Most people referred to rapid access chest pain clinics have non-cardiac chest pain, and in those diagnosed with stable coronary heart disease, guidance recommends that first-line treatment is usually medication rather than revascularisation. Consequently, many patients are not reassured they have the correct diagnosis or treatment. A previous trial reported that, in people with non-cardiac chest pain, a brief discussion with a health psychologist before the tests about the meaning of potential results led to people being significantly more reassured. The aim of this pilot was to test study procedures and inform sample size for a future multi-centre trial and to gain initial estimates of effectiveness of the discussion intervention.This was a two-arm pilot randomised controlled trial in outpatient rapid access chest pain clinic in 120 people undergoing investigation for new onset, non-urgent chest pain. Eligible participants were randomised to receive either: a discussion about the meaning and implication of test results, delivered by a nurse before tests in clinic, plus a pre-test pamphlet covering the same information (Discussion arm) or the pre-test pamphlet alone (Pamphlet arm). Main outcome measures were recruitment rate and feasibility for a future multi-centre trial, with an estimate of reassurance in the groups at month 1 and 6 using a 5-item patient-reported scale.Two hundred and seventy people attended rapid access chest pain clinic during recruitment and 120/270 participants (44%) were randomised, 60 to each arm. There was no evidence of a difference between the Discussion and Pamphlet arms in the mean reassurance score at month 1 (34.2 vs 33.7) or at month 6 (35.3 vs 35.9). Patient-reported chest pain and use of heart medications were also similar between the two arms.A larger trial of the discussion intervention in the UK would not be warranted. Patients reported high levels of reassurance which were similar in patients receiving the discussion with a nurse and in those receiving a pamphlet alone.ISRCTN60618114 (assigned 27.05.2011).Current Controlled Trials The online version of this article (doi:10.1186/1471-2261-14-138) contains supplementary material, which is available to authorized users. Chest pain is a common reason why people access health services, with over 400,000 people per year being referred to rapid access chest pain clinics (RACPCs) in England . RACPCs Psychological factors have been targeted for treatment of NCCP. A recent review of randomised controlled trials (RCTs) of psychological interventions for symptomatic management of non-specific chest pain in patients with normal coronary anatomy showed modest to moderate success in terms of reduced chest pain frequency, particularly for those using cognitive behavioural therapy . This suplus a brief pre-test discussion with a health psychologist re-iterating the same information. People receiving the pre-test discussion were more reassured at one month after the test than patients randomised to the pamphlet alone or to the usual care arm (results explained after the test). Only the difference between the discussion and usual care arms reached statistical significance when considering mean reassurance score . The proportion of patients reporting chest pain at one month decreased significantly from baseline in the discussion group and pamphlet-only group, but not in the usual care group. It is possible that a key element in the relative success of the NZ pre-test interventions was the fact that they were delivered before the test. Donkin et al. found that, in people with NCCP, patients’ beliefs before an exercise stress test predicted the amount of reassurance they felt once they had received their negative test result [Petrie et al. (2007) undertook a small RCT in New Zealand (NZ) to assess whether it was possible to improve people’s preparedness for negative results, and so increase reassurance . The stut result .It is not only those who get a negative result in RACPC that may require reassurance; patients who receive a positive result (CHD) may also need reassuring. According to guidance from the National Institute for Health and Care Effectiveness (NICE), initial treatment for people diagnosed with stable CHD should be optimal pharmacotherapy to control symptoms together with effective secondary prevention. Interventions such as percutaneous coronary intervention or coronary artery bypass graft surgery should be restricted to those in whom optimal medical treatment fails to reduce symptoms, or if further testing by non-invasive imaging or by angiography shows left main stem or severe three-vessel disease . This paThe NZ study was limited by small sample size and short duration of follow-up (one month), and it only included people with NCCP. The clinical pathway for patients with chest pain differs between NZ and the UK and the discussion intervention was delivered by a health psychologist, a profession which is not routinely available in NHS outpatient clinics.The aim of this study was to adapt the discussion intervention for delivery in UK RACPCs and conduct a 2-arm pilot RCT comparing discussion (plus pamphlet) versus pamphlet alone. The pre-test pamphlet had already been recommended for use at the study site, as part of the chest pain pathway. The aim of the pilot trial was to test study procedures and gain data to inform the choice of primary outcome measure and the sample size calculation for a future, multi-centre RCT of effectiveness and cost-effectiveness. A preliminary investigation into whether the face-to-face discussion with a nurse may improve patient reassurance was also made. If a simple discussion intervention was found to be effective and cost-effective when delivered by a nurse to people with both NCCP and with a diagnosis of CHD in UK RACPCs, then it could be relatively easily incorporated into the clinical pathway.The NZ discussion intervention and pamphlet were adapted so that they covered both positive and negative test results, and the different treatment options. This was undertaken by an expert reference group with input from service users and RACPC staff. The pamphlet  versus the pamphlet alone in patients attending RACPC with new onset chest pain. The study was conducted at the University Hospital of South Manchester  RACPC. It was approved by North West 9 Research Ethics Committee – Greater Manchester West (reference no. 10/H1014/82) and the R&D Directorate of UHSM NHS Foundation Trust.Patients were sent information about the trial with their RACPC appointment letter and asked on arrival at clinic if they wished to take part. Patients were eligible if they were: attending RACPC for assessment of new-onset, non-urgent chest pain; able to read written English; able to comprehend spoken English; aged 18 years and over and able and willing to give informed consent. Patients were excluded if they: had a previously diagnosed cardiac pathology; had no symptoms of chest pain; were undertaking the exercise test as part of a pre-surgical medical examination; were pregnant; were involved in another research study; had a severe documented psychiatric disorder or had a life-threatening co-morbidity. Eligible patients gave written informed consent.Patients were randomised by a research nurse telephoning a remote randomisation service , University of York, UK). Random permuted blocks (block sizes of four and six) were used to allocate patients in a 1:1 ratio.Patients were told that the study was to compare two different ways of giving information about possible test results and treatments but not what the two formats were (pamphlet and discussion), or that one (the pamphlet) was considered to be the control arm. Staff treating patients in the RACPC appointment were not informed of treatment group allocation.After randomisation, all patients were given the pre-test pamphlet by the research nurse and were allowed sufficient time to read it. Patients allocated to the Discussion arm were then engaged in a brief (5–15 min) discussion with the research nurse. After receiving the pamphlet and discussion (Discussion arm), or the pamphlet alone (Pamphlet arm), patients returned to clinic and underwent assessment and tests as usual. All patients received the usual advice and information from staff during the initial RACPC appointment and any visits for further tests.Assessment in clinic was led by a senior cardiac specialist nurse according to UHSM’s protocol. It included an assessment of risk factors, typicality of symptoms (symptom score 0 to 3), Diamond and Forrester percentage score  and the At the end of the initial appointment patients were either given a diagnosis (CHD or NCCP) or, if a particular test  could not be performed on the day, they were asked to return for further tests. In each case, test results/diagnosis were explained to the patient by a clinic nurse, face-to-face, before leaving clinic. Patients with NCCP were reassured that there was no evidence of coronary disease and were advised to see their GP within the next week for reassessment for other causes of the chest pain. Other possible causes of the chest pain were suggested if the patient asked, but the nurse emphasised that they should go to their GP. If patients were at high risk of developing heart disease, lifestyle-change advice and leaflets were provided to the patient, and their GP was informed that aggressive risk factor management was needed. A CHD diagnosis resulted in the initiation of appropriate treatment: medication with review after 3 months or referral for an angiogram (possibly followed by angioplasty or surgery).As this was a pilot study, primary outcomes included recruitment rate and process, proportion of patients attending RACPC randomised, and reasons for non-participation. The study was powered to give initial estimates of effectiveness using the patient-reported 5-item reassurance questionnaire used in the NZ study  Table 11. OutcomSecondary outcomes included the feasibility/acceptability of the discussion intervention, follow-up rates, questionnaire completion rates, and patient-reported chest pain, heart-related drug use, Hospital Anxiety and Depression Scale (HADS) , Brief IAs a pilot trial, the main aim was to inform the feasibility and sample size of a future multi-centre trial, however a sample size calculation was carried out in order to obtain reasonable estimates of effectiveness within the study. Petrie et al.  observedAll analyses were conducted on an intention to treat basis, including all patients in the arms to which they were randomised, assuming data were available. No imputation was carried out in this pilot analysis. Analyses were conducted in SAS version 9.3 .The reliability and validity of the 5-item reassurance questionnaire was investigated using standard psychometric tests. Internal consistency between items was tested using Cronbach’s alpha, where >0.7 was considered acceptable . The disThe proportion of patients reassured  was sumPatient-reported data on resource use  and health related quality of life (EQ5D) were summarised by intervention arm and timepoint in order to preview future cost-effectiveness analysis issues, such as the accuracy and completeness of the data collection methods and the need to account for censored/missing data in a future trial.120 patients (60/arm) were recruited in 8 months (Oct 2011 to May 2012). Figure Forty-three 35.8%) patients received a diagnosis at their initial clinic visit, whilst 65 54.2%) returned for further tests and got their diagnosis at a second visit. The remaining 12 (10.0%) patients were invited to return for further tests but declined. Cardiac tests performed are presented in Table 5.8% pati.2% returReturn rates for the reassurance questionnaire were good, with 80% of participants returning a questionnaire at month 1 and at month 6. However, the timing of questionnaire return varied considerably, with month 1 questionnaires being completed at a median of 6 weeks (range 4 to 17) and month 6 questionnaires at a median of 28 weeks (range 24 to 41).The validity of the reassurance questionnaire was investigated in this sample as previously it was used for NCCP patients only . AlthougDifferences between the arms in the proportion of patients classed as reassured were not consistent over time . Other questionnaires ranged from 28-100% completed Table . ResultsAt baseline 92/113 (81%) patients reported some chest pain in the previous seven days. At month 1 a smaller proportion of the Discussion arm reported chest pain in the period since they last completed a questionnaire, 24/45 (53%) compared to 29/47 (62%) of the Pamphlet arm. At month 6 these proportions were more similar (59% in the Discussion arm vs 52% in the Pamphlet arm).Data from a 7-day chest pain diary completed at month 1 and month 6 showed a similar reduction in the proportion of patients reporting chest pain over time in both arms . At month 6 the proportions were 40% of the Discussion arm and 29% of the Pamphlet arm.The discussion intervention, assessed through qualitative interviews, was found to be acceptable to patients and staff. This will be reported more fully elsewhere. Change from baseline in treatment satisfaction from the SAQ-UK, showed a trend towards improvement at month 1 for the Discussion arm (median 8 points) with a return to baseline levels by month 6, whilst the Pamphlet arm showed no change at either timepoint. For other secondary outcomes, the intervention arms showed similar trends over time. Tables for secondary outcome data are available in Additional file Completion rates for resource use questions and EQ5D are summarised in Table An aim of the pilot was to provide information regarding the feasibility of conducting a large-scale trial in this patient population. Prior to the pilot, during the development of the interventions, patients received information about the study by letter and were asked to telephone a YTU researcher if they were interested in taking part. The response rate for this strategy was very poor and so it was altered for the pilot RCT. Rather than having actively to telephone a researcher, patients were asked by clinic staff on arrival at RACPC if they wanted to take part. This was much more successful, with an uptake rate for patients attending RACPC to recruitment into the pilot trial at around 40%.We considered that the discussion intervention could improve reassurance in all patients attending RACPC, so patients with both positive (CHD) and negative (NCCP) test results were included in this pilot. Consistent with other studies, the majority of the patients recruited in RACPC received an NCCP diagnosis. Only 14% of patients were diagnosed with CHD so our numbers were too small to investigate effectiveness in the CHD subgroup separately. For example, we wished to investigate how satisfied patients receiving a CHD diagnosis were with their proposed treatment, measured by the treatment satisfaction scale within SAQ-UK, however this was not possible due to low numbers. Future trials would have to be considerably larger to recruit a reasonable number of CHD patients from this setting.Return rates for the reassurance questionnaire were reasonable (80%) but many participants required one or more reminders. Up to three reminders were sent: reminder letters after 3 and 4 weeks with a final telephone reminder after 4 to 5 weeks. This led to some questionnaires being completed much later than planned. An earlier telephone reminder to encourage the return of primary outcome data should be considered for future trials. However, we do not think this altered our main outcomes following a sensitivity analysis including all patients with a questionnaire returned within a two week window either side of month 1.Completion rates for other patient-reported questionnaires were lower . This was partly because patients’ responses to the reassurance questionnaire were collected during the reminder telephone call, but not the other questionnaires. Also, it is possible that the other questionnaires seemed less relevant to patients at month 1 and month 6, particularly if they were no longer experiencing chest pain. For example the BIPQ refers to the patient’s “illness”, whilst SAQ-UK and Guys and St Thomas’ questionnaire refer to chest pain or tightness. For future studies in this area, only the most relevant questionnaires should be included, focussing on those with high compliance. Additional instructions within the questionnaire could be included to improve completion rates.This pilot study included investigations into the effectiveness of the discussion intervention, in terms of providing reassurance to patients about their test results in RACPC. According to a recent review “there is no generally accepted instrument to measure the level of reassurance” . We usedWe found no evidence of a difference in reassurance (both proportion of patients classed as “reassured” or mean score) between the discussion and pamphlet-only arms at month 1 or 6. The NZ study reported a significantly higher proportion of reassured patients in the discussion group (69%) compared to both the pamphlet-only group (40%) and a usual care control (35%) at month 1. Their results using mean reassurance score, however, were more similar to our pilot study; at month 1 the mean score was higher in the discussion group  compared to both the pamphlet-only  and control group , but only the difference between discussion and control groups reached statistical significance. The NZ study was just in patients who received a negative (NCCP) test result, whereas this UK pilot also included patients diagnosed with CHD. Our sensitivity analyses on the NCCP subgroup showed a possible trend for higher reassurance in the Discussion arm  and interaction with different staff for the different tests. It is possible that the usual care advice/information and explanation of test results in the UK RACPC was of a standard such that no additional benefit could be gained from a pre-test discussion. The discussion intervention was delivered by a research nurse who was not trained in psychological techniques and this may have contributed to the ineffectiveness of the discussion intervention. The target is to see UK patients in RACPC within 2 weeks of their GP visit, although this was not measured in this study, whereas patients had to wait longer for their clinic appointment in the NZ study (median 6 weeks). The NZ patients had more time to build up negative beliefs, which can influence reassurance in people with NCCP .A limitation to this pilot was the absence of a third “no pre-test information” control arm. This was because Greater Manchester, where the study was conducted, had recommended that a Petrie-style pre-test pamphlet should be usual care in RACPC. As a result, we have no information on whether a pre-test pamphlet alone is better than no pre-test information in a UK setting. Since RACPCs are likely to send an information pamphlet with the appointment letter anyway, for example explaining what clothes to wear and what tests the patients may have in RACPC, it may be that RACPCs in regions other than Greater Manchester should consider including information regarding possible test results and ensuing treatments.An additional face-to-face discussion with a nurse, which re-iterated information given in a pre-test pamphlet, did not significantly improve reassurance in patients. Whilst there was a possible trend in the NCCP subgroup for improved reassurance with a discussion, the difference was not considered to be clinically important and does not warrant a larger trial of the discussion intervention in UK RACPCs.Pretest pamphlet. All patients in the study received this pre-test pamphlet  at the start of their RACPC appointment. (PDF 469 KB)Additional file 1:Responses to 5 reassurance questions.doc. Plots of patients’ responses to the five questions (Questions 1 to 5) in the reassurance questionnaire at baseline (Questions 1 and 2 only), post-clinic, month 1 and month 6. Answers on a 0–10 scale. (DOCX 65 KB)Additional file 2:Chest pain diary data. Table presenting patient-reported chest pain in a 7-day period at month 1 and month 6, collected from chest pain diaries. (DOCX 15 KB)Additional file 3:Secondary outcome data_HADS_BIPQ_SAQ-UK_Guys and St Thomas. Three tables: (i) Change from baseline, at month 1 and month 6, for HADS, BIPQ and SAQ-UK; (ii) Individual item scores from the Brief Illness Perception Questionnaire at baseline, month 1 and month 6 and (iii) Guys and St Thomas’ chest pain score at baseline, month 1 and month 6. (DOCX 27 KB)Additional file 4:Reassurance Question 3. Patients’ response to Question 3 of the Reassurance Questionnaire (How reassured were you by the test?) for those categorised as “reassured” and “not reassured” according to the method of Petrie et al., 2007. (DOCX 15 KB)Additional file 5:NCCP subgroup results. Proportion of patients reassured and reassurance score at month 1 and month 6 for NCCP patients only. (DOCX 13 KB)Additional file 6:


Patient specific therapy is emerging as an important possibility for many cancer patients. However, to identify such therapies it is essential to determine the genomic and transcriptional alterations present in one tumor relative to control samples. This presents a challenge since use of a single sample precludes many standard statistical analysis techniques. We reasoned that one means of addressing this issue is by comparing transcriptional changes in one tumor with those observed in a large cohort of patients analyzed by The Cancer Genome Atlas (TCGA). To test this directly, we devised a bioinformatics pipeline to identify differentially expressed genes in tumors resected from patients suffering from the most common malignant adult brain tumor, glioblastoma (GBM). We performed RNA sequencing on tumors from individual GBM patients and filtered the results through the TCGA database in order to identify possible gene networks that are overrepresented in GBM samples relative to controls. Importantly, we demonstrate that hypergeometric-based analysis of gene pairs identifies gene networks that validate experimentally. These studies identify a putative workflow for uncovering differentially expressed patient specific genes and gene networks for GBM and other cancers. Glioblastoma multiforme (GBM) is the most common malignant adult brain tumor, comprising 15.6% of all central nervous system tumors Recent developments in oncogenomics point to a highly heterogeneous genomic landscape in GBM One possibility to increase the available sample size is to utilize transcriptome data in publicly available databases as a reference. For instance, The Cancer Genome Atlas (TCGA) has performed gene expression microarray analysis in over 400 GBM patients examining them using two different platforms (Agilent and Affymetrix). Thus, it is possible to use these data as a reference set, to compare the RNA sequencing results from a single tumor sample and identify differentially expressed genes and gene networks. Utilizing a novel bioinformatics pipeline we were able to perform a patient-specific analysis of the GBM transcriptome based on the overlap between our RNA-Seq data and the TCGA GBM data. This approach allowed us to identify and filter out potential artifacts due to low sample size.In this report we identified a patient specific list of differentially expressed genes (DEGs), which can be used as input for multiple types of analyses including gene co-expression networking. Genes that co-express across multiple samples are often implicated in similar functions We performed whole transcriptome sequencing on two GBM tumors (GBM17 and GBM31) and two control samples from epileptic patients using the Illumina HiSeq sequencing platform. Preliminary screening was performed in FastQC (FASTQC 2012) and BLAST After read trimming, samples GBM17, GBM31, Control16, and Control34 had 87.18%, 78.56%, 86.79%, and 92.31%, reads mapped, respectively. For each sample, we also assessed the distribution of genes that mapped to the human genome in order to gauge the quality of the experiment. GBM17, GBM31, and Control 34 yielded approximately 15,000 genes with nearly 100% transcript coverage in the reference human genome. Control16 had only 8,085 mapped genes. Only the common 8,085 genes were used in the 4 differential expression analyses that followed.Four differential expression analysis tools, rather than one single tool, were applied to the data and the results from all four tools were compared. This yielded results that are relatively robust to both varying tool approaches to sequencing depth normalization and statistical tests employed, as well as to inherent variability in the RNA-Seq data. The four methods used were: baySeq 1.10.0 https://tcga-data.nci.nih.gov/tcga/). The first dataset contained tumor specific expression data from 433 glioblastoma patients (P1-P433) and the second dataset contained brain tissue expression data from 10 epileptic patients. All samples were analyzed with both the AgilentG4502A Microarray Platform and the Affymetrix HG-U133 Microarray Platform. The Level 3 (processed) data for these samples were downloaded and further analyzed. The data processing and quality control were performed by The Broad Institute's TCGA workgroup. The AgilentG4502A Level 3 data consisted of the lowess normalized log2 expression values Two expression datasets were collected from The Cancer Genome Atlas (TCGA) in 07/02/2014  genes between glioblastoma patients and epileptic controls were identified by using the A hypergeometric-based test was used to assess the significance of co-expression across samples between two genes of a gene pair. The rationale behind using the hypergeometric test was that if 2 genes had any biological and/or functional association, they would be found co-expressed in a higher number of samples than expected by chance. We tested under the null hypothesis that the property of a gene to be DE in one sample is independent of the property of another gene to be DE in the same sample. The p-value was derived from the hypergeometric function below where f: total number of patients, d: number of patients for which Gene1 is DE, g: number of patients for which Gene2 is DE, n: number of patients for which both Gene1 and Gene2 are DE found in .Networks from the selected gene pairs were created using the open source Cytoscape 3.1.0 as described in We performed RNA sequencing on 2 GBM tumors (GBM17 and GBM31) and 2 epilepsy control tissues (Control16 and Control34) using the Illumina HiSeq platform. Focusing on patient specific transcriptionally expressed genes, we compared the transcriptome of each tumor individually with the two controls. In order to ameliorate the increased uncertainty of the different algorithms due to low sample size not upregulated in one platform and downregulated in another platform. Of these 5,200 DE genes, we found that 585 are DE in GBM17 and 514 are DE in GBM31 (In order to assess whether these results represent the phenotype of interest (GBM) or individual sample variability, we compared our RNA sequencing results to results from a greater number of samples, namely, the TCGA microarray dataset. Previous studies have shown that RNA-Seq results can be compared to those derived from microarrays in GBM31 .. In S2 As acquired drug resistance is one of the main reasons for the ineffectiveness of current glioblastoma treatment, the identification and simultaneous inhibition of multiple therapeutic targets is essential for identifying effective combination therapies. However, the large genetic variation among glioblastoma tumors necessitates a more patient-specific approach when identifying potential therapeutic targets. For this, we tried to create gene networks based only on genes that were DE in that specific RNA-Seq sample. After determining the DE genes for each sample, and ‘filtering’ or selecting those that are also DE in the TCGA data, we searched for any significant co-expression among these patient-specific DE genes in the TCGA data. Our hypothesis was that if there were any functional association between gene pairs, then this association could be observed based upon their co-expression in the TCGA population. We utilized two methods to identify co-expression. First, the Pearson Correlation Coefficient (PCC) was used to determine if the expression level of one gene could be indicative of the expression level of the second gene. Next, a hypergeometric test was used to calculate the probability of a pair of genes being both DE in a specific number of patients by chance. Gene pairs with a low p-value indicate the tendency of these genes to be DE together in a higher number of patient samples than we would expect by chance. For every gene pair, we plotted both its PCC and its hypergeometric probability in the TCGA population .. Our re10 scale . These gene pairs were selected for each patient sample separately and were imported to Cytoscape As our aim was to define patient-specific and glioblastoma-relevant gene networks, we used the most statistically significant gene pairs in each RNA-Seq sample in order to reconstruct the networks. Our most significant gene pairs  consisteSeveral studies suggest that epigenetic and signaling pathways control GBM progression Combination therapies that effectively disrupt multiple pathways are likely to reduce GBM recurrence. However, identifying these therapies is contingent upon uncovering patient-specific genomic and transcriptomic alterations. One major issue is how to generate robust analytical results from gene expression data when sample size is low. To circumvent this problem, we elected to employ multiple different RNA-Seq algorithms and compare the results common to most algorithms with results based on the transcriptional profile of over 400 GBM tumors analyzed by TCGA. With this approach, we identified genes that not only were differentially expressed in our patient specific sample but also were differentially expressed in a significant number of TCGA patient samples. These true positive genes were subsequently used to create gene co-expression networks to identify any potential functional similarity. By using a hypergeometric test in addition to the PCC, we identified experimentally validated gene-gene interactions.One gene network that has been experimentally verified in multiple biological contexts is the highly conserved MCM (Mini-Chromosome Maintenance) network containing the DNA replication licensing factors MCM2, MCM3, and MCM7. We identified this network as overexpressed in GBM sample 31. With the hypergeometric test, we detected a high probability of the MCM subunits to be overexpressed in the same patient samples in the TCGA dataset and were able to distinguish them from other gene pairs that only showed a high correlation coefficient (but little co-occurrence within patients). Importantly, the MCM pathway has been implicated in multiple cancers including GBM The stringency of our filtering of the DE genes from any given patient, however, is likely to also yield false negatives. For instance, we chose to only explore DE genes that were detected in at least 3 out of 4 RNA-Seq algorithms, which may have excluded some true positives. It may be informative to use other statistical methods in addition to the hypergeometric test to determine whether there are alternative approaches that would also yield results that are enriched for experimentally verified gene networks. In addition any proposed pipeline will involve subjective choices of thresholds and criteria for significance. We have made reasonable choices, but it is possible that moving to nonparametric and permutation-based results to establish a more systematic approach to threshold selection could lead to pipeline improvements. Nonetheless, our studies identify a robust method for identifying patient-specific gene networks, which can inform the design of effective combination therapies.We implemented this method to identify potential targets for combination therapies involving epigenetic pathways and the Notch, SHH, and WNT pathways. Our recent studies and those from other laboratories suggest that epigenetic pathways contain attractive new therapeutic targets in GBM S1 FigOverlap of DE genes calculated by 4 RNAseq Algorithms . We analyzed genes that were shown to be DE by at least 3 out of the 4 algorithms (* symbol). We then filtered for genes that were shown to be DE by both Microarray Platforms in the TCGA GBM cohort and also were shown to have a |fold change| >1.2. The Pearson Correlation Coefficient and the p-value of the hypergeometric test were then plotted for every gene pair.(TIF)Click here for additional data file.S2 FigFold Change dependent overlap of DE genes calculated by 4 RNAseq Algorithms and the TCGA Database. The fold change threshold did not change the number of overlapped genes between the RNAseq and the TCGA analysis, when the consensus of 3+ RNAseq algorithms was used.(TIFF)Click here for additional data file.S3 FigComparison between two Correlation Coefficients. The Pearson and the Spearman Correlation Coefficients were calculated for every gene pair. In both patients gene pairs with high Pearson Correlation Coefficient show also high values for the Spearman Correlation Coefficient.(TIF)Click here for additional data file.S4 FigPipeline for calculating the Hypergeometric Distribution and the Pearson Correlation Coefficient for every gene pair.(TIFF)Click here for additional data file.S1 Table10 scale.Gene pairs consisting of the ones that had a PCC above 0.7 and were in the lowest 40% of the range of the hypergeometric log(XLSX)Click here for additional data file.S2 Table10 scale values.Gene pairs with a PCC above 0.7 and the highest hypergeometric log(XLSX)Click here for additional data file.S3 TableGene list containing 464 genes are either epigenetic modulators, or genes implicated in the Notch, Shh and Wnt Pathways (though KEGG Pathways).(XLSX)Click here for additional data file.S1 FilePerl scripts used in the pipeline.(TXT)Click here for additional data file.


Drosophila sperm are highly polarized cells—on one side is a nearly 2 mm long flagellar tail that comprises most of the cell, while on the other is the sperm head, which carries the gamete's genetic information. The polarization of the sperm cells commences after meiosis is complete and the 64-cell spermatid cyst begins the process of differentiation. The spermatid nuclei cluster to one side of the cyst, while the flagellar axonemes grows from the other. The elongating spermatid bundles are also polarized with respect to the main axis of the testis; the sperm heads are always oriented basally, while the growing tails extend apically. This orientation within the testes is important for transferring the mature sperm into the seminal vesicles. We show here that orienting cyst polarization with respect to the main axis of the testis depends upon atypical Protein Kinase C (aPKC), a factor implicated in polarity decisions in many different biological contexts. When apkc activity is compromised in the male germline, the direction of cyst polarization within this organ is randomized. Significantly, the mechanisms used to spatially restrict apkc activity to the apical side of the spermatid cyst are different from the canonical cross-regulatory interactions between this kinase and other cell polarity proteins that normally orchestrate polarization. We show that the asymmetric accumulation of aPKC protein in the cyst depends on an mRNA localization pathway that is regulated by the Drosophila CPEB protein Orb2. orb2 is required to properly localize and activate the translation of apkc mRNAs in polarizing spermatid cysts. We also show that orb2 functions not only in orienting cyst polarization with respect to the apical-basal axis of the testis, but also in the process of polarization itself. One of the orb2 targets in this process is its own mRNA. Moreover, the proper execution of this orb2 autoregulatory pathway depends upon apkc.Mature  orb2. orb2 is required to asymmetrically localize and activate the translation of apkc mRNAs during spermatid differentiation. In addition to correctly orienting the direction of cyst polarization, orb2 is required for the process of polarization itself. One of the orb2 regulatory targets in this process is its own mRNA, and this autoregulatory activity depends, in turn, upon apkc.After completion of meiosis, the 64 cells in the spermatid cyst begin differentiating into sperm. Sperm are highly polarized cells and a critical step in their differentiation is spermatid cyst polarization. Spermatids are also polarized within the testis, with the heads of the elongating spermatids located basally, while the tails extend apically. We show that aPKC accumulates preferentially on the apical side of the cyst during polarization and is required to correctly orient cyst polarization with respect to the apical-basal axis of the testis. Unexpectedly, aPKC activity is spatially restricted by a mechanism that depends upon the CPEB family translational regulator  C. elegans embryo C.elegans embryo. Moreover, as in C.elegans, antagonistic interactions between aPKC-PAR family proteins are critical for establishing and propagate cell asymmetry in many systems . The classic model for polarity determination by the aPKC-PAR machinery is the establishment of the anterior-posterior axis in the D. melanogaster sperm. At one end of the mature sperm cell is the sperm head, which contains the highly condensed haploid genome encased in a multilayer membrane. The rest of the cell is the nearly 2 mm long flagellar axoneme tail, which is connected to the head by a centrosome-derived structure called the basal body. The formation of this polarized cell commences after meiosis is completed and the 64 interconnected spermatids begin the process of differentiation , much of this protein is likely to be somatically derived. In whole mounts of wild type testes probed with aPKC antibody, only a low level of unlocalized protein is detected in spermatocytes before and during the first and second meiotic divisions , arrow. Drosophila Par3), Discs large (Dlg) and Par-1 during spermatogenesis. As shown in In other biological contexts, proteins that function together with aPKC in cell polarization often exhibit similar or reciprocal localization patterns. To identify other potential players, we examined the expression of other classic polarity regulators Bazooka  of cyst polarization. To explore this possibility we analyzed the effects of ogenesis . apkck06apkc activity is compromised, spermatid nuclei clusters appear at the apical side of the testes , MTD, that drives higher levels of UAS dependent expression in germline cells in most stages of spermatogenesis UAS-apkc RNAi lines, UAS-apkc::34332 and apkc:35140, that express double strand RNA, dsRNA-HMS01320 and dsRNA-GL00007, targeting two different exon regions that are common for all apkc mRNA species . This defect suggests that apkc activity might be needed to sustain the elongation of the flagellar axoneme.Orientation defects like those observed in the hypomorphic mutants were also seen when nockdown . For exatid cyst . Moreoveid cysts . In addiet al.Since several of the proteins that usually collaborate with aPKC do not seem to be expressed in differentiating spermatids, other mechanisms are likely important for localizing aPKC asymmetrically and facilitating its function in correctly orienting cyst polarization. One such mechanism would be mRNA localization. Support for this possibility comes from the studies of Barreau apkc mRNA is similarly localized in differentiating spermatids, we generated a set of oligo probes specific to the large exon that is common to all apkc mRNAs  and, together with an extensive set of alternatively spliced exons and UTRs, it is predicted to generate more than 10 different mRNAs  for RT-PCR , has an unusually long 3′ UTR that is not found in any of the other predicted mRNA species.The nt mRNAs . To idenr RT-PCR . These ecis-acting elements in the 3′ UTR, we generated in situ probes specific for apkc-RA mRNA species. The apkc-RA expression pattern differs substantially from that of the “bulk” apkc mRNAs that hybridizes to the large common exon probe. Unlike “bulk” apkc mRNA, apkc-RA can not be detected in the pre-meiotic stages, while only low levels are present in the meiotic cysts  in their 3′ UTRs. CPE motifs are recognized by a conserved family of RNA binding proteins, CPEBs, which in flies are known to function both in mRNA localization and translational regulation apkc-RA 3′ UTR indicates that it has three canonical CPE motifs , which share a different UTR sequence, have a single CPE sequence. Thus, an intriguing idea is that a fly CPEB protein binds to the RA mRNA species and perhaps to one or more of these other apkc mRNAs, facilitates their localization to the tip of the elongating sperm tails and controls their translation. Flies have two CPEB genes, orb and orb2, and both are expressed in testes. Of these, orb is not likely to have either of these functions as its message is not translated until after spermatid elongation is complete orb2, on the other hand, would be a plausible candidate for the regulatory factor. It is required at multiple steps during spermatogenesis including spermatid differentiation. We've found that one of its differentiation functions is to control the translation of post-meiotically expressed mRNAs like orb that have CPE motifs in their 3′ UTRs. Moreover, like these post-meiotic mRNAs, Orb2 protein is distributed in a comet pattern in elongating spermatids orb2 might regulate the localization and/or translation of apkc-RA and perhaps other CPE containing apkc mRNAs species in the testis. First, we found that orb2 is required for the apical accumulation of aPKC in embryonic neuroblasts during asymmetric cell division apkc-RA RNA can pull down Orb2 protein from adult fly brain extracts apkc-RA mRNA species as it has a post-meiotic expression pattern.Several of the post-meiotic mRNAs identified by Barreau E motifs . Severalapkc mRNAs (com-GS in RA 3′ UTR (RA-GS) probe, but not the common 3′ UTR (com-GS) probe  probe , S2. We  element , S2. Thempetitor . In contapkc-RA mRNA (PF-PR) from testis extracts, while β-galactosidase antibodies did not . While Orb2 protein and apkc-RA mRNA disappear as soon as elongation is complete, apkc mRNA can still be detected with the common exon probe during the individualization phase (data not shown).If on probe   side of the the case .apkc mRNAs in elongating spermatid cysts and binds directly to the 3′ UTR to an apkc mRNA species that is specifically expressed at this stage of spermatogenesis. If this association is important for apkc activity during spermatid differentiation, orb2 should also be required for correctly polarizing the 64-cell cysts. To test this prediction we examined spermatid cyst polarization in two different orb2 mutants, 36orb2 and ΔQorb2. 36orb2 is a null allele that lacks the entire Orb2 protein coding sequence. Meiosis is blocked in 36orb2 and 16-cell cysts, which have duplicated their DNA but not undergone the 1st meiotic division, accumulate in the mutant testes. These cysts ultimately exit meiosis and then attempt but fail to differentiate into mature sperm ΔQorb2, is a hypomorph. It has an in frame deletion that removes a short poly-glutamine domain in the N-terminal half of the protein. While the sequence of the Orb2 protein is altered, its level of expression remains the same ΔQorb2, and ΔQorb2 males produce some functional sperm and are fertile. However, in a subset of the spermatid cysts there are abnormalities in spermatid differentiation, including polarization defects  and phalloidin staining of actin . The IC consists of 64 aligned actin cones. After elongation is complete, the IC assembles using the condensed spermatid nuclei as a scaffold and then travels along the flagellar axonemes separating syncytial spermatids from each other. The ΔQorb2 testes in ΔQorb2 testes, ICs moving in opposite directions were sometimes observed  and otherwise seemingly normal polarization. In contrast, as illustrated by the disorganized distribution of the Boule translation factor and spermatid nuclei, the process of cyst polarization itself seems to be disrupted in 36orb2. In wild type, Boule accumulates in a comet pattern near the tip of the elongating flagellar tails just like Orb2  or 36orb2 . The pattern of aPKC protein accumulation in ΔQorb2 parallels that of apkc-RA mRNA: aPKC stripes are absent in flagellar axonemes that are polarized in the wrong orientation .We also examined apkc or any other mRNA at the tips of the axonemes as the sperm tails elongate, there would have to be a continuous source of Orb2 in the comet head. One way to maintain high levels of Orb2 at the tip of the elongating axonemes would be a positive autoregulatory loop in which Orb2 helps direct the localization and translation of its own mRNA. An orb2 autoregulatory activity could also help promote the initial polarization of the spermatid cyst. Moreover, there is precedence for CPEB proteins having autoregulatory activity. In the female germline, a two step positive autoregulatory mechanism, in which Orb mediates the localization and translation of orb mRNA, is known to be important in targeting Orb to the oocyte when it is first specified and then ensuring that Orb continues to accumulate within oocyte as it develops orb2 mRNAs have consensus CPE motifs in their 3′ UTRs . The apparent failure of orb2 autoregulation in ΔQorb2 cysts that are incorrectly polarized could also explain why apkc mRNAs are not localized in the comet pattern and why there are no aPKC protein stripes.Further evidence that rm tails . In contorb2-apkc genetic interactions is that the functioning of the orb2 autoregulatory loop at this stage of spermatogenesis could be intimately linked to apkc activity. To test this idea, we examined Orb2 protein expression in elongating spermatid cysts in testes from the ex55apkc allele and from the MTD/UAS-apkc:35140 RNAi knockdown. There were no obvious effects on Orb2 expression in the hypomorphic allele ex55apkc in either incorrectly or correctly oriented elongating spermatid cysts. On the other hand, we found that the accumulation of Orb2 protein in the characteristic comet pattern at the tips of the elongating flagellar axonemes is disrupted when apkc is knockdown using the MTD/UAS-apkc:35140 transgene combination  in which it resides is invariant: the nuclei cluster on the basal side of the cyst, while basal bodies localize on the opposite side of the cyst so that the axonemes can elongate apically towards the stem cell region of the testis. The factors involved in polarizing the cyst and in correctly orienting the polarized cyst within the testis are largely unknown. Here we have identified two genes that function to orient cyst polarization with respect to the apical-basal axis of the testis, orb2 but is also likely to be relevant to properly orienting polarization with respect to the main axis of the testis is most clearly illustrated by the phenotypes in the hypomorphic allele, ΔQorb2. All ΔQorb2 cysts that polarize in the incorrect orientation share a common set of defects. First, instead of being localized in the characteristic comet pattern, apkc-RA and “bulk” apkc mRNAs are spread uniformly though the cyst. Second, the aPKC protein stripes at the ends of the growing flagellar axonemes are absent. Third, while Orb2 protein and orb2 mRNA can be detected in these cysts, neither is localized. This latter finding would provide an explanation for the defects in both apkc mRNA localization and the expression of aPKC protein. By contrast, most but not all of the ΔQorb2 cysts that elongate in the correct direction resemble wild type: apkc and orb2 mRNAs and Orb2 protein are localized in the characteristic comet pattern, with aPKC stripes at the ends of the flagellar axonemes.During the first steps of polarization all of the spermatid nuclei in the cyst congregate on the basal side, while aPKC protein accumulates in a series of puncta on the other, apical side, near the ends of the nascent flagellar axonemes. As elongation progresses, the aPKC puncta transform into a series of short stripes at the ends of the elongating axonemes. That this spatially restricted pattern of aPKC accumulation is not only mediated by orb2 regulatory target is the apkc-RA mRNA. Although apkc mRNAs can be detected with a common exon probe in the adult male germline in all but the last stages of spermatogenesis, the apkc-RA mRNA is unusual in that it is expressed post-meiotically, and like other post-meiotic transcripts, it accumulates in a comet pattern in elongating spermatid cysts. This mRNA is transcribed from one of the four apkc promoters, and differs from the 12 other predicted apkc mRNA species in that it has a unique 3′ UTR. The RA 3′ UTR contain 3 CPE motifs and we've found that Orb2 binds to it both in vitro and in vivo. As is true for other mRNA targets of CPEB proteins, it is likely that orb2 promotes the localized production of aPKC by directly activating the translation of the apkc-RA mRNAs in the comet head. Consistent with this idea, the stripes of aPKC at the ends of the elongating flagellar axonemes are localized on the distal  side of the Orb2 protein/apkc-RA mRNA comet head. Several other apkc mRNA species share a different UTR sequence that also contains CPE motifs. While we haven't examined the expression of the mRNAs containing this specific UTR sequence, it is possible that one or more is expressed at this stage of spermatogenesis. Since the apkc mRNAs detected with the common exon probe localize in a comet pattern that is similar to apkc-RA and this localization is disrupted in orb2 mutants, it would appear that if other apkc mRNA species are expressed at this stage of spermatogenesis they could also be orb2 regulatory targets.One likely orb2 and apkc seems to be reciprocal. The first suggestion of cross-regulation came from the synergistic genetic interactions seen in trans-heterozygous combinations between orb2 and apkc mutants. Whereas polarization defects are rarely observed in the testes of males heterozygous for the hypomorphic ex48apkc or ex55apkc alleles, when they are combined in trans with the hypomorphic ΔQorb2 allele the frequency of testes with misoriented spermatid cysts increases by more than 10-fold. Trans-heterozygous genetic interactions between weak hypomorphic alleles are somewhat unusual, and raise the possibility that the two interacting genes are functionally interdependent. Consistent with a cross-regulatory connection, Orb2 is not localized in its characteristic comet pattern in elongating flagellar axonemes when apkc activity is knocked down in the MTD/UAS-apkc:35140 combination. Instead it is uniformly distributed in the elongating axonomes. This finding indicates that the localized accumulation of Orb2 protein in differentiating spermatid cysts depends upon apkc activity. Since Orb2 binds to its own mRNA and appears to be required for both the localization and translation of this mRNA during spermatid cyst differentiation, a plausible hypothesis is that apkc is a component of the orb2 positive autoregulatory loop. While apkc need not function directly, it is interesting to note that Orb2 has three (high stringency) predicted aPKC phosphorylation sites  orb2 mRNA, and in turn the localization and translation of apkc mRNAs, by phosphorylating Orb2 protein. In principle, this reciprocal regulatory relationship could help trigger the choice of orientation at the start of polarization and then serve to reinforce this choice.Significantly, the regulatory relationship between orb2 localizing and regulating the translation of apkc mRNAs, many important questions remain unanswered. One is whether apkc is required only for choosing the direction of cyst polarization within the testis, or if it also has a role in the process of polarization itself. Neither the apkc mutants nor the knockdowns are useful in answering this question as they certainly retain apkc activity. On the other hand, it seems likely that apkc is needed during the formation of the sperm tails since the elongating tails in the strongest RNAi knockdowns are considerably shorter than in wild type. As Orb2 protein accumulation is perturbed in this RNAi knockdown, one of the apkc functions during this phase of spermatogenesis is to maintain high levels of localized Orb2 protein.While our finding would be consistent with a model in which aPKC activity is spatially restricted by a mechanism that depends upon orb2. With the caveat that the 36orb2 cysts might have structural abnormalities arising from the failure to undergo meiosis, the phenotypes of this mutant argue that orb2 is required for polarization per se. If the only apkc function in this process is orienting the direction of polarization, then orb2 would have to have regulatory targets that control the actual process of polarization. In fact, there are several plausible candidates. Studies by Fabian et. al.2) and components of the exocyst complex are required for cyst polarization. The exocyst complex also mediates plasma membrane addition during spermatid elongation and localizes around the tip of the growing sperm tails. mRNAs encoding 4 of the 8 exocyst complex subunits  have CPE sequences in their 3′ UTRs, and their localization and/or translation could be regulated by orb2. Another possible orb2 regulatory target in cyst polarization is cdc42. This small membrane anchored GTPase directs exocyst complex localization during ciliogenesis in kidney epithelial cells, interacting directly with Sec10 orb2. While we have not tested the effects of reducing cdc42 activity, we found that a subset of the spermatid cysts are polarized in the incorrect direction in par6 heterozygous males (data not shown).A similar question can be asked about orb2 has other mRNA targets in cyst polarization would also be consistent with the effects of orb2 mutations on asymmetric cell division in the embryo. We previously found that the accumulation of aPKC along the apical cortex of dividing neuroblasts depends upon orb2orb2 asymmetric cell division phenotypes is a failure to properly orient the mitotic spindle. Since spindle orientation in dividing neuroblasts is thought to be independent of apkcorb2. In addition to cdc42, another potential orb2 target that has functions in spindle orientation would be the mRNA encoding Inscuteable (insc). In fact, Hughes et. al.insc mRNA is important for Insc function in neuroblast cell division, and like apkc-RA mRNA it has CPE sequences in its 3′ UTR. Thus, a plausible inference from their studies is that Orb2 may help localize insc mRNA to the apical side of the neuroblast, and then activate its on site translation. , the underlying polarity of the cell, cyst, egg, embryo or organ is pre-defined by the activity of an upstream and seemingly distinct polarizing pathway, most typically involving the aPKC/PAR machinery. The mRNAs encoding the cell fate or axis determinants function primarily in the elaboration or execution of this polarity decision, and not in the initial definition of polarity orb2 seems to be intimately involved in the upstream polarity pathway, helping the aPKC/PAR machinery define and then maintain the underlying polarity. In fact, in the process of correctly orienting spermatid cyst polarization the functional interdependence of orb2 and apkc would seem to be mechanistically equivalent to the cross-regulatory interactions that underpin “classical” polarization by the aPKC/PAR machinery.In this context, it is worth noting that the role of Other unresolved questions include the identity of the signals that initiate and orient cyst polarization relative to the testis itself. The latter, cyst orientation, most probably depends upon an external signal and the most likely source would be the two somatic support cells, the head and tail cyst cells, which encase the spermatid cyst . These tapkc mutant alleles k06403, apkcex55apkc, ex48apkc and par1-GFP are kind gifts from Dr. Elizabeth Gavis, Dr. Yu-Chiun Wang and Dr. Eric Wieschaus at Princeton University. apkc RNAi lines are obtained from Bloomington Drosophila Stock Center (stock # 34332 and 35140), targeting two different exons common to all apkc mRNAs (sequence: CTGGAGAAGACGATTCGTATA and CAAGCTGTTGGTGCACAAGAA) orb2 mutant allele 36orb2 was generated in the lab ΔQorb2 is a gift from Dr. Barry Dickson from IMBA, Austria.Testes were dissected and fixed/stained following standard whole mount staining procedures Whole mount staining was performed as in in situ hybridization was performed as described in apkc and orb2 were synthesized by Biosearch Technologies (www.biosearchtech.com) or synthesized in Tyagi lab. Forty non-overlapping 17 bp probes targeted at orb2 mRNA sequence from cctggacgatcagatgt to atatgttatttaatctcac were synthesized and labeled with Quasar 670 and used at 1∶100 dilution. For combined in situ hybridization-antibody staining experiment, the in situ hybridization was performed first, followed by a sample re-fix and then standard whole mount antibody staining.Fluorescence Figure S1par1-GFP testes with monoclonal antibodies against Baz , Dlg  or GFP . While Baz, Dlg and Par1-GFP proteins are observed in somatic cyst cells that encase the developing germline cysts , there appears to be only limited expression in the germline cells, especially at stages when aPKC is highly expressed. Arrows in B, D and F indicate the tips of the elongating spermatid cysts where aPKC protein normally accumulate. Note that Baz. Dlg and Par1-GFP are not detected in this region of the cyst. All images are orientated with apical side of the testis to the left and basal to the right.Baz, Dlg and Par1-GFP expression during spermatogenesis. Whole mount staining of wild type or (TIF)Click here for additional data file.Figure S2apkc-RA expression during spermatid elongation. A) apkc-RA is not detected in the mitotic or meiotic spermatocyte stages (SMC). It first spears at low levels in the spermatids that just completed meiosis (early SPT), while its levels gradually increase once the spermatids begin to differentiate (late SPT). In the merged panel on the far right: green, apkc-RA mRNA; red, Orb2. B) At early stages of spermatid elongation as the cyst polarizes, apkc-RA accumulates at higher levels at the apical (with respect to the testis) side of the cyst (arrow) while the spermatid nuclei cluster at the other, basal side of the cyst (arrowhead). Insert in B is a zoom-in view of the boxed region. In the merged panel: green, apkc-RA; blue, DNA. Scale bar: 50 λm.(TIF)Click here for additional data file.Figure S3apkc-RA 3′ UTR in vitro. Lanes in left half: Recombinant Orb2-RRM (com-GS 3′ UTR probe (Probe C) or the CPE containing apkc-RA 3′ UTR probe (Probe A). The C probe is derived from a common 3′ UTR Click here for additional data file.Text S1Supplemental (PDF)Click here for additional data file.Text S2apkc and orb2 mRNA 3′UTRs, and of the probes/competitors used in EMSAs.Sequences of the (PDF)Click here for additional data file.


Capsid gene sequencing showed substantial sequence variation among NoV GII.4 variant Den Haag 2006b strains from one single institution during a nine months’ period. This method proved useful to understand the local epidemiology and, when used promptly, has the potential to make infection control measures more targeted.Norovirus (NoV) is a leading cause of gastroenteritis and genotype II.4 (GII.4) is responsible for the majority of nosocomial NoV infections. Our objective was to examine whether sequencing of the capsid gene might be a useful tool for the hospital outbreak investigation to define possible transmission routes. All NoV positive samples submitted from one university hospital during the 2007/8 season were selected. Genotyping of selected samples by partial polymerase gene sequencing had shown that the majority belonged to the GII.4 variant Den Haag 2006b and had identical polymerase sequences. Sequences of the capsid gene (1412 nucleotides) were obtained from the first available sample from 55 patients. From six immunocompromised patients with persistent infections a second sample was also included. As a control for a point-source outbreak, five samples from a foodborne outbreak caused by the same GII.4 variant were analyzed. Forty-seven of the inpatients (85%) were infected with the GII.4 variant Den Haag 2006b. Phylogenetic analysis of the Den Haag 2006b sequences identified four distinct outbreaks in different departments and a fifth outbreak with possible inter-department spread. In addition, a more heterogeneous cluster with evidence of repeated introductions from the community, but also possible inter-department spread was observed. In all six patients with paired sequences, evidence for  Caliciviridae. As other RNA-viruses, it is characterized by a high mutation rate, leading to the rapid emergence of genetically diverse strains. At least five genogroups can be distinguished and subdivided into approximately 30 genotypes [Norovirus (NoV) is a leading cause of acute gastroenteritis worldwide, causing both outbreaks and sporadic cases –6. It isenotypes , 7. The enotypes , 9 and tenotypes –13.In areas with a temperate climate, NoV infections occur mainly during the winter season. Outbreaks occur frequently in semi-closed or closed environments such as hospitals, schools and cruise ships  and can in vivo evolution of the virus, leading to the co-existence of quasispecies [Although symptomatic NoV infection in immunocompetent patients is usually limited to a few days, NoV can cause persistent infections in immunosuppressed patients accompanied by substantial ispecies –16.For the detection and partial sequencing of NoV RNA, primers targeting the polymerase gene –19, the Our objective was to investigate the possible transmission routes of GII.4 infections in one hospital during a nine months’ period by sequencing of the capsid gene. The aim was to assess if this method can be used to differentiate sustained nosocomial transmission from repeated introductions of different strains from the community and to distinguish between distinct outbreaks in different hospital departments and inter-department spread.All stool samples positive for NoV and submitted from of a 770-bed university hospital in the Copenhagen area, Denmark, to the virological department at Statens Serum Institut for diagnosis during November 2007 to July 2008, were identified from the laboratory database. One hundred-and-fifty-three samples from 105 patients had been submitted from seven different departments. Capsid and/or polymerase typing demonstrated that the majority (95% of 60 samples examined) belonged to GII.4.The first available sample from each patient was included for analysis with a GII.4 specific reverse transcription polymerase chain reaction (RT-PCR). For 29 patients, samples were no longer available and for another 20 patients the GII.4 specific capsid RT-PCR was negative. One sample was excluded since previous genotyping had shown a genotype GI.3. Thus, sequences from a total of 55 patients were analyzed. From six of these patients, additional sequences were obtained from follow-up samples taken at least 14 days after the first sample. In addition, five samples from a foodborne outbreak caused by GII.4 variant Den Haag 2006b, occurring in 2008, were included in the study in order to analyze the capsid gene sequence variation in a known point-source outbreak. In total, 66 capsid sequences were obtained and analyzed.For 22 of the inpatients with available capsid sequences and for the five samples from the foodborne outbreak, polymerase gene sequences were available from previous genotyping.Electronic patient records were reviewed for admission data, onset of gastrointestinal symptoms and presence of immunosuppressive disorders or prescription of immunosuppressive therapy.NoV diagnostics and capsid and/or polymerase typing was performed as previously described .2 4 mM, dNTP 0.4 mM, primers 0.6 µM), using GeneAmp 10X PCR Buffer II, MgCl2 and AmpliTaq DNA Polymerase  and cycling conditions: 95°C for 5 min, 35 cycles of 95°C for 30 s, 52°C for 30 s, 72°C for 2 min and final extension at 72°C for 5 min. The PCR product was sequenced with the PCR primers, eventually supplemented with sequencing primers [For the GII.4 specific RT-PCR; RNA was extracted from 10% stool suspensions, which had been kept frozen at-80°C, with the MagNAPure LC . A NoV GII.4-specific nested RT-PCR amplifying 1571 nucleotides (nt) of the capsid gene (ORF2) was performed using primers as previously described . Reverse primers  using Bihttp://www.rivm.nl/mpf/norovirus/typingtool) [Sequences were quality assessed and assembled using the BioNumerics version 6.6 software . BioNumerics has an in-built algorithm for sequence quality assessment and automatically discards low quality sequences before assembly. In addition, all sequence chromatograms were inspected manually and finally, all sequences were compared with publically available sequences deposited in GenBank via BLASTN and through manual alignments. For polymerase gene sequences, the full available sequences with a length ranging from 226 to 285 nucleotides (nt) were analyzed. For capsid gene sequences, a 1412 nucleotide (nt) region, corresponding to nt position 110 to 1521 of the reference sequence, was shared by all sequences and was used for further analysis. The norovirus sequence Hu/GII.4/Shellharbour/NSW696T/2006/AUS (GenBank no. EF684915.2)  was usedingtool) .MEGA version 6 [For further analysis, sequence alignment, conceptual translation to amino acid sequences, estimates of evolutionary divergence and phylogenetic analysis were performed in ersion 6 . Sequencersion 6  were manAll sequences were submitted to GenBank. Capsid sequences have accession numbers KJ144938 to KJ145003, and partial polymerase sequences have accession numbers KJ956701 to KJ956727. A detailed assignment is available as supplemental material .http://www.R-project.org/) was used for statistical analysis. For comparison of categorical data, Fisher’s exact test was used if expected values were <5, otherwise the Chi-squared test was used. P-values ≤0.05 were considered statistically significant.The computer program “R: A language and environment for statistical computing”, version 3.0.2  was used for graphics.The study was approved by the Danish Data Protection Agency (Record no. 2012–54–0202). Because of the retrospective design of the study, no written or verbal informed consent could be given by the patients. That being the case, access to patient records has to be approved by the Danish Health and Medicines Authority according to Danish law. This approval was obtained (Record no. 3-3013-292/1/). After retrieving information from electronicpatient records data was anonymized by the research team for further analysis.According to the “Danish Act on Research Ethics Review of Health Research Projects” this study does not require approval by the ethics committees, as it is considered a quality development project. This was confirmed by the Committees on Health Research Ethics for the Capital Region of Denmark in a specific waiver of approval (H-6-2014-FSP-055).Capsid sequencing showed that the majority of the inpatients (47 of 55) were infected with the Den Haag 2006b variant and three and five inpatients were infected with the Osaka 2007 variant and the Apeldoorn 2007 variant, respectively. The foodborne outbreak was caused by the Den Haag 2006b variant.In all 24 samples, where a genotype could be assigned from the polymerase sequence, it was congruent with the capsid genotype. Thus, no recombinants were detected.Comparing all 66 capsid sequences, nucleotide changes were observed in 238 of 1412 sites (17%). There were no deletions or insertions. The estimated evolutionary divergence between the three GII.4 variants is available as supporting information .Between four of the five sequences belonging to the Apeldoorn 2007 variant, no nucleotide changes were found. These samples were from patients in the same department and also temporarily related, while the fifth sequence differed by one nucleotide and was epidemiologically unrelated (sample obtained three months later in another department). Two sequences belonging to the Osaka 2007 variant did not show any nucleotide changes and had been obtained from patients in the same department taken with one day’s interval. The third differed by two nucleotides and was obtained two weeks earlier in another department, suggesting that this case was not related to the other two.Among the 58 Den Haag 2006b sequences, nucleotide changes were detected in 79 sites (6%), 31 of which were located in the P2 region. The number of nucleotide substitutions was higher within the P2 region  than outside , but this difference was not statistically significant . However, substitutions in the codons of the P2 region were significantly more often located in the first or second position of the codon  and transversions (as opposed to transitions) were also significantly more common . As both of these observations are associated with non-synonymous nucleotide substitutions, 14 of the 18 amino acid changes occurred in the P2 region . The 18 non-synonymous substitutions resulted in 17 amino acid alterations, 5 of which were located in key amino acid positions in the P2 region  marked .To exclude the possibility of RT-PCR introduced nucleotide changes or sequencing mistakes, cDNA synthesis, PCR and sequencing was repeated for 5 samples with unique substitutions not shared with any of the other sequences. This repeated testing showed 100% reproducibility for a total of ten nucleotide substitutions.In addition to the above described nucleotide changes, a total of 47 mixed bases were detected in 15 sequences at 39 different positions. These mixed bases indicate quasispecies, as a mixed signal would be expected, if more than one viral strain has been co-PCR amplified and co-sequenced. The 15 sequences were from samples of 12 different patients, ten of which were receiving immunosuppressive therapy .The first capsid sequence from each of the 55 inpatients, the five samples from the foodborne outbreak and the reference sequence were included in the phylogenetic analysis.Cluster 7 represented the foodborne point source outbreak and these five sequences were identical. Four of the six hospital clusters were locally confined to one department. The three smallest clusters  were restricted to one department each and to a period of less than one month and the sequences differed by no more than one nucleotide substitution. Thus, in these clusters the molecular epidemiology confirmed the epidemiological relation and added the information, that each of these clusters was due to a new introduction of the virus into the hospital environment. Cluster 4 included 13 samples from the hematology department over a period of 78 days. Six distinct sequence patterns differing at 12 sites (0.8%) were observed. A more detailed description of the sequence variation in this cluster, taking into account mixed bases and follow up samples from four of the patients, is given in The clusters 1 and 2 included sequences from samples from different departments. Cluster 2 was composed of sequences from eight samples obtained from the nephrology department and one from the hematology department. The earliest of the nephology samples was taken one day after admission in a patient undergoing chronic hemodialysis. The ninth sample was from the hematology department and was taken at the patient’s admission two weeks earlier. Thus, this cluster could have been caused by either two separate introductions or inter-department spread of the virus. Cluster 1 was epidemiologically more heterogeneous, with sequences of samples obtained from four different departments. The first sample (Neph-12/18/2007) was taken in the nephrology department in December 2007. About two months later, four samples belonging to the same cluster were taken in the cardiology department within three weeks; one of these samples differed by one nucleotide from the other three. Another two samples in this cluster were taken in the internal medicine department 1 within three days after the first sample from the cardiology department . One of these had an identical sequence compared to the three cardiology sequences and the other one differed by one nucleotide. This indicates that transmission between these two departments has occurred. Six weeks after the last sample was taken in the cardiology department, a sample taken from a patient in the internal medicine department 1 (IntMed1-03/27/2008) revealed a sequence differing by one nucleotide. As this sample was taken within 48 hours after admission in a patient without previous hospital contact, this most likely represents a new introduction of the virus into the hospital environment. A sequence obtained from a sample taken two days later from a chronic hemodialysis patient within 48 hours after admission (Neph-03/29/2008) and a third sequence taken two weeks later from a patient in the internal medicine department 2 (IntMed2-04/08/2008.1) were identical. Inter-department spread could have occurred here. Again one month later, three samples from the internal medicine department 2 yielded identical sequences differing from the last mentioned ones by one nucleotide substitution. This could either represent a new introduction or an ongoing outbreak in that department. Taken together, in cluster one, most likely several new introductions have taken place, but inter-department spread is also likely to have occurred .One sample with a sporadic sequence (“singleton 1”) was taken on the same day and in the same department as a sample from cluster 1 (IntMed2-04/08/2008.1). The sequences from these two samples differed only by one nucleotide substitution , making nosocomial transmission very likely and indicating that a more reasonable classification of this sequence would be in cluster 1.The temporal distribution of the different genotypes, variants and clusters in each department is shown in For 27 samples with a GII.4 variant Den Haag 2006 capsid sequence, polymerase sequences from previous genotyping were also available, with lengths ranging from 226 to 285 nt. Phylogenetic analysis of the polymerase and the capsid sequences of these 27 samples was conducted separately to compare the resolution of these two methods. Nineteen of the 22 samples from inpatients had identical polymerase sequences, whereas phylogenetic analysis of the capsid gene showed that this apparent cluster was comprised of the above described clusters 1, 2, 3 and 4 and singleton 3 . This dePaired samples from six patients, all receiving immunosuppressive therapy, were available for sequencing. The samples were taken with an interval of 16 to 77 (median 45) days. All paired sequences were closely related and there was no evidence of reinfection with another NoV strain. However, sequence variation  was detected between all paired samples and mixed bases were observed in all later samples. In total, mixed bases indicating NoV quasispecies were detected at 37 sites in the paired samples. A significantly higher frequency of mixed bases were observed in the second samples (32 in six 1412 nt sequences) than in the first samples .in vivo evolution, were found in nine positions.The nucleotide changes and mixed bases in the sequences from the four patients belonging to cluster 4, together with the remaining sequences of that cluster, are shown in We used sequencing of a large part of the capsid gene to investigate NoV infections in a university hospital during a nine months’ period in the winter season 2007/2008. Routine polymerase genotyping had shown that the majority of strains belonged to the GII.4 Den Haag 2006b variant and that most of the sequences were identical . For furThe phylogenetic analysis of the 1412 nt long capsid sequence showed that the accumulation of NoV infections in the hospital was due to several outbreaks mostly confined to one department each. In two clusters (GII.4 Den Haag 2006b clusters 1 and 2), possible inter-department spread was observed. The heterogeneous cluster 1 contained sequences from four different departments over a time span of nearly half a year. One of the later samples in this cluster was taken from a patient without earlier hospital contact within 48 hours after admission, thus indicating a new introduction of the virus from the community into the hospital. However, inter-department spread could have occurred in temporarily related samples from this cluster. An example of this could be the simultaneously occurring norovirus infections in the cardiology department and the internal medicine department 1 in week 5–7/2008. In other temporary and/or locally related cases with sequences differing by no more than one nucleotide the transmission route was unclear. Identical sequences belonging to cluster 1 were for example found in three patients on three different wards in week 13–15/2008. Both nosocomial transmission and repeated introduction from the community could explain these infections. The same is true for the first two samples from cluster 2 which were from patients from two different departments.In the nephrology department and both internal medicine departments, consecutive outbreaks with distinct clusters of the GII.4 variant Den Haag 2006b were detected, indicating repeated introductions of different strains from the community. As opposed to this, a prolonged outbreak over 12 weeks with the same cluster occurred in the hematology department.Sequencing of the capsid gene has previously been shown to be helpful for investigating outbreaks. Comparable to our study, which found a presumed larger hospital outbreak to consist of several distinct smaller outbreaks, Xerry et al.  could diThe frequency of nucleotide changes found in our study (0 to 12 substitutions per cluster in 1412 nt sequences) is in concordance with previous studies investigating nosocomial NoV GII.4 outbreaks: Dingle et al. showed a diversity of six nucleotide changes in the entire NoV genome in a 1-week outbreak with presumed person-to-person transmission, whereas the strains of an outbreak with a presumed point source only differed by one substitution . Sukhriein vivo evolution.A possible epidemiological explanation for outbreaks consisting of identical strains could be a point source such as contaminated food (as seen in the foodborne outbreak in our study) or continuous transmission of the same strain from a contaminated environment, the extent of which is still debated . In our in vivo evolution of the virus leading to the development of quasispecies has been shown [In immunocompromised patients, the en shown –16. In aen shown .Repeated analysis of the data by generation of a Maximum Likelihood tree allocated the sequences to the same clusters , demonstThis study was designed to investigate sequence variation as an indicator for NoV evolution to study transmission routes. However, further characterization of the nucleotide changes showed interesting findings. Transversions (compared to transitions) and nucleotide changes in the first two codon positions were significantly more common within the P2 region than outside the P2 region, as were non-synonymous substitutions. These findings are in accordance with previous studies and indicate positive selection in this surface-exposed region, which is consistent with its predicted key role for antigenic variation and receptor binding , 16, 38.A drawback of this study is that the available sequences only represent a part of the actual burden of NoV infections. Usually, most samples are taken in the beginning of an outbreak and subsequent cases are diagnosed based on clinical findings. In addition, in our study a substantial part of the samples were not available or sequences could not be obtained. However, as the phylogenetic analysis shows a clear clustering according to department and time of sampling, we feel confident that this bias has not influenced the major findings and conclusions of the study.This study also lacks information about the genetic variability of strains occurring in the community during the study period. Especially for the interpretation of the heterogeneous Den Haag 2006b cluster 1, this information would have been valuable.Interestingly, it was difficult to find a clear consensus in the literature about the exact demarcation of the P2 region in NoV GII.4 strains. Several slightly different regions, ranging in length from 125 to 152 amino acids, have been reported , 33. In In conclusion, sequencing of the capsid gene proved useful for the investigation of a NoV season dominated by the GII.4 variant Den Haag 2006b in one university hospital. Polymerase sequences which were available from genotyping performed continuously during the outbreak were identical. Phylogenetic analysis of the capsid sequences, however, showed that repeated introductions were common, leading to smaller outbreaks, which were most often confined to a single department. However, a few cases of possible inter-department transmission were also detected. If promptly available, these results would have been of value for outbreak management. In this setting, one should have focused on correct isolation measures upon patient admission to prevent subsequent intra-department spread instead of regarding the outbreak as a pan-institutional outbreak. The sustained outbreak on the hematology ward was shown to be due to repeated person-to-person transmission indicating that outbreak management should have focused on isolation measures of chronically infected patients.S1 TableThe accession numbers and sequence names of the 66 capsid sequences and 27 polymerase sequences included in this study are given.(PDF)Click here for additional data file.S1 FigThe number of base substitutions per site from averaging over all sequence pairs are shown. Analyses were conducted using the Jukes-Cantor model.(TIF)Click here for additional data file.S2 FigA ML tree of all capsid sequences (first sample per patient) was constructed and rooted on the branch between the Den Haag 2006b variant and the Osaka 2007 and Apeldoorn 2007 sequences. The subtree of the 2006b variant is displayed here. Sites with mixed bases were ignored for phylogenetic analysis.Sequence names represent hospital department  and date of sampling (mm/dd/yyyy), eventually followed by a serial number to ensure uniqueness.Sequences from patients with symptom onset within 48 hours after hospital admission are marked with a circle . Sequences from the first samples from six patients with persistent diarrhea are marked with a filled triangle. Sequences from samples with an available polymerase gene sequence from routine genotyping (n = 27) are marked with asterisks.(TIF)Click here for additional data file.