Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

Epigenomic Profiling of Human CD4+ T Cells Supports a Linear Differentiation Model and Highlights Molecular Regulators of Memory Development.

The impact of epigenetics on the differentiation of memory T (Tmem) cells is poorly defined. We generated deep epigenomes comprising genome-wide profiles of DNA methylation, histone modifications, DNA accessibility, and coding and non-coding RNA expression in naive, central-, effector-, and terminally differentiated CD45RA+ CD4+ Tmem cells from blood and CD69+ Tmem cells from bone marrow (BM-Tmem). We observed a progressive and proliferation-associated global loss of DNA methylation in heterochromatic parts of the genome during Tmem cell differentiation. Furthermore, distinct gradually changing signatures in the epigenome and the transcriptome supported a linear model of memory development in circulating T cells, while tissue-resident BM-Tmem branched off with a unique epigenetic profile. Integrative analyses identified candidate master regulators of Tmem cell differentiation, including the transcription factor FOXP1. This study highlights the importance of epigenomic changes for Tmem cell biology and demonstrates the value of epigenetic data for the identification of lineage regulators.

GenomeTornadoPlot: a novel R package for CNV visualization and focality analysis.

MOTIVATION: Analysis of focal copy number variations (CNVs) is highly relevant for cancer research, as they pinpoint driver genes. More specifically, due to selective pressure oncogenes and tumor suppressor genes are more often affected by these events than neighboring passengers. In cases where multiple candidates co-reside in a genomic locus, careful comparison is required to either identify multigenic minimally deleted regions of synergistic co-mutations, or the true single driver gene. The study of focal CNVs in large cancer genome cohorts requires specialized visualization and statistical analysis. RESULTS: We developed the GenomeTornadoPlot R-package which generates gene-centric visualizations of CNV types, locations and lengths from cohortwise NGS data. Furthermore, the software enables the pairwise comparison of proximate genes to identify co-mutation patterns or driver-passenger hierarchies. The visual examination provided by GenomeTornadoPlot is further supported by adaptable local and global focality scoring. Integrated into the GenomeTornadoPlot R-Package is the comprehensive PCAWG database of CNVs, comprising 2976 cancer genome entities from 46 cohorts of the Pan-cancer Analysis of Whole Genomes project. The GenomeTornadoPlot R-package can be used to perform exploratory or hypothesis-driven analyses on the basis of the PCAWG data or in combination with data provided by the user. AVAILABILITY AND IMPLEMENTATION: GenomeTornadoPlot is written in R script and released via github: . The package is under the license of GPL-3.0.

TelomereHunter - in silico estimation of telomere content and composition from cancer genomes.

BACKGROUND: Establishment of telomere maintenance mechanisms is a universal step in tumor development to achieve replicative immortality. These processes leave molecular footprints in cancer genomes in the form of altered telomere content and aberrations in telomere composition. To retrieve these telomere characteristics from high-throughput sequencing data the available computational approaches need to be extended and optimized to fully exploit the information provided by large scale cancer genome data sets. RESULTS: We here present TelomereHunter, a software for the detailed characterization of telomere maintenance mechanism footprints in the genome. The tool is implemented for the analysis of large cancer genome cohorts and provides a variety of diagnostic diagrams as well as machine-readable output for subsequent analysis. A novel key feature is the extraction of singleton telomere variant repeats, which improves the identification and subclassification of the alternative lengthening of telomeres phenotype. We find that whole genome sequencing-derived telomere content estimates strongly correlate with telomere qPCR measurements (r = 0.94). For the first time, we determine the correlation of in silico telomere content quantification from whole genome sequencing and whole genome bisulfite sequencing data derived from the same tumor sample (r = 0.78). An analogous comparison of whole exome sequencing data and whole genome sequencing data measured slightly lower correlation (r = 0.79). However, this is considerably improved by normalization with matched controls (r = 0.91). CONCLUSIONS: TelomereHunter provides new functionality for the analysis of the footprints of telomere maintenance mechanisms in cancer genomes. Besides whole genome sequencing, whole exome sequencing and whole genome bisulfite sequencing are suited for in silico telomere content quantification, especially if matched control samples are available. The software runs under a GPL license and is available at https://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html .

MicroRNA transcription start site prediction with multi-objective feature selection.

MicroRNAs (miRNAs) are non-coding, short (21-23nt) regulators of protein-coding genes that are generally transcribed first into primary miRNA (pri-miR), followed by the generation of precursor miRNA (pre-miR). This finally leads to the production of the mature miRNA. A large amount of information is available on the pre- and mature miRNAs. However, very little is known about the pri-miRs, due to a lack of knowledge about their transcription start sites (TSSs). Based on the genomic loci, miRNAs can be categorized into two types --intragenic (intra-miR) and intergenic (inter-miR). While it is already an established fact that intra-miRs are commonly transcribed in conjunction with their host genes, the transcription machinery of inter-miRs is poorly understood. Although it is assumed that miRNA promoters are similar in structure to gene promoters, since both are transcribed by RNA polymerase II (Pol II), computational validations exhibit poor performance of gene promoter prediction methods on miRNAs. In this paper, we concentrate on the problem of TSS prediction for miRNAs. The present study begins with the identification of positive and negative promoter samples from recently published data stemming from RNA-sequencing studies. From these samples of experimentally validated miRNA TSSs, a number of standard sequence features are extracted. Furthermore, to account for potential footprints related to promoter regulation by CpG dinucleotide targeted DNA methylation, a number of novel features are defined. We develop a support vector machine (SVM) with RBF kernel for the prediction of miRNA TSSs trained on human miRNA promoters. A novel feature reduction technique based on archived multi-objective simulated annealing (AMOSA) identifies the final set of features. The resulting model trained on miRNA promoters shows improved performance over the one trained on protein-coding gene promoters in terms of classification accuracy, sensitivity and specificity. Results are also reported for a completely independent biologically validated test set. In a part of the investigation, the proposed approach is used to predict protein-coding gene TSSs. It shows a significantly improved performance when compared to previously published gene TSS prediction methods.

BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing.

Bisulfite sequencing is a widely used method for measuring DNA methylation in eukaryotic genomes. The assay provides single-base pair resolution and, given sufficient sequencing depth, its quantitative accuracy is excellent. High-throughput sequencing of bisulfite-converted DNA can be applied either genome wide or targeted to a defined set of genomic loci (e.g. using locus-specific PCR primers or DNA capture probes). Here, we describe BiQ Analyzer HT (http://biq-analyzer-ht.bioinf.mpi-inf.mpg.de/), a user-friendly software tool that supports locus-specific analysis and visualization of high-throughput bisulfite sequencing data. The software facilitates the shift from time-consuming clonal bisulfite sequencing to the more quantitative and cost-efficient use of high-throughput sequencing for studying locus-specific DNA methylation patterns. In addition, it is useful for locus-specific visualization of genome-wide bisulfite sequencing data.

Reconstructing the ancestral germ line methylation state of young repeats.

One of the key objectives of comparative genomics is the characterization of the forces that shape genomes over the course of evolution. In the last decades, evidence has been accumulated that for vertebrate genomes also epigenetic modifications have to be considered in this context. Especially, the elevated mutation frequency of 5-methylcytosine (5mC) is assumed to facilitate the depletion of CpG dinucleotides in species that exhibit global DNA methylation. For instance, the underrepresentation of CpG dinucleotides in many mammalian genomes is attributed to this effect, which is only neutralized in so-called CpG islands (CGIs) that are preferentially unmethylated and thus partially protected from rapid CpG decay. For primate-specific CpG-rich transposable elements from the ALU family, it is unclear whether their elevated CpG frequency is caused by their small age or by the absence of DNA methylation. In consequence, these elements are often misclassified in CGI annotations. We present a method for the estimation of germ line methylation from pairwise ancestral-descendant alignments. The approach is validated in a simulation study and tested on DNA repeats from the AluSx family. We conclude that a predicted unmethylated state in the germ line is highly correlated with epigenetic activity of the respective genomic region. Thus, CpG-rich repeats can be facilitated as in silico probes for the epigenetic potential of their genomic neighborhood.

The antileukemic activity of decitabine upon PML/RARA-negative AML blasts is supported by all-trans retinoic acid: in vitro and in vivo evidence for cooperation.

The prognosis of AML patients with adverse genetics, such as a complex, monosomal karyotype and TP53 lesions, is still dismal even with standard chemotherapy. DNA-hypomethylating agent monotherapy induces an encouraging response rate in these patients. When combined with decitabine (DAC), all-trans retinoic acid (ATRA) resulted in an improved response rate and longer overall survival in a randomized phase II trial (DECIDER; NCT00867672). The molecular mechanisms governing this in vivo synergism are unclear. We now demonstrate cooperative antileukemic effects of DAC and ATRA on AML cell lines U937 and MOLM-13. By RNA-sequencing, derepression of >1200 commonly regulated transcripts following the dual treatment was observed. Overall chromatin accessibility (interrogated by ATAC-seq) and, in particular, at motifs of retinoic acid response elements were affected by both single-agent DAC and ATRA, and enhanced by the dual treatment. Cooperativity regarding transcriptional induction and chromatin remodeling was demonstrated by interrogating the HIC1, CYP26A1, GBP4, and LYZ genes, in vivo gene derepression by expression studies on peripheral blood blasts from AML patients receiving DAC + ATRA. The two drugs also cooperated in derepression of transposable elements, more effectively in U937 (mutated TP53) than MOLM-13 (intact TP53), resulting in a "viral mimicry" response. In conclusion, we demonstrate that in vitro and in vivo, the antileukemic and gene-derepressive epigenetic activity of DAC is enhanced by ATRA.

5'isomiR-183-5p|+2 elicits tumor suppressor activity in a negative feedback loop with E2F1.

BACKGROUND: MicroRNAs (miRNAs) and isomiRs play important roles in tumorigenesis as essential regulators of gene expression. 5'isomiRs exhibit a shifted seed sequence compared to the canonical miRNA, resulting in different target spectra and thereby extending the phenotypic impact of the respective common pre-miRNA. However, for most miRNAs, expression and function of 5'isomiRs have not been studied in detail yet. Therefore, this study aims to investigate the functions of miRNAs and their 5'isomiRs. METHODS: The expression of 5'isomiRs was assessed in The Cancer Genome Atlas (TCGA) breast cancer patient dataset. Phenotypic effects of miR-183 overexpression in triple-negative breast cancer (TNBC) cell lines were investigated in vitro and in vivo by quantifying migration, proliferation, tumor growth and metastasis. Direct targeting of E2F1 by miR-183-5p|+2 was validated with a 3'UTR luciferase assay and linked to the phenotypes of isomiR overexpression. RESULTS: TCGA breast cancer patient data indicated that three variants of miR-183-5p are highly expressed and upregulated, namely miR-183-5p|0, miR-183-5p|+1 and miR-183-5p|+2. However, TNBC cell lines displayed reduced proliferation and invasion upon overexpression of pre-miR-183. While invasion was reduced individually by all three isomiRs, proliferation and cell cycle progression were specifically inhibited by overexpression of miR-183-5p|+2. Proteomic analysis revealed reduced expression of E2F target genes upon overexpression of this isomiR, which could be attributed to direct targeting of E2F1, specifically by miR-183-5p|+2. Knockdown of E2F1 partially phenocopied the effect of miR-183-5p|+2 overexpression on cell proliferation and cell cycle. Gene set enrichment analysis of TCGA and METABRIC patient data indicated that the activity of E2F strongly correlated with the expression of miR-183-5p, suggesting transcriptional regulation of the miRNA by a factor of the E2F family. Indeed, in vitro, expression of miR-183-5p was regulated by E2F1. Hence, miR-183-5p|+2 directly targeting E2F1 appears to be part of a negative feedback loop potentially fine-tuning its activity. CONCLUSIONS: This study demonstrates that 5'isomiRs originating from the same arm of the same pre-miRNA (i.e. pre-miR-183-5p) may exhibit different functions and thereby collectively contribute to the same phenotype. Here, one of three isomiRs was shown to counteract expression of the pre-miRNA by negatively regulating a transcriptional activator (i.e. E2F1). We speculate that this might be part of a regulatory mechanism to prevent uncontrolled cell proliferation, which is disabled during cancer progression.

On the impact of batch effect correction in TCGA isomiR expression data.

MicroRNAs (miRNAs) are small non-coding RNAs with diverse functions in post-transcriptional regulation of gene expression. Sequence and length variants of miRNAs are called isomiRs and can exert different functions compared to their canonical counterparts. The Cancer Genome Atlas (TCGA) provides isomiR-level expression data for patients of various cancer entities collected in a multi-center approach over several years. However, the impact of batch effects within individual cohorts has not been systematically investigated and corrected for before. Therefore, the aim of this study was to identify relevant cohort-specific batch variables and generate batch-corrected isomiR expression data for 16 TCGA cohorts. The main batch variables included sequencing platform, plate, sample purity and sequencing depth. Platform bias was related to certain length and sequence features of individual recurrently affected isomiRs. Furthermore, significant downregulation of reported tumor suppressive isomiRs in lung tumor tissue compared to normal samples was only observed after batch correction, highlighting the importance of working with corrected data. Batch-corrected datasets for all cohorts including quality control are provided as supplement. In summary, this study reveals that batch effects present in the TCGA dataset might mask biologically relevant effects and provides a valuable resource for research on isomiRs in cancer (accessible through GEO: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE164767).

The landscape and driver potential of site-specific hotspots across cancer genomes.

Large sets of whole cancer genomes make it possible to study mutation hotspots genome-wide. Here we detect, categorize, and characterize site-specific hotspots using 2279 whole cancer genomes from the Pan-Cancer Analysis of Whole Genomes project and provide a resource of annotated hotspots genome-wide. We investigate the excess of hotspots in both protein-coding and gene regulatory regions and develop measures of positive selection and functional impact for individual hotspots. Using cancer allele fractions, expression aberrations, mutational signatures, and a variety of genomic features, such as potential gain or loss of transcription factor binding sites, we annotate and prioritize all highly mutated hotspots. Genome-wide we find more high-frequency SNV and indel hotspots than expected given mutational background models. Protein-coding regions are generally enriched for SNV hotspots compared to other regions. Gene regulatory hotspots show enrichment of potential same-patient second-hit missense mutations, consistent with enrichment of hotspot driver mutations compared to singletons. For protein-coding regions, splice-sites, promoters, and enhancers, we see an excess of hotspots associated with cancer genes. Interestingly, missense hotspot mutations in tumor suppressors are associated with elevated expression, suggesting localized amino-acid changes with functional impact. For individual non-coding hotspots, only a small number show clear signs of positive selection, including known sites in the TERT promoter and the 5' UTR of TP53. Most of the new candidates have few mutations and limited driver evidence. However, a hotspot in an enhancer of the oncogene POU2AF1, which may create a transcription factor binding site, presents multiple lines of driver-consistent evidence.

Alternative lengthening of telomeres in childhood neuroblastoma from genome to proteome.

Telomere maintenance by telomerase activation or alternative lengthening of telomeres (ALT) is a major determinant of poor outcome in neuroblastoma. Here, we screen for ALT in primary and relapsed neuroblastomas (n = 760) and characterize its features using multi-omics profiling. ALT-positive tumors are molecularly distinct from other neuroblastoma subtypes and enriched in a population-based clinical sequencing study cohort for relapsed cases. They display reduced ATRX/DAXX complex abundance, due to either ATRX mutations (55%) or low protein expression. The heterochromatic histone mark H3K9me3 recognized by ATRX is enriched at the telomeres of ALT-positive tumors. Notably, we find a high frequency of telomeric repeat loci with a neuroblastoma ALT-specific hotspot on chr1q42.2 and loss of the adjacent chromosomal segment forming a neo-telomere. ALT-positive neuroblastomas proliferate slowly, which is reflected by a protracted clinical course of disease. Nevertheless, children with an ALT-positive neuroblastoma have dismal outcome.

Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis.

Long non-coding RNAs (lncRNAs) are a growing focus of cancer genomics studies, creating the need for a resource of lncRNAs with validated cancer roles. Furthermore, it remains debated whether mutated lncRNAs can drive tumorigenesis, and whether such functions could be conserved during evolution. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we introduce the Cancer LncRNA Census (CLC), a compilation of 122 GENCODE lncRNAs with causal roles in cancer phenotypes. In contrast to existing databases, CLC requires strong functional or genetic evidence. CLC genes are enriched amongst driver genes predicted from somatic mutations, and display characteristic genomic features. Strikingly, CLC genes are enriched for driver mutations from unbiased, genome-wide transposon-mutagenesis screens in mice. We identified 10 tumour-causing mutations in orthologues of 8 lncRNAs, including LINC-PINT and NEAT1, but not MALAT1. Thus CLC represents a dataset of high-confidence cancer lncRNAs. Mutagenesis maps are a novel means for identifying deeply-conserved roles of lncRNAs in tumorigenesis.

Genomic footprints of activated telomere maintenance mechanisms in cancer.

Cancers require telomere maintenance mechanisms for unlimited replicative potential. They achieve this through TERT activation or alternative telomere lengthening associated with ATRX or DAXX loss. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we dissect whole-genome sequencing data of over 2500 matched tumor-control samples from 36 different tumor types aggregated within the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium to characterize the genomic footprints of these mechanisms. While the telomere content of tumors with ATRX or DAXX mutations (ATRX/DAXXtrunc) is increased, tumors with TERT modifications show a moderate decrease of telomere content. One quarter of all tumor samples contain somatic integrations of telomeric sequences into non-telomeric DNA. This fraction is increased to 80% prevalence in ATRX/DAXXtrunc tumors, which carry an aberrant telomere variant repeat (TVR) distribution as another genomic marker. The latter feature includes enrichment or depletion of the previously undescribed singleton TVRs TTCGGG and TTTGGG, respectively. Our systematic analysis provides new insight into the recurrent genomic alterations associated with telomere maintenance mechanisms in cancer.

The landscape of chromothripsis across adult cancer types.

Chromothripsis is a recently identified mutational phenomenon, by which a presumably single catastrophic event generates extensive genomic rearrangements of one or a few chromosome(s). Considered as an early event in tumour development, this form of genome instability plays a prominent role in tumour onset. Chromothripsis prevalence might have been underestimated when using low-resolution methods, and pan-cancer studies based on sequencing are rare. Here we analyse chromothripsis in 28 tumour types covering all major adult cancers (634 tumours, 316 whole-genome and 318 whole-exome sequences). We show that chromothripsis affects a substantial proportion of human cancers, with a prevalence of 49% across all cases. Chromothripsis generates entity-specific genomic alterations driving tumour development, including clinically relevant druggable fusions. Chromothripsis is linked with specific telomere patterns and univocal mutational signatures in distinct tumour entities. Longitudinal analysis of chromothriptic patterns in 24 matched tumour pairs reveals insights in the clonal evolution of tumours with chromothripsis.

Response to olaparib in a PALB2 germline mutated prostate cancer and genetic events associated with resistance.

Prostate cancers harboring DNA repair gene alterations are particularly sensitive to PARP inhibitor treatment. We report a case of an advanced prostate cancer patient profiled within the NCT-MASTER (Molecularly Aided Stratification for Tumor Eradication Research) precision oncology program using next-generation sequencing. Comprehensive genomic and transcriptomic analysis identified a pathogenic germline PALB2 variant as well as a mutational signature associated with disturbed homologous recombination together with structural genomic rearrangements. A molecular tumor board identified a potential benefit of targeted therapy and recommended PARP inhibition and platinum-based chemotherapy. Single-agent treatment with the PARP inhibitor olaparib as well as subsequent combination with platinum-based chemotherapy resulted in disease stabilization and substantial improvement of clinical symptoms. Upon progression, we performed whole-exome and RNA sequencing of a liver metastasis, which demonstrated up-regulation of several genes characteristic for the neuroendocrine prostate cancer phenotype as well as a novel translocation resulting in an in-frame, loss-of-function fusion of RB1. We suggest that multidimensional genomic characterization of prostate cancer patients undergoing PARP inhibitor therapy will be necessary to capture and understand predictive biomarkers of PARP inhibitor sensitivity and resistance.

Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma.

Burkitt lymphoma (BL) is the most common B-cell lymphoma in children. Within the International Cancer Genome Consortium (ICGC), we performed whole genome and transcriptome sequencing of 39 sporadic BL. Here, we unravel interaction of structural, mutational, and transcriptional changes, which contribute to MYC oncogene dysregulation together with the pathognomonic IG-MYC translocation. Moreover, by mapping IGH translocation breakpoints, we provide evidence that the precursor of at least a subset of BL is a B-cell poised to express IGHA. We describe the landscape of mutations, structural variants, and mutational processes, and identified a series of driver genes in the pathogenesis of BL, which can be targeted by various mechanisms, including IG-non MYC translocations, germline and somatic mutations, fusion transcripts, and alternative splicing.

Methylation profiling identifies two subclasses of squamous cell carcinoma related to distinct cells of origin.

Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer and usually progresses from a UV-induced precancerous lesion termed actinic keratosis (AK). Despite various efforts to characterize these lesions molecularly, the etiology of AK and its progression to cSCC remain partially understood. Here, we use Infinium MethylationEPIC BeadChips to interrogate the DNA methylation status in healthy, AK and cSCC epidermis samples. Importantly, we show that AK methylation patterns already display classical features of cancer methylomes and are highly similar to cSCC profiles. Further analysis identifies typical features of stem cell methylomes, such as reduced DNA methylation age, non-CpG methylation, and stem cell-related keratin and enhancer methylation patterns. Interestingly, this signature is detected only in half of the samples, while the other half shows patterns more closely related to healthy epidermis. These findings suggest the existence of two subclasses of AK and cSCC emerging from distinct keratinocyte differentiation stages.

Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories.

Identifying the earliest somatic changes in prostate cancer can give important insights into tumor evolution and aids in stratifying high- from low-risk disease. We integrated whole genome, transcriptome and methylome analysis of early-onset prostate cancers (diagnosis ≤55 years). Characterization across 292 prostate cancer genomes revealed age-related genomic alterations and a clock-like enzymatic-driven mutational process contributing to the earliest mutations in prostate cancer patients. Our integrative analysis identified four molecular subgroups, including a particularly aggressive subgroup with recurrent duplications associated with increased expression of ESRP1, which we validate in 12,000 tissue microarray tumors. Finally, we combined the patterns of molecular co-occurrence and risk-based subgroup information to deconvolve the molecular and clinical trajectories of prostate cancer from single patient samples.