Nbs1 ChIP-Seq Identifies Off-Target DNA Double-Strand Breaks Induced by AID in Activated Splenic B Cells

Activation-induced cytidine deaminase (AID) is required for initiation of Ig class switch recombination (CSR) and somatic hypermutation (SHM) of antibody genes during immune responses. AID has also been shown to induce chromosomal translocations, mutations, and DNA double-strand breaks (DSBs) involving non-Ig genes in activated B cells. To determine what makes a DNA site a target for AID-induced DSBs, we identify off-target DSBs induced by AID by performing chromatin immunoprecipitation (ChIP) for Nbs1, a protein that binds DSBs, followed by deep sequencing (ChIP-Seq). We detect and characterize hundreds of off-target AID-dependent DSBs. Two types of tandem repeats are highly enriched within the Nbs1-binding sites: long CA repeats, which can form Z-DNA, and tandem pentamers containing the AID target hotspot WGCW. These tandem repeats are not nearly as enriched at AID-independent DSBs, which we also identified. Msh2, a component of the mismatch repair pathway and important for genome stability, increases off-target DSBs, similar to its effect on Ig switch region DSBs, which are required intermediates during CSR. Most of the off-target DSBs are two-ended, consistent with generation during G1 phase, similar to DSBs in Ig switch regions. However, a minority are one-ended, presumably due to conversion of single-strand breaks to DSBs during replication. One-ended DSBs are repaired by processes involving homologous recombination, including break-induced replication repair, which can lead to genome instability. Off-target DSBs, especially those present during S phase, can lead to chromosomal translocations, deletions and gene amplifications, resulting in the high frequency of B cell lymphomas derived from cells that express or have expressed AID

Inducible DNA breaks in Ig S regions are dependent on AID and UNG

Class switch recombination (CSR) occurs by an intrachromosomal deletion whereby the IgM constant region gene (Cμ) is replaced by a downstream constant region gene. This unique recombination event involves formation of double-strand breaks (DSBs) in immunoglobulin switch (S) regions, and requires activation-induced cytidine deaminase (AID), which converts cytosines to uracils. Repair of the uracils is proposed to lead to DNA breaks required for recombination. Uracil DNA glycosylase (UNG) is required for most CSR activity although its role is disputed. Here we use ligation-mediated PCR to detect DSBs in S regions in splenic B cells undergoing CSR. We find that the kinetics of DSB induction corresponds with AID expression, and that DSBs are AID- and UNG-dependent and occur preferentially at G:C basepairs in WRC/GYW AID hotspots. Our results indicate that AID attacks cytosines on both DNA strands, and staggered breaks are processed to blunt DSBs at the initiating ss break sites. We propose a model to explain the types of end-processing events observed

APE1- and APE2-dependent DNA breaks in immunoglobulin class switch recombination

Antibody class switch recombination (CSR) occurs by an intrachromosomal deletion requiring generation of double-stranded breaks (DSBs) in switch-region DNA. The initial steps in DSB formation have been elucidated, involving cytosine deamination by activation-induced cytidine deaminase and generation of abasic sites by uracil DNA glycosylase. However, it is not known how abasic sites are converted into single-stranded breaks and, subsequently, DSBs. Apurinic/apyrimidinic endonuclease (APE) efficiently nicks DNA at abasic sites, but it is unknown whether APE participates in CSR. We address the roles of the two major mammalian APEs, APE1 and APE2, in CSR. APE1 deficiency causes embryonic lethality in mice; we therefore examined CSR and DSBs in mice deficient in APE2 and haploinsufficient for APE1. We show that both APE1 and APE2 function in CSR, resulting in the DSBs necessary for CSR and thereby describing a novel in vivo function for APE2

The DNA Glycosylases Ogg1 and Nth1 Do Not Contribute to Ig Class Switching in Activated Mouse Splenic B Cells

During activation of B cells to undergo class switching, B cell metabolism is increased, and levels of reactive oxygen species (ROS) are increased. ROS can oxidize DNA bases resulting in substrates for the DNA glycosylases Ogg1 and Nth1. Ogg1 and Nth1 excise oxidized bases, and nick the resulting abasic sites, forming single-strand DNA breaks (SSBs) as intermediates during the repair process. In this study, we asked whether splenic B cells from mice deficient in these two enzymes would show altered class switching and decreased DNA breaks in comparison with wild-type mice. As the c-myc gene frequently recombines with the IgH S region in B cells induced to undergo class switching, we also analyzed the effect of deletion of these two glycosylases on DSBs in the c-myc gene. We did not detect a reduction in S region or c-myc DSBs or in class switching in splenic B cells from Ogg1- or Nth1-deficient mice or from mice deficient in both enzymes

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019 : a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019