Citations

Abstract Background Current literature suggestsisocitrate dehydrogenase (IDH)-mutant astrocytoma contains several molecular subgroups. In this study, we are interested in determining the connection between different molecular subgroups with grade and/or survival. Methods A cohort of 470 Mayo Clinic adult patients (≥18 years, 56.2% male) with primary IDH-mutant astrocytoma diagnosed by World Health Organization (WHO) 2021 criteria were examined. Results were validated in an independent cohort of 614 Mayo Clinic Neuropathology consult patients and 235 The Cancer Genome Atlas (TCGA) patients. Results The Mayo Clinic Practice cohort confirmed the association of CDKN2A/B deletion with overall survival (OS, homozygous vs hemizygous vs intact, 2.7 vs 9.6 vs 17.2 years, P < .001). Phosphatase and tensin homolog (PTEN) deletion was also associated with poor OS (7.3 vs 17.4 years, P < .001). Increased number of copy number alterations was associated with OS (continuous variable, HR = 1.027, P < .001). Carrying one or more copies of the germline risk allele at rs55705857 was associated with earlier age of onset (median age 33 vs 35 years, P = .01), and a shorter OS after adjusting for age, grade, sex and treatment (HR = 1.81, P = .007). The Mayo Clinic Neuropathology Consult cohort and TCGA were utilized to validate age of onset and survival, respectively. Unsupervised clustering of the copy number alterations identified several clinically significant groups that may define pathways to disease progression. Losses of chromosomes 11p, 13q, 1p, and 10q were all associated with reduced overall survival in the Mayo Clinic cohort. Conclusions Patients with hemizygous loss of CDKN2A/B, loss of PTEN, increased number of copy number alterations, specific chromosomal arm losses or rs55705857 germline risk allele have reduced overall survival.

Abstract The WHO 2021 classification of central nervous system tumors incorporated molecular markers to better define diffuse glioma subgroups. We analyzed array-based copy number, targeted next-generation sequencing, germline genotyping, and Illumina EPIC array methylation data from 404 primary IDH-mutant astrocytomas to further understand the relationship between copy number and outcomes. Loss of chromosome arm 13q was associated with poor overall survival after adjusting for age, sex, tumor grade, and treatment status (hazard ratio [HR]=2.04 (95% confidence interval: 1.25-3.33), p=0.004). Chromosome 13q loss was also significantly associated with the total number of copy number alterations (p<0.001). Loss of arm 11p was associated with poor survival in the adjusted analysis (HR=2.29 (1.38-3.79), p=0.001). Unsupervised clustering of the raw copy number data identified 12 clusters, where each cluster was defined by distinct copy number alteration(s). Clusters that contained 13q loss exhibited worse overall survival compared to other clusters. The clusters were significantly associated with age at diagnosis (p=0.015), tumor grade (p<0.001) and copy number complexity (p<0.001). The clusters with a high proportion of grade 4 tumors and with the highest complexity had the poorest overall survival. These findings highlight the prognostic relevance of chromosome 13q and 11p losses in IDH-mutant astrocytomas and support the integration of additional copy number alterations into molecular classification frameworks of IDH-mutant astrocytomas to improve risk stratification and patient management.

Abstract Advances in sequencing technologies have led to availability of huge amount of genomic data. However, accessing and hosting such data needs significant amount of expertise to deploy and manage existing tools. To circumvent this, we developed a comprehensive portable tool, galEupy, a lightweight and scalable platform that makes genome data management and visualization seamless. galEupy encompasses a compact schema capable of capturing all genome feature information in a layered format. The user interface is empowered with a genome browser and data query features for retrieval of meaningful information. galEupy can be deployed with simple commands into a full-fledged genome data warehouse within minutes. Subsequent to installation, the system can be populated with any genomic data and its annotation by launching the data loader. The data loader automatically parses the data and creates appropriate relationship within the data and populates the tables. galEupy can parse and upload medium sized genome and its annotation in minutes. Other features of galEupy includes data analysis tools and metabolic pathway visualization. By combining speed, usability, and flexibility, galEupy bridges the gap between genome data generation and meaningful biological insights, offering a practical solution for researchers working with a wide range of organisms.

Abstract Summary Copy number variation (CNV) and alteration (CNA) analysis is a crucial component in many genomic studies and its applications span from basic research to clinic diagnostics and personalized medicine. CNVpytor is a tool featuring a read depth-based caller and combined read depth and B-allele frequency (BAF) based 2D caller to find CNVs and CNAs. The tool stores processed intermediate data and CNV/CNA calls in a compact HDF5 file—pytor file. Here, we describe a new track in igv.js that utilizes pytor and whole genome variant files as input for on-the-fly read depth and BAF visualization, CNV/CNA calling and analysis. Embedding into HTML pages and Jupiter Notebooks enables convenient remote data access and visualization simplifying interpretation and analysis of omics data. Availability and implementation The CNVpytor track is integrated with igv.js and available at https://github.com/igvteam/igv.js. The documentation is available at https://github.com/igvteam/igv.js/wiki/cnvpytor. Usage can be tested in the IGV-Web app at https://igv.org/app and also on https://github.com/abyzovlab/CNVpytor.

Abstract INTRODUCTION Prior to 2021, (classic) glioblastoma (GBM) required absence of IDH mutation and histologic features of hypercellularity, nuclear atypia, microvascular proliferation (MVP), and necrosis. Absence of histologic features can be a result of undersampling, with molecular, radiologic, and clinical features consistent with GBM. Accordingly, WHO 2021 defined molecular glioblastoma as diffuse glioma IDHwt, H3wt, with one or more of MVP, necrosis, TERT promoter mutation, EGFR gene amplification (EGFRamp), and/or +7/−10. We hypothesized that there is clinical and radiographic heterogeneity among tumors defined as molecular GBM. METHODS We identified 121 patients that met the criteria for molecular GBM. 121 Classic GBM, defined as IDHwt with hypercellularity, MVP or necrosis, were matched to molecular GBM cases by age, sex, and diagnosis date. All cases were reviewed for relevant histologic features and molecular features. Examined clinical variables included: first symptom, time from first symptom to date of pathological diagnosis, date of first MRI, tumor location, radiographic features of enhancement, diffusion or mass effect, time to progression and overall survival. Clinical, radiologic, and molecular features were compared between classic and molecular GBM. RESULTS Currently,160 cases have been reviewed. Preliminary results show that there is a longer time from first symptom to diagnosis for molecular GBM. Molecular GBM is significantly more likely to be discovered coincidentally, and without enhancement or radiographic necrosis. Classic GBM is significantly more likely to present with focal neurologic deficit as first symptom, regional mass effect on index imaging and have monosomy 10. CONCLUSION While pathologic undersampling accounts for a significant proportion of molecular GBM, our data suggest that there are significant clinical, radiographic, and outcome differences between classical and molecular GBM. Final analysis of the entire cohort will help better define this clinical spectrum.

The CRISPR-Cas9 system has enabled researchers to precisely modify/edit the sequence of a genome. A typical editing experiment consists of two steps: (1) editing cultured cells; (2) cell cloning and selection of clones with and without intended edit, presumed to be isogenic. The application of CRISPR-Cas9 system may result in off-target edits, whereas cloning will reveal culture-acquired mutations. We analyzed the extent of the former and the latter by whole genome sequencing in three experiments involving separate genomic loci and conducted by three independent laboratories. In all experiments we hardly found any off-target edits, whereas detecting hundreds to thousands of single nucleotide mutations unique to each clone after relatively short culture of 10–20 passages. Notably, clones also differed in copy number alterations (CNAs) that were several kb to several mb in size and represented the largest source of genomic divergence among clones. We suggest that screening of clones for mutations and CNAs acquired in culture is a necessary step to allow correct interpretation of DNA editing experiments. Furthermore, since culture associated mutations are inevitable, we propose that experiments involving derivation of clonal lines should compare a mix of multiple unedited lines and a mix of multiple edited lines.

Establishing causal links between inherited polymorphisms and cancer risk is challenging. Here, we focus on the single-nucleotide polymorphism rs55705857, which confers a sixfold greater risk of isocitrate dehydrogenase ( IDH) –mutant low-grade glioma (LGG). We reveal that rs55705857 itself is the causal variant and is associated with molecular pathways that drive LGG. Mechanistically, we show that rs55705857 resides within a brain-specific enhancer, where the risk allele disrupts OCT2/4 binding, allowing increased interaction with the Myc promoter and increased Myc expression. Mutating the orthologous mouse rs55705857 locus accelerated tumor development in an Idh1 R132H -driven LGG mouse model from 472 to 172 days and increased penetrance from 30% to 75%. Our work reveals mechanisms of the heritable predisposition to lethal glioma in ~40% of LGG patients.

We analyzed 131 human brains (44 neurotypical, 19 with Tourette syndrome, 9 with schizophrenia, and 59 with autism) for somatic mutations after whole genome sequencing to a depth of more than 200×. Typically, brains had 20 to 60 detectable single-nucleotide mutations, but ~6% of brains harbored hundreds of somatic mutations. Hypermutability was associated with age and damaging mutations in genes implicated in cancers and, in some brains, reflected in vivo clonal expansions. Somatic duplications, likely arising during development, were found in ~5% of normal and diseased brains, reflecting background mutagenesis. Brains with autism were associated with mutations creating putative transcription factor binding motifs in enhancer-like regions in the developing brain. The top-ranked affected motifs corresponded to MEIS (myeloid ectopic viral integration site) transcription factors, suggesting a potential link between their involvement in gene regulation and autism.

Abstract Background Detecting copy number variations (CNVs) and copy number alterations (CNAs) based on whole-genome sequencing data is important for personalized genomics and treatment. CNVnator is one of the most popular tools for CNV/CNA discovery and analysis based on read depth. Findings Herein, we present an extension of CNVnator developed in Python—CNVpytor. CNVpytor inherits the reimplemented core engine of its predecessor and extends visualization, modularization, performance, and functionality. Additionally, CNVpytor uses B-allele frequency likelihood information from single-nucleotide polymorphisms and small indels data as additional evidence for CNVs/CNAs and as primary information for copy number–neutral losses of heterozygosity. Conclusions CNVpytor is significantly faster than CNVnator—particularly for parsing alignment files (2–20 times faster)—and has (20–50 times) smaller intermediate files. CNV calls can be filtered using several criteria, annotated, and merged over multiple samples. Modular architecture allows it to be used in shared and cloud environments such as Google Colab and Jupyter notebook. Data can be exported into JBrowse, while a lightweight plugin version of CNVpytor for JBrowse enables nearly instant and GUI-assisted analysis of CNVs by any user. CNVpytor release and the source code are available on GitHub at https://github.com/abyzovlab/CNVpytor under the MIT license.

Abstract BACKGROUND Determination of the causation of germline single nucleotide polymorphisms (SNPs) located in non-coding regions of the genome is challenging. The genomic region of 8q24 has been identified as important in many kinds of cancer, linked to a topologically associated domain (TAD) encompassing MYC; this TAD contains a GWAS SNP (rs55705857) associated with IDH-mutant glioma. METHODS Germline genotyping data from 622 IDH-mutant glioma and 668 controls were used to fine map the rs55705857 locus by detailed haplotype analysis. Chromatin immunoprecipitation sequencing (ChIP-seq) of histone markers H3K4me1, H3K4me3, H3K27ac and H3K36me3 was performed on normal brain samples (n=8) and human glioma samples (n=11 IDH-wt and 52 IDH-mut). RNAseq from 9 normal and 83 brain tumors (n=26 IDH-wt and 55 IDH-mut) were used to assess differential gene expression. RESULTS Fine-mapping identified rs55705857 SNP as the most likely causative allele (OR=8.69; p<0.001) within 8q24 for the development of IDH-mutant glioma. At rs55705857, both H3K27ac and H3K4me1 in IDH-mutant vs IDH-wt tumors were increased 3.05- and 1.58-fold, respectively (DiffBind; p=5.81×10-7 and p=2.31×10-3). ChromHMM analysis of the marks indicated that promoter and enhancer functions were significantly increased, and the activity broadened at rs55705857 in IDH-mut gliomas compared to IDH-wt tumors and normal brain samples. This enhancement correlated with significant increased MYC expression in IDH-mut gliomas (p=3.1×10-13), as well as alterations of Myc signaling targets. Publicly available ATACseq, ChIPseq and long-range DNA interaction data demonstrated that the rs55705857 locus is open and interacts with the MYC promoter. CONCLUSIONS Fine-mapping of the 8q24 locus provided strong evidence that rs55705857 is the causative 8q24 locus associated with IDH-mut glioma. Functional experiments suggest that IDH mutation facilitates rs55705857 interaction with MYC to alter downstream MYC targets.