ATM mutations improve radio-sensitivity in wild-type isocitrate dehydrogenase-associated high-grade glioma: retrospective analysis using next-generation sequencing data

Abstract PURPOSE/OBJECTIVES To identify the association of somatic ATM mutation (mATM) with improved radiotherapy sensitivity, we retrospectively reviewed the next-generation sequencing (NGS) data from high grade glioma patients. MATERIALS/METHODS This analysis includes 48 consecutive individuals diagnosed with high grade glioma (diffuse astrocytoma IDH-wild type n=2, anaplastic astrocytoma n=18, and glioblastoma n=28) between June 2017 and October 2018. Patients who underwent subtotal (n=30, 62.5%), partial (n=17, 35.4%) removal or biopsy (n=1, 2.1%) were included in this analysis for interpreting radio-sensitivity of residual tumor. We investigated mATM by NGS of FFPE specimens with a TruSight Tumor 170 (TST-170) cancer panel. RESULTS Among 48 samples, mATM was detected in 17% of cases (n=8). There was no significant difference in patient or tumor characteristics. Among mATM patients, there were 5 patients with glioblastoma and 3 patients with anaplastic astrocytoma IDH-wildtype. Most mutation was missense mutation (n=7, 88%). Median variant allele frequency was 44.7% (Interquartile range, IQR, 10.5–59.9%). Median follow-up duration after radiotherapy was 11.4 (IQR, 8.0–15.8) months. Radiation-related change was observed in 34 patients (71%). Tumors with mATM were related to higher frequency of radiation-related change at 6 months than tumors without mATM, respectively (88% and 64%, p = 0.016). Cases with mATM exhibited significantly 1-year progression free survival (PFS, 100% vs. 54%, p = 0.036). On subgroup of IDH WT (n=39) known as poor prognostic molecular marker, patients with mATM showed significantly higher PFS than patients without mATM (p=0.016, 1yr PFS 100% vs 43%). On subgroup with sub-ventricular zone involvement (n=38) representative of aggressiveness, PFS of patients with mATM was significantly higher than others (p=0.026, 1yr PFS 100% vs 43.9%). CONCLUSIONS Our results demonstrated that mATM is involved in radio-sensitivity with immediate radiologic change after radiation therapy followed by favorable radiologic response and clinical outcome beyond the aggressive nature of high grade glioma.

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Detection of viral pathogens in high grade gliomas from unmapped next-generation sequencing data

Experimental and Molecular Pathology ◽

10.1016/j.yexmp.2014.03.010 ◽

2014 ◽

Vol 96 (3) ◽

pp. 310-315 ◽

Cited By ~ 31

Author(s):

Patrick J. Cimino ◽

Guoyan Zhao ◽

David Wang ◽

Jennifer K. Sehn ◽

James S. Lewis ◽

...

Keyword(s):

Next Generation Sequencing ◽

Next Generation Sequencing Data ◽

High Grade ◽

Next Generation ◽

Sequencing Data ◽

Viral Pathogens ◽

High Grade Gliomas ◽

Generation Sequencing

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Faculty Opinions recommendation of VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718272765.793499663 ◽

2014 ◽

Author(s):

Gary Bader ◽

Mohamed Helmy

Keyword(s):

Next Generation Sequencing ◽

Network Analysis ◽

Next Generation Sequencing Data ◽

Cancer Genes ◽

Next Generation ◽

Sequencing Data ◽

Generation Sequencing

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Faculty Opinions recommendation of Bioinformatory-assisted analysis of next-generation sequencing data for precision medicine in pancreatic cancer.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.727775566.793536095 ◽

2017 ◽

Author(s):

Steve Pereira

Keyword(s):

Pancreatic Cancer ◽

Next Generation Sequencing ◽

Precision Medicine ◽

Next Generation Sequencing Data ◽

Next Generation ◽

Sequencing Data ◽

Assisted Analysis ◽

Generation Sequencing

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NGSremix: A software tool for estimating pairwise relatedness between admixed individuals from next-generation sequencing data

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab174 ◽

2021 ◽

Author(s):

Anne Krogh Nøhr ◽

Kristian Hanghøj ◽

Genis Garcia Erill ◽

Zilong Li ◽

Ida Moltke ◽

...

Keyword(s):

Next Generation Sequencing ◽

Genetic Research ◽

Likelihood Estimation ◽

Software Tool ◽

Estimation Methods ◽

Next Generation Sequencing Data ◽

Next Generation ◽

Sequencing Data ◽

Ngs Data ◽

Generation Sequencing

Abstract Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.

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recoup: flexible and versatile signal visualization from next generation sequencing

BMC Bioinformatics ◽

10.1186/s12859-020-03902-x ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Panagiotis Moulos

Keyword(s):

Next Generation Sequencing ◽

Next Generation Sequencing Data ◽

Special Focus ◽

Next Generation ◽

Sequencing Data ◽

User Friendliness ◽

Computational Environment ◽

Level Data ◽

Data Signal ◽

Generation Sequencing

Abstract Background The relentless continuing emergence of new genomic sequencing protocols and the resulting generation of ever larger datasets continue to challenge the meaningful summarization and visualization of the underlying signal generated to answer important qualitative and quantitative biological questions. As a result, the need for novel software able to reliably produce quick, comprehensive, and easily repeatable genomic signal visualizations in a user-friendly manner is rapidly re-emerging. Results recoup is a Bioconductor package for quick, flexible, versatile, and accurate visualization of genomic coverage profiles generated from Next Generation Sequencing data. Coupled with a database of precalculated genomic regions for multiple organisms, recoup offers processing mechanisms for quick, efficient, and multi-level data interrogation with minimal effort, while at the same time creating publication-quality visualizations. Special focus is given on plot reusability, reproducibility, and real-time exploration and formatting options, operations rarely supported in similar visualization tools in a profound way. recoup was assessed using several qualitative user metrics and found to balance the tradeoff between important package features, including speed, visualization quality, overall friendliness, and the reusability of the results with minimal additional calculations. Conclusion While some existing solutions for the comprehensive visualization of NGS data signal offer satisfying results, they are often compromised regarding issues such as effortless tracking of processing and preparation steps under a common computational environment, visualization quality and user friendliness. recoup is a unique package presenting a balanced tradeoff for a combination of assessment criteria while remaining fast and friendly.

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