/ORMCV = 1.11, p = 0.0054). GRSEBNA was associated with both increased risk for IDH mutated gliomas (OR = 1.09, p = 0.040) and improved survival (HR = 0.86, p = 0.010). HLA-DQA1∗03:01 was significantly associated with decreased risk of glioma overall (OR = 0.85, p = 3.96 × 10-4) after multiple testing adjustment. This systematic investigation of the role of genetic determinants of viral antigen reactivity in glioma risk and survival provides insight into complex immunogenomic mechanisms of glioma pathogenesis. These results may inform applications of antiviral-based therapies in glioma treatment.

CpGtools: a python package for DNA methylation analysis.

MOTIVATION: DNA methylation can be measured at the single CpG level using sodium bisulfite conversion of genomic DNA followed by sequencing or array hybridization. Many analytic tools have been developed, yet there is still a high demand for a comprehensive and multifaceted tool suite to analyze, annotate, QC and visualize the DNA methylation data. RESULTS: We developed the CpGtools package to analyze DNA methylation data generated from bisulfite sequencing or Illumina methylation arrays. The CpGtools package consists of three types of modules: (i) 'CpG position modules' focus on analyzing the genomic positions of CpGs, including associating other genomic and epigenomic features to a given list of CpGs and generating the DNA motif logo enriched in the genomic contexts of a given list of CpGs; (ii) 'CpG signal modules' are designed to analyze DNA methylation values, such as performing the PCA or t-SNE analyses, using Bayesian Gaussian mixture modeling to classify CpG sites into fully methylated, partially methylated and unmethylated groups, profiling the average DNA methylation level over user-specified genomics regions and generating the bean/violin plots and (iii) 'differential CpG analysis modules' focus on identifying differentially methylated CpGs between groups using different statistical methods including Fisher's Exact Test, Student's t-test, ANOVA, non-parametric tests, linear regression, logistic regression, beta-binomial regression and Bayesian estimation. AVAILABILITY AND IMPLEMENTATION: CpGtools is written in Python under the open-source GPL license. The source code and documentation are freely available at https://github.com/liguowang/cpgtools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pediatric brain tumor cell lines exhibit miRNA-depleted, Y RNA-enriched extracellular vesicles.

BACKGROUND: Medulloblastoma (MB) and diffuse infiltrative pontine glioma (DIPG) are malignant pediatric tumors. Extracellular vesicles (EVs) and their bioactive cargoes have been implicated in tumorigenesis. Most studies have focused on adult tumors, therefore the role of EVs and the noncoding RNA (ncRNA) landscape in pediatric brain tumors is not fully characterized. The overall aim of this pilot study was to isolate EVs from MB and DIPG patient-derived cell lines and to explore the small ncRNA transcriptome. METHODS: EVs from 3 DIPG and 4 MB patient-derived cell lines were analyzed. High-throughput next generation sequencing interrogated the short non-coding RNA (ncRNA) transcriptome. Known and novel miRNAs were quantified. Differential expression analysis, in silico target prediction, and functional gene enrichment were performed. RESULTS: EV secretomes from MB and DIPG patient-derived cell lines demonstrated discrete ncRNA biotypes. Notably, miRNAs were depleted and Y RNAs were enriched in EV samples. Hierarchical cluster analysis revealed high discrimination in miRNA expression between DIPG and MB cell lines and RNA-Seq identified novel miRNAs not previously implicated in MB or DIPG pathogenesis. Known and putative target genes of dysregulated miRNAs were identified. Functional annotation analysis of the target genes for differentially expressed EV-and parental-derived miRNAs revealed significant cancer-related pathway involvement. CONCLUSIONS: This hypothesis-generating study demonstrated that pediatric brain tumor-derived cell lines secrete EVs comprised of various ncRNA cargoes. Validation of these findings in patient samples may provide new insights into the pediatric brain tumor microenvironment and identification of novel therapeutic candidates.

Population-based incidence and clinico-radiological characteristics of tumefactive demyelination in Olmsted County, Minnesota, United States.

BACKGROUND AND PURPOSE: Tumefactive demyelination (TD) presents with large inflammatory lesions mimicking tumors or other space-occupying lesions. Limited epidemiological, clinical and radiological data exist for TD. We aimed to report the incidence rate, and clinical and radiological features of TD in Olmsted County, Minnesota. METHODS: We retrospectively reviewed patients with central nervous system inflammatory demyelination-related diagnostic codes (January 1, 1998 to December 31, 2018) in the Rochester Epidemiology Project database, and adjusted incidence rates by age and sex to the 2010 US total population. We used the Expanded Disability Status Scale (EDSS) to assess outcomes (index attack and last follow-up). RESULTS: Of 792 multiple sclerosis (MS) patients, 15 (eight males, seven females) had tumefactive MS, representing 1.9% of the MS population. The median (range) age at attack onset was 34.2 (2-61) years. Tumefactive lesion was the first clinical MS attack in 8/16 patients. Cerebrospinal fluid oligoclonal bands (OCBs) were present in 8/12 patients and 11/16 patients met the Barkhof criteria for dissemination in space. Most patients remained fully ambulatory (EDSS score ≤4 in 13/16 patients [81%]) after a median (range) follow-up duration of 10.5 (1-20.5) years. Age-adjusted annual incidence rates were 0.46/100,000 (95% confidence interval [CI] 0.12-0.81) for female patients, 0.66/100,000 (95% CI 0.23-1.02) for male patients, and 0.56/100,000 [95% CI 0.28-0.83] overall. When age- and sex-adjusted to the 2010 US total population, the overall annual incidence rate was 0.57 (95% CI 0.28-0.84). Despite aggressive clinical presentation at disease onset, most patients remained fully ambulatory (EDSS score ≤4 in 13/16 patients) with a relapsing-remitting course. CONCLUSIONS: Although incidence is rare, TD should be suspected in patients presenting with subacutely progressive neurological deficits associated with magnetic resonance imaging findings of ring enhancement, apparent diffusion coefficient restriction, and OCB on spinal fluid analysis.

Generative Adversarial Networks to Synthesize Missing T1 and FLAIR MRI Sequences for Use in a Multisequence Brain Tumor Segmentation Model.

Background Missing MRI sequences represent an obstacle in the development and use of deep learning (DL) models that require multiple inputs. Purpose To determine if synthesizing brain MRI scans using generative adversarial networks (GANs) allows for the use of a DL model for brain lesion segmentation that requires T1-weighted images, postcontrast T1-weighted images, fluid-attenuated inversion recovery (FLAIR) images, and T2-weighted images. Materials and Methods In this retrospective study, brain MRI scans obtained between 2011 and 2019 were collected, and scenarios were simulated in which the T1-weighted images and FLAIR images were missing. Two GANs were trained, validated, and tested using 210 glioblastomas (GBMs) (Multimodal Brain Tumor Image Segmentation Benchmark [BRATS] 2017) to generate T1-weighted images from postcontrast T1-weighted images and FLAIR images from T2-weighted images. The quality of the generated images was evaluated with mean squared error (MSE) and the structural similarity index (SSI). The segmentations obtained with the generated scans were compared with those obtained with the original MRI scans using the dice similarity coefficient (DSC). The GANs were validated on sets of GBMs and central nervous system lymphomas from the authors' institution to assess their generalizability. Statistical analysis was performed using the Mann-Whitney, Friedman, and Dunn tests. Results Two hundred ten GBMs from the BRATS data set and 46 GBMs (mean patient age, 58 years ± 11 [standard deviation]; 27 men [59%] and 19 women [41%]) and 21 central nervous system lymphomas (mean patient age, 67 years ± 13; 12 men [57%] and nine women [43%]) from the authors' institution were evaluated. The median MSE for the generated T1-weighted images ranged from 0.005 to 0.013, and the median MSE for the generated FLAIR images ranged from 0.004 to 0.103. The median SSI ranged from 0.82 to 0.92 for the generated T1-weighted images and from 0.76 to 0.92 for the generated FLAIR images. The median DSCs for the segmentation of the whole lesion, the FLAIR hyperintensities, and the contrast-enhanced areas using the generated scans were 0.82, 0.71, and 0.92, respectively, when replacing both T1-weighted and FLAIR images; 0.84, 0.74, and 0.97 when replacing only the FLAIR images; and 0.97, 0.95, and 0.92 when replacing only the T1-weighted images. Conclusion Brain MRI scans generated using generative adversarial networks can be used as deep learning model inputs in case MRI sequences are missing. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Zhong in this issue. An earlier incorrect version of this article appeared online. This article was corrected on April 12, 2021.

Glioma risk associated with extent of estimated European genetic ancestry in African Americans and Hispanics.

Glioma incidence is highest in non-Hispanic Whites, and to date, glioma genome-wide association studies (GWAS) to date have only included European ancestry (EA) populations. African Americans and Hispanics in the US have varying proportions of EA, African (AA) and Native American ancestries (NAA). It is unknown if identified GWAS loci or increased EA is associated with increased glioma risk. We assessed whether EA was associated with glioma in African Americans and Hispanics. Data were obtained for 832 cases and 675 controls from the Glioma International Case-Control Study and GliomaSE Case-Control Study previously estimated to have <80% EA, or self-identify as non-White. We estimated global and local ancestry using fastStructure and RFMix, respectively, using 1,000 genomes project reference populations. Within groups with ≥40% AA (AFR≥0.4 ), and ≥15% NAA (AMR≥0.15 ), genome-wide association between local EA and glioma was evaluated using logistic regression conditioned on global EA for all gliomas. We identified two regions (7q21.11, p = 6.36 × 10-4 ; 11p11.12, p = 7.0 × 10-4 ) associated with increased EA, and one associated with decreased EA (20p12.13, p = 0.0026) in AFR≥0.4 . In addition, we identified a peak at rs1620291 (p = 4.36 × 10-6 ) in 7q21.3. Among AMR≥0.15 , we found an association between increased EA in one region (12q24.21, p = 8.38 × 10-4 ), and decreased EA in two regions (8q24.21, p = 0. 0010; 20q13.33, p = 6.36 × 10-4 ). No other significant associations were identified. This analysis identified an association between glioma and two regions previously identified in EA populations (8q24.21, 20q13.33) and four novel regions (7q21.11, 11p11.12, 12q24.21 and 20p12.13). The identifications of novel association with EA suggest regions to target for future genetic association studies.

8q24 clear cell renal cell carcinoma germline variant is associated with VHL mutation status and clinical aggressiveness.

BACKGROUND: The four most commonly-mutated genes in clear cell renal cell carcinoma (ccRCC) tumors are BAP1, PBRM1, SETD2 and VHL. And, there are currently 14 known RCC germline variants that have been reproducibly shown to be associated with RCC risk. However, the association of germline genetics with tumor genetics and clinical aggressiveness are unknown. METHODS: We analyzed 420 ccRCC patients from The Cancer Genome Atlas. Molecular subtype was determined based on acquired mutations in BAP1, PBRM1, SETD2 and VHL. Aggressive subtype was defined clinically using Mayo SSIGN score and molecularly using the ccA/ccB gene expression subtype. Publically-available Hi-C data were used to link germline risk variants with candidate target genes. RESULTS: The 8q24 variant rs35252396 was significantly associated with VHL mutation status (OR = 1.6, p = 0.0037) and SSIGN score (OR = 1.9, p = 0.00094), after adjusting for multiple comparisons. We observed that, while some germline variants have interactions with nearby genes, some variants demonstrate long-range interactions with target genes. CONCLUSIONS: These data further demonstrate the link between rs35252396, HIF pathway and ccRCC clinical aggressiveness, providing a more comprehensive picture of how germline genetics and tumor genetics interact with respect to tumor development and progression.

Alcohol consumption, variability in alcohol dehydrogenase genes and risk of renal cell carcinoma.

Alcohol consumption has been associated inversely with renal cell carcinoma (RCC) risk; however, no study has examined effect modification by germline variation in alcohol-metabolizing genes. We investigated whether the association between alcohol intake and RCC risk is modulated by germline variants in alcohol dehydrogenase genes in a large case-control study. Data from 652 RCC cases and 1,366 non-cancer controls were analyzed. Alcohol intake was assessed using a standardized risk factor questionnaire. Three previously genotyped polymorphisms in ADH6 and ADH7 with the TaqMan assay were examined. Odds ratios (ORs) and 95% confidence interval (CI) were calculated using logistic regression, adjusting for covariates. Compared to non-drinkers, ever consumption of alcohol was associated with lower RCC risk (OR = 0.52, 95% CI = 0.42-0.65). Analysis with cubic spline regression curve showed a "J-shaped" relationship between alcohol drinks/day and RCC risk, such that there was no added benefit against RCC for consumption of more than two drinks/day. We observed effect modification by variation in rs1154454 (ADH7) (pinteraction = 0.007); a per unit increase in alcohol drink/day was associated with 35% lower RCC risk among non-minor allele carriers, a 27% lower risk among those who carry one copy of the minor allele, but no association was observed among those with two copies of the minor allele. These findings indicate that alcohol consumption is associated with lower RCC risk. Consuming more than two drinks a day does not confer additional protection against RCC. The association between alcohol intake and RCC risk appears to be modulated by inter-individual germline variation in alcohol-metabolizing genes.

Age-specific genome-wide association study in glioblastoma identifies increased proportion of 'lower grade glioma'-like features associated with younger age.

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 [p54-63 = 1.50x10-9 , OR54-63 = 1.28, 95%CI54-63 = 1.18-1.39; p64+ = 2.14x10-11 , OR64+ = 1.32, 95%CI64+ = 1.21-1.43] and rs11979158 [p54-63 = 6.13x10-8 , OR54-63 = 1.35, 95%CI54-63 = 1.21-1.50; p64+ = 2.18x10-10 , OR64+ = 1.42, 95%CI64+ = 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 (p18-53 = 9.30 × 10-11 , OR18-53 = 1.76, 95%CI18-53 = 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.'

Influence of obesity-related risk factors in the aetiology of glioma.

BACKGROUND: Obesity and related factors have been implicated as possible aetiological factors for the development of glioma in epidemiological observation studies. We used genetic markers in a Mendelian randomisation framework to examine whether obesity-related traits influence glioma risk. This methodology reduces bias from confounding and is not affected by reverse causation. METHODS: Genetic instruments were identified for 10 key obesity-related risk factors, and their association with glioma risk was evaluated using data from a genome-wide association study of 12,488 glioma patients and 18,169 controls. The estimated odds ratio of glioma associated with each of the genetically defined obesity-related traits was used to infer evidence for a causal relationship. RESULTS: No convincing association with glioma risk was seen for genetic instruments for body mass index, waist-to-hip ratio, lipids, type-2 diabetes, hyperglycaemia or insulin resistance. Similarly, we found no evidence to support a relationship between obesity-related traits with subtypes of glioma-glioblastoma (GBM) or non-GBM tumours. CONCLUSIONS: This study provides no evidence to implicate obesity-related factors as causes of glioma.

Glioma Groups Based on 1p/19q, IDH, and TERT Promoter Mutations in Tumors.

BACKGROUND: The prediction of clinical behavior, response to therapy, and outcome of infiltrative glioma is challenging. On the basis of previous studies of tumor biology, we defined five glioma molecular groups with the use of three alterations: mutations in the TERT promoter, mutations in IDH, and codeletion of chromosome arms 1p and 19q (1p/19q codeletion). We tested the hypothesis that within groups based on these features, tumors would have similar clinical variables, acquired somatic alterations, and germline variants. METHODS: We scored tumors as negative or positive for each of these markers in 1087 gliomas and compared acquired alterations and patient characteristics among the five primary molecular groups. Using 11,590 controls, we assessed associations between these groups and known glioma germline variants. RESULTS: Among 615 grade II or III gliomas, 29% had all three alterations (i.e., were triple-positive), 5% had TERT and IDH mutations, 45% had only IDH mutations, 7% were triple-negative, and 10% had only TERT mutations; 5% had other combinations. Among 472 grade IV gliomas, less than 1% were triple-positive, 2% had TERT and IDH mutations, 7% had only IDH mutations, 17% were triple-negative, and 74% had only TERT mutations. The mean age at diagnosis was lowest (37 years) among patients who had gliomas with only IDH mutations and was highest (59 years) among patients who had gliomas with only TERT mutations. The molecular groups were independently associated with overall survival among patients with grade II or III gliomas but not among patients with grade IV gliomas. The molecular groups were associated with specific germline variants. CONCLUSIONS: Gliomas were classified into five principal groups on the basis of three tumor markers. The groups had different ages at onset, overall survival, and associations with germline variants, which implies that they are characterized by distinct mechanisms of pathogenesis. (Funded by the National Institutes of Health and others.).

Impact of atopy on risk of glioma: a Mendelian randomisation study.

BACKGROUND: An inverse relationship between allergies with glioma risk has been reported in several but not all epidemiological observational studies. We performed an analysis of genetic variants associated with atopy to assess the relationship with glioma risk using Mendelian randomisation (MR), an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations. METHODS: Two-sample MR was undertaken using genome-wide association study data. We used single nucleotide polymorphisms (SNPs) associated with atopic dermatitis, asthma and hay fever, IgE levels, and self-reported allergy as instrumental variables. We calculated MR estimates for the odds ratio (OR) for each risk factor with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighting (IVW), maximum likelihood estimation (MLE), weighted median estimate (WME) and mode-based estimate (MBE) methods. Violation of MR assumptions due to directional pleiotropy were sought using MR-Egger regression and HEIDI-outlier analysis. RESULTS: Under IVW, MLE, WME and MBE methods, associations between glioma risk with asthma and hay fever, self-reported allergy and IgE levels were non-significant. An inverse relationship between atopic dermatitis and glioma risk was found by IVW (OR 0.96, 95% confidence interval (CI) 0.93-1.00, P = 0.041) and MLE (OR 0.96, 95% CI 0.94-0.99, P = 0.003), but not by WME (OR 0.96, 95% CI 0.91-1.01, P = 0.114) or MBE (OR 0.97, 95% CI 0.92-1.02, P = 0.194). CONCLUSIONS: Our investigation does not provide strong evidence for relationship between atopy and the risk of developing glioma, but findings do not preclude a small effect in relation to atopic dermatitis. Our analysis also serves to illustrate the value of using several MR methods to derive robust conclusions.

Coffee consumption and risk of renal cell carcinoma.

BACKGROUND: Studies have suggested an inverse association between coffee consumption and risk of renal cell carcinoma (RCC); however, data regarding decaffeinated coffee are limited. METHODS: We conducted a case-control study of 669 incident RCC cases and 1,001 frequency-matched controls. Participants completed identical risk factor questionnaires that solicited information about usual coffee consumption habits. The study participants were categorized as non-coffee, caffeinated coffee, decaffeinated coffee, or both caffeinated and decaffeinated coffee drinkers. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression, adjusting for multiple risk factors for RCC. RESULTS: Compared with no coffee consumption, we found an inverse association between caffeinated coffee consumption and RCC risk (OR 0.74; 95% CI 0.57-0.99), whereas we observed a trend toward increased risk of RCC for consumption of decaffeinated coffee (OR 1.47; 95% CI 0.98-2.19). Decaffeinated coffee consumption was associated also with increased risk of the clear cell RCC (ccRCC) subtype, particularly the aggressive form of ccRCC (OR 1.80; 95% CI 1.01-3.22). CONCLUSIONS: Consumption of caffeinated coffee is associated with reduced risk of RCC, while decaffeinated coffee consumption is associated with an increase in risk of aggressive ccRCC. Further inquiry is warranted in large prospective studies and should include assessment of dose-response associations.

Adult infiltrating gliomas with WHO 2016 integrated diagnosis: additional prognostic roles of ATRX and TERT.

The "integrated diagnosis" for infiltrating gliomas in the 2016 revised World Health Organization (WHO) classification of tumors of the central nervous system requires assessment of the tumor for IDH mutations and 1p/19q codeletion. Since TERT promoter mutations and ATRX alterations have been shown to be associated with prognosis, we analyzed whether these tumor markers provide additional prognostic information within each of the five WHO 2016 categories. We used data for 1206 patients from the UCSF Adult Glioma Study, the Mayo Clinic and The Cancer Genome Atlas (TCGA) with infiltrative glioma, grades II-IV for whom tumor status for IDH, 1p/19q codeletion, ATRX, and TERT had been determined. All cases were assigned to one of 5 groups following the WHO 2016 diagnostic criteria based on their morphologic features, and IDH and 1p/19q codeletion status. These groups are: (1) Oligodendroglioma, IDH-mutant and 1p/19q-codeleted; (2) Astrocytoma, IDH-mutant; (3) Glioblastoma, IDH-mutant; (4) Glioblastoma, IDH-wildtype; and (5) Astrocytoma, IDH-wildtype. Within each group, we used univariate and multivariate Cox proportional hazards models to assess associations of overall survival with patient age at diagnosis, grade, and ATRX alteration status and/or TERT promoter mutation status. Among Group 1 IDH-mutant 1p/19q-codeleted oligodendrogliomas, the TERT-WT group had significantly worse overall survival than the TERT-MUT group (HR: 2.72, 95% CI 1.05-7.04, p = 0.04). In both Group 2, IDH-mutant astrocytomas and Group 3, IDH-mutant glioblastomas, neither TERT mutations nor ATRX alterations were significantly associated with survival. Among Group 4, IDH-wildtype glioblastomas, ATRX alterations were associated with favorable outcomes (HR: 0.36, 95% CI 0.17-0.81, p = 0.01). Among Group 5, IDH-wildtype astrocytomas, the TERT-WT group had significantly better overall survival than the TERT-MUT group (HR: 0.48, 95% CI 0.27-0.87), p = 0.02). Thus, we present evidence that in certain WHO 2016 diagnostic groups, testing for TERT promoter mutations or ATRX alterations may provide additional useful prognostic information.

BAP1 and PBRM1 in metastatic clear cell renal cell carcinoma: tumor heterogeneity and concordance with paired primary tumor.

BACKGROUND: BAP1 and PBRM1 are frequently mutated in primary clear cell renal cell carcinoma (ccRCC) tumors; however, the frequency and clinical relevance of these mutations in metastatic ccRCC tumors is unknown. Additionally, while intra-tumor heterogeneity has been shown to be common in primary ccRCC, little is known regarding heterogeneity in metastatic ccRCC tumors. MATERIALS AND METHODS: We analyzed BAP1 and PBRM1 loss of protein expression in patient-matched primary and metastatic tumors from 97 patients. Expression was determined using a validated immunohistochemistry assay, which has been shown to be correlated with mutation status. RESULTS: Of the 97 patients evaluated, 20 and 57% showed loss of BAP1 and PBRM1 in their primary tumors, respectively. Comparing expression across patient-matched primary-metastatic tumor pairs, 98 and 90% had concordant BAP1 and PBRM1 expression, respectively. Both patients who demonstrated discordant BAP1 expression showed loss of BAP1 expression during progression to metastatic ccRCC. Similarly, seven of the ten patients that demonstrated discordant PBRM1 expression showed loss of PBRM1 expression during progression to metastatic ccRCC. We evaluated intra-metastatic tumor heterogeneity using 12 patients who had multiple blocks available from the same tumor with representative pathology; 100 and 92% showed concordant BAP1 and PBRM1 expression, respectively. Amongst 32 patients who had serial metastatic tumors available, both BAP1 and PBRM1 had 97% concordant expression. CONCLUSIONS: We observed minimal intra- and inter- tumor heterogeneity in metastatic ccRCC tumors. Patients with discordant BAP1 or PBRM1 expression across their matched primary and metastatic tumors usually showed loss of expression during progression to metastatic ccRCC.

Measure transcript integrity using RNA-seq data.

BACKGROUND: Stored biological samples with pathology information and medical records are invaluable resources for translational medical research. However, RNAs extracted from the archived clinical tissues are often substantially degraded. RNA degradation distorts the RNA-seq read coverage in a gene-specific manner, and has profound influences on whole-genome gene expression profiling. RESULT: We developed the transcript integrity number (TIN) to measure RNA degradation. When applied to 3 independent RNA-seq datasets, we demonstrated TIN is a reliable and sensitive measure of the RNA degradation at both transcript and sample level. Through comparing 10 prostate cancer clinical samples with lower RNA integrity to 10 samples with higher RNA quality, we demonstrated that calibrating gene expression counts with TIN scores could effectively neutralize RNA degradation effects by reducing false positives and recovering biologically meaningful pathways. When further evaluating the performance of TIN correction using spike-in transcripts in RNA-seq data generated from the Sequencing Quality Control consortium, we found TIN adjustment had better control of false positives and false negatives (sensitivity = 0.89, specificity = 0.91, accuracy = 0.90), as compared to gene expression analysis results without TIN correction (sensitivity = 0.98, specificity = 0.50, accuracy = 0.86). CONCLUSION: TIN is a reliable measurement of RNA integrity and a valuable approach used to neutralize in vitro RNA degradation effect and improve differential gene expression analysis.

Genes associated with histopathologic features of triple negative breast tumors predict molecular subtypes.

Distinct subtypes of triple negative (TN) breast cancer have been identified by tumor expression profiling. However, little is known about the relationship between histopathologic features of TN tumors, which reflect aspects of both tumor behavior and tumor microenvironment, and molecular TN subtypes. The histopathologic features of TN tumors were assessed by central review and 593 TN tumors were subjected to whole genome expression profiling using the Illumina Whole Genome DASL array. TN molecular subtypes were defined based on gene expression data associated with histopathologic features of TN tumors. Gene expression analysis yielded signatures for four TN subtypes (basal-like, androgen receptor positive, immune, and stromal) consistent with previous studies. Expression analysis also identified genes significantly associated with the 12 histological features of TN tumors. Development of signatures using these markers of histopathological features resulted in six distinct TN subtype signatures, including an additional basal-like and stromal signature. The additional basal-like subtype was distinguished by elevated expression of cell motility and glucose metabolism genes and reduced expression of immune signaling genes, whereas the additional stromal subtype was distinguished by elevated expression of immunomodulatory pathway genes. Histopathologic features that reflect heterogeneity in tumor architecture, cell structure, and tumor microenvironment are related to TN subtype. Accounting for histopathologic features in the development of gene expression signatures, six major subtypes of TN breast cancer were identified.

Loss of histone H3 lysine 36 trimethylation is associated with an increased risk of renal cell carcinoma-specific death.

Sequencing of clear cell renal cell carcinomas identified loss-of-function mutations of SETD2, a gene that encodes a nonredundant methytransferase responsible for histone H3 lysine 36 trimethylation (H3K36me3), and H3K36me3 is progressively deregulated in metastases. However, few data exist regarding the impact of loss of H3K36me3 on outcomes. We assessed the association of SETD2 DNA alterations and mRNA expression with overall survival using The Cancer Genome Atlas clear cell renal carcinoma data (N=411). Additionally, we assessed the association of H3K36 loss of methylation with renal cell carcinoma-specific survival and progression-free survival using an independent cohort at Mayo Clinic (N=1454). Overall survival, renal cell carcinoma-specific survival and progression-free survival were estimated using Kaplan-Meier method, and differences in survival across groups was compared using Cox regression models, adjusted for age and the Mayo SSIGN (stage, size, grade, and necrosis) score. In The Cancer Genome Atlas cohort, SETD2 DNA alterations or mRNA expression was not associated with overall survival (P>0.05). In the Mayo cohort, patients with H3K36me3-negative tumors were two times more likely to experience renal cell carcinoma-specific death than patients with H3K36me3-positive tumors (hazard ratio, 2.23; 95% confidence interval, 1.77-2.81); P<0.0001. After stratifying for the SSIGN score, H3K36me3-negative tumors in the low-risk SSIGN group had a worse renal cell carcinoma-specific survival (hazard ratio, 2.18; 95% confidence interval, 1.09-4.36); P=0.03. Although SETD2 DNA and mRNA alterations are not associated with overall survival, we provide evidence that deregulation of the H3K36me3 axis is associated with a higher risk of renal cell carcinoma-specific death. This association remains significant after stratifying for the SSIGN score, particularly among those patients with low-risk tumors.