5-Fluorouracil (5-FU) is a chemotherapeutic drug commonly used for the treatment of solid cancers. It is proposed that 5-FU interferes with nucleotide synthesis and incorporates into DNA, which may ...have a mutational impact on both surviving tumor and healthy cells. Here, we treat intestinal organoids with 5-FU and find a highly characteristic mutational pattern that is dominated by T>G substitutions in a CTT context. Tumor whole genome sequencing data confirms that this signature is also identified in vivo in colorectal and breast cancer patients who have received 5-FU treatment. Taken together, our results demonstrate that 5-FU is mutagenic and may drive tumor evolution and increase the risk of secondary malignancies. Furthermore, the identified signature shows a strong resemblance to COSMIC signature 17, the hallmark signature of treatment-naive esophageal and gastric tumors, which indicates that distinct endogenous and exogenous triggers can converge onto highly similar mutational signatures.
Genetic investigation of tumor heterogeneity and clonal evolution in solid cancers could be assisted by the analysis of liquid biopsies. However, tumors of various entities might release different ...quantities of circulating tumor cells (CTCs) and cell-free DNA (cfDNA) into the bloodstream, potentially limiting the diagnostic potential of liquid biopsy in distinct tumor histologies. Patients with advanced colorectal cancer (CRC), head and neck squamous cell carcinoma (HNSCC), and melanoma (MEL) were enrolled in the study, representing tumors with different metastatic patterns. Mutation profiles of cfDNA, CTCs, and tumor tissue were assessed by panel sequencing, targeting 327 cancer-related genes. In total, 30 tissue, 18 cfDNA, and 7 CTC samples from 18 patients were sequenced. Best concordance between the mutation profile of tissue and cfDNA was achieved in CRC and MEL, possibly due to the remarkable heterogeneity of HNSCC (63%, 55% and 11%, respectively). Concordance especially depended on the amount of cfDNA used for library preparation. While 21 of 27 (78%) tissue mutations were retrieved in high-input cfDNA samples (30-100 ng, N = 8), only 4 of 65 (6%) could be detected in low-input samples (<30 ng, N = 10). CTCs were detected in 13 of 18 patients (72%). However, downstream analysis was limited by poor DNA quality, allowing targeted sequencing of only seven CTC samples isolated from four patients. Only one CTC sample reflected the mutation profile of the respective tumor. Private mutations, which were detected in CTCs but not in tissue, suggested the presence of rare subclones. Our pilot study demonstrated superiority of cfDNA- compared to CTC-based mutation profiling. It was further shown that CTCs may serve as additional means to detect rare subclones possibly involved in treatment resistance. Both findings require validation in a larger patient cohort.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The functional complexity of the human transcriptome is not yet fully elucidated. We report a high-throughput sequence of the human transcriptome from a human embryonic kidney and a B cell line. We ...used shotgun sequencing of transcripts to generate randomly distributed reads. Of these, 50% mapped to unique genomic locations, of which 80% corresponded to known exons. We found that 66% of the polyadenylated transcriptome mapped to known genes and 34% to nonannotated genomic regions. On the basis of known transcripts, RNA-Seq can detect 25% more genes than can microarrays. A global survey of messenger RNA splicing events identified 94,241 splice junctions (4096 of which were previously unidentified) and showed that exon skipping is the most prevalent form of alternative splicing.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Gene expression analysis by RNA sequencing is now widely used in a number of applications surveying the whole transcriptomes of cells and tissues. The recent introduction of ribosomal RNA depletion ...protocols, such as RiboZero, has extended the view of the polyadenylated transcriptome to the poly(A)- fraction of the RNA. However, substantial amounts of intronic transcriptional activity has been reported in RiboZero protocols, raising issues regarding their potential nuclear origin and the impact on the actual sequence depth in exonic regions.
Using HEK293 human cells as source material, we assessed here the impact of the two commonly used RNA extraction methods and of the library construction protocols (rRNA depletion versus mRNA) on 1) the relative abundance of intronic reads and 2) on the estimation of gene expression values. We benchmarked the rRNA depletion-based sequencing with a specific analysis of the cytoplasmic and nuclear transcriptome fractions, suggesting that the large majority of the intronic reads correspond to unprocessed nuclear transcripts rather than to independent transcriptional units. We show that Qiagen or TRIzol extraction methods retain differentially nuclear RNA species, and that consequently, rRNA depletion-based RNA sequencing protocols are particularly sensitive to the extraction methods.
We could show that the combination of Trizol-based RNA extraction with rRNA depletion sequencing protocols led to the largest fraction of intronic reads, after the sequencing of the nuclear transcriptome. We discuss here the impact of the various strategies on gene expression and alternative splicing estimation measures. Further, we propose guidelines and a double selection strategy for minimizing the expression biases, without loss of information.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Current therapies for medulloblastoma, a highly malignant childhood brain tumour, impose debilitating effects on the developing child, and highlight the need for molecularly targeted treatments with ...reduced toxicity. Previous studies have been unable to identify the full spectrum of driver genes and molecular processes that operate in medulloblastoma subgroups. Here we analyse the somatic landscape across 491 sequenced medulloblastoma samples and the molecular heterogeneity among 1,256 epigenetically analysed cases, and identify subgroup-specific driver alterations that include previously undiscovered actionable targets. Driver mutations were confidently assigned to most patients belonging to Group 3 and Group 4 medulloblastoma subgroups, greatly enhancing previous knowledge. New molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions that target KBTBD4 and 'enhancer hijacking' events that activate PRDM6. Thus, the application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.
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IJS, KISLJ, NUK, SBMB, UL, UM, UPUK
Matrin 3 (MATR3) is a highly conserved, inner nuclear matrix protein with two zinc finger domains and two RNA recognition motifs (RRM), whose function is largely unknown. Recently we found MATR3 to ...be phosphorylated by the protein kinase ATM, which activates the cellular response to double strand breaks in the DNA. Here, we show that MATR3 interacts in an RNA-dependent manner with several proteins with established roles in RNA processing, and maintains its interaction with RNA via its RRM2 domain. Deep sequencing of the bound RNA (RIP-seq) identified several small noncoding RNA species. Using microarray analysis to explore MATR3's role in transcription, we identified 77 transcripts whose amounts depended on the presence of MATR3. We validated this finding with nine transcripts which were also bound to the MATR3 complex. Finally, we demonstrated the importance of MATR3 for maintaining the stability of several of these mRNA species and conclude that it has a role in mRNA stabilization. The data suggest that the cellular level of MATR3, known to be highly regulated, modulates the stability of a group of gene transcripts.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link ...in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.
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•High-resolution maps of promoter interactions in 17 human primary blood cell types•Interaction patterns are cell type specific and segregate with the hematopoietic tree•Promoter-interacting regions enriched for regulatory chromatin features and eQTLs•Promoter interactions link non-coding GWAS variants with putative target genes
This study deploys a promoter capture Hi-C approach in 17 primary blood cell types to match collaborating regulatory regions and identify genes regulated by noncoding disease-associated variants. Explore this and other papers at the Cell Press IHEC webportal at http://www.cell.com/consortium/IHEC.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Characterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, ...epigenetic, and transcriptomic profiling in three major human immune cell types (CD14+ monocytes, CD16+ neutrophils, and naive CD4+ T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of cis-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.
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•Genome, transcriptome, and epigenome reference panel in three human immune cell types•Identified 4,418 genes associated with epigenetic changes independent of genetics•Described genome-epigenome coordination defining cell-type-specific regulatory events•Functionally mapped disease mechanisms at 345 unique autoimmune disease loci
As part of the IHEC consortium, this study integrates genetic, epigenetic, and transcriptomic profiling in three immune cell types from nearly 200 people to characterize the distinct and cooperative contributions of diverse genomic inputs to transcriptional variation. Explore the Cell Press IHEC web portal at http://www.cell.com/consortium/IHEC.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Ependymal tumors across age groups are currently classified and graded solely by histopathology. It is, however, commonly accepted that this classification scheme has limited clinical utility based ...on its lack of reproducibility in predicting patients’ outcome. We aimed at establishing a uniform molecular classification using DNA methylation profiling. Nine molecular subgroups were identified in a large cohort of 500 tumors, 3 in each anatomical compartment of the CNS, spine, posterior fossa, supratentorial. Two supratentorial subgroups are characterized by prototypic fusion genes involving RELA and YAP1, respectively. Regarding clinical associations, the molecular classification proposed herein outperforms the current histopathological classification and thus might serve as a basis for the next World Health Organization classification of CNS tumors.
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•DNA methylation profiling of ependymomas identifies nine molecular subgroups•YAP1 and RELA fusions characterize two distinct groups of supratentorial ependymoma•Patients with PFA or supratentorial RELA-positive ependymoma show dismal prognosis•Risk stratification by molecular subgrouping is superior to histological grading
Pajtler et al. classify 500 ependymal tumors using DNA methylation profiling into nine molecular subgroups. This molecular classification outperforms the current histopathological grading in the risk stratification of patients.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The regulation of gene expression in response to environmental signals and metabolic imbalances is a key step in maintaining cellular homeostasis. BTB and CNC homology 1 (BACH1) is a heme-binding ...transcription factor repressing the transcription from a subset of MAF recognition elements at low intracellular heme levels. Upon heme binding, BACH1 is released from the MAF recognition elements, resulting in increased expression of antioxidant response genes. To systematically address the gene regulatory networks involving BACH1, we combined chromatin immunoprecipitation sequencing analysis of BACH1 target genes in HEK 293 cells with knockdown of BACH1 using three independent types of small interfering RNAs followed by transcriptome profiling using microarrays. The 59 BACH1 target genes identified by chromatin immunoprecipitation sequencing were found highly enriched in genes showing expression changes after BACH1 knockdown, demonstrating the impact of BACH1 repression on transcription. In addition to known and new BACH1 targets involved in heme degradation (HMOX1, FTL, FTH1, ME1, and SLC48A1) and redox regulation (GCLC, GCLM, and SLC7A11), we also discovered BACH1 target genes affecting cell cycle and apoptosis pathways (ITPR2, CALM1, SQSTM1, TFE3, EWSR1, CDK6, BCL2L11, and MAFG) as well as subcellular transport processes (CLSTN1, PSAP, MAPT, and vault RNA). The newly identified impact of BACH1 on genes involved in neurodegenerative processes and proliferation provides an interesting basis for future dissection of BACH1-mediated gene repression in neurodegeneration and virus-induced cancerogenesis.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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