scholarly journals Transposable Element Exprssion in Tumors is Associated with Immune Infiltration and Increased Antigenicity

2018 ◽  
Author(s):  
Yu Kong ◽  
Chris Rose ◽  
Ashley A. Cass ◽  
Martine Darwish ◽  
Steve Lianoglou ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Transposable Element ◽  
De Novo ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Genome Wide ◽  
Dna Damage Responses ◽  
Cancer Genome Atlas ◽  
Demethylation Agent

AbstractProfound loss of DNA methylation is a well-recognized hallmark of cancer. Given its role in silencing transposable elements (TEs), we hypothesized that extensive TE expression occurs in tumors with highly demethylated DNA. We developed REdiscoverTE, a computational method for quantifying genome-wide TE expression in RNA sequencing data. Using The Cancer Genome Atlas database, we observed increased expression of over 400 TE subfamilies, of which 262 appeared to result from a proximal loss of DNA methylation. The most recurrent TEs were among the evolutionarily youngest in the genome, predominantly expressed from intergenic loci, and associated with antiviral or DNA damage responses. Treatment of glioblastoma cells with a demethylation agent resulted in both increased TE expression and de novo presentation of TE-derived peptides on MHC class I molecules. Therapeutic reactivation of tumor-specific TEs may synergize with immunotherapy by inducing both inflammation and the display of potentially immunogenic neoantigens.One Sentence SummaryTransposable element expression in tumors is associated with increased immune response and provides tumor-associated antigens

scholarly journals Transposable element expression in tumors is associated with immune infiltration and increased antigenicity

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Yu Kong ◽  
Christopher M. Rose ◽  
Ashley A. Cass ◽  
Alexander G. Williams ◽  
Martine Darwish ◽  
...  
Keyword(s):  
Dna Methylation ◽  
De Novo ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Potential Consequence ◽  
Sequencing Data ◽  
Antiviral Responses ◽  
Genome Wide ◽  
Cancer Genome Atlas ◽  
Demethylation Agent

AbstractProfound global loss of DNA methylation is a hallmark of many cancers. One potential consequence of this is the reactivation of transposable elements (TEs) which could stimulate the immune system via cell-intrinsic antiviral responses. Here, we develop REdiscoverTE, a computational method for quantifying genome-wide TE expression in RNA sequencing data. Using The Cancer Genome Atlas database, we observe increased expression of over 400 TE subfamilies, of which 262 appear to result from a proximal loss of DNA methylation. The most recurrent TEs are among the evolutionarily youngest in the genome, predominantly expressed from intergenic loci, and associated with antiviral or DNA damage responses. Treatment of glioblastoma cells with a demethylation agent results in both increased TE expression and de novo presentation of TE-derived peptides on MHC class I molecules. Therapeutic reactivation of tumor-specific TEs may synergize with immunotherapy by inducing inflammation and the display of potentially immunogenic neoantigens.

scholarly journals Genome wide efficiency profiling reveals modulation of maintenance and de novo methylation by Tets

2020 ◽  
Author(s):  
Pascal Giehr ◽  
Charalampos Kyriakopoulos ◽  
Karl Nordström ◽  
Abduhlrahman Salhab ◽  
Fabian Müller ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Molecular Mechanisms ◽  
De Novo ◽  
Epigenetic Modification ◽  
Embryonic Stem ◽  
Regulatory Elements ◽  
Sequencing Data ◽  
Reduced Representation ◽  
Genome Wide ◽  
Global And Local

AbstractBackgroundDNA methylation is an essential epigenetic modification which is set and maintained by DNA methyl transferases (Dnmts) and removed via active and passive mechanisms involving Tet mediated oxidation. While the molecular mechanisms of these enzymes are well studied, their interplay on shaping cell specific methylomes remains less well understood. In our work we model the activities of Tets and Dnmts at single CpGs across the genome using a novel type of high resolution sequencing data.ResultsTo accurately measure 5mC and 5hmC levels at single CpGs we developed RRHPoxBS, a reduced representation hairpin oxidative bisulfite sequencing approach. Using this method we mapped the methylomes and hydroxymethylomes of wild type and Tet triple knockout mouse embryonic stem cells. These comprehensive datasets were then used to develop an extended Hidden Markov model allowing us i) to determine the symmetrical methylation and hydroxymethylation state at millions of individual CpGs, ii) infer the maintenance and de novo methylation efficiencies of Dnmts and the hydroxylation efficiencies of Tets at individual CpG positions. We find that Tets exhibit their highest activity around unmethylated regulatory elements, i.e. active promoters and enhancers. Furthermore, we find that Tets’ presence has a profound effect on the global and local maintenance and de novo methylation activities by the Dnmts, not only substantially contributing to a universal demethylation of the genome but also shaping the overall methylation landscape.ConclusionsOur analysis demonstrates that a fine tuned and locally controlled interplay between Tets and Dnmts is important to modulate de novo and maintenance activities of Dnmts across the genome. Tet activities contribute to DNA methylation patterning in the following ways: They oxidize 5mC, they locally shield DNA from accidental de novo methylation and at the same time modulate maintenance and de novo methylation efficiencies of Dnmts across the genome.

scholarly journals CloneSig can jointly infer intra-tumor heterogeneity and mutational signature activity in bulk tumor sequencing data

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Judith Abécassis ◽  
Fabien Reyal ◽  
Jean-Philippe Vert
Keyword(s):  
Tumor Heterogeneity ◽  
Cancer Genomics ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Cancer Dataset ◽  
Whole Exome Sequencing Data ◽  
Cancer Genome Atlas ◽  
Pan Cancer ◽  
Mutational Processes

AbstractSystematic DNA sequencing of cancer samples has highlighted the importance of two aspects of cancer genomics: intra-tumor heterogeneity (ITH) and mutational processes. These two aspects may not always be independent, as different mutational processes could be involved in different stages or regions of the tumor, but existing computational approaches to study them largely ignore this potential dependency. Here, we present CloneSig, a computational method to jointly infer ITH and mutational processes in a tumor from bulk-sequencing data. Extensive simulations show that CloneSig outperforms current methods for ITH inference and detection of mutational processes when the distribution of mutational signatures changes between clones. Applied to a large cohort of 8,951 tumors with whole-exome sequencing data from The Cancer Genome Atlas, and on a pan-cancer dataset of 2,632 whole-genome sequencing tumor samples from the Pan-Cancer Analysis of Whole Genomes initiative, CloneSig obtains results overall coherent with previous studies.

scholarly journals DNA Methylation-Driven Genes for Developing Survival Nomogram for Low-Grade Glioma

2022 ◽  
Vol 11 ◽  
Author(s):  
Yingyun Guo ◽  
Yuan Li ◽  
Jiao Li ◽  
Weiping Tao ◽  
Weiguo Dong
Keyword(s):  
Dna Methylation ◽  
The Cancer Genome Atlas ◽  
Clinicopathological Parameters ◽  
Low Grade ◽  
Lasso Regression ◽  
Sequencing Data ◽  
Cancer Genome Atlas ◽  
Auc Value ◽  
User Friendly ◽  
Genome Atlas

Low-grade gliomas (LGG) are heterogeneous, and the current predictive models for LGG are either unsatisfactory or not user-friendly. The objective of this study was to establish a nomogram based on methylation-driven genes, combined with clinicopathological parameters for predicting prognosis in LGG. Differential expression, methylation correlation, and survival analysis were performed in 516 LGG patients using RNA and methylation sequencing data, with accompanying clinicopathological parameters from The Cancer Genome Atlas. LASSO regression was further applied to select optimal prognosis-related genes. The final prognostic nomogram was implemented together with prognostic clinicopathological parameters. The predictive efficiency of the nomogram was internally validated in training and testing groups, and externally validated in the Chinese Glioma Genome Atlas database. Three DNA methylation-driven genes, ARL9, CMYA5, and STEAP3, were identified as independent prognostic factors. Together with IDH1 mutation status, age, and sex, the final prognostic nomogram achieved the highest AUC value of 0.930, and demonstrated stable consistency in both internal and external validations. The prognostic nomogram could predict personal survival probabilities for patients with LGG, and serve as a user-friendly tool for prognostic evaluation, optimizing therapeutic regimes, and managing LGG patients.

scholarly journals Crunch: Integrated processing and modeling of ChIP-seq data in terms of regulatory motifs

2016 ◽  
Author(s):  
Severin Berger ◽  
Saeed Omidi ◽  
Mikhail Pachkov ◽  
Phil Arnold ◽  
Nicholas Kelley ◽  
...  
Keyword(s):  
De Novo ◽  
Computational Method ◽  
Sequencing Data ◽  
Read Mapping ◽  
Binding Motifs ◽  
Encode Project ◽  
Regulatory Motifs ◽  
Genome Wide ◽  
Integrated Processing ◽  
Comprehensive Modeling

Although it has become routine for experimental groups to apply ChIP-seq technology to quantitatively characterize the genome-wide binding of transcription factors (TFs), computational analysis procedures remain far from standardized, making it difficult to meaningfully compare ChIP-seq results across experiments. In addition, while genome-wide binding patterns must ultimately be determined by local constellations of binding sites in the DNA, current analysis is typically limited to a standard search for enriched motifs in ChIP-seq peaks.Here we present Crunch, a completely automated computational method that performs all ChIP-seq analysis from quality control through read mapping and peak detecting, and integrates comprehensive modeling of the ChIP signal in terms of known and novel binding motifs, quantifying the contribution of each motif, and annotating which combinations of motifs explain each binding peak.Applying Crunch to 128 ChIP-seq datasets from the ENCODE project we find that TFs naturally separate into ‘solitary TFs’, for which a single motif explains the ChIP-peaks, and ‘co-binding TFs’ for which multiple motifs co-occur within peaks. Moreover, for most datasets the motifs that Crunch identifiedde novooutperform known motifs and both the set of co-binding motifs and the top motif of solitary TFs are consistent across experiments and cell lines. Crunch is implemented as a web server (crunch.unibas.ch), enabling standardized analysis of any collection of ChIP-seq datasets by simply uploading raw sequencing data. Results are provided both in a graphical interface and as downloadable files.

scholarly journals CloneSig: Joint inference of intra-tumor heterogeneity and signature deconvolution in tumor bulk sequencing data

2019 ◽  
Author(s):  
Judith Abécassis ◽  
Fabien Reyal ◽  
Jean-Philippe Vert
Keyword(s):  
Cancer Progression ◽  
Tumor Heterogeneity ◽  
Cancer Genomics ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Joint Inference ◽  
Nucleotide Context ◽  
Cancer Genome Atlas ◽  
Mutational Processes

The possibility to sequence DNA in cancer samples has triggered much effort recently to identify the forces at the genomic level that shape tumorigenesis and cancer progression. It has resulted in novel understanding or clarification of two important aspects of cancer genomics: (i) intra-tumor heterogeneity (ITH), as captured by the variability in observed prevalences of somatic mutations within a tumor, and (ii) mutational processes, as revealed by the distribution of the types of somatic mutation and their immediate nucleotide context. These two aspects are not independent from each other, as different mutational processes can be involved in different subclones, but current computational approaches to study them largely ignore this dependency. In particular, sequential methods that first estimate subclones and then analyze the mutational processes active in each clone can easily miss changes in mutational processes if the clonal decomposition step fails, and conversely information regarding mutational signatures is overlooked during the subclonal reconstruction. To address current limitations, we present CloneSig, a new computational method to jointly infer ITH and mutational processes in a tumor from bulk-sequencing data, including whole-exome sequencing (WES) data, by leveraging their dependency. We show through an extensive benchmark on simulated samples that CloneSig is always as good as or better than state-of-the-art methods for ITH inference and detection of mutational processes. We then apply CloneSig to a large cohort of 8,954 tumors with WES data from the cancer genome atlas (TCGA), where we obtain results coherent with previous studies on whole-genome sequencing (WGS) data, as well as new promising findings. This validates the applicability of CloneSig to WES data, paving the way to its use in a clinical setting where WES is increasingly deployed nowadays.

scholarly journals Upgrading the Repertoire of miRNAs in Gastric Adenocarcinoma to Provide a New Resource for Biomarker Discovery

2019 ◽  
Vol 20 (22) ◽  
pp. 5697 ◽  
Author(s):  
Michelle E. Pewarchuk ◽  
Mateus C. Barros-Filho ◽  
Brenda C. Minatel ◽  
David E. Cohn ◽  
Florian Guisier ◽  
...  
Keyword(s):  
Gastric Adenocarcinoma ◽  
Biomarker Discovery ◽  
The Cancer Genome Atlas ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Specific Expression ◽  
Novel Mirna ◽  
Cancer Genome Atlas ◽  
Context Specific ◽  
Independent Cohort

Recent studies have uncovered microRNAs (miRNAs) that have been overlooked in early genomic explorations, which show remarkable tissue- and context-specific expression. Here, we aim to identify and characterize previously unannotated miRNAs expressed in gastric adenocarcinoma (GA). Raw small RNA-sequencing data were analyzed using the miRMaster platform to predict and quantify previously unannotated miRNAs. A discovery cohort of 475 gastric samples (434 GA and 41 adjacent nonmalignant samples), collected by The Cancer Genome Atlas (TCGA), were evaluated. Candidate miRNAs were similarly assessed in an independent cohort of 25 gastric samples. We discovered 170 previously unannotated miRNA candidates expressed in gastric tissues. The expression of these novel miRNAs was highly specific to the gastric samples, 143 of which were significantly deregulated between tumor and nonmalignant contexts (p-adjusted < 0.05; fold change > 1.5). Multivariate survival analyses showed that the combined expression of one previously annotated miRNA and two novel miRNA candidates was significantly predictive of patient outcome. Further, the expression of these three miRNAs was able to stratify patients into three distinct prognostic groups (p = 0.00003). These novel miRNAs were also present in the independent cohort (43 sequences detected in both cohorts). Our findings uncover novel miRNA transcripts in gastric tissues that may have implications in the biology and management of gastric adenocarcinoma.

scholarly journals Promoter Methylation of PRKCB, ADAMTS12, and NAALAD2 Is Specific to Prostate Cancer and Predicts Biochemical Disease Recurrence

2021 ◽  
Vol 22 (11) ◽  
pp. 6091
Author(s):  
Kristina Daniunaite ◽  
Arnas Bakavicius ◽  
Kristina Zukauskaite ◽  
Ieva Rauluseviciute ◽  
Juozas Rimantas Lazutka ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Practice ◽  
Promoter Methylation ◽  
Disease Recurrence ◽  
The Cancer Genome Atlas ◽  
Cancer Dataset ◽  
Protein Coding ◽  
Diagnosis And Prognosis ◽  
Genome Wide ◽  
Cancer Genome Atlas

The molecular diversity of prostate cancer (PCa) has been demonstrated by recent genome-wide studies, proposing a significant number of different molecular markers. However, only a few of them have been transferred into clinical practice so far. The present study aimed to identify and validate novel DNA methylation biomarkers for PCa diagnosis and prognosis. Microarray-based methylome data of well-characterized cancerous and noncancerous prostate tissue (NPT) pairs was used for the initial screening. Ten protein-coding genes were selected for validation in a set of 151 PCa, 51 NPT, as well as 17 benign prostatic hyperplasia samples. The Prostate Cancer Dataset (PRAD) of The Cancer Genome Atlas (TCGA) was utilized for independent validation of our findings. Methylation frequencies of ADAMTS12, CCDC181, FILIP1L, NAALAD2, PRKCB, and ZMIZ1 were up to 91% in our study. PCa specific methylation of ADAMTS12, CCDC181, NAALAD2, and PRKCB was demonstrated by qualitative and quantitative means (all p < 0.05). In agreement with PRAD, promoter methylation of these four genes was associated with the transcript down-regulation in the Lithuanian cohort (all p < 0.05). Methylation of ADAMTS12, NAALAD2, and PRKCB was independently predictive for biochemical disease recurrence, while NAALAD2 and PRKCB increased the prognostic power of multivariate models (all p < 0.01). The present study identified methylation of ADAMTS12, NAALAD2, and PRKCB as novel diagnostic and prognostic PCa biomarkers that might guide treatment decisions in clinical practice.

scholarly journals Heme Biosynthesis mRNA Expression Signature: Towards a Novel Prognostic Biomarker in Patients with Diffusely Infiltrating Gliomas

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 662
Author(s):  
Mario Mischkulnig ◽  
Barbara Kiesel ◽  
Daniela Lötsch ◽  
Thomas Roetzer ◽  
Martin Borkovec ◽  
...  
Keyword(s):  
Overall Survival ◽  
Mrna Expression ◽  
Postoperative Management ◽  
Heme Biosynthesis ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Who Grade ◽  
Expression Signature ◽  
Cancer Genome Atlas ◽  
The Impact

Diffusely infiltrating gliomas are characterized by a variable clinical course, and thus novel prognostic biomarkers are needed. The heme biosynthesis cycle constitutes a fundamental metabolic pathway and might play a crucial role in glioma biology. The aim of this study was thus to investigate the role of the heme biosynthesis mRNA expression signature on prognosis in a large glioma patient cohort. Glioma patients with available sequencing data on heme biosynthesis expression were retrieved from The Cancer Genome Atlas (TCGA). In each patient, the heme biosynthesis mRNA expression signature was calculated and categorized into low, medium, and high expression subgroups. Differences in progression-free and overall survival between these subgroups were investigated including a multivariate analysis correcting for WHO grade, tumor subtype, and patient age and sex. In a total of 693 patients, progression-free and overall survival showed a strictly monotonical decrease with increasing mRNA expression signature subgroups. In detail, median overall survival was 134.2 months in the low, 79.9 months in the intermediate, and 16.5 months in the high mRNA expression signature subgroups, respectively. The impact of mRNA expression signature on progression-free and overall survival was independent of the other analyzed prognostic factors. Our data indicate that the heme biosynthesis mRNA expression signature might serve as an additional novel prognostic marker in patients with diffusely infiltrating gliomas to optimize postoperative management.

scholarly journals Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mariana G. Ferrarini ◽  
Avantika Lal ◽  
Rita Rebollo ◽  
Andreas J. Gruber ◽  
Andrea Guarracino ◽  
...  
Keyword(s):  
Transposable Element ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Initiation Factor ◽  
Sequence Variant ◽  
The Novel ◽  
Sequencing Data ◽  
Genome Wide ◽  
Respiratory Cells ◽  
Nuclear Ribonucleoprotein

AbstractThe novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after emerging in Wuhan, China. Here we analyzed public host and viral RNA sequencing data to better understand how SARS-CoV-2 interacts with human respiratory cells. We identified genes, isoforms and transposable element families that are specifically altered in SARS-CoV-2-infected respiratory cells. Well-known immunoregulatory genes including CSF2, IL32, IL-6 and SERPINA3 were differentially expressed, while immunoregulatory transposable element families were upregulated. We predicted conserved interactions between the SARS-CoV-2 genome and human RNA-binding proteins such as the heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) and eukaryotic initiation factor 4 (eIF4b). We also identified a viral sequence variant with a statistically significant skew associated with age of infection, that may contribute to intracellular host–pathogen interactions. These findings can help identify host mechanisms that can be targeted by prophylactics and/or therapeutics to reduce the severity of COVID-19.

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