Myeloid-specific blockade of notch signaling alleviates dopaminergic neurodegeneration in Parkinson’s disease by dominantly regulating resident microglia activation through NF-κB signaling

Yolk sac–derived microglia and peripheral monocyte–derived macrophages play a key role during Parkinson’s disease (PD) progression. However, the regulatory mechanism of microglia/macrophage activation and function in PD pathogenesis remains unclear. Recombination signal–binding protein Jκ (RBP-J)–mediated Notch signaling regulates macrophage development and activation. In this study, with an 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) hydrochloride-induced acute murine PD model, we found that Notch signaling was activated in amoeboid microglia accompanied by a decrease in tyrosine hydroxylase (TH)–positive neurons. Furthermore, using myeloid-specific RBP-J knockout (RBP-JcKO) mice combined with a PD model, our results showed that myeloid-specific disruption of RBP-J alleviated dopaminergic neurodegeneration and improved locomotor activity. Fluorescence-activated cell sorting (FACS) analysis showed that the number of infiltrated inflammatory macrophages and activated major histocompatibility complex (MHC) II+ microglia decreased in RBP-JcKO mice compared with control mice. Moreover, to block monocyte recruitment by using chemokine (C-C motif) receptor 2 (CCR2) knockout mice, the effect of RBP-J deficiency on dopaminergic neurodegeneration was not affected, indicating that Notch signaling might regulate neuroinflammation independent of CCR2+ monocyte infiltration. Notably, when microglia were depleted with the PLX5622 formulated diet, we found that myeloid-specific RBP-J knockout resulted in more TH+ neurons and fewer activated microglia. Ex vitro experiments demonstrated that RBP-J deficiency in microglia might reduce inflammatory factor secretion, TH+ neuron apoptosis, and p65 nuclear translocation. Collectively, our study first revealed that RBP-J–mediated Notch signaling might participate in PD progression by mainly regulating microglia activation through nuclear factor kappa-B (NF-κB) signaling

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Type III Secretion System Translocon Component EseB Forms Filaments on and Mediates Autoaggregation of and Biofilm Formation by Edwardsiella tarda

The type III secretion system (T3SS) of Edwardsiella tarda plays an important role in infection by translocating effector proteins into host cells. EseB, a component required for effector translocation, is reported to mediate autoaggregation of E. tarda. In this study, we demonstrate that EseB forms filamentous appendages on the surface of E. tarda and is required for biofilm formation by E. tarda in Dulbecco's modified Eagle's medium (DMEM). Biofilm formation by E. tarda in DMEM does not require FlhB, an essential component for assembling flagella. Dynamic analysis of EseB filament formation, autoaggregation, and biofilm formation shows that the formation of EseB filaments occurs prior to autoaggregation and biofilm formation. The addition of an EseB antibody to E. tarda cultures before bacterial autoaggregation prevents autoaggregation and biofilm formation in a dose-dependent manner, whereas the addition of the EseB antibody to E. tarda cultures in which biofilm is already formed does not destroy the biofilm. Therefore, EseB filament-mediated bacterial cell-cell interaction is a prerequisite for autoaggregation and biofilm formation

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that -80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAFPeer reviewe

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Sex differences in oncogenic mutational processes

Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research.Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research.Peer reviewe

Sex differences in oncogenic mutational processes

Funder: Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada (NSERC Canadian Network for Research and Innovation in Machining Technology); doi: https://doi.org/10.13039/501100002790Funder: Genome Canada (Génome Canada); doi: https://doi.org/10.13039/100008762Funder: Canada Foundation for Innovation (Fondation canadienne pour l'innovation); doi: https://doi.org/10.13039/501100000196Funder: Terry Fox Research Institute (Institut de Recherche Terry Fox); doi: https://doi.org/10.13039/501100004376Abstract: Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research

Author Correction: Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

: Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20128-w

Integrative pathway enrichment analysis of multivariate omics data

Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations