The brain’s response to radiation exposure is an important concern for patients undergoing cancer therapy and astronauts on long missions in deep space. We assessed whether this response is specific and prolonged and is linked to epigenetic mechanisms. We focused on the response of the hippocampus at early (2-weeks) and late (20-week) time points following whole body proton irradiation. We examined two forms of DNA methylation, cytosine methylation (5mC) and hydroxymethylation (5hmC). Impairments in object recognition, spatial memory retention, and network stability following proton irradiation were observed at the two-week time point and correlated with altered gene expression and 5hmC profiles that mapped to specific gene ontology pathways. Significant overlap was observed between DNA methylation changes at the 2 and 20-week time points demonstrating specificity and retention of changes in response to radiation. Moreover, a novel class of DNA methylation change was observed following an environmental challenge (i.e. space irradiation), characterized by both increased and decreased 5hmC levels along the entire gene body. These changes were mapped to genes encoding neuronal functions including postsynaptic gene ontology categories. Thus, the brain’s response to proton irradiation is both specific and prolonged and involves novel remodeling of non-random regions of the epigenome. The former involves protons and fully ionized atomic nuclei while the latter includes predominantly low to medium energy protons2. Proton radiation exposures may pose a significant health hazard to space flight crews during and following the mission3. Proton irradiation is also clinically relevant, as it is increasingly used in cancer therapy6. The hazards associated with the space environment will likely impact many organ systems. In the central nervous system (CNS), radiation exposure significantly affects the hippocampus24, a structure critical for memory function. For example, object recognition memory25, which uses a 24-hour interval between learning and memory assessment to test hippocampal function26, is impaired twelve weeks following irradiation of 2-month-old mice with protons 27. Young-adult mice exposed to protons  failed to show habituation to an open field when tested two weeks after exposure28. Similarly, spatial learning and memory in the water maze were not affected by proton irradiation of young-adult (250–275 g) rats 29. Whether habituation to an open field, object recognition, and spatial learning and memory in the water maze are sensitive to effects of proton irradiation in adult mice irradiated at 6 months of age, a biological age relevant to the typical ages of astronauts during space missions, is not known.A unique feature of the space radiation environment is the presence of galactic cosmic rays (GCR) and solar particle events (SPE)Arc) in the hippocampus have been reported30. The study of Arc expression provides important insight into the post-transcriptional infrastructure of gene expression involved in synaptic plasticity and memory31 , play a key role in regulating expression of genes required for spatial learning and memory38. A second form of DNA methylation, hydroxymethylcytosine (5hmC), is derived from 5mC by the action of three TET enzymes (TET 1–3)39. In brain, levels of TET2 are higher than those of TET1 or TET3 and therefore TET2 is believed most important for brain function41. The levels and localizations of 5mC and 5hmC levels are high and exceptionally dynamic in the brain44. Their high and dynamic levels in neurons during development and aging46 suggest strongly that they play critical roles.Hippocampal DNA methylation is affected 22 weeks following proton irradiationIn the current study, we assessed the effects of whole body proton irradiation at early (2-week) and late (20-week) time points on hippocampus-dependent cognitive performance and whether these effects are associated with changes in hippocampal DNA methylation (both 5mC and 5hmC).n = 84 mice in total) were obtained from Jackson Laboratories, Bar Harbor Maine. The biological age of the mice was selected to be relevant to the biological age of astronauts during space missions. The mice were shipped from Jackson Laboratories to Brookhaven National Laboratory (BNL), Upton, New York, and allowed to accommodate to the housing facility there for one week. Subsequently, the mice were irradiated with 1 Gy of 150 MeV protons or sham-irradiated (n = 42 mice/radiation dose). For irradiation, mice were individually loaded into 8 × 3 × 3 cm plastic square enclosures with air holes and placed in a foam fixture in the beam line of the NASA Space Radiation Laboratory (NSRL). They were exposed to a rectangular beam of approximately 20 × 20 cm. The focused beam of high-energy was generated by the Booster accelerator at BNL and transferred to the experimental beam line at the NSRL facility. Dose calibration was performed so that the desired dose could be delivered. Sham-irradiated mice were placed into the plastic enclosures for the same amount of time as the irradiated mice. Mice were randomly assigned to the experimental groups. The week after the irradiation or sham-irradiation, the mice were shipped to Oregon Health & Science University (OHSU) and were assigned to one of two time points . Cognitive testing started two or twenty weeks following irradiation. Following cognitive testing, the mice were killed by cervical dislocation followed by decapitation. The hippocampus of one hemibrain was dissected for DNA methylation and RNAseq analyses. The other hemibrain was processed for Arc mRNA and TET2 immunohistochemical analyses. All protocols were reviewed and approved by the Institutional Animal Care and Use Committees (IACUC) of OHSU and BNL and were in compliance with all Federal regulations.Six-month-old C57BL/6 J male mice  for 3 times for 10 min each over three subsequent days. On day 4, the mice were placed in the open field containing two identical objects and they were allowed to freely explore for 15 minutes. On day 5, the mice were placed again in the open field, but one familiar object was replaced with a novel object. The mice were allowed to explore for 15 minutes. Movement and time spent exploring each object was recorded using Ethovision XT video tracking system  and hand scored by a researcher blinded to the treatment of the mice. The percent time exploring the novel object, out of the total time exploring the novel and familiar objects on day 5, was used to assess novel object recognition. For each group, the preference for the novel versus the familiar object was assessed. The open field arena and objects were cleaned with 5% acetic acid between mice and trials.The novel object recognition test was performed as described47. A circular pool (diameter 140 cm) was filled with water made opaque with nontoxic chalk (24 °C) and mice were trained to locate a submerged platform. To determine if irradiation affected the ability to swim or learn the water maze task, mice were first trained to locate a clearly marked platform . The mice were subsequently trained to locate the platform when it was hidden beneath the surface of opaque water (Days 3–5). Training during the hidden platform sessions (acquisition) required the mice to learn the location of the hidden platform based on extra-maze cues. For both visible and hidden sessions, there were two daily sessions, morning and afternoon, which were 2-h apart. Each session consisted of two trials . A trial ended when the mice located the platform. Mice that failed to locate the platform within 60 s were led to the platform by placing a finger in front of their swim path. The mice were taken out of the pool after they were physically on the platform for a minimum of 3 s. During visible platform training, the platform was moved to a different quadrant of the pool for each session. For the hidden platform training, the platform location was kept constant. The mice were placed into the water facing the edge of the pool in one of nine randomized locations. The start location was changed for each trial. The swimming patterns of the mice were recorded with Noldus Ethovision video tracking software  set at six samples/s. The time to locate the platform (latency) and cumulative distance to the target were used as measures of performance for the visible and hidden sessions. Because swim speeds can influence the time it takes to reach the platform, they were also analyzed.Spatial learning and memory was assessed in the water maze as describedTo measure spatial memory retention, probe trials (platform removed) were conducted 24 h after the last hidden trial of each mouse on the second day of hidden platform training and 72 h following the last hidden trial of each mouse on the third day of hidden platform training and the time spent in the target quadrant as compared to any other quadrant during the probe trials was analyzed.31. The method called catFISH  relies on the precise temporal kinetics of the IEG Arc, which has been used to provide important insight into the post-transcriptional infrastructure of gene expression involved in synaptic plasticity and memory33,  can be clearly distinguished, providing means to identify which neurons were active during distinct behavioral experiences31.Three days after the last water maze test day, exploration of identical or different environments was used to study the stability of hippocampal networks33. Environment A is a square open field . After exploration, mice were returned to their cage for 25 min, returned to the same environment for an additional 5 min (AA Paradigm). Another 8 mice of each experimental radiation condition were allowed to explore environment A for 5 minutes, and 25 minutes later they were placed in a different environment (B), a circular arena 45 cm in diameter, and allowed to explore for 5 minutes (AB Paradigm). Following the last environmental exposure, the mice were killed by cervical dislocation and the brains quickly removed, as described above.Eight mice from each experimental radiation condition were placed individually into a novel environment (A) and allowed to explore for five minutes, as describedArc can be distinguished using intronic and full-length probe respectively labeled with digoxigenin or fluorescein. Arc staining was classified as: a) None (no Arc staining); b) cytoplasmic Arc staining only; c) nuclear Arc staining only; or d) both Arc-foci/Arc-cyto (containing both foci and cytoplasmic staining). We can determine if the neurons responding (i.e. Arc+) to an initial experience (exploration of environment A) are the same neurons that respond to a second and identical experience as expected based on sham-irradiated animals (AA Paradigm), and if the hippocampal networks activated during exploration of the first environment are statistically independent from those activated by the exploration of a different environment (AB Paradigm). For the CA1 and CA3 regions of the hippocampus, the percentage of neurons showing both foci and cytoplasmic staining was analyzed. As the pattern of percentages of Arc-positive neurons in both environments might reflect differences in the total number of Arc-positive neurons  this number was also determined. For the dentate gyrus, the percent of neurons expressing Arc only in the cytoplasm or expressing both Arc-foci/Arc-cyto (containing both foci and cytoplasmic staining) was analyzed. This measure was analyzed as it reflects the total response to the environment(s).Using catFISH, Arc mRNA appear as discrete nuclear foci (recent transcription ~5–10 min), and/or as diffuse mRNA in the cytoplasm (earlier transcription). Nuclear and cytoplasmic 48 and stored at −80 °C. The hemibrains were shipped to the University of California, San Francisco, and cut at 20 µm using a cryostat. Slides were sent to OHSU for analysis of Tet2 immunoreacttivity using a specific primary antibody from Santa Cruz Biotechnology . Briefly, sections (n = 3 sections per hemibrain and approximately 200 µm apart) were rinsed in phosphate buffered saline (PBS), and incubated in 4% normal goat serum (NGS) in PBS with 0.4% triton X-100 (PBS-TX). Next, sections were incubated overnight with primary antibodies against Tet2 (1:250) in 4%NGS in PBS-TX. The next day, tissue sections were washed in PBS, incubated for 2.5 hours in donkey anti-rabbit Alexa 488 (1:200) in 4% NGS in PBS-TX and again rinsed in PBS. Analysis of Tet2 immunoreactivity was performed using an Olympus IX81 confocal microscope equipped with Slidebook software. Images of hippocampal regions  and the cortex were captured within 3 sections (Bregma −1.58 to −2.46) using a 20x objective . Tet2 immunoreactivity was quantified within fixed area frames; CA1 , CA3 , dentate gyrus , and cortex . Background threshold levels were set and applied to all images for comparison. Pixel intensities above this threshold were used for quantification measures (area occupied by pixels and intensities of pixels). The total intensity was also quantified as a measure of overall pixel intensity within a specific brain region.Following cervical dislocation and decapitation, hemibrains were rapidly removed and frozen using isopentane and dry ice, as described36. These antibodies were used to precipitate genomic regions that are enriched for either 5mC or 5hmC. Following immunoprecipitation, high throughput genomic sequencing was used to identify the enriched genomic regions. For DIP-Seq library preparation, RNAse-treated DNA was isolated using the Qiagen Allprep DNA/RNA protocol. The DNA was sonicated using a Cole Parmer CPX-132 sonicator  and polished using the DNA terminator end repair kit (Lucigen). DNA fragments were A-tailed using Klenow exo- (Epicenter) and ligated to un-methylated HT TrueSeq indexed adapters and purified. The resulting purified DNA was denatured at 95 C, resuspended in 100 ul of DIP IP buffer, and immunoprecipitated with 1 μg of the highly specific 5-methylcytosine antibody (Eurogentec) or 2 ul of 5-hydroxymethylcytosine (Active Motif) antibody and Dynal anti-mouse IgG beads. Beads were rinsed 7 times with IP buffer, eluted with 1% SDS at room temperature and the eluted DNA purified and subjected to limited amplification (~18 cycles). Libraries were sequenced on the HiSeq. 2000 platform at the OHSU Massively Parallel Sequencing Shared Resource or the Oregon State University Center for Genome ReseArch. DIP-Seq regions methylated above “background” were identified using a sliding window method and enriched regions selected via a Montecarlo-permutation test49.DNA was isolated from the hippocampus. For the 2-week time point, antibodies against 5mC and 5hmC were used to immunoprecipitate sonicated DNA preparations for methyl-DNA immunoprecipitation  and hydroxymethyl-DNA immunoprecipitation , respectively, from eight pools of tissues . For the 20-week time point, the isolation of the DNA and DNA methylation was analyzed using 2 × 2 pools of hippocampal tissues, as reported50. Read statistics and quality control data for sequencing data can be found in Supplemental Table 51. Significance was assessed using the DESeq2 package52. The Storey Q-test was used to adjust for multiple comparisons53. Differential exon usage analyses utilized Tophat gapped alignment54 and the DEXSeq pipeline as described in the supplemental materials55.To facilitate direct comparison of DIP-Seq data with gene expression data for the 2-week time point, RNA-Seq was used to profile transcription from the same animals used for the DIP-Seq experiments. For the 2-week time point, RNA was isolated using the NEBnext poly A selection kit (New England Biolabs). Illumina high-throughput sequencing technology was used to profile RNA levels in an unbiased manner. Differential methylation may occur at novel regions and the unbiased nature of RNA-Seq analyses enables analysis of associated un-annotated transcription. For Illumina RNA-Seq library preparation, we used the NEBnext Ultra kit according to the manufacturers specifications (New England Biolabs). Libraries were sequenced on the HiSeq. 2000 platform at the OHSU Massively Parallel Sequencing Shared Resource. Illumina data were mapped to the UC Santa Cruz assembly using BowtieArc data are shown as mean ± SEM. The statistical analyses of the data were performed using SPSS™  and GraphPad Prism™  software packages. To assess effects of radiation on spatial memory retention in the individual probe trials, ANOVAs were used, followed up by Dunnett’s posthoc tests when appropriate. To analyze locomotor activity over three days, ability to locate a visible platform over two days, and ability to locate a hidden platform over three days, repeated measures ANOVA was used. To compare exploration of the objects and the percentage of Arc-positive cells and total number of Arc cells following exposure to the two different environmental conditions, t-tests were used. All figures were generated using GraphPad Prism software. We considered p < 0.05 as statistically significant.All behavioral, cognitive, and 50. Sequences that map to a single location were selected and domains enriched for 5mC or 5hmC were selected using a parameter-optimized Monte-Carlo-based segmentation algorithm49. A 1000 bp sliding-window was used based on iterative analyses that maximized the number of enriched regions. A comparison of different high-throughput sequencing based methods to study DNA methylation concluded that MeDIP-Seq covers ~67% of genomic CpGs56.Single read sequence data was mapped to the mouse reference genome (UCSC mm9) using the Bowtie algorithm using standard flags and allowing 2 mismatches57. Statistical and visualization studies involved the R programming language and Bioconductor packages51. Gene ontology analyses utilized the Bioconductor Goseq package, which adjusts for RNA-Seq length bias artifacts58. KEGG analyses were conducted using the DAVID-EASE site59. For gene ontology analyses the top 2000 DMRs  or DHRs  (FDR-adjusted p < 0.01) within a 50 kb window centered on the transcriptional start site were non-redundantly annotated. Unless otherwise stated, overlap between DMRs and RNA-Seq data was analyzed using a similar windowing approach.For statistical comparisons of biological samples, regions of methylation enrichment were merged and differences in methylation interrogated with FDR-adjusted negative binomial statisticsp < 0.01 as statistically significant.DIP sequence-tag heatmaps were generated in R by plotting median-normalized DIP-Seq tag density in gene bodies and indicated flanking regions with color-maps scaled to the 80% quantile. Statistical analyses of pathway data were conducted via FDR-adjusted Fisher exact test. Statistical analyses of DHR density in genomic regions were conducted using a Monte-Carlo-based permutation statistic (“coin” R package). We considered (FDR-adjusted) F = 140.6, p < 0.0001; Fig. F = 4.833, p = 0.01), but when activity levels were analyzed for each of the three days separately there were no significant effects of irradiation on activity levels. However, detrimental effects of proton irradiation were seen when object recognition was assessed. While sham-irradiated mice showed object recognition and spent significantly more time exploring the novel than the familiar object , irradiated mice did not   Fig. .Figure 1F = 14.14, p < 0.0001) but there was no effect of radiation (not shown). However, effects of proton irradiation were seen when spatial memory retention was assessed in the first probe trial (no platform) 24 hours after the second day of hidden platform training. Sham-irradiated mice showed spatial memory retention and spent more time in the target quadrant that had contained the platform during the hidden platform sessions, but proton-irradiated mice did not , but this was not seen in irradiated mice   Fig. . In addi60. These libraries were sequenced to a depth of ~40 million tags of which 55–69% mapped to a genomic locus. Genomic regions enriched for 5mC or 5hmC were segmented using a Monte Carlo-based algorithm and the union of these regions was tested for significant difference using a negative binomial approach. This approach identified thousands of differentially methylated and hydroxymethylated regions , of which the majority were within 25 kb of a transcription start site  and/or cytosine hydroxymethylation (5hmC)-DIP-Seq libraries from the hippocampi of mice exposed and not exposed to 1 Gy proton radiation using highly specific antibodiesite Fig. . Consist5mC Fig. . Both 5m5mC Fig. . As expee.g., all down-regulated). Instead, we observed genes within specific gene ontology pathways with increased or decrease 5hmC levels, or both (see below). These results suggest that dynamic changes in 5hmC after proton exposure are more strongly associated with gene pathways and that changes within these pathways are complex.Gene ontology analysis of significantly-regulated DMR and DHRs identified gene ontology categories for the 5hmC data Fig. , with bo64, we analyzed proton-radiation differential exon usage (DEU). Only 4 DEU events were detected  with annotated- DHRs found that they were less likely to be associated with bidirectional DHRs than control “unidirectional” DHRs  Fig.  and synap < 0.1). Surprisingly, this analysis suggested that genes associated with both increased and decreased DHRs had higher intragenic DHR density and that these changes extended across entire gene bodies, as opposed to unidirectional changes that tend to cluster at the 5′ ends . Bidirectional regulation of DHRs for individual replicates is shown via heatmaps , irradiated mice did not  but there was no effect of radiation (not shown). Both groups showed spatial memory retention in the first probe trial, spending more time in the target platform than any other platform  radiation, whereas protons are a form of low LET radiation. Accordingly, we re-analyzed our previously published DIP-Seq data that examined the effects of 0.1 Gy and 0.2 Gy 56Fe (600 MeV/n) on hippocampal 5mC and 5hmC at the 2- week time point, which unlike the proton-induced changes partially disappeared at the 20-week time point. Both 0.1 and 0.2 Gy 56Fe gene-associated DHRs and DMRs showed a highly-significant correlation with proton DHRs and DMRs from this study  after exposure and suggest altered gene ontology and KEGG pathways that account for altered cognitive function. Cognitive changes occur relatively rapidly because impairment for object recognition, spatial memory retention in the water maze, and network stability following proton irradiation were observed at the two-week time point. Our data also showed epigenetic remodeling of a subset of genes with critical neuronal functions within four weeks of exposure.i.e., depletion at the transcriptional start sites of active genes and enrichment at genes expressed at low levels, and 5hmC and gene expression, i.e., high levels for active genes and low levels for inactive genes. These data show differential biological function for these two forms of DNA methylation, which did not respond identically to proton exposure. Changes in 5hmC levels were more likely to localize to genes required for synaptic and neuronal functions, suggesting that dynamic changes in 5hmC are more strongly associated with functionally significant gene pathways. Strikingly, a significant percentage of genes exhibited both increased and decreased intragenic 5hmC levels, suggesting that proton irradiation triggers a complex remodeling at some gene-associated loci in a spatially-restricted manner. In contrast, 5hmC changes at genes exhibiting only increased or decreased levels were restricted more to their 5′ ends. Because bi-directionally-affected DHR density increased in significance distal to transcriptional start sites, it is conceivable that 5hmC remodeling is linked to transcription or RNA processing. Interestingly, a recent study found an association between dynamic regulation of 5hmC in response to cocaine administration and alternative splicing66. It would be interesting to determine whether transcripts enriched for bidirectional DHR remodeling are associated with changes in RNA transcription or splicing and whether bidirectional and unidirectional 5hmC remodeling generalizes to other experimental models. These results suggest that DNA methylation changes as a result of proton exposure can occur via multiple pathways and that these pathways are gene specific.The DNA methylation data for the unexposed hippocampus showed anticipated relationships between 5mC and gene expression, When we analyzed changes in 5hmC that correlate with changes in transcription, significant overlap was observed for genes within neuronal gene ontology pathway that exhibited both increased 5hmC levels and transcription demonstrating a clear relationship, but whether one change precedes the other or if they occur simultaneously is not known. A kinetic analysis will be necessary to address this question. In addition, the RNA-seq data identified other gene ontology pathways associated with RNA function and cellular morphology that were not detected in our 5hmC analysis.Consistent with the gene ontology analyses, KEGG pathways linked to synaptic function and neuronal processes were significantly enriched for gene-associated DHRs. For example, the long-term potentiation pathway was enriched for both up- and down-regulated DHRs. The genes present in the up and down-regulated long-term potentiation KEGG category showed perfect overlap, highlighting the dynamic and spatially-restricted regulation of 5hmC at gene loci by proton radiation. The data suggest that radiation-induced changes in 5hmC may predominantly utilize pre-existing pools of methylation. Genes that are expressed at higher levels in the hippocampus were not more affected than those expressed at lower levels and the variance in 5hmC was similar in the sham- and proton-irradiated mice.36, which demonstrates functional significance for these stable changes that relate to tissue specific functions. Further work will be required to determine the functional significance of these stable 5mC changes that result from proton exposure. The DNA methylation data are consistent with involvement of post-synaptic rather than pre-synaptic mechanisms in the effects of proton irradiation. A striking observation was the enrichment for 5hmC changes near NMDA-subtype glutamate receptors and genes linked to LTP, both of which have been linked to alterations in postsynaptic function. Interestingly, changes in NMDA receptor composition in response to radiation have been observed in rodent models and in human patients70 Consistent with this, following proton irradiation increases in hippocampal levels of postsynaptic density protein 95 (PSD95)71 and an increase in the rate of miniature excitatory postsynaptic currents of in the CA1 hippocampal region were reported72. Genes that are differentially-regulated in the synapse category at the 2-week time point include the GABA receptor  used in this study showed similar susceptibility to detrimental effects of proton irradiation at the 2-week time point but differential susceptibility to these effects at the 20-week time point with impaired object recognition but not impaired spatial memory retention. These data indicate that the object recognition test might be particularly sensitive to detect detrimental effects of proton irradiation. Impaired object recognition was seen three months, but not one month, following proton  only or mixed proton and Arc-positive cells and the percentage of neurons expressing Arc in the nucleus and cytoplasm was similar in sham-irradiated mice exposed to the same environment and proton-irradiated mice exposed to different environments. This pattern, showing a mirror image of opposing effects of environment in the sham-irradiated and irradiated groups, might be specific to proton irradiation as we did not see this following 56Fe ion irradiation55. There seem two impairments here: 1) inability for proton- and 56Fe ion-irradiated mice to remember that they were in the same environment before. So, that would explain why following exposure to the same environment there the Arc outcome measures are lower in irradiated than sham-irradiated mice; and 2) inability to detect a novel environment and, as a result, an environment that is clearly different, the proton-irradiated mice experience as identical and therefore they show the same pattern as seen in sham-irradiated mice that are exposed to different environments. So, the proton-irradiated mice must pick up some clues as to what environment they are in but cannot detect the difference.”It is intriguing that the pattern for the total number of 56Fe ion irradiation were more pronounced at 2 rather than 20 weeks following exposure. Post-synaptic synapse remodeling might be particularly important in these effects. Comparison of changes in DNA methylation following irradiation with protons and 56Fe showed an overlap in changes in distinct pathways, demonstrating a radiation signature. Future efforts are warranted to compare these distinct effects of proton and 56Fe ion irradiation on hippocampal function with those of another heavy ion exposure such as 28Si ion exposure, how these radiation quality-dependent changes might interact, and finally how they occur.In summary, proton irradiation has short- and long-term detrimental effects on object recognition and is associated with short- and long-term alterations in 5hmC in the hippocampus. There is a fundamental epigenetic remodeling for a subset of genes with critical neuronal functions and other cellular functions as a result of exposure. The long-term detrimental effects of proton irradiation on hippocampal function are remarkable, considering that the effects of Suppl fileSuppl Table 1Suppl Table 2Suppl Table 3Suppl Table 4


RNA detection was achieved through amplification of a ribozyme region target, with a limit of detection of 5 IU/ml. The prototype serology assay (IgG) was developed using peptides derived from HDV large antigen (HDAg), and linear epitopes were further identified by peptide scan. Specificity of an HBV negative population was 100% for both assays. A panel of 145 HBsAg positive samples from Cameroon with unknown HDV status was tested using both assays: 16 (11.0%) had detectable HDV RNA, and 23 (15.7%) were sero-positive including the 16 HDV RNA positive samples. Additionally, an archival serial bleed panel from an HDV superinfected chimpanzee was tested with both prototypes; data was consistent with historic testing data using a commercial total anti-Delta test. Overall, the two prototype assays provide sensitive and specific methods for HDV detection using high throughput automated platforms, allowing opportunity for improved diagnosis of HDV infected patients.Worldwide, an estimated 5% of hepatitis B virus (HBV) infected people are coinfected with hepatitis delta virus (HDV). HDV infection leads to increased mortality over HBV mono-infection, yet HDV diagnostics are not widely available. Prototype molecular (RNA) and serologic (IgG) assays were developed for high-throughput testing on the Abbott  Infection is established simultaneously with HBV or through superinfection of an HBV positive individual. HDV infection is associated with elevated risk of chronic hepatitis, accelerated liver disease, and poorer prognosis than HBV infection alone5. Despite global HBV vaccination programs, HDV infection is on the rise in different geographies8. The estimated global burden of HDV is 15–20 million (5% of HBV infections) with an increased mortality rate among dually infected individuals9.Hepatitis delta virus (HDV) is classified as a defective virus as viral particle assembly requires packaging of RNA into the HDV encoded capsid (HDAg) which is associated with an envelope protein provided by the hepatitis B virus (HBV) surface antigen  proteins12. To date, there are eight proposed genotypes for HDV, with genotype 1 the most globally prominent13. The genotype 3 clade of HDV, endemic to South America, exhibits the greatest divergence with approximately 70% similarity to the other genotypes14. It has been proposed that genotype-dependent variations in disease progression exist15, but needs to be further evaluated. The presence of quasispecies is noted within individual patients and is thought to result from poor editing ability of the RNA polymerase involved in HDV replication17. The most conserved region of HDV genome is within the ribozyme10, which has served as a target for molecular based assays21.HDV exhibits a high degree of genetic heterogeneity, with intra-genotypic divergence less than 16% and approximately 19–38% between genotypes8. Serologic testing is suitable for initial evaluation with reflex RNA testing to differentiate active from resolved infections. The current diagnostic landscape includes a need for highly sensitive and specific serologic and molecular assays for HDV detection: however, in resource limited areas availability is scarce and there is no standardized molecular assay for HDV detection globally available22. Further, many RNA tests work well for genotype 1, but not for other genotypes23. In 2013, the World Health Organization (WHO) established an international standard for HDV RNA, a genotype 1 strain, that can be used in nucleic acid amplification technique (NAT)-based assays22, but assessment of assay performance using the WHO standard may not capture the challenge of detecting diverse HDV strains.Because of the higher risk of developing liver-related complications resulting from HDV superinfection, HDV diagnostic testing is recommended for all patients with chronic HBV infectionm2000 (molecular) platforms, respectively. The molecular assay targeted the conserved ribozyme region and was challenged by testing in vitro transcripts representative of the diversity within published HDV sequences. A panel of HBV carriers from Cameroon (n = 145) was tested and assay performance was validated by testing with two additional published assays24. A serology assay for the detection of HDV IgG was developed using peptides from the large antigen, and regions having linear epitopes were identified by testing a peptide scan library. Testing with both HDV molecular and serologic prototypes revealed all HDV RNA positives detected were antibody positive supporting serologic testing for routine diagnosis of HDV.Herein, we describe the development of prototype serologic (anti-HDV IgG) and molecular  assays to detect HDV infection, adapted for high-throughput screening on the Abbott ARCHITECT (serology) and m2000 platform. Primers and probe targeted the conserved ribozyme region. HDV genome sequences from genotypes 1–8 (n = 291) were aligned and the targeted regions were analyzed for genetic diversity  was present in 2 in vitro transcribed RNAs and did not impact detection  of 0.9983 demonstrated linearity across the tested range; the mean slope of −3.28 showed high amplification efficiency  were evaluated, and the provisional limit of detection (LOD) was determined to be 5 IU/ml , HCV (antibodies and NAT), HIV (antibodies and NAT) (n = 68). No false positives were observed: specificity was 100%  in this population.The utility of the molecular assay to detect active HDV infection was evaluated by testing 145 HBsAg positive samples from Cameroon with unknown HDV RNA or antibody status. A total of 16 of 145 (11.0%) samples had detectable HDV RNA and viral loads ranged between 1.49 to 7.90 log IU/ml using the prototype molecular assay Table . In orde24 and Assay 220  in contrast to Assay 2 which showed low correlation with the other two assays , HCV (antibodies and NAT), HIV (antibodies and NAT) (n = 173). A provisional cut-off was determined based on the population median +20 standard deviations; and resulted in a specificity of 100%.The complete 145 HBsAg positive sample set from Cameroon was tested with the prototype HDV IgG assay using the provisional cut-off. In total, 23 of 145 (16.0%) samples in this cohort were HDV IgG positive Fig. . The comAdditionally, a peptide scan of the entire HDV large antigen open reading frame was designed to identify small linear epitopes. The study using the larger 7 peptides defined antigenic regions within amino acids 59–84 and 92–114. HDV RNA positive samples were tested with the scanning peptides in an indirect IgG assay Fig. . Two ove25. Historic testing data showed detection of HDV antigen in the serum between days 25–52, whereas detection in in the liver occurred between days 27 – end of study day 119  compared to the historic testing data (day 42) using a FDA approved assay (Abbott Anti-Delta) which detected total antibody (IgM and IgG)  Fig. . The IgMgG) Fig. . HDV RNAgG) Fig. . Viral tm2000 platforms, respectively. The HDV molecular prototype displays highly sensitive and reproducible detection of HDV RNA with a limit of detection of 5 IU/ml  in the prototype assay, and were anti-HDV IgG positive using the prototype serology assay  detected 14 of 16 RNA positive samples, but the smaller scanning peptides covering that region did not. The assay format using a blend of peptides is amendable to adding additional peptide variants as more diverse HDV strains are isolated.The prototype serology assay was developed to detect the IgG response to HDV infection. The initial study used peptides spanning regions from the large antigen predicted to be antigenic, followed by a peptide scan to find discrete linear epitopes. The peptides 2 and 4 were designed to encompass non-overlapping regions (aa 59–84 and 92–114) and a combination of both detected all HDV RNA positive samples tested  and IgG (day 42); RNA was detectable from day 7 and remained detectable throughout the study . The IgM and IgG responses developed at similar times to each other and to historic data, but the IgM response declined quickly while the IgG response remained, suggesting that testing for IgG only is sufficient as a primary screen. Consistent with this, all HDV RNA positive samples from the Cameroon cohort tested were IgG positive. Combining the seroconversion testing and the positive predictive value of an HDV IgG result for HDV RNA presence supports the importance of the anti-HDV IgG testing in detection of early phase HDV superinfection as well as established persistent HDV infection in HBsAg positive patients.29. Currently, as more HDV specific therapies emerge31 the need for highly specific and sensitive assays is evident. As the genetic diversity of HDV is better understood, additional updates to serologic and molecular assays will be needed. Diagnostic testing for HDV provides an opportunity for treatment and potentially improved clinical outcomes.All patients with HBV are susceptible to HDV infection and testing should be a part of HBV monitoring32 or higher to remove gaps. The primers and probe regions were identified in the alignment and point mutations were determined.Full length genomes for HDV (>1680 nt)  protocol . For RNA amplification, the oligonucleotides forward , reverse , and probe  were used with the AgPath ID One-Step RT-PCR kit  mastermix including proprietary Detection Enhancer added according to the manufacturer’s protocol. 15 ul of the 50 ul eluate was then added for a total reaction volume of 50 ul. Amplification and detection were performed on the m2000rt  under the following cycling conditions: 50 C, 45 min; 95 C, 10 min; 50X . Sample viral loads were determined by plotting to a standard curve generated from quantified dilutions of the WHO HDV NAT standard (PEI code number 7657/12).1.0 ml of plasma was extracted for total nucleic acids on the 24 . Gene blocks were used as template in the MEGAscript T7 Transcription kit  according to the manufacturer’s instructions. Transcripts were extracted with an equal volume of TRIzol , and chloroform . The upper aqueous phase containing the transcripts was recovered and purified by twice passing through a NucAway spin column hydrated in water. Transcripts were quantified by determining A260 (DU800 Beckman Spectrophotometer) and evaluated using the prototype HDV molecular assay.Sequences from 12 different HDV isolates encompassing the assay amplicon (to 341 nt) were appended with an upstream T7 promoter for The WHO HDV standard for nucleic acid amplification techniques (NAT)-based assays (PEI code number 7657/12) was acquired through the Paul-Ehrlich-Institut  and was reconstituted according to instructions per use in 0.5 ml of sterile nuclease-free water .Volunteer donor serum for specificity studies was sourced from the United States through purchase from ProMedDx, LLC  as negative for HBsAg, anti-HBc, HBV DNA, HCV (antibodies and NAT), HIV (antibodies and NAT). The specificity for the serology prototype was tested with 173 donor samples, where 68 had remaining volume available for specificity testing using the molecular assay.33; the study protocol was approved by the National Ethics Committee of Cameroon and samples were collected in accordance with relevant guidelines and regulations. Informed consent was obtained prior to sample collection. HBsAg status of samples was determined using either the ARCHITECT HBsAg (1L80) or ARCHITECT HBsAg Qualitative (4P53) assays . HBV viral load was determined using the RealTime HBV viral load (2G34) . This cohort was chosen for HDV assay development due to the availability of large sample volumes (>5 ml).HBsAg reactive plasma samples (n = 145) were selected from a well-characterized convenience population that was available retrospectively from blood donations collected in Douala and Yaoundé, Cameroon between 2006 and 2011The limit of detection (LOD) was established by testing the WHO HDV standard (PEI code number  7657/12) diluted in HBV/HCV/HIV negative human plasma to 1.25, 2.5, 5, 10, and 20 IU/ml and extracted as described above  . Briefly, the biotinylated peptides were diluted at 400 ng/ml each and incubated with magnetic streptavidin microparticles and sample for 18 minutes (first step) to allow for immunocomplex formation. The magnetic microparticles were washed and an acridinium conjugated mouse anti-human IgG was added (second step) for detection of immunocomplexes specific for the HDV peptides. The 7 original peptides were tested individually with HDV RNA positive samples to evaluate serologic utility. After determining that three peptides  had value in the detection of HDV RNA positive samples, subsequent testing for sensitivity and specificity was performed with the peptides blended at 400 ng/ml each in a prototype assay. Peptide 1 was included because it may provide value for peptide 2 non-reactive or weakly reactive samples  were dissected for individual peptide reactivity.For serology assay comparison testing, the XpressBio HDV-IgG ELISA  was used as a comparator assay for testing the HBsAg positive samples from Cameroon as per manufacturer’s instructions.36. Serial bleeds were collected for 119 days post superinfection and were originally used in a publication describing the assay performance of the Abbott Anti-Delta EIA  to detect acute HDV infection25. Briefly, both chimpanzee liver and serum HDAg were detected by using a modified research sandwich enzyme immunoassay37. Serum alanine aminotransferase (ALT) was measured by a commercial reference laboratory at the study site the day of the chimp bleed. Small volumes of the serial bleeds from the study were preserved at −80 °C in 1985 were used for testing herein. The prototype serology assay was modified where the conjugate used for detection was changed to either a goat anti-monkey IgG or goat anti-monkey IgM for use in the indirect assay format. Provisional cut-offs for IgM and IgG assays were set at 10 times the background (negative control) signal.An HBV infected chimpanzee (HBsAg positive) was experimentally superinfected with HDV (genotype 1) in 1984 using a standardized acute-phase inoculum provided by the National Institutes of Health (NIH), which had been derived from the plasma of a previously infected chimpanzee. All procedures were performed under institutionally approved protocols at the Laboratory for Experimental Medicine and Surgery in Primates  in accordance with relevant guidelines and regulations in place at the time of the study, 1984Positive predictive value and P-value (unpaired student’s t-test) were determined using Prism . Regression analyses were performed in JMP .Sequences deposited in Genbank under accession numbers .Supplemental Information


Sister chromatid exchanges (SCEs) are considered sensitive indicators of genome instability. Detection of SCEs typically requires cells to incorporate bromodeoxyuridine (BrdU) during two rounds of DNA synthesis. Previous studies have suggested that SCEs are induced by DNA replication over BrdU-substituted DNA and that BrdU incorporation alone could be responsible for the high number of SCE events observed in cells from patients with Bloom syndrome (BS), a rare genetic disorder characterized by marked genome instability and high SCE frequency. Here we show using Strand-seq, a single cell DNA template strand sequencing technique, that the presence of variable BrdU concentrations in the cell culture medium and in DNA template strands has no effect on SCE frequency in either normal or BS cells. We conclude that BrdU does not induce SCEs and that SCEs detected in either normal or BS cells reflect DNA repair events that occur spontaneously. Sister chromatid exchanges (SCEs) are a possible outcome of DNA double-strand breaks (DSBs) that were repaired through homologous recombination. As such, SCEs are considered sensitive indicators for genome instability in cells . This isBLM gene  was added to cultures at indicated concentrations for indicated periods of time.The following cell lines were obtained from the Corriell Cell Repository: GM07492 , GM03402 , GM12891  and GM16375 . Fibroblasts were cultured in Dulbecco's modified Eagle's medium (Life Technologies) supplemented with 15% v/v fetal bovine serum (Sigma Aldrich) and 1% v/v penicillin-streptomycin (Life Technologies), lymphoblasts in RPMI1640 (Life Technologies) supplemented with 15% v/v FBS and 1% v/v penicillin-streptomycin. All cells were cultured at 37°C in 5% CO2, 0.5 mM MgCl2, 0.1% NP-40 and 2% bovine serum albumin). Nuclei were stained with Hoechst 33258 (Life Technologies) and propidium iodide (Sigma Aldrich) at final concentrations of 10 μg/ml. Nuclei were analyzed and sorted based on low PI (G1 phase) and low Hoechst . DNA quality was assessed and quantified on a High Sensitivity dsDNA kit (Agilent) on the Agilent 2100 Bio-Analyzer and on the Qubit 2.0 Fluorometer (Life Technologies). For sequencing, clusters were generated on the CBot (HiSeq2500) and single-end 50 bp reads were generated were generated using the HiSeq2500 sequencing platform (Illumina).Indexed bam files were aligned using bowtie2  and furtIn order to assess any potential effect of BrdU on SCE rates, we first established baseline SCE rates in both normal and BS cells. We used primary fibroblasts and EBV-transformed lymphoblasts from healthy donors and BS patients for our analysis. Logarithmically growing cells were pulsed with 40 μM for one cell division . Cells were harvested directly after the BrdU pulse, nuclei suspensions were made and single nuclei were sorted by means of flow cytometry. Nuclei from cells in G1 phase (low PI fluorescence) that had incorporated BrdU into their DNA (low Hoechst fluorescence) were sorted and Strand-seq libraries were made. SCEs were detected by the BAIT analysis software  and confTwo representative libraries made from a normal fibroblast Figure  and a BSNext, we investigated whether incorporation of BrdU into newly formed DNA strands could induce SCEs. Both normal and BS cells were cultured with increasing concentrations of BrdU. First, the effect of BrdU on proliferation was determined by culturing cells in increasing concentrations of BrdU and tracking proliferation over the course of 7 days. Fibroblasts were seeded at 10% confluency, lymphoblasts at 200 000 cells/ml. The number of live cells was counted using the trypan blue exclusion method every 24 h or until cultures reached confluency. The results Figure –D show tBrdU is thought to affect SCE frequencies when it is present in the DNA, so therefore we attempted to confirm that higher doses of BrdU also lead to higher BrdU incorporation into the DNA during cell division. Because fluorescence of Hoechst bound to DNA decreases when BrdU is present in the DNA , we deciIn order to determine if BrdU does indeed induce SCEs, all four cell lines were pulsed with 10–200 μM BrdU for one cell division and Strand-seq was performed to assess SCE rates under the different conditions. The results confirmed the high SCE rates in BS cells at each BrdU concentration, but we did not detect any significant effect of BrdU concentration on SCE rates in any of the cell lines Figure  and H.It has previously been proposed that DNA replication over BrdU-substituted DNA induces SCEs . AlthougThe role BrdU plays in SCE formation has been debated for several decades, but has not been resolved convincingly. Here we use Strand-seq to show that BrdU does not induce SCEs in either normal or BS cells and that Strand-seq can be used to detect spontaneously occurring SCEs in cultured cells.SCE detection by means of staining of metaphase spreads requires two rounds of DNA replication in the presence of BrdU. Because of this, the number of SCEs that occurred during a first cell cycle had to be estimated based on complex staining patterns in second or third cell cycle metaphase spreads. Using Strand-seq, it is possible, for the first time, to directly detect SCEs after one cell division. Our results indicate firstly that SCE frequencies are elevated in both BS fibroblasts and lymphoblasts compared to their normal counterparts. Secondly, the concentration of BrdU used during cell culture has no effect on SCE frequencies. Thirdly, SCE frequencies do not increase during a second cell cycle in the presence of BrdU in either normal or BS cells. Based on these results, we conclude that BS cells display spontaneously elevated SCE rates and that BrdU has no effect on SCE rates in either normal or BS cells.These results disagree with the generally accepted notion that BrdU does induce SCEs, either during incorporation into nascent DNA strands or during DNA replication over BrdU-substituted DNA –11. AlthIt has previously been suggested that BS cells only display elevated SCE rates when replicating DNA over BrdU-labeled template strands, suggesting that the high SCE rates are induced by BrdU and do not occur spontaneously ,18. In oOne major difference between these previously reported studies are the cell types used for experiments: Epstein-Barr virus (EBV) transformed B lymphoblastoid cell lines ,18, primBased on these results, we conclude that BS cells display spontaneously elevated SCE rates and that this reflects high levels of genomic instability in patient cells that likely contributes to the wide range of symptoms associated with BS, including the strong cancer predisposition seen in patients . FinallySequencing data have been deposited in the European Nucleotide Archive under accession number PRJEB13795.


TP53 signature has a robust predictive performance for prognosis in early-stage breast cancer, but the experiment that reported this relied on public microarray data and fresh-frozen samples. Before TP53 signature can be used in a clinical setting, a simple and low-cost diagnostic system using formalin-fixed paraffin-embedded (FFPE) samples is needed. New treatments based on the biological characteristics of TP53 signature are expected to follow.TP53 signature was evaluated in 174 FFPE early breast cancer specimens using digital quantification via the nCounter technique (NanoString). Patients were classified as TP53 signature mutant type (n = 64) or wild type (n = 110). Predictive power of TP53 signature was compared with those of other gene expression signatures in 153 fresh-frozen samples of the same cohort by RNA-seq. The molecular features of TP53 signature were elucidated using TCGA omics data and RNA-seq data to explore new therapeutic strategies for patients with TP53 signature mutant type.TP53 signature was a strong predictor of prognosis and was also more accurate than other gene expression signatures and independent of other clinicopathological factors. TCGA data analysis showed that risk score of TP53 signature was an index of chromosomal and genomic instability and that TP53 signature mutant type was associated with higher PD-L1 expression, variation in copy numbers, and numbers of somatic mutations.TP53 signature as diagnosed using the nCounter system is not only a robust predictor of prognosis but also a potential predictor of responsiveness to immune checkpoint inhibitors. TP53 gene were seen in 30 percent of whole breast cancer patients and 80 percent of triple-negative breast cancer patients [TP53 structural mutation status is associated with worse overall and disease-free survival, but its predictive value is still debated [TP53 structural mutations are missense mutations, and the function of each mutation was verified using a yeast system [TP53 missense mutations, however, and several comprehensive analyses by next-generation sequencing (NGS) have revealed other key genes associated with the p53 pathway, epigenetic abnormalities and copy number alternations without TP53 missense mutation [TP53 signature, a gene expression profile composed of 33 genes including two housekeeping genes to predict TP53 structure [TP53 signature can be used to classify breast cancer patients into wild type (TP53 signature WT type) or mutant type (TP53 signature MT type) based on the expression pattern of 33 genes. The TP53 status determined by TP53 signature does not completely match to the TP53 status defined by TP53 structural status. There were some samples without TP53 structural mutation in TP53 signature mutant type. Recent reports revealed TP53 signature could also predict prognosis of early-stage breast cancer more accurately than TP53 status determined by DNA sequencing or immunohistochemically examination. Uji et al. reported that TP53 signature was a powerful predictive prognostic indicator for ER-positive breast cancer rather than TP53 structural mutation detected by NGS, Sanger sequence method, and immunohistochemistry [TP53 signature had a robust capacity for predicting prognosis in early-stage breast cancer compared to other gene expression profiles including Mammaprint and Oncotype DX [The functional loss of p53 plays a very important role in oncogenesis , 2. Repopatients . There i debated . Many TPmutation . Becausemutation . Previoutructure . TP53 sihemistry . In addiotype DX , which hotype DX –18.TP53 signature have been based on microarrays. Before the robust predictive ability of TP53 signature can be used in an ordinary clinical situation, a simple and low-cost diagnostic system for TP53 signature using formalin-fixed paraffin-embedded (FFPE) tissue samples is absolutely needed. The nCounter  is a gene expression analysis machine which can analyze a maximum of 800 kinds of gene expression values at the same time without PCR reaction [TP53 signature using the nCounter would provide us with more accurate prognostic predictive ability for early breast cancer in actual clinical situations. At the same time, it is necessary to develop new therapeutic strategies for patients with poor prognosis as diagnosed by TP53 signature.To date, diagnostic systems for reaction . The ProTP53 signature through an analysis of 223 FFPE breast cancer specimens using nCounter and to demonstrate the robust predictive ability of TP53 signature compared to other expression profiles by analyzing RNA-seq data. The second purpose of this study was to clarify the molecular biological background of TP53 signature using RNA-seq data of 153 breast cancer patients and TCGA public data [The first purpose of this study was to develop a diagnostic system for Figure TP53 signature data were derived from microarray data using FF samples. In order to evaluate whether the data acquired through nCounter analysis from FF and FFPE were comparable, we examined correlations between the expression levels of the 31 genes comprising the TP53 signature in FF and FFPE samples. The gene-set used in this study is the same as gene-set used in original TP53 signature. Some reports have confirmed good correlation between the expression values of FFPE and FF samples [TP53 signature with the nCounter system.The previous reports of  samples . Good coTP53 signature status as measured with the nCounter system was determined by analyzing samples from the 30 patients constituting the learning cohort. Fourteen patients had TP53 somatic mutations as detected by Sanger sequence  compared with TP53 signature WT type patients in the nCounter validation cohort  method. Of these 126 filtered genes, 78 were more frequently seen in the TP53 signature MT type than in the WT type , “microtubule-based process”,  or “chromosome organization”  , “regulation of cellular macromolecule biosynthetic process”  or “nucleic acid metabolic process”  . Next, sprocess” , 5. Anal results .Although somatic mutation call using RNA-seq was still challenging, we investigated whether a result similar to that of the TCGA data analysis would be obtained in analysis of our clinical breast cancer samples. We found that, in fact, similar results were obtained (data not shown).PD-L1 and CD8B mRNA expression values, copy number variance (CNV), and somatic mutation number (SMN) were compared between the TP53 signature status groups as defined according to the SVM method using TCGA microarray data. Both PD-L1 and CD8B mRNA expression values were higher in TP53 signature MT type than in TP53 signature WT type . In RNA-seq data of clinical samples, there was no significantly difference in CD8B expression value between TP53 signature status, but PD-L1 mRNA expression value was higher in TP53 signature MT type than in TP53 signature WT type (data not shown).Secondly, e Figure . In addiTP53 signature statuses as determined by nCounter were compared among intrinsic subtypes. The intrinsic subtype of each sample in the nCounter RNA-seq common cohort was determined using RNA-seq count data. All samples in the luminal A subtype were TP53 signature WT type. Half of the samples in the luminal B subtype were TP53 signature MT type. Many samples in the basal and Her2 enriched subtypes were TP53 signature MT type . Furthermore, BRCA1, RB1 mutation, and other gene mutations rarely reported in breast cancer but relating to DNA repair or chromosomal instability were found in samples with TP53 signature MT type along with TP53 gene mutation. These results indicated that the risk score of TP53 signature is an index of chromosomal or genome instability.In order to clarify the reason why MDM2 in tumor cells decreases their ability to activate p53 [MDM2 were diagnosed with TP53 signature MT type, although these samples did not show TP53 structural mutation. This result shows that TP53 signature can evaluate TP53 function comprehensively with or without TP53 structural mutations. Several reports have suggested that not only mutations in the TP53 gene itself but also structural abnormality in other molecules related to the pathway is the mechanism underlying tolerance to DNA-damaging drugs [TP53 signature is a new functional assay system that satisfies this requirement.The presence of high levels of vate p53 . We founng drugs –24. ThesTP53 signature status is a classification indicating genomic and chromosomal instability. Treatment decisions for breast cancer patients are typically based on the oncodriver genes that constitute the treatment targets, and intrinsic subtype is used to classify patients with regard to treatment target. Among the intrinsic subtypes, however, the basal-like subtype is considered to have no clear molecular treatment target. Our data showed that almost all patients with basal-like subtype belonged to the TP53 signature MT type. This result indicates that the basal subtype group is characterized by high genomic and chromosomal instability. Our data also showed that there were some patients with genomic and chromosomal instability in the luminal B and Her2-enriched subgroups. In patients with Luminal B type, about a half of them were TP53 signature MT type. Some Luminal B type patients with TP53 signature MT type did not show TP53 structural mutations. This result showed that there might be other mechanisms except for TP53 structural mutation to obtain chromosomal and genome instability in luminal B type patients. In the TCGA data, 75 patients were diagnosed as Luminal B type, of which 8 were deceased. Seven of these eight patients were diagnosed as TP53 signature MT type. These results showed that breast cancer patients could be classified in more detail using TP53 signature in addition to intrinsic subtype classification, and suggested that the prognosis of patients with TP53 signature MT type is poor with or without molecular target oncodriver genes because of genomic instability. The development of new treatment strategies for patients with genomic instability will improve prognosis of breast cancer patients.As explained above, TP53 signature MT type were consistent with these biomarkers for responsiveness to immune checkpoint inhibitors. These results indicate that the TP53 signature has a potential predictive value for responsiveness to immune checkpoint inhibitors. Indeed, Tolaney et al. reported in a phase 1b/2 study that eribulin mesylate in combination with pembrolizumab led to a high response rate  in patients with metastatic triple-negative breast cancer [TP53 signature MT type. To date, no clinical trials treating breast cancer patients with immune check point inhibitors as adjuvant therapy have been reported. To prove our hypothesis that the TP53 signature has a potential predictive value for responsiveness to immune checkpoint inhibitors, future prospective study or a retrospective sample analysis associated with a clinical trial using immune checkpoint inhibitors should be conducted.Recently, treatments with immune checkpoint inhibitors have led to good outcomes in many type of cancers –28. In st cancer , of whicTP53 signature that is suitable for clinical use. TP53 signature appears to be an index of chromosomal and genomic instability and to have potential predictive value for responsiveness to immune checkpoint inhibitors. The diagnostic system based on TP53 signature developed in this study will help in prognostic assessment, therapeutic decision-making, and treatment optimization in patients with breast cancer.Taken together, we developed a powerful diagnostic system based on TP53 signature status using nCounter. None of this cohort had received chemotherapy or endocrine therapy preoperatively. The same cohort had been used in our previous microarray-based study [TP53 status had been identified in all samples by means of TP53 DNA-direct sequencing.This study was approved by the Ethics Committee at the Tohoku University Hospital. We analyzed 30 patients’ FFPE samples, a set which we called the “nCounter learning cohort,” to determine the cutoff value for diagnosis of ed study , and TP5in situ, those with unknown histology or those with squamous cell carcinoma were excluded from the analysis. Among the validation cohort, we called the samples analyzed by nCounter only the “nCounter cohort” (n = 190) and cases analyzed by RNA-seq the “RNA-seq cohort” (n =153). From within these cohorts, we selected the curatively resected patients with stage I–II breast cancer and called them the “nCounter validation cohort” (n = 174) and the “RNA-seq validation cohort” (n = 132). Samples that were in both the “nCounter validation cohort” and the “RNA-seq validation cohort” were grouped in an “nCounter RNA-seq common cohort” (n = 120).The validation cohort was a prospective breast cancer case series from Hoshi General Hospital and Miyagi Cancer Center from September 2007 to October 2010. Written informed consent for the study was obtained from all patients. None of the patients received had chemotherapy or endocrine therapy preoperatively. A part of each surgical specimen of breast cancer was stored as FF tissue, and the remainder was stored as FFPE tissue. Among the patients enrolled in this study, patients with ductal carcinoma Glass slide specimens with 10-μm thick sections of FF and FFPE tissue blocks were prepared. Tumor cells were collected from FF tissue or FFPE tissue by macrodissection in reference to an HE-stained specimen. Total RNA was extracted from FF tissue or FFPE tissue using an RNeasy mini kit  or an RNeasy FFPE kit (Qiagen), respectively.TP53 signature gene set for nCounter. Primers for each of these 36 genes were designed. In accordance with the manufacturer's instructions, we measured the expression values of the 36 genes using nCounter with 200 ng of total RNA extracted from each FF or FFPE sample.A set of thirty-six genes including five internal control genes was used as the Five patients with both FFPE and FF samples were randomly selected, and expression data of these patients’ samples were measured using the nCounter system. We compared expression data of FFPE with that of FF samples in these five patients by Pearson's product moment correlation coefficient.RNA quality was monitored using the 2200 TapeStation system . Sequencing libraries were generated using the TruSeq RNA Library Prep kit  according to the manufacturer's directions. Sequencing was performed on the Illumina HiSeq2500 platform (Illumina) in rapid mode. Raw image files were processed using the Illumina pipeline for basecalling with default parameters. On average, we obtained 50 million 50-bp-long paired-end reads from the RNA-seq. RNA-seq reads were aligned using STAR2 against the hg19 reference genome . On averTP53 somatic mutations accurately, we checked all samples visually using Integrative Genomics Viewer.Somatic mutation call using RNA-seq data was performed according to the following two steps. First, the SNP call for RNA-seq data was performed using the Genome Analysis Tool kit (GATK version 3.6). Next, we defined the SNP, of which a few were reported in the database as somatic mutations. In brief, each sequenced read was aligned against the human reference genome (hg19) by STAR2, and duplicate-read removals were performed using Picard (version 2.6.0). Splitting reads in splicing site fields were performed using the SplitNCigarReads program, base quality score recalibration using the BaseRecalibrator program, and variant discovery using the Haplotype caller program. All programs were run according to the GATK tool kit. Annotation information was attached to all variants using ANNOVAR (version 20160201), and variants were filtered using the SNP databases 1000g2015aug_eas and esp6500. We identified the base substitutions, the proportion of which was under 1 percent in both SNP databases; the read count of the base substitutions as somatic mutations was over 20 (DP > 20). To determine TP53 signature was calculated using count data of nCounter or RNA-seq according to the following formula.Risk score of TP53 signature = (sum of counts of 22 genes that were upregulated in tumors with TP53 mutation) / (sum of counts of 9 genes that were downregulated in tumors with TP53 mutation)Risk score of TP53 signature status, because TP53 status according to Sanger sequence was known for all patients in this cohort. The cutoff value of TP53 signature score for TP53 signature status was determined to maximize accuracy of TP53 status according to Sanger sequence, and an ROC curve was drawn. TP53 status was determined using only TP53 signature score by the nCounter system, because all samples in the nCounter learning cohort were analyzed only by the nCounter system. In the RNA-seq cohort, on the other hand, only risk score was calculated and cutoff value for TP53 signature status was not determined, because TP53 status according to Sanger sequence was not known in this cohort. TP53 signature status was considered to be mutant type (TP53 signature MT type) when the risk score was higher than the cutoff value, and wild type (TP53 signature WT type) when the risk score was lower than the cutoff value. R package “ROCR” was used to draw the ROC curve and calculate the area under the curve (AUC) [We used the learning cohort to determine the cutoff value for ve (AUC) .TP53 signature status as determined using the nCounter system was evaluated using the chi-square test or the Kruskal–Wallis exact test. RFS rates were calculated according to the Kaplan–Meier method and evaluated by the log-rank test. RFS was defined as the period from the date of operation to the date of recurrence. Univariate and multivariate analysis of various parameters for the prediction of recurrences was conducted using the Cox proportional hazards model. Regardless of the statistical test performed, differences with P < 0.05 were considered statistically significant. In the nCounter RNA-seq common cohort, TP53 structural mutation data was added to clinical factors and TP53 signature status as a predictive factor. All static analysis was conducted using R ver3.25.The association between the various clinicopathological parameters and TP53 signature, Mammaprint, OncotypeDX, and PAM50. Concordance index calculated using the R package survcomp was used to compare predictive performance [Risk scores of Mammaprint, OncotypeDX, and PAM50 were calculated using RNA-seq count data from the nCounter RNA-seq common cohort. R package, genefu version 2.6.0 was used to calculate risk scores . Predictformance . Intrinsformance .http://www.cbioportal.org/study?id=brca_tcga_pub).All TCGA data was retrieved from cbioportal . The differences in CNV and SMN between the TP53 signature groups were compared by the Mann-Whitney test.The differences in CNV and SMN were compared between the different PD-L1 and CD8B obtained from TCGA microarray data were compared between the TP53 signature status groups. Expression values of both PD-L1 and CD8B were compared between TP53 signature status groups by Wilcox test.Expression values of p value under 0.1 was considered indicative of a statistically significant difference.GO enrichment analysis was performed using David ver6.7 , 44. In


A 54-year-old patient presented with mild right-sided weakness of hand and face with a National Institutes of Health Stroke Scale (NIHSS) of 2 and occlusion of the left middle cerebral artery (MCA) in the M1 segment with a large perfusion deficit on computed tomography (CT). Due to mild neurological deficits no IVT was performed. Nine hours after symptom onset the patient gradually deteriorated with a NIHSS fluctuating between 9 and 15. MRI showed a persistent occlusion of the MCA with a large diffusion-perfusion mismatch. Immediate endovascular thrombectomy was performed 14 hours after symptom onset with complete recanalization and complete clinical recovery. Although mechanical thrombectomy is generally considered an effective alternative strategy up to 8 hours after stroke onset, selected patients with a large diffusion/perfusion mismatch and small infarct cores may benefit from an expanded therapeutic window. For two decades intravenous thrombolysis (IVT) has been the most important therapy for patients with an acute ischemic stroke . HoweverRecently, data from several randomized clinical trials demonstrated a clear benefit of endovascular treatment in patients with acute ischemic stroke caused by a proximal vessel occlusion in the anterior circulation . SelectiCurrently the time window for favorable outcome after endovascular treatment is not well defined. Endovascular treatment with stent retriever thrombectomy is recommended up to 8 hours after symptom onset .A 54-year old, right-handed previously healthy male patient presented with an acute right sided weakness and facial palsy to a peripheral hospital (NIHSS on admission: 2). Computed tomography (CT) angiography 4 hours and 20 minutes after symptom onset showed an occlusion of the left MCA in the M1 segment with a large perfusion deficit in the complete MCA territory. Since clinical symptoms were very mild the treating physicians decided against IVT and the patient received best medical treatment, that is, 250 mg acetylsalicylic acid intravenously, Atorvastatin 40 mg per os, and enoxaparin 40 mg s.c. He was transferred to the local stroke unit for further monitoring. Within nine hours after symptom onset the patient gradually deteriorated, without any obvious cause . After transferal to our stroke center he presented with severe aphasia and sensorimotor right-sided hemiparesis with an NIHSS fluctuating between 9 and 15. Immediately after admission to our hospital , the patient underwent a cerebral magnetic resonance imaging (MRI)  showing NIHSS immediately after the intervention was 4, and on the following day 2 with a mild weakness of the right arm. MRI 24 hours after intervention showed small left sided basal ganglia infarction . The patEndovascular treatment in acute stroke patients with occlusion of large vessels in the anterior circulation improves functional outcome . RecanalHowever, the time window for favorable outcome after endovascular treatment is not well defined. Only very recently first results of the DAWN study—presented on the 3rd European Stroke Organisation Conference in Prague and not jet fully published—showed that removal of a clot by endovascular thrombectomy within up to 24 hours after onset of signs and symptoms reduced the disability in selected stroke patients, such as wake-up strokes . As demo


Cervus elaphus nelsoni) prion protein gene (PRNP) is polymorphic at codon 132, with leucine (L132) and methionine (M132) allelic variants present in the population. In elk experimentally inoculated with the chronic wasting disease (CWD) agent, different incubation periods are associated with PRNP genotype: LL132 elk survive the longest, LM132 elk are intermediate, and MM132 elk the shortest. The purpose of this study was to investigate potential mechanisms underlying variations in incubation period in elk of different prion protein genotypes. Elk calves of three PRNP genotypes  were orally inoculated with brain homogenate from elk clinically affected with CWD.The Rocky Mountain elk  revealed differences in the ability of PrPSc seed from elk of different genotypes to convert recombinant 132 M or 132 L substrate.Elk with longer incubation periods accumulated relatively less PrPPRNP genotype in the pathogenesis of CWD of elk. The longer incubation periods observed in LL132 elk are associated with PrPSc that is more stable and relatively less abundant at the time of clinical disease. The biochemical properties of PrPSc from MM132 and LM132 elk are similar to each other and different to PrPSc from LL132 elk. The shorter incubation periods in MM132 compared to LM132 elk may be the result of genotype-dependent differences in the efficiency of propagation of PrPSc moieties present in the inoculum. A better understanding of the mechanisms by which the polymorphisms at codon 132 in elk PRNP influence disease pathogenesis will help to improve control of CWD in captive and free-ranging elk populations.This study provides further evidence of the importance of  Sc) in the nervous system and other body tissues. In cervids, CWD infection is associated with clinical signs including behavioral abnormalities, excess salivation, emaciation, and eventually death  of 0.25 M and application to the IDEXX plate. The amount of PrPSc remaining was then plotted against GdnHCl concentration. The midpoint of the curve, or [GdnHCl]1/2, is defined as the concentration of GdnHCl at which the PrPSc signal was reduced by half of the signal at 0.25 M GdnHCl; PrPSc with a smaller [GdnHCl]1/2 is less stable. As described previously [PrPviously  homogenate was assigned a brain unit equivalent (BU) value of 100 and equivalent BU’s were calculated for each dilution, i.e. 1:2 dilution = 50 BU, 1:4 dilution = 25 BU. For each sample, the EIA OD reading in the linear range  was divided by the BU of the dilution at which the linear range OD was measured, to generate an OD/BU value. We then calculated the ratio of the OD/BU values for each sample compared to the sample with the lowest OD/BU value. Ratio values were plotted against incubation period.To determine the relative amount of PrPE. coli (BL21(λDE3)) was transformed with the pET28a vector containing the elk PrP gene corresponding to mature length PrP , and elk recombinant PrP was expressed and purified as described for bovine PrP [− 1 cm− 1 as calculated for mature length elk prion protein.vine PrP , 46. Thew/v) brainstem homogenized in PBS from elk #1 (MM132), elk #4 (LM132) and elk #7 (LL132) as described previously [RT- QuIC was performed on 10%  developed loss of appetite and body condition. Both elk rapidly became unable to stand without assistance and were euthanized. At 38 (#3) and 40 (#4) MPI respectively, LM132 elk developed similar clinical signs and were euthanized (average incubation period = 39 MPI) , diaphragm, kidney, urinary bladder, nose skin, turbinate, trachea, lung, tongue, liver, pancreas, salivary gland, and thyroid were negative in all samples examined.In elk of all genotypes, PrPSc immunoreactivity was widespread in the central nervous system and peripheral lymphoid tissues of all elk. Intraneuronal immunolabeling was less prominent in LM132 and MM132 elk compared to LL132 elk. Glial-associated immunolabeling observed in LL132 elk was not seen in LM132 or MM132 elk.PrPSc and incubation period in CWD-affected elk, we assessed the stability of PrPSc using an EIA-based stability assay.To determine whether there is an association between fibril stability of PrPSc in homogenized brainstem of elk of each genotype was measured, two clusters of curves were evident . Since unfixed brainstem tissue was unavailable for the second MM132 elk (elk #2) spinal cord homogenate was used to determine the fibril stability of PrPSc from this elk. The stability of PrPSc from the elk #2 spinal cord sample was similar to PrPSc from brainstem homogenate from the other MM132 elk (#1) in the study (data not shown).When the fibril stability of PrPent Fig. . Samplesles Fig. , averageSc from samples from MM132 and LM132 elk that have short and intermediate incubation periods, respectively, was less stable than PrPSc from samples from LL132 elk that have the longest incubation periods.In summary, PrPSc accumulation in the brain, the amount of PrPSc in brain homogenates was quantified using EIA.To investigate the relationship between the incubation period and relative amount of PrPSc in the brain was lowest for LL132 elk, intermediate for LM132 elk, and highest for MM132 elk. When the relative amount of PrPSc in the brain was plotted against elk incubation period, a strong negative correlation between these two variables was apparent . For LM132 and MM132 seeds, the lag times in assays using 132 M substrate  were shorter than the lag times in assays using 132 L substrate . The lag time for the LL132 seed in 132 L substrate (19 h) was similar to the lag time in 132 M substrate (20.5 h).Using the 132 L substrate Fig.  and 132 PRNP codon 132 (MM132) or heterozygous for leucine and methionine (LM132) elk are associated with PrPSc that is less stable than PrPSc from elk that are homozygous for leucine (LL132), which have the longest incubation periods. Subjectively, the amount of PrPSc immunoreactivity in the brain was similar across elk of all genotypes using IHC. However, serial dilution studies using EIA revealed that the brains of LL132 elk contain relatively lower amounts of PrPSc than LM132 and MM132 elk. Although the interpretation of results from this study is limited by the small number of elk of each genotype that were available for inoculation, this study nevertheless provides valuable baseline data on the relationship between PRNP codon 132 genotype and disease pathogenesis in elk with chronic wasting disease.We demonstrate that the shorter incubation periods of elk that are homozygous for methionine at Sc in the brain in elk of different genotypes, i.e. elk with longer incubation periods accumulate less PrPSc. Differences in the relative amount of PrPSc in the brain were detected using EIA on frozen brain tissue and IHC on formalin-fixed paraffin-embedded brain tissue. This suggests that MM132 elk may be more permissive to PrPSc accumulation than LM132 elk. This observation is supported by a previous study in transgenic mice that showed that the L132 polymorphism severely restricts propagation of CWD prions [Sc from MM132 and LM132 elk show similar fibril stability profiles and RT-QuIC conversion profiles using recombinant 132 L and 132 M elk prion protein, one explanation for the rapid PrPSc accumulation in MM132 elk may be a potential difference in the effective concentration of PrPC-132M. In heterozygous sheep, both allelic variants of PrPC are present in equal amounts [C-132M in MM132 elk is twice that of LM132 elk. In transgenic mice higher expression levels of PrPC result in reduced incubation times (reviewed in [C-132M in MM132 elk compared to LM132 elk may contribute to the relatively shorter incubation times observed in MM132 elk.We observed a strong negative association between incubation period and the relative amount of PrPD prions . Since P amounts . It is aiewed in ). TherefC to PrPSc is more efficient when the PRNP genotype of the inoculum and substrate are the same [C moiety of the allele associated with a higher susceptibility to disease [Sc in the LM132 brain was predominantly PrPSc-132M and therefore that the pooled brain homogenate contained mostly PrPSc-132M. This PrPSc-132M would propagate more efficiently in elk expressing PrPC-132M than those expressing PrPC-132L or a mixture of PrPC-132M and PrPC-132L. Experimental challenge of elk of each genotype with brain homogenates from homozygous and heterozygous donors may help to elucidate the relative contribution of donor and recipient PRNP genotypes to incubation time in CWD-affected elk.In sheep, conversion of PrPthe same , 3, 21.  disease , 27. Sin disease , 27 it iPRNP genotypes to PrPSc accumulation and by extension, their susceptibility to disease, our findings support previous CWD surveys that have shown that MM132 elk are most susceptible to CWD, the susceptibility of LM132 elk is intermediate, and LL132 elk are least susceptible to CWD [If relative incubation period reflects the relative permissibility of elk of different e to CWD , 41. Thee to CWD . The elke to CWD  so infecSc from elk with shorter incubation periods (i.e. MM132 and LM132) is lower, while PrPSc fibrils from elk with longer incubation periods (LL132) are more stable. These observations are in agreement with previous observations in mice challenged with synthetic [Sc fibril fragmentation that facilitates the conversion of PrPC to PrPSc and results in faster replication of PrPSc and reduced incubation periods [Sc from animals with shorter incubation periods is more stable – has been observed in Syrian hamsters challenged with hamster adapted scrapie or transmissible mink encephalopathy strains [Sc can influence incubation periods.We have shown that the fibril stability of PrPynthetic  and mousynthetic  prion stynthetic . It is h periods , 51. How strains , sheep w strains , 48, and strains . These vSc were observed in all elk and samples from MM132 and LM132 elk showed similar migration profiles, glycoform ratios, and N-terminal cleavage sites [Western blot analyses of brain samples from elk in this study have been published previously , 28. Thege sites , 28. Howge sites . TherefoUntil now, RT-QuIC applications in cervids have mainly focused on detection of small amounts of prions in fluids and tissues relevant to pre-clinical diagnosis of disease or disease transmission: urine , 20, fecSc influences incubation period, real-time quaking induced conversion (RT-QuIC) was performed using recombinant mature length elk prion protein (132 L and 132 M) seeded with brain homogenates from one elk of each genotype. These experiments revealed differences in the ability of PrPSc seed from CWD-infected elk of different genotypes to convert recombinant elk prion substrate. The MM132 or LM132 seeds convert 132 M substrate protein readily, whereas LL132 seed is much slower to do so. In contrast, all seeds convert 132 L substrate protein although the LL132 seed exhibited the fastest conversion. This conversion data suggests two potential hypotheses: (a) there are two distinct and stably propagating conformations of elk PrPSc present, one that is adopted more readily by 132 M protein and one that is adopted more readily by 132 L protein; or (b) the differences in conversion rate  are the result of genotype mismatches between seed PrPSc and substrate. The similar lag phases observed with MM132 and LM132 seed are consistent with previously reported RT-QuIC analyses [Sc-132M. The results of the stability assay also provide evidence that there are two conformations with distinct molecular properties, but future investigations are needed to explore this question. Inoculation of both the MM132 and LL132 seeds into transgenic mice carrying the elk prion gene will be useful in assessing differences in PrPSc fibril stability and incubation times upon serial passage into mice of a single PRNP genotype.To investigate if conversion efficiency of PrPanalyses  and the Sc from CWD-infected LL132 elk shares a number of immunohistochemical features with the ovine scrapie strain CH1641, namely a loss of the epitope for the anti-PrP monoclonal antibody P4 that binds PrP residues 93–99 [Sc accumulation in the brain of sheep with CH1641 is characterized by prominent intracellular immunoreactivity in neurons and glial cells, and relatively little extracellular immunoreactivity [Sc accumulation is rare in MM132 and LM132 elk with CWD [PrPes 93–99 , and redes 93–99 ) [19, 28with CWD  but was PRNP genotype in the pathogenesis of CWD of elk. We have shown that the biochemical properties of PrPSc from MM132 and LM132 elk are similar to each other and different to PrPSc from LL132 elk. The shorter incubation periods in MM132 compared to LM132 elk may be the result of genotype-dependent differences in the efficiency of propagation of PrPSc moieties present in the inoculum. Further work is needed to develop a better understanding of the underlying mechanisms by which the polymorphisms at codon 132 in elk PRNP influence disease pathogenesis, with a view to improving control of CWD in captive and free-ranging elk populations.This study provides further evidence of the importance of