Cervical cancer is responsible for 10–15% of cancer-related deaths in women worldwide1,2. The etiological role of infection with high-risk human papilloma viruses (HPV) in cervical carcinomas is well established3. Previous studies have implicated somatic mutations in PIK3CA, PTEN, TP53, STK11 and KRAS4–7 as well as several copy number alterations in the pathogenesis of cervical carcinomas8,9. Here, we report whole exome sequencing analysis of 115 cervical carcinoma-normal paired samples, transcriptome sequencing of 79 cases and whole genome sequencing of 14 tumor-normal pairs. Novel somatic mutations in 79 primary squamous cell carcinomas include recurrent E322K substitutions in the MAPK1 gene (8%), inactivating mutations in the HLA-B gene (9%), and mutations in EP300 (16%), FBXW7 (15%), NFE2L2 (4%) TP53 (5%) and ERBB2 (6%). We also observed somatic ELF3 (13%) and CBFB (8%) mutations in 24 adenocarcinomas. Squamous cell carcinomas had higher frequencies of somatic mutations in the Tp*C dinucleotide context than adenocarcinomas. Gene expression levels at HPV integration sites were significantly higher in tumors with HPV integration compared with expression of the same genes in tumors without viral integration at the same site. These data demonstrate several recurrent genomic alterations in cervical carcinomas that suggest novel strategies to combat this disease.

To gain insight into the genomic basis of diffuse large B-cell lymphoma (DLBCL), we performed massively parallel whole-exome sequencing of 55 primary tumor samples from patients with DLBCL and matched normal tissue. We identified recurrent mutations in genes that are well known to be functionally relevant in DLBCL, including MYD88, CARD11, EZH2, and CREBBP. We also identified somatic mutations in genes for which a functional role in DLBCL has not been previously suspected. These genes include MEF2B, MLL2, BTG1, GNA13, ACTB, P2RY8, PCLO, and TNFRSF14. Further, we show that BCL2 mutations commonly occur in patients with BCL2/IgH rearrangements as a result of somatic hypermutation normally occurring at the IgH locus. The BCL2 point mutations are primarily synonymous, and likely caused by activation-induced cytidine deaminase-mediated somatic hypermutation, as shown by comprehensive analysis of enrichment of mutations in WRCY target motifs. Those nonsynonymous mutations that are observed tend to be found outside of the functionally important BH domains of the protein, suggesting that strong negative selection against BCL2 loss-of-function mutations is at play. Last, by using an algorithm designed to identify likely functionally relevant but infrequent mutations, we identify KRAS, BRAF, and NOTCH1 as likely drivers of DLBCL pathogenesis in some patients. Our data provide an unbiased view of the landscape of mutations in DLBCL, and this in turn may point toward new therapeutic strategies for the disease.next-generation sequencing | human genetics | activation-induced deaminase D iffuse large B-cell lymphoma (DLBCL) is an aggressive nonHodgkin lymphoma that affects 30,000 new patients in the United States every year (1, 2). The standard of care for the treatment of most cases of DLBCL is the R-CHOP regimen (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) consisting of multiagent chemotherapy plus a therapeutic antibody directed against CD20, a marker of B lymphocytes. The 3-year event-free survival rate is approximately 60%, with the majority of the remaining 40% dying of their disease (3). To date, treatment strategies to improve outcome have largely included increased doses of standard agents in the context of autologous stem cell transplantation (4). Therefore, there is a great medical need to define the genetic abnormalities that are associated with DLBCL to define novel targets for therapy.Germinal centers (GCs) in lymphoid tissues are sites of clonal expansion and editing of the Ig receptor in B lymphocytes, and this GC reaction is a physiological component of the humoral immune response. Somatic hypermutation (SHM) is part of the GC reaction, and its dysregulation contributes to the accumulation of somatic mutations in oncogenes and tumor-suppressor genes in B lymphocytes.Traditionally, DLBCL has been classified by the morphology and immunophenotype of the malignant B-cells but more recently, molecular classifications have been reported. Specifically, gene expression-based classification o...

Formation of the three primary germ layers during gastrulation is an essential step in the establishment of the vertebrate body plan and is associated with major transcriptional changes [1][2][3][4][5] . Global epigenetic reprogramming accompanies these changes [6][7][8] , but the role of the epigenome in regulating early cell fate choice remains unresolved, and the coordination between different molecular layers is unclear. Here we describe the first single cell triple-omics map of chromatin accessibility, DNA methylation and RNA expression during the onset of gastrulation in mouse embryos. The initial exit from pluripotency coincides with the establishment of a global repressive epigenetic landscape, followed by the emergence of lineage-specific epigenetic patterns during gastrulation. Notably, cells committed to mesoderm and endoderm undergo widespread coordinated epigenetic rearrangements at enhancer marks, driven by TET-mediated demethylation, and a concomitant increase of accessibility. In striking contrast, the methylation and accessibility landscape of ectodermal cells is already established in the early epiblast. Hence, regulatory elements associated with each germ layer are either epigenetically primed or remodelled prior to cell fate decisions, providing the molecular logic for a hierarchical emergence of the primary germ layers.Recent technological advances have enabled the profiling of multiple molecular layers at single cell resolution 9-13 , providing novel opportunities to study the relationship between the transcriptome and epigenome during cell fate decisions. We applied scNMT-seq (singlecell Nucleosome, Methylome and Transcriptome sequencing 12 ) to profile 1,105 single cells isolated from mouse embryos at four developmental stages (Embryonic Day (E) 4.5, E5.5, E6.5 and E7.5) which comprise the exit from pluripotency and primary germ layer specification (Figure 1a-d, Extended Data Fig. 1). Cells were assigned to a specific lineage by mapping their RNA expression profiles to a comprehensive single-cell atlas 4 from the same stages, when available, or using marker genes (Extended Data Fig. 2). By performing Argelaguet et al.

We performed next-generation sequencing of Ewing sarcoma, a pediatric cancer involving bone, characterized by expression of EWS-ETS fusions. We found remarkably few mutations. However, we discovered that loss of STAG2 expression occurs in 15% of tumors and is associated with metastatic disease, suggesting a potential genetic vulnerability in Ewing sarcoma.

Highlights d Multiple transcriptional trajectories underlie somite emergence d Outlining the in vivo molecular journey toward the anterior Tindependent somites d T does not negatively regulate Sox2 to control neural output at E8.

Background Single-cell technologies are transforming biomedical research, including the recent demonstration that unspliced pre-mRNA present in single-cell RNA-Seq permits prediction of future expression states. Here we apply this RNA velocity concept to an extended timecourse dataset covering mouse gastrulation and early organogenesis. Results Intriguingly, RNA velocity correctly identifies epiblast cells as the starting point, but several trajectory predictions at later stages are inconsistent with both real-time ordering and existing knowledge. The most striking discrepancy concerns red blood cell maturation, with velocity-inferred trajectories opposing the true differentiation path. Investigating the underlying causes reveals a group of genes with a coordinated step-change in transcription, thus violating the assumptions behind current velocity analysis suites, which do not accommodate time-dependent changes in expression dynamics. Using scRNA-Seq analysis of chimeric mouse embryos lacking the major erythroid regulator Gata1, we show that genes with the step-changes in expression dynamics during erythroid differentiation fail to be upregulated in the mutant cells, thus underscoring the coordination of modulating transcription rate along a differentiation trajectory. In addition to the expected block in erythroid maturation, the Gata1-chimera dataset reveals induction of PU.1 and expansion of megakaryocyte progenitors. Finally, we show that erythropoiesis in human fetal liver is similarly characterized by a coordinated step-change in gene expression. Conclusions By identifying a limitation of the current velocity framework coupled with in vivo analysis of mutant cells, we reveal a coordinated step-change in gene expression kinetics during erythropoiesis, with likely implications for many other differentiation processes.

BackgroundObesity is a well-recognized risk factor for insulin resistance and type 2 diabetes (T2D), although the precise mechanisms underlying the relationship remain unknown. In this study we identified alterations of DNA methylation influencing T2D pathogenesis, in subcutaneous and visceral adipose tissues, liver, and blood from individuals with obesity.MethodsThe study included individuals with obesity, with and without T2D. From these patients, we obtained samples of liver tissue (n = 16), visceral and subcutaneous adipose tissues (n = 30), and peripheral blood (n = 38). We analyzed DNA methylation using Illumina Infinium Human Methylation arrays, and gene expression profiles using HumanHT-12 Expression BeadChip Arrays.ResultsAnalysis of DNA methylation profiles revealed several loci with differential methylation between individuals with and without T2D, in all tissues. Aberrant DNA methylation was mainly found in the liver and visceral adipose tissue. Gene ontology analysis of genes with altered DNA methylation revealed enriched terms related to glucose metabolism, lipid metabolism, cell cycle regulation, and response to wounding. An inverse correlation between altered methylation and gene expression in the four tissues was found in a subset of genes, which were related to insulin resistance, adipogenesis, fat storage, and inflammation.ConclusionsOur present findings provide additional evidence that aberrant DNA methylation may be a relevant mechanism involved in T2D pathogenesis among individuals with obesity.Electronic supplementary materialThe online version of this article (10.1186/s12881-018-0542-8) contains supplementary material, which is available to authorized users.

BackgroundThyroid cancer (TC) is the most common malignant cancer of the Endocrine System. Histologically, there are three main subtypes of TC: follicular, papillary and anaplastic. Diagnosing a thyroid tumor subtype with a high level of accuracy and confidence is still a difficult task because genetic, molecular and cellular mechanisms underlying the transition from differentiated to undifferentiated thyroid tumors are not well understood.A genome-wide analysis of these three subtypes of thyroid carcinoma was carried out in order to identify significant differences in expression levels as well as enriched pathways for non-shared molecular and cellular features between subtypes.ResultsInhibition of matrix metalloproteinases pathway is a major event involved in thyroid cancer progression and its dysregulation may result crucial for invasiveness, migration and metastasis. This pathway is drastically altered in ATC while in FTC and PTC, the most important pathways are related to DNA-repair activation or cell to cell signaling events.ConclusionA progression from FTC to PTC and then to ATC was detected and validated on two independent datasets. Moreover, PTX3, COLEC12 and PDGFRA genes were found as possible candidates for biomarkers of ATC while GPR110 could be tested to distinguish PTC over other tumor subtypes. The genome-wide analysis emphasizes the preponderance of pathway-dysregulation mechanisms over simple gene-malfunction as the main mechanism involved in the development of a cancer phenotype.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1372-0) contains supplementary material, which is available to authorized users.