P = 0.03), higher peak  and higher postprandial BGLs than T1D , despite similar pre-meal BGLs . Regarding test breakfast, greater pre and post-meal BGL difference correlated with longer CD duration . Total energy and macronutrient intake didn’t differ between groups; however the majority of participants collectively had inadequate intake of calcium (76%), folate (71%) and fiber (53%), with excessive saturated fat (12%) and sodium . The GFD is associated with greater glycemic excursions and inadequate nutritional intake in youth with T1D+CD. Clinical management should address both glycemic variability and dietary quality.The gluten free diet (GFD) has a high glycemic index and low-fiber content, which potentially influences glycemic excursions in type 1 diabetes (T1D) and celiac disease (CD). Participants in this case-control study of youth with T1D+CD (n = 10) and T1D only (n = 7) wore blinded continuous glucose monitoring systems for six days. Blood glucose levels (BGLs) were compared between groups for each meal, including pre-meal, peak, 2-hour postprandial and time-to-peak. Participants consumed a test-breakfast of GF cereal and milk for three days and kept weighed food diaries; nutrient intake was analyzed and compared to national recommendations. Youth with T1D+CD had shorter time-to-peak BGL (77 vs 89 mins,  The gluten free diet (GFD) recommended for management of celiac disease (CD) requires the complete avoidance of wheat, rye and barley, which is often replaced by white rice or corn4Restrictive diets such as the GFD are at risk of nutritional deficiencies, requiring increased vigilance in growing children and adolescents5411Adults and youth with CD have a lower carbohydrate intake compared with the general population512This was a case-control, observational study of youth with T1D and biopsy-proven CD, individually matched to controls with T1D only by age, diabetes duration and HbA1c . Inclusion criteria were T1D+CD, age <18 years, treatment with either multiple daily injections or insulin pump therapy, willingness to test at least four blood glucose levels (BGLs) per day, and the ability to read and record food diaries in the English language. Participants were recruited from the Diabetes Clinic at The Children’s Hospital at Westmead, a tertiary pediatric hospital in Sydney, Australia. We aimed to recruit 10 youth with T1D+CD and 10 with T1D. The sample size was based on a minimum mean post-prandial BGL difference of 3 mmol/L (standard deviation 3 mmol/L) between groups over three days , with α = 0.5 and power 80%, assuming a drop out or missed BGL rate of 20%. The study protocol included youth wearing a blinded continuous glucose monitoring system (CGMS), consumption of the same test breakfast for three days, completion of a weighed food diary and documentation of diabetes care . All participants attended their diabetes review appointment with their pediatric endocrinologist in the six weeks prior to the study visit for adjustment of insulin doses, or insulin pump settings. Participants used their pre-exiting insulin to carbohydrate ratios and insulin sensitivity factors, which had been set and adjusted according to standard clinical criteriath November 2012). The methods were carried out in accordance with the relevant guidelines and regulations. Informed consent was obtained from parents and assent from children aged 12–16 years prior to participation.The study was approved by the Sydney Children’s Hospital Network Human Research Ethics Committee . Patients underwent a structured interview, which involved documentation of their typical daily food intake, including weekend variations for meals both inside and outside the home. Carbohydrate counting skills were reviewed using food replicas , food packaging and real food . Measuring scales and cups were used as educational tools to assist with quantifying carbohydrate intake. Anthropometric measures were taken with the participant in light clothing and without shoes. Height was measured to the nearest 0.1 cm (Harpenden stadiometer) and weight was measured to the nearest 0.1 kg; BMI was calculated with z-scores computed using Centers for Disease Control and Prevention (CDC) 2000 reference data.CGMS (Medtronic Enlite Sensor with a blinded iPro2 transmitter) was inserted by the diabetes educator and worn uninterrupted for six days. Details of the sensor properties are described in detail elsewhereT) was calculated as the standard deviation (SD) for all of the measurements for all of the study daysTotal variability (SDw) was calculated as the SD of all measurements in a 24 hour period, averaged over the sensor reading daysWithin day glucose variability (SDBetween day variability was measured by Mean of daily differences (MODD), and calculated as the average of the absolute difference in glucose values at the exact time of day (midnight), and averaged over five daysMeal effect was measured by Area Under the Curve (AUC) and calculated as the sum of the absolute value of excursions from sensor value at the start of the meal and was calculated for 2 hoursParticipants were stratified by the presence or absence of CD co-existence for data analysis. For each main meal consumed and accompanied by a pre-prandial insulin bolus, time to reach peak BGL, peak BGL, and 2 hour postprandial BGL were examined. The following variability parameters were measured:Participants maintained a standardized weighed food diary for three days in which they were asked to document meal and snack times, weigh and/or measure the quantity of all foods and drinks, the brand name and serving size consumed, and all BGL measurements. Participants were provided with electronic kitchen scales and measuring cups. Food diaries were analyzed using Foodworks 7 , which uses the Food Standards Australia New Zealand (FSANZ) published AusNut and NUTTAB 2010 databasesDietary intake was compared to the Australian National Health and Medical Research Council (NHMRC) age and gender specific nutrient reference valuesAll participants were given the same low glycemic index breakfast  for consumption on the first three study days together with portion-controlled ultra-high temperature (UHT) milk . At the study visit, participants indicated their usual portion of cereal; using this information the dietitian weighed out the same quantity and labeled the carbohydrate amount for each individual breakfast. Participants were asked to refrain from consuming other foods for breakfast.Tissue Transglutaminase (TTG) IgA and deamidated IgG were measured in all participants at least once within the previous 12 months and negative CD serology was confirmed for the T1D only controls. For T1D+CD patients, GFD adherence was assessed both clinically and serologically as previously describedU tests for skewed data. Categorical data were compared using chi-squared tests. Statistical analyses were performed using SPSS  and Stata 14 . P-values < 0.05 were considered significant.Descriptive statistics are reported as mean + standard deviation (SD) for normally distributed data or median (range) for skewed data. Continuous variables, including clinical characteristics and glucose variability parameters, were compared between groups using student’s t-test for normally distributed data and Mann-Whitney Twenty youth  were recruited into the study. Three patients had CGMS equipment failure . Comparing patients with CD (n = 10) and those without (n = 7), there were no statistically significant differences in demographic or clinical features other than TTG titers . InsulinDietary intake per participant was calculated as the average of the three recorded days. Total energy and proportional macronutrient intake were not statistically different between those on the gluten-containing or GFD diet . For theA total of 2,245 hours of data were recorded by CGMS, with a mean of 132 ± 26 hours and 1,585 ± 314 sensor readings per patient. Blood glucose profiles did not significantly differ between youth with T1D vs T1D+CD , includiP = 0.03), higher peak BGL values post prandial , and 2 hour post prandial BGLs  (P = 0.02) and 2 hour post prandial BGLS . The difference between post-meal BGL and peak BGL post-meal was significantly correlated with longer CD duration . In the diabetes alone group, diabetes duration was not associated with change in pre- to peak BGL values (P = 0.50).A total of 222 main meals were identified from CGMS traces and pre-meal BGL records throughout the study period  and of these 179 (81%) were accompanied by an insulin bolus, with no difference in the proportion of delivered boluses in those with or without coexisting CD . Glycemic profiles for meals where an insulin bolus was delivered are reported in  = 0.02) . For theThis is the first study to examine the impact of the GFD in youth with coexisting CD and T1D on glycemic variability and nutrient intake. The GFD was associated with greater glycemic excursions, characterized by a faster time to peak BGL, higher peak and higher two-hour post prandial BGLs, despite similar exogenous insulin requirements. The GFD and the gluten-containing diet had similar macronutrient distributions that met national nutritional guidelines, however the intake of saturated fat and sodium were above national and international recommendations, while the intake of dietary fiber and calcium was inadequate.The test meal of GF cereal consumed by all study participants was associated with greater glycemic excursions in youth with T1D+CD compared with their T1D only peers. The observation of faster glucose absorption in those with CD expands on a physiological study in which solutions of increasing glucose concentrations were infused into the small intestine and glucose absorption measured by the production of electrical activity (Apparent Km)The dietary intake of youth with T1D or T1D+CD was at the lower end of both national and international guideline recommendations for carbohydrates, inadequate for fiber and calcium and high for saturated fats222829304The micronutrient intake in our two study groups was comparable, however more than half of youth reported below average daily recommended intakes for calcium, iron and folate. The low intake of folate is surprising, since fortification of wheat flour with thiamin and folic acid is mandatory in many countries across the world including Australia335Limitations of our study include the small patient numbers, however most CGMS studies have included similar patient numbers and are adequately powered to investigate glucose variability data2025In conclusion, we have demonstrated that youth with T1D+CD have greater post-prandial glucose excursions, suggesting that either the GFD or intestinal characteristics influence glucose absorption. Youth with co-existing T1D and CD have similar macronutrient intake to their peers with T1D alone. Dietary advice for youth with T1D should emphasize increasing fiber, folate and calcium intake, and reducing saturated fat and sodium intake, with further attention to increase thiamin intake for those on the GFD.How to cite this article: Pham-Short, A. et al. Greater postprandial glucose excursions and inadequate nutrient intake in youth with type 1 diabetes and celiac disease. Sci. Rep.7, 45286; doi: 10.1038/srep45286 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Here we explored the responses of the NMD pathway to prolonged seizures (status epilepticus) and investigated the effects of NMD inhibition on epilepsy in mice. Status epilepticus led to increased protein levels of Up-frameshift suppressor 1 homolog (Upf1) within the mouse hippocampus. Upf1 protein levels were also higher in resected hippocampus from patients with intractable temporal lobe epilepsy. Immunoprecipitation of Upf1-bound RNA from the cytoplasmic and synaptosomal compartments followed by RNA sequencing identified unique populations of NMD-associated transcripts and altered levels after status epilepticus, including known substrates such as Arc as well as novel targets including Inhba and Npas4. Finally, long-term video-EEG recordings determined that pharmacologic interference in the NMD pathway after status epilepticus reduced the later occurrence of spontaneous seizures in mice. These findings suggest compartment-specific recruitment and differential loading of transcripts by NMD pathway components may contribute to the process of epileptogenesis.The nonsense mediated decay (NMD) pathway is a critical surveillance mechanism for identifying aberrant mRNA transcripts. It is unknown, however, whether the NMD system is affected by seizures  Important check-points exist on the journey from gene transcription to translation that support surveillance of the quality of mRNA transcripts in order to prevent translation of aberrant transcripts which could lead to the production of mutated or harmful proteins234675Arc1517The brain displays one of the highest rates of NMD activity among tissuesNonsense mutations have been described in γ-amino butyric acid (GABA) receptors and synaptic proteins which have been implicated in the human epilepsies and experimentally verified to be targeted by the NMD system1920212224252628All procedures were performed in accordance with the guidelines of the European Communities Council Directives (86/609/EU and 2010/63/EU) and were reviewed and approved by the Research Ethics Committee of the Royal College of Surgeons in Ireland  under license from the Department of Health and Health Products Regulatory Authority, Dublin, Ireland (AE19127/P001). Male, C57BL/6 mice  were used in all studies. Intraamygdala kainic acid (KA)-induced status epilepticus was induced as previously describedNMD inhibition was achieved using a small molecule inhibitor, NMDI14Acute EEG during status epilepticus in mice was recorded using a Grass Comet XL digital EEG. Seizure activity was defined as high amplitude high frequency discharges  recorded within the 40 minute period following KA administration. For long-term epilepsy monitoring studies, continuous EEG and video recordings were performed using implantable EEG telemetry devices n = 6) were referred for surgical resection of the temporal lobe for the treatment of intractable temporal lobe epilepsy (TLE). After temporal lobe resection, the hippocampus was divided, with one piece frozen in liquid nitrogen and stored at −80 °C. The remaining bloc was processed for routine pathological analysis and samples were assessed for the presence of hippocampal sclerosis and other pathological changes. Control (autopsy) hippocampi (n = 6) were obtained from individuals with no history of neurological disease from the Brain and Tissue Bank for Developmental Disorders at the University of Maryland, Baltimore, MD, USA. Sex ratios for each group were 2 M:4 F for TLE patients and 3 M:3 F for autopsy controls. Average ages for each group were: 33.5 years (range 17–54) for TLE patients and 42.3 years (range 37–50) for controls. The average post-mortem interval was 15 hours. Full details of control and patient pathology and clinical data can be found in This study was approved by the Ethics  Committee of Beaumont Hospital, Dublin  and written informed consent was obtained from all patients. All human-related study methods were performed in accordance with all relevant legislative requirements and the research was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki and Good Clinical Practice. Patients (® West Pico Chemiluminescent Substrate (Millipore) and imaged using a Fuji-film LAS-3000. Band densities were analysed using ImageJ software. Protein levels were corrected to Actin, Tubulin or synaptophysin (synaptoneurosomes) loading controls.Western blotting was performed as describedSynaptoneurosomes (SN) were prepared from mouse hippocampi according to previous techniques35Free-floating sections (30 μm) were obtained from mice perfused with 4% paraformaldehyde (PFA). Sections were incubated with 0.1% Triton-X/PBS for 15 minutes, after which 1 M glycine was added and incubated for 30 minutes. Sections were then washed in PBS and incubated with 1% Bovine Serum Albumin (BSA)/PBS for 1 hour to block unspecific binding of primary antibodies to the sections. Sections were then incubated with Upf1 (Abcam ab109363), AnkyrinB (NeuroMab 75–145) and/or Map2 (Sigma M9942) antibody overnight at 4 °C, washed three times for 5 minutes with PBS, incubated with fluorescently-labelled secondary antibodies Alexa-fluor 488 and Alexa-fluor 546 and nuclear marker Hoechst, washed with PBS and finally mounted on glass slides and coverslipped with Fluorsave (Millipore). Sections were imaged using a Leica DM400B fluorescent microscope or a Zeiss Axiovert 200 M confocal microscope.n = 6 each) mice were combined and synaptoneurosome and cytoplasmic fractions were isolated as described above. For these studies it was necessary to pool large numbers of hippocampi and therefore biological replicates were not attempted. Upf1 (Abcam ab109363) was immunoprecipitated from samples using Protein-G-conjugated Dynabeads (Thermo Fisher Scientific) and Upf1-bound RNA was extracted using TRIzol (Thermo Fisher Scientific). Ribosomal RNA was removed from the co-precipitated RNA using the Ribo-Zero Magnetic Kit (Illumina) and the RNA library was constructed using the ScriptSeqTM v2 RNA-Seq Library Preparation Kit (Illumina) according to the manufacturer’s instructions. 3′Adapter sequences were removed and the quality of sequenced reads were first checked using FASTqc software38All buffers and reagents used in the preparation of samples for RNA-seq were RNAse free. Pools of hippocampi from control and SE . Quantitative real-time PCR was performed using a LightCycler 1.5 (Roche Diagnostics) and QuantiTech SYBR Green PCR kit (Qiagen) as per the manufacturer’s instructions and 1.25 μM of primer pair was used. Arc forward: AGCAGCAGACCTGACATCCT, reverse: GTGATGCCCTTTCCAGACAT; FosB forward: AGGAACCAGCTACTCAACCC, reverse: AAGTCGATCTGTCAGCTCCC; Inhba forward: CATCACCTTTGCCGAGTCAG, reverse: AGACGGATGGTGACTTTGGT; Npas4 forward: TGAAGACATTGTGGCAGCAC, reverse: TGGTCAGCAGGGTCAATGAT; Pcdh8 forward: ATCGGAACCCTTGCAGAAGA, reverse: CTGACAACATCGAAGGCCAG; S18 forward: AAGAGGGCTGGAGAACTCA, reverse: GCAGCTTGTTGTCTAGACCG; Slc1a2 forward: GCCTGCTTGATTTGTGGGAA, reverse: AGTTCCCAGAGCAGTGATCC; Tll1 forward: CGCCAAGCCAGTACAGAATC, reverse: CACTTCAGGTATGTCAGCGC). Data were normalized to expression of S18 RNA.Total RNA was extracted using the Trizol method2 fold-change in a given transcript and significant p values (both raw and corrected for multiple testing).Data are presented as means ± standard error of the mean (SEM). Data were analysed using ANOVA with either Dunnet’s post-hoc test when comparing all groups to just one group and Bonferroni’s post-hoc analysis otherwise. Student’s t-test for two-group comparison and Mann–Whitney test for qPCR validation of RNA sequencing results. Significance was accepted at p < 0.05. For RIP-seq analysis Bowtie open access software was usedAnimal studies were approved by the Research Ethics Committee of the Royal College of Surgeons in Ireland (REC) under license from the Department of Health and Health Products Regulatory Authority, Dublin, Ireland. Human tissue studies were approved by the Ethics  Committee of Beaumont Hospital, Dublin (05/18). Written informed consent was obtained from all epilepsy patients.Multiple components of the NMD system were expressed in the hippocampus of control mice, including Upf1, Upf2 and Upf3b . To dete31Western blot analysis revealed an increase in Upf1 and p-Upf1 at 8 and 24 hours  and Upf2Previous studies have indicated that NMD is active at distal sites from the nucleus during neuronal development and after neuronal activity1213To support these observations we generated synaptoneurosomes (SN) from the hippocampus of control and seizure mice. These are isolated portions of neurons containing resealed presynaptic structures (synaptosomes) together with attached sealed postsynaptic entities (neurosomes)We next sought to determine whether there were changes in Upf1-targeting of mRNA transcripts after status epilepticus. To this end, we used RNA-immunoprecipitation sequencing (RIP-seq)6 (The number of reads (hits) from RIP-seq experiments were between 18–47 × 106 . We then6  of all r6  suggesti6 .Since the targets of compartmentalized Upf1 in the normal hippocampus are unknown we next queried the type of transcripts that are targeted by Upf1 in SNs and cytoplasm. GO analyses of the set of transcripts that were unregulated in both SN and cytoplasm and exclusively in either SNs or cytoplasm of control hippocampus are shown in 84546Next, we investigated GO terms associated with transcripts that were expressed only in control samples or with a log2 fold-change ≤−1.5 after status epilepticus and exclusively in status epilepticus or with a log2 fold-change ≥1.5 after status epilepticus in SNs and cytoplasm . GO termArc was included as it is a well-characterised NMD targetFosB and Pcdh8 both contain an up-stream in frame stop codon and in addition to Tll1 were previously found in other studies47Inhba and Npas4 were chosen as they have not previously been associated with NMD regulation84546474849Arc, FosB, Inhba, Npas4, Pchd8 and Tll1 bound to Upf1 after status epilepticus whereas levels of Slc1a2 were not different between groups (In order to look for specific transcripts that are targeted by Upf1 we explored the data for genes that were both significantly (p < 0.05) altered after status epilepticus and had a FPKM log2 fold change ≥1.5 . Comparin groups .It is unknown whether the changes in transcript targeting by NMD as a result of status epilepticus affect functional outcomes. To investigate this, we targeted NMD after status epilepticus using a recently described NMD inhibitor, NMDI14Spontaneous seizures emerged in both groups of mice within a few days of status epilepticus and NMDI14 had no effect on the emergence or time to first spontaneous seizure. However, NMDI14-treated mice had fewer spontaneous seizures overall during long-term monitoring compared to vehicle-treated mice . Total sScn9a, Cdk5rap2 and Stx212RNA surveillance mechanisms such as the NMD pathway are increasingly recognized as important in nervous system development and function, synaptic plasticity and neurological diseases including certain epilepsies19202122Arc at synapses to maintain synaptic homeostatic mechanisms1254Arc, limiting translation to protein. Consistent with this, we detected increased Arc levels bound to Upf1 after status epilepticus in the model. Together, these observations indicate that both prolonged acute seizures and perhaps chronic epilepsy alter NMD component levels and localization that may reflect homeostatic or mal-adaptive changes in the hippocampus to the transcriptional and translational burden imposed by seizures.NMD components and activity have been reported to localize to distal sites in neurons including axons where they locally regulate transcripts and specific splice variants in synaptic development and plasticityThe present study provides the first analysis of Upf1-bound RNA transcripts in the hippocampus of mice subject to status epilepticus. Here we used Upf1 pull-down followed by RNA sequencing to identify and assess the abundance of mRNAs targeted by NMD. This has the advantage of providing much broader insights into the transcript landscape targeted by NMD and allows for the detection of unannotated and novel transcripts compared to techniques such as microarrays8454647484943Arc, GO terms related to responses to stimulus were under-represented. Also under-represented were terms associated with immune responses. This was surprising because status epilepticus is known to provoke a strong neuroinflammatory response and the NMD pathway is known to target transcripts with roles in immune responses1Our GO analysis of Upf1 targeted transcripts in control samples indicates there is a set of biological processes which are specifically NMD targets including mRNA transport, transcription and protein processing. This fits with the restricted and compartmentalized location of NMD components in the hippocampus. Of note, numerous GO terms related to adhesion and development were over-represented in genes exclusive to SNs which is consistent with roles of NMD in growth and development of neurons13Arc, FosB, Gadd45b, Pcdh8 and Tll1 which have been previously identified as NMD mRNA targets8124547Inhba and Npas4. As for several other Upf1-bound transcripts, expression of both genes has been reported to be enhanced by seizures58595859628The present study included validation of RIP-seq data that confirmed status epilepticus results in increased binding of numerous mRNA transcripts to Upf1. This included Current treatments for epilepsy patients work through a limited number of mechanisms, including inhibiting various ion channels and neurotransmitter systems351252The present study provides evidence for changes in the expression and activity of NMD in response to status epilepticus and indicates this system of RNA surveillance may also be altered in patients with epilepsy. We show initial evidence that targeting the NMD system can reduce the occurrence of spontaneous seizures. Whether targeting the NMD system represents a realistic target for the prevention of seizures or disease-modification in human epilepsy is uncertain. The NMD system is critical for normal neuronal function by maintaining strict regulation of the levels of aberrant transcripts. However, results here suggest a short period of treatment following an insult to the brain could be sufficient to yield disease-modifying effects while avoiding any potential detrimental effects of protracted inhibition. It will be important in future studies to investigate optimal dosing of this or similar NMD inhibitor compounds and validate disease-modifying effects in other models of acquired epilepsy.How to cite this article: Mooney, C. M. et al. RNA sequencing of synaptic and cytoplasmic Upf1-bound transcripts supports contribution of nonsense-mediated decay to epileptogenesis. Sci. Rep.7, 41517; doi: 10.1038/srep41517 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


This study aimed to evaluate the patient-reported outcome (PRO) content of ovarian cancer randomised-controlled trial (RCT) publications, describe PRO compliance, and explore potential relationships among these and completeness of PRO protocol content.Publications of Phase III ovarian cancer RCTs with PRO endpoints were identified by Medline and Cochrane systematic search: January 2000 to February 2016. Two reviewers determined the number of Consolidated Standards of Reporting Trials (CONSORT)-PRO Extension items addressed in publications. Compliance rates  were extracted. The relationship between CONSORT-PRO score and compliance rates was explored using scatter plots. Additionally CONSORT-PRO score and PRO compliance rates respectively were compared with corresponding PRO protocol scores obtained from a previous study.n = 33 with secondary PRO endpoint) were identified and analysed. The average number of CONSORT-PRO items addressed in publications was 6.7 . Three RCTs did not report PRO results; in 1 case due to poor compliance. Some compliance information was reported in 26 RCTs, but was considered complete for only 10 (28%) RCTs. Compliance rates were poor overall, ranging from 59 to 83%; therefore missing PRO data from 17 to 41% of participants in these trials could have been avoided.Thirty-six eligible RCTs (Of the 26 (73%) RCTs for which PRO protocol completeness scores were available, 6 RCTs reported complete compliance information and the 3 of these RCTs with highest PRO compliance had highest protocol checklist scores.Few RCTs reported PRO compliance information in a manner enabling assessment of the generalisability of PRO results. This information is particularly important in RCTs of advanced ovarian cancer because it is important to be able to determine if missing data was due to worsening illness compared to methodological issues. Poor compliance appeared related to poor PRO protocol content, and in one case prevented PRO results from being reported, highlighting the need to address compliance strategies in the protocol. Adhering to protocol and CONSORT-PRO reporting guidance should improve PRO implementation and reporting respectively in ovarian cancer RCTs and allow results to meaningfully inform clinical practice.The online version of this article (doi:10.1186/s41687-017-0008-3) contains supplementary material, which is available to authorized users. Patient-reported outcomes (PROs), including health-related quality of life (HRQOL), assessed in cancer randomised controlled trials (RCTs) provide valuable information on the impact of treatment from the patient’s perspective , 2. PRO PROs have long been included as secondary endpoints in ovarian cancer RCTs , as treaA comprehensive RCT protocol with well-considered PRO hypotheses is essential to communicate the rationale and methods for high-quality PRO data collection. It is therefore concerning that recent evidence indicates trial staff perceive PRO data collection guidance to be inadequate . InsuffiAdding to the complexity of PRO interpretation in oncology is missing data, which may be unavoidable if related to disease progression or death; in such cases missing data is considered to be “informative” of poor health status . HoweverAnother challenge for the uptake of PRO evidence from RCTs is poor PRO reporting according to CONSORT (CONsolidated Standards for Reporting) reporting standards –22. PoorFor any RCT, both the protocol and resultant publication should clearly articulate PRO hypotheses, endpoints, methodology and analyses. This is reflected in overlapping content of the CONSORT-PRO  and PRO-In our earlier study , we estaThe aims of this study were to describe the quality of reporting of PROs in ovarian cancer RCTs based on the CONSORT-PRO Extension; describe PRO compliance rates and the reporting of PRO compliance. We also aimed to explore the relationship between CONSORT-PRO reporting score and other key variables which we thought may influence reporting, including whether there was a significant difference in the primary trial endpoint or the PRO endpoint, compliance rates and year of publication. We also explored whether the PRO content of the ovarian cancer RCT protocols reviewed previously  had an iOur search and selection strategy were published previously  and summWe sought the RCT protocol for all 36 RCTs for evaluation in this study by searching online or by contacting the corresponding author of the trial publication. Protocol authors did not have access to the PRO protocol checklist, which minimised the risk of them augmenting their protocols prior to our evaluation.n = 26, Fig. Two authors  independently reviewed PRO content of each protocol obtained (n = 36) against the CONSORT-PRO checklist adapted for review purposes  independently assessed PRO content of all eligible RCT publications . RCTs that failed to report any of this information were classified as having reported ‘no compliance information’. Our grading of compliance reporting did not consider the actual rate of compliance, therefore it was possible for a trial with a poor PRO compliance rate to have ‘adequate’ compliance reporting. Discrepancies were resolved upon discussion (with MK or MC).finition  or proviWe defined PRO compliance rate as the proportion of participants included in the principal PRO analysis, of those from whom PRO assessments were expected per protocol  . This leRelationships among CONSORT-PRO score, the PRO protocol checklist total score (in the subgroup of 26 RCTs with a protocol), and year of main RCT publication were examined using scatterplots. Dot plots compared total CONSORT-PRO scores for RCTs that reported (versus did not report) a significant difference in either the primary or PRO endpoints.The potential relationship between PRO compliance rates at the principal time-point of PRO analysis and PRO protocol checklist total scores was assessed with a scatter plot.The potential relationship between reporting any compliance information (yes vs no) and PRO protocol checklist total score was assessed with dot plots. RCTs with ‘adequate’ and ‘incomplete’ reporting of compliance were pooled (these RCTs made an attempt at reporting compliance) and compared against RCTs reporting ‘no compliance information’.If any of these visual displays suggested an apparent relationship, an exploratory independent t-test was conducted. All plots and analyses were conducted using SPSS Version 22 .n = 19, 53%) reported a statistically significant difference between treatment groups in at least one PRO scale, 14 (39%) reported no PRO differences, and it was unclear whether there were any PRO differences in the remaining 3 RCTs (12%) as they did not report PRO results.Of the 36 eligible RCTs identified  ranged from 0 to 13.5/14, with a mean of 6.7 (48%). Most  reported some PRO results. Of the 3 (12%) RCTs that did not report any PRO results, 2 stated that these would be reported subsequently . The other did not analyse the PRO data due to poor compliance, and did not address any other recommended CONSORT-PRO criteria, scoring 0/14. Another low-scoring publication (scoring 1/14) simply reported that there were no differences in global QOL at any time point, but did not report the time points assessed, analysis methods, or results for other questionnaire domains. The majority of RCTs addressed some CONSORT-PRO items: 27 (75%) RCTs reported results of pre-specified PRO endpoints or all domains of the PRO questionnaire used, 25 (69%) interpreted PROs in the context of clinical endpoints, 19 (53%) provided the number of participants included in each PRO analysis, and 23 (64%) cited evidence of the validity of the PRO questionnaire used. However, other items were reported poorly; most concerning was the limited number of RCTs reporting baseline PROs , or reporting approaches for dealing with missing PRO data   compared to RCTs reporting no significant PRO difference  RCTs, and ‘incompletely’ by 16 (44%) RCTs. The remaining10 (25%) RCTs did not report PRO compliance. Eight of 10 RCTs with adequately reported compliance information addressed >11/14 (79% or higher) CONSORT-PRO items, whilst the remaining 2 scored 3.5 and 4/14. Six (17%) RCTs reported a definition of compliance, all of which were consistent with our definition and all bar one reported compliance ‘adequately’.Nineteen (53%) RCTs reported the number of baseline questionnaires submitted, and all but 1 of these reported the number submitted for the principal analysis time-point. Six (17%) RCTs reported use of a form to collect reasons for missing PRO data, however, of these, only 3 reported ‘adequate’ compliance information while 3 reported ‘incomplete’ information.t = 7.56, p < .001; Additional file Dot plots showed a wide range in the distribution of PRO protocol checklist scores for RCTs that reported any compliance information compared to RCTs reporting none  as opposed to avoidable reasons. However all these RCTs reported increasing rates of missing PRO data overtime, as is typical in cancer RCTs [For 16 RCTs with cer RCTs .One RCT analysed PRO data only from 1 country , due to poor compliance in other countries, though comparisons of the analysed compared to accrued sample were clearly presented and the paper reported compliance ‘adequately’.This study reviewed the relationship between the completeness of PRO content of ovarian cancer RCT protocols and corresponding publications and PRO compliance rates. There was a large range in CONSORT-PRO scores, much the same as we observed a large variation in corresponding PRO protocol checklist scores previously . On averBecause survival time is short in advanced ovarian cancer , 28, triStatisticians also need to know the reasons for missing PRO data so they may handle it appropriately in analyses . Thus itnot as a representative sub-group of the recruited sample, as the latter would present an overly optimistic picture of the effects of the trial treatments (bias). Not reporting any PRO data at all due to poor compliance represents a failure to extract the important evidence in the available data (research waste).We found that 2 RCTs failed to report PRO data due to poor compliance. This represents a waste of research effort as unpublished PRO data cannot possibly be used to improve knowledge or inform clinical practice , 30. FaiWe did not see a relationship overall between protocol content and CONSORT-PRO reporting scores in this sample. Encouragingly this finding suggests that PRO endpoints may reported in line with CONSORT-PRO guidance, even if the trial protocol did not comprehensively address PROs. However, further research is needed as we found that the 2 RCTs that did not report any details on their PRO studies (i.e. CONSORT-PRO scores of 0) addressed less than 20% of recommended PRO-specific protocol items. Non-reporting of PRO results is undoubtedly emerging as a problem in this field. Schandelmaier and colleagues found only 20% of 173 oncology RCTs with PRO endpoints listed in the protocol subsequently went on to publish the PRO data - again dSome CONSORT-PRO items were reported by most RCTs, for example 75% reported results by PRO domain and 69% of publications discussed PRO results in the context clinical endpoints, yet the limited number of RCTs that reported baseline PROs (36%) and approaches for missing data (42%) is concerning. Failing to report this information, and incomplete reporting generally, can lead to biased interpretation or make it difficult to assess generalisability of results, which in turn may limit the potential for PROs to impact policy decisions and patient care. It must be noted that all of the RCTs included in our review were designed without the benefit of the yet-to-be-finalised SPIRIT-PRO checklist, and many (69%) were published before the release of CONSORT-PRO guidance in 2013. The deficiencies summarised in this paper underscore the value of those checklists. We hope that by identifying these issues, future investigators will take necessary steps towards improving the quality and dissemination of PRO data collected in RCTs.Historically, PROs have had a limited role in oncology labelling claims. The earliest FDA drug approval for oncology was in 1995 , and by Oncology societies and policy makers are now formally recognising the value of PROs. QOL is incorporated into the scoring of the ESMO Magnitude of Clinical Benefit Scale (MCBS) for the management of solid cancers without curative intent, whereby the maximum MCBS score can only be achieved if the therapy “demonstrates improved QOL or delayed deterioration in QOL using a validated scale” as well as superior survival  relevant to our aims.Further work on the impact of PRO protocol content on the quality of data and reporting is needed in other clinical sub-groups for which PROs are of particular importance, and in oncology generally. A similar analysis in a mixed oncology cohort is ongoing as part of the UK Macmillan Cancer Support EPiC study . RelatioThis study provides preliminary evidence that a trial protocol with more complete details on the PRO endpoint may reduce the risk of avoidable missing PRO data. Poor compliance led to non-reporting of PROs for 2 RCTs, meaning that efforts invested into PRO data collection for these RCTs was wasted as the PRO data cannot possibly impact patient care. It also provides evidence that the reporting of PROs requires improvement, particularly reporting of the rates, reasons and impact of missing PRO data. Given that rates of avoidable and informative missing PRO data were quite high in this sample, clear reporting is crucial and should include a transparent discussion of generalisability concerns in light of avoidable and informative missing data. Investigators should refer to the forthcoming SPIRIT-PRO Extension  to develAdditional file 1: Appendix 1.PRO protocol checklist CONSORT-PRO scoring sheets. (DOCX 27 kb)Additional file 2: Appendix 2.List of Included RCTs. (DOCX 21 kb)Additional file 3: Appendix 3. Supplementary plots. (DOCX 135 kb)


PLAU (the uPA gene) and C10orf55, a gene of unknown function. QPD increases uPA in platelets and megakaryocytes >100 fold, far more than expected for a gene duplication. To investigate the tissue-specific effect that PLAU duplication has on gene expression and transcript structure in QPD, we tested if QPD leads to: 1) overexpression of normal or unique PLAU transcripts; 2) increased uPA in leukocytes; 3) altered levels of C10orf55 mRNA and/or protein in megakaryocytes and leukocytes; and 4) global changes in megakaryocyte gene expression. Primary cells and cultured megakaryocytes from donors were prepared for quantitative reverse polymerase chain reaction analyses, RNA-seq and protein expression analyses. Rapidly isolated blood leukocytes from QPD subjects showed only a 3.9 fold increase in PLAU transcript levels, in keeping with the normal to minimally increased uPA in affinity purified, QPD leukocytes. All subjects had more uPA in granulocytes than monocytes and minimal uPA in lymphocytes. QPD leukocytes expressed PLAU alleles in proportions consistent with an extra copy of PLAU on the disease chromosome, unlike QPD megakaryocytes. QPD PLAU transcripts were consistent with reference gene models, with a much higher proportion of reads originating from the disease chromosome in megakaryocytes than granulocytes. QPD and control megakaryocytes contained minimal reads for C10orf55, and C10orf55 protein was not increased in QPD megakaryocytes or platelets. Finally, our QPD megakaryocyte transcriptome analysis revealed a global down regulation of the interferon type 1 pathway. We suggest that the low endogenous levels of uPA in blood are actively regulated, and that the regulatory mechanisms are disrupted in QPD in a megakaryocyte-specific manner.Quebec Platelet disorder (QPD) is a unique bleeding disorder that markedly increases urokinase plasminogen activator (uPA) in megakaryocytes and platelets but not in plasma or urine. The cause is tandem duplication of a 78 kb region of chromosome 10 containing  Urokinase-type plasminogen activator (uPA) is an important activator of fibrinolysis. The uPA from blood cells is important for fibrinolysis as bone marrow transplantation corrects the fibrinolytic defect of uPA deficient mice . NormallPLAU (the uPA gene) during megakaryocyte differentiation [in vivo [The fibrinolytic abnormalities of QPD are unique: the disorder selectively increases platelet uPA without triggering systemic fibrinolysis , 7, 8, dntiation , 9, 10. ntiation , it has ntiation , 11, 12.[in vivo , 9. In Q[in vivo . Immunoein vivo leads to markedly increased storage of uPA in alpha-granules, consumption of active PAI-1 in platelets and intra-platelet plasmin generation with secondary proteolysis of diverse alpha-granule proteins [A better understanding of the genetic mechanisms underlying QPD would provide direct tissue-specific insights into how fibrinolysis is regulated and altered by disease. Persons with this disorder suffer from bleeding symptoms and delayed wound healing that respond well to treatment with fibrinolytic inhibitors , suggestproteins , 7. The proteins . When acproteins  from theproteins .PLAU [PLAU and C10orf55, the latter being antisense to PLAU [PLAU from the disease chromosome in megakaryocytes, based on allele-specific, real-time, reverse transcription, polymerase chain reaction (qRT-PCR) analysis of expressed single nucleotide polymorphisms (SNP) [C10orf55 have not been studied.QPD is linked to PLAU  and it i to PLAU . PersonsC10orf55 functions are unknown, but could include PLAU regulation, based on large regions of complementary sequences. While uPA mRNA levels in QPD hematopoietic stem cells and saliva cells are consistent with PLAU duplication, the >100 fold increase in uPA mRNA and protein levels in day 13 cultured QPD megakaryocytes and in QPD platelets [C10orf55. While indirect evidence suggests that QPD platelets account for most of the increased uPA in QPD blood [latelets , 15 grealatelets . We ask PD blood , QPD leuPLAU in megakaryocytes, we investigated if QPD leads to: 1) markedly increased levels of PLAU transcripts and uPA in leukocytes, and specifically, in cells of the granulocyte and monocyte lineages as like megakaryocytes, these cells are derived from myeloid differentiation of a common hematopoietic progenitor cell; 2) overproduction of specific PLAU transcripts by the disease chromosome; 3) altered levels of C10orf55 mRNA and protein in megakaryocytes/platelets and/or leukocytes and 4) global gene expression differences in megakaryocytes. We found that QPD dysregulates PLAU, but not C10orf55, and selectively increases production of normal PLAU transcripts from the disease chromosome in megakaryocytes but not leukocytes. We also found that QPD is associated with downregulation of the interferon type 1 pathway in the megakaryocyte transcriptome.To further determine if QPD selectively dysregulates The studies were conducted in accordance with the revised Helsinki Declaration with approval from the Hamilton Integrated Research Ethics Board and the Centre Hospitalier Universitaire Sainte Justine Research Ethics Board. All participants provided written informed consent.Peripheral blood samples (≤200 mL/donation) were collected by multiple donations from 7 QPD subjects and 10 controls . Peripheral blood that was used to rapidly prepare total leukocyte RNA using LeukoLOCK™ Total RNA System kits  was collected into 6 ml BD Vacutainer® tubes  containing EDTA. For platelet and CD34+ cell isolation [g for 15 min, twice) to minimize leukocyte contamination. Platelets were pelleted (1200 x g for 12 min), washed once with ~30–40 mL of wash buffer  before solubilizing samples for protein and molecular analyses.Blood platelets were isolated from the upper two thirds of platelet rich plasma (PRP) by double centrifugation  to isolate CD66b+ (granulocytes) and CD3+ (T-lymphocytes) cells from blood and CD14+ cells (monocytes) from buffy coats. Flow cytometry was used to validate that the method yielded acceptable purities (>90%) of harvested cells, as described [For most experiments, peripheral blood leukocytes were harvested by immuno-magnetic separation using EasySepurities >0% of harTM SFEM II media and Megakaryocyte Expansion Supplement containing cytokines were used, as recommended by STEMCELL Technologies, and megakaryocytes were harvested on day 14. Harvested megakaryocytes were assessed for acceptable viability and differentiation by flow cytometry and ELISA, as previously described [Megakaryocytes were grown in liquid culture from peripheral blood CD34+ cells, as described , except escribed . For eacescribed .9 platelets/mL; WBC 106/mL or 107/mL). For RNA analysis, cell pellets of washed platelets, cultured megakaryocytes and affinity purified leukocytes were dissolved in TRIzol® Reagent  followed by total RNA isolation (as recommended by the manufacturer) then treatment with RNAse-free DNAse before confirming RNA quantity and quality [For protein analysis, cell pellets were solubilized in Tris-saline containing 1.0% Triton X-100 and protease inhibitors as described  , C10orf55 , VWF  and TFPI2 . As platelets are far more abundant than leukocytes in blood, the percentage of platelet contamination in leukocyte preparations (collected at least twice/QPD donor) was estimated using each donor’s VWF data for platelets and affinity purified granulocytes, monocytes and T-lymphocytes. Affinity purified leukocytes were excluded from uPA determinations if their estimated platelet contamination (based on VWF levels) exceeded 15% and results were averaged if multiple samples from a donor were acceptable.http://antibodyregistry.org/search?q=ps074); secondary: 1:25,000 Peroxidase AffiniPure Donkey Anti–Rabbit IgG . Cellular uPA was analyzed non-reduced and reduced using the following quantities of lysate and purified proteins: platelet lysates (109/mL): 5 and 15 μl; granulocyte lysates (107/mL): 25 and 52 μl; monocyte lysates (107/mL): 35 and 50 μl; purified proteins , followed by Western blotting, as described , 9 usingRT was performed using High-Capacity RNA-to-cDNA kits  by incubating total RNA in a Thermocycler  with recommended RT Kit components and 20 units RNasin® Plus RNase Inhibitor .PLAU expression, qPCR was performed using the Applied Biosystems ViiA™ 7 Real-Time PCR System and TaqMan® Gene Expression Assays  as recommended, using included primers. Simultaneous analysis of the endogenous control housekeeping genes glyceraldehyde 3-phosphate dehydrogenase (GAPDH), TATA box binding protein  and hypoxanthine guanine phosphoribosyl transferase 1 (HPRT1) was used to correct for potential variations in template RNA, RT and qPCR efficiencies. qPCR singleplex reaction mixtures included: 2 μL cDNA, 7.5 μL TaqMan® Gene Expression Master Mix (containing DNA polymerase), 0.75 μL 20× TaqMan® Gene Expression Assay reagents and 4.75 μL RNAse-free water. Assays were done in triplicate (duplicate if limited cDNA) in 96-well TaqMan® optical reaction plates, with no-template and no RT controls. Data were evaluated using ViiA™ 7 Software. PLAU expression, relative to the endogenous control genes TBP , GAPDH and HPRT1, was calculated using the efficiency corrected method of Pfaffl [TFPI2, samples were submitted to The Center for Applied Genomics  for droplet digital PCR (ddPCR) [TBP as an endogenous control for TFPI2.To evaluate To evaluate transcripts generated by the region of the QPD duplication, including the QPD breakpoint, approximately 1 μg of total RNA/sample from 3 control and 3 QPD samples of day 14 cultured megakaryocytes and affinity purified granulocytes was prepared. The quality of total RNA samples was checked on an Agilent Bioanalyzer 2100 RNA Nano chip  following recommendations. RNA library preparation was performed following the NEB NEBNext Ultra Directional Library Preparation protocol . Briefly, 100–500 ng of total RNA was used as the input material and enriched for poly-A mRNA, fragmented into the 200-300-bases range for 4 minutes at 94°C and converted to double stranded cDNA, end-repaired and adenylated at the 3’ to create an overhang A to allow for ligation of Illumina adapters with an overhang T; library fragments were amplified under the following conditions: initial denaturation at 98°C for 10 seconds, followed by 10 cycles of 98°C for 10 seconds, 60°C for 30 seconds and 72°C for 30 seconds, and finally an extension step for 5 minutes at 72°C; at the amplification step, each sample were amplified with a different barcoded adapters to allow for multiplex sequencing. 1 μl of the final RNA libraries was loaded on a Bioanalyzer 2100 DNA High Sensitivity chip (Agilent Technologies) to check for size; RNA libraries were quantified by qPCR using the Kapa Library Quantification Illumina/ABI Prism Kit protocol . Libraries were pooled in equimolar quantities and paired-end sequenced on a Rapid Run Mode flowcell with the V3 sequencing chemistry on an Illumina HiSeq 2500 platform  following Illumina’s recommended protocol to generate paired-end reads of 100-bases in length. Sequencing and library preparation were performed by TCAG. Two of the three QPD subjects provided both cell types.RNA-seq libraries were sequenced to a depth of ~23 million paired-end 100 bp reads. Reads were dynamically trimmed based on quality using Trimmomatic  and aligF:TGCCACACAGAGTGGTCTTT; R:CTCTACCTCCCAAAGCTCCAT) and genotyped by Sanger sequencing, as described [To determine the rs2227574 allele associated with QPD, DNA from 38 QPD subjects  wasescribed .The Mann Whitney U test was used to compare QPD and control protein and qPCR data. ANOVA were used to compare multiple cell types. p values <0.05 were considered significant. All tests were two sided.Gene level raw counts for RNA-seq data were obtained using htseq-count with mode = intersection-strict and GENCODE V19 annotation . Genes w6 cells; QPD <25–65 pg/106 cells, not shown).While indirect evidence suggests that QPD platelets account for most of the increased uPA in QPD blood , we studWestern blots indicated that the uPA in QPD and control leukocytes had the same mobility and confirmed that the amount of uPA was only modestly increased in QPD granulocyte and monocytes . On non-PLAU rs4065 , unlike the marked overexpression of PLAU by the disease chromosome in QPD megakaryocytes, which were included in the analyses as a known abnormal control : 3.9, PLAU transcript levels were higher in affinity purified QPD granulocytes and monocytes compared to control cells  had reliable coverage across all annotated splice junctions in QPD and control megakaryocytes   .PLAU represented only ~1–9% of all reads at the PLAU locus in all samples evaluated by RNA-seq  mapped to unannotated regions downstream of C10orf55  and the final exon  analysis of control versus QPD megakaryocytes identified a total of 32 significantly DE genes  (LOX), megakaryocyte-erythroid transcription factors , cell surface markers , and alpha-granule proteins . Megakaryocyte markers showed elevated expression in megakaryocytes versus granulocytes and did not significantly differ between QPD and control samples (in vitro differentiation was comparable between control and QPD cultured megakaryocytes (Although our study was designed to look at  < 0.05)  that did < 0.05) . Among t < 0.05) , the gen plasmin , 30 thatryocytes . Some DE (TMEM56). We furt (TMEM56). These i samples . Furtherryocytes . Gene seryocytes . In contEGR1, which was ~ 8-fold upregulated compared to controls . Third, affinity purified QPD granulocytes and monocytes contained minimally increased uPA (levels: ~2–5 fold greater than controls), unlike QPD megakaryocytes and platelets (levels: >100 fold greater than controls). Fourth, we observed an abundance of PLAU intronic reads in affinity purified QPD granulocytes, which is known to occur during acute gene transcription [The molecular mechanism underlying the much greater than expected increases in both uPA mRNA and protein during QPD megakaryopoiesis is not well understood (12). As other hematopoietic lineages, and the other duplicated gene, cription , 35  (4) and our new observations that the uPA in QPD granulocytes and monocytes also had a normal mobility. We did observe some differences in the non-reduced and reduced profile of QPD platelet and leukocyte uPA, likely due to cell-type specific differences in extent of uPA proteolysis and in sizes of proteins that formed complexes with uPA  [C10orf55 does not explain the increased PLAU expression in QPD. We detected no reads spanning annotated splice junctions in the C10orf55 gene model (GENCODE v19) [PLAU in QPD granulocytes did not map to the annotated exon of C10orf55  , the dupODE v19) . As the PLAU transcript levels in QPD compared to control total blood leukocyte RNA (prepared after rapid filter capture), that were within the range expected for a gene duplication [PLAU expression by megakaryocytes but not by leukocytes. The handling of blood samples ex vivo is known to alter leukocyte transcripts, and induce expression of some genes [PLAU expression by both QPD chromosomes ex vivo, implicating a different mechanism than the defect that upregulates PLAU expression in QPD megakaryocytes in vivo. The greater platelet contamination of QPD leukocyte preparations, despite the lower QPD platelet counts, likely reflects proportionately more platelet attachment to leukocytes in QPD samples despite their processing with inhibitors of fibrinolysis and platelet activation. As we excluded leukocytes samples with ≥15% platelet contamination when analyzing uPA, and as platelets are much smaller and have a much lower RNA content than leukocytes [ITGA2B and ITGB3. It is nonetheless possible that increased plasmin generation during the processing of QPD samples increased platelet activation, platelet adhesion to leukocytes, and leukocyte activation, as plasmin is known to activate platelet and leukocytes, and activated platelets bind to leukocytes [Our observation that there were minimal increases in lication , illustrme genes . It was ukocytes , we suggukocytes –45.TFPI2 in megakaryocytes is of potential interest as TFPI2 is a plasmin inhibitor [TFPI2 expression is unlikely to have major contributions to QPD pathology. While it is possible that TFPI2 expression in other cell types may be of relevance, RNA-seq data from 8 blood cell types recently profiled by the BLUEPRINT consortium [TFPI2 expression in blood cells is limited to megakaryocytes and hematopoietic progenitor cells. Likewise, we did not detect reads for TFPI2 in any of our granulocyte RNA-seq datasets. Gene set enrichment analysis revealed an enrichment of genes involved in type I interferon signaling, amongst genes showing decreased expression in QPD versus control megakaryocytes. Given that both urokinase-plasminogen receptor (uPAR) and type I interferon signaling act through JAK-activation of STAT1/STAT2 to initiate transcriptional responses [PLAU and consequent uPAR activation may lead to feedback control of STAT responsive gene expression. The increased expression of the transcriptional regulator EGR1 in QPD megakaryocytes is interesting as EGR1 is involved in the regulation of uPA, and overexpression of EGR1 has been shown to down-regulate uPA and uPAR in osteosarcomas [EGR1 in QPD reflects a feedback mechanism to compensate for increased levels of uPA and uPAR signaling. Interestingly, we did not observe significant differences in the expression of EGR1 nor other interferon response genes between QPD and control granulocytes. One possible explanation is that these changes in the expression of TFPI2, EGR1 and other genes in QPD megakaryocytes are due to long-term exposure to high (>100-fold increased) levels of uPA in QPD megakaryocytes [EGR1 is normal in QPD megakaryocytes and unlikely to explain differences in transcript abundance. We had insufficient reads for similar analysis of TFPI2 in QPD megakaryocytes. However, as individuals with QPD are closely related, we cannot rule out that genetic factors other than the PLAU duplication contributed to the observed differences in the expression of interferon response genes and other genes  between QPD and control subjects. The modest differences between the QPD and control subject populations support that: a) our cultured megakaryocyte differentiation procedure was robust; b) we had the power to detect changes in lowly expressed megakaryocyte genes; and c) that the phenotype of QPD megakaryocytes is similar to non-affected individuals at the level of the transcriptome. While more replicates and megakaryocytes from unaffected family members would be necessary to further study the biological effect of increased PLAU on megakaryocytes, our results underscore the clinical observation that QPD megakaryocytes are phenotypically normal apart from their fibrinolytic defect.The analysis of transcriptome-wide changes with RNA-seq identified modest differences in gene expression between control and QPD megakaryocytes. Notably, canonical megakaryocyte markers and transcripts for megakaryocyte-produced alpha-granule proteins did not differ significantly. These observations are consistent with the previous finding that alpha-granule protein changes in QPD are due to proteolytic degradation rather than altered expression. The observed differences in the expression of nhibitor . Howevernsortium  suggestsesponses –49, we ssarcomas . It is pPLAU, but not C10orf55, by a mechanism that is specific to megakaryocyte, but not granulocyte or monocyte differentiation, and selectively increases production of normal PLAU transcripts (but not C10orf55 transcripts) from the disease chromosome beyond the level expected for a gene duplication mutation. Further clues about the molecular pathogenesis underlying QPD will likely require a detailed epigenomic analysis of the PLAU locus in QPD and control megakaryocytes. Future studies will need to compare epigenomic findings for QPD megakaryocytes to QPD hematopoietic cells that do not show marked overexpression of PLAU by the disease chromosome, to help identify the regulatory changes that are unique to QPD megakaryocytes.Our current study provides important new direct evidence that the QPD gene regulatory defect specifically and selectively dysregulates PLAU in megakaryocytes but not in leukocytes, leading to increased production of normal PLAU transcripts by megakaryocytes that far exceed the modest increases expected for a gene duplication mutation. The observation that QPD dysregulates PLAU but not C10orf55 (the other duplicated gene) in megakaryocytes, and that QPD increases production of normal PLAU transcripts from the disease chromosome in megakaryocytes [PLAU transcript levels underlies the pathogenesis of QPD.The QPD duplication mutation selectively dysregulates S1 FigTop: individual signal tracks  are shown at a fixed (log transformed) scale. Bottom: Same as top panel, except scales are adjusted to reflect the highest value within the viewing range. Paired samples from the same individual have the same numeric identifier.(EPS)Click here for additional data file.S2 FigPanels A and B compares data for QPD vs control megakaryocytes (A) and granulocytes (B) evaluated using JunctionSeq, with the relative expression level for each tested exon and splice junction normalized to compensate for differences in gene expression, which are shown as gene-level expression values. Data were plotted as described in the legend to (EPS)Click here for additional data file.S3 FigTFPI2 and EGR1 genes. Normalization, samples, and color coding as described in the legend to TFPI2 is shown on a linear scale. Panel C shows junctionSeq analysis of EGR1 for megakaryocytes and granulocytes . Axes and labels are as described in the legend to Panels A and B show UCSC genome browser sessions of normalized RNA-seq signal for the (EPS)Click here for additional data file.S1 Supporting Information(PDF)Click here for additional data file.S2 Supporting InformationThis spreadsheet contains 6 tables. Tables A and B contain the results of DE analysis with DESeq2 for QPD versus control megakaryocytes and granulocytes, respectively. Tables C-F contain the gene set enrichment analysis results using for top 10 enriched pathways/terms for downregulated and upregulated genes in megakaryocytes and granulocytes, respectively.(XLSX)Click here for additional data file.


This case will illustrate the clinical and unique technical challenges, not previously reported, in a patient with a history of progressive left ventricular (LV) systolic dysfunction, congestive heart failure (CHF), myocardial infarction (MI), and a complex bifurcation lesion of the left subclavian artery (SA) involving the left internal mammary artery (LIMA) in the setting of coronary subclavian steal syndrome (CSSS). The approach to this lesion is complicated by significant LIMA involvement requiring intervention directed toward both the SA and the LIMA in the presence of severe LV systolic dysfunction. This clinical scenario necessitates a careful technique, utilizing bifurcation methods similar to those used in coronary intervention. Coronary subclavian steal syndrome (CSSS), first described in 1974, is characterized by a stenotic proximal left subclavian artery (SA) causing reversal of flow in the LIMA resulting in a “steal” phenomenon , 3. The A 75-year-old Caucasian male was referred for evaluation with the following history: coronary artery bypass grafting (CABG) with left internal mammary artery (LIMA) to left anterior descending (LAD) and sequential saphenous vein grafting (SVG) to ramus, obtuse marginal, right posterolateral and right posterior descending arteries, repeat CABG two years later with revision of the SVG, severe peripheral arterial disease (PAD) with a history of left lower extremity surgical revascularization, right iliac artery occlusion, atherosclerotic carotid artery disease, and chronic kidney disease (CKD) Stage III. He had been hospitalized for the treatment of CHF and non-ST elevation myocardial infarction (NSTEMI) within the prior three months and continued to experience increasing angina and dyspnea on exertion (NYHA Class III), which was refractory to medications. He was noted to have had a decrease in LV ejection fraction by echocardiogram from 45% to 15% and underwent cardiac catheterization.Cardiac catheterization revealed a patent sequential SVG and severe disease of the body of the SA, distal to the left vertebral artery, and involving the LIMA . The lesA 6 Fr FR 4.0 Medtronic Launcher coronary guide catheter was placed via the left femoral artery (LFA) into the proximal SA, and a 6-French IMA Medtronic Launcher coronary guide catheter was placed via the left radial artery (LRA) into the SA distal to the LIMA origin. Initial attempts to cross the diffusely calcific SA stenosis anterograde via the LFA, using multiple wire sizes and tips, were unsuccessful. A 0.018 Terumo Glidewire Advantage wire was then placed retrograde via the LRA across the SA stenosis and into the ascending aorta. A 0.014 Terumo Runthrough NS Hypercoat coronary guidewire was placed from the LFA into the LIMA . The SA A 0.014 Terumo Runthrough NS Hypercoat coronary guidewire was then placed from the LRA through the stent struts into the LIMA. The coronary guidewire which had been placed into the LIMA from the LFA was removed. A 0.035 Terumo Glidewire Advantage wire was then placed from the LFA into the SA.The stent struts were then dilated via the LRA, and a 3 mm × 12 mm drug-eluting stent  was easily passed through. A 5 mm × 15 mm noncompliant balloon  was then placed into the SA stent via the LFA, and a small portion of the LIMA stent was pulled back into the SA stent in order to perform “T and small Protrusion” or TAP stenting  of the SThe patient was symptom free with improved LV ejection fraction to 30% by echocardiography at 6 months.Subclavian artery stenosis (SAS) is found in up to 18% of patients with PAD . ProximaEndovascular treatment of SAS has evolved into first-line therapy. Balloon expandable stents have been associated with low periprocedural complication rates. In addition, ten-year patency and event-free survival appear comparable to surgical treatment of SAS , 9.The case described is anatomically unique due to the presence of extensive atherosclerosis of the subclavian/LIMA bifurcation resulting in severe ischemia leading to progressive LV systolic dysfunction and congestive heart failure. This complex bifurcation anatomy creates not only substrate for CSSS but compromises inflow to and outflow from the LIMA, likely compounding the severity of the LAD territory ischemia causing significant cardiac compromise .The lesion was classified as a Medina 1,1,1 bifurcation type  using thAccessing the lesion from both the proximal and distal SA (MB) provided a unique approach to bifurcation stenting, which is not available in the coronary tree. The decision to utilize a two-stent technique was based on the large size of the SB (LIMA) with disease extending greater than 5 mm from the carina into the SB . The “T


RNA and DNA sequencing data are traditionally used to discern intrinsic cellular pathways in cancer pathogenesis, their utility for investigating the tumor microenvironment (TME) has not been fully explored. This study explores the use of sequencing data to investigate immunity within the TME.Here, we use immune cell fraction estimation analysis to determine the immune profiles in the microenvironment of neuroblastoma (NB) based on RNA-seq data in the TARGET database. The correlation between immune cell transcripts and prognosis in pediatric NB is also investigated.In silico analysis revealed a strong inverse correlation between MYCN amplification and leukocyte infiltration. This finding was validated by immunohistochemistry analysis in tumor samples. Moreover, the abundance of CD4 T cells strongly associated with better patient survival regardless of MYCN gene amplification, while those of CD8 T cells, NK or B cells do not. Based on characteristic cytokine expression of CD4 subsets in tumors, the Th2 rather than Th1 levels were associated with better prognosis.in silico analysis of TARGET database reflected tumor immunity and was validated by the immunohistochemical tumor data. Our results reveal the association of MYCN amplification with repressed cellular immunity and the potential prognostic value of infiltrating CD4 T cell transcripts in pediatric NB. This analysis illustrates the potential role of MYCN in NB as a regulator of immune privilege and characterizes the power of in silico analysis for delineating cancer immunology and risk stratification.We found that the  MYCN amplification and unbalanced 11q aberration have emerged as the dominant factors in risk assignment (Neuroblastoma (NB) is among the most common cancers in childhood. More than 90% of NB are diagnosed prior to 5 years of age, in which the prognosis of NB varies greatly based on risk stratification –3. WhileThe theory of immune surveillance, as originally proposed by Burnet, predicts that immune response is a key determinant of cancer risk . In a 19MYCN amplified and non-amplified tumors. We also observed the unexpected association between MYCN gene amplification and lack of inflammatory profiles suggesting the impact of MYCN gene amplification in repressing NB host immunity. These findings were verified by selective immunohistochemistry in patient samples. Furthermore, these data show the power of in silico analysis for cancer immunology and raises the intriguing possibility of assigning cancer risk based on nextgen RNA-seq data.Whole genome sequencing of tumor samples is now routinely performed for cancer samples. The wealth of data collected from these studies allows one to unveil molecular pathogenesis of cancer cells. Since host inflammatory cells are now considered an integral part of the tumor microenvironment (TME), it is inevitable that deep sequencing of cancer tissues will also capture information of inflammatory cells. CIBERSORT is a recently reported computational approach that uses gene expression profiles to estimate relative fractions of diverse cell subsets in complex tissues, including tumors , 9. The via accession phs000471. A total of 148 NB patients were included based on availability detailed RNA-seq FPKM data, survival time after diagnosis, risk assignment, and MYCN-amplification status. The demography, risk stratification of NB with or without MYCN amplification were summarized in Table The TARGET initiative provides sequencing data and de-identified clinical information of cancer patients (available through the TARGET Data Matrixn = 148) were input as a Mixture file and 500 permutations were performed. The percentage data of 22 immune cell types in each patient were transferred into the cell fraction of tumor by normalization with the ratio of CD45 and ACTB expression value. Additionally, 22 human hematopoietic cell phenotypes were merged into 16 immune cell types as follows: naive and memory B cells were merged into B cells; naïve, memory, resting, and activated CD4 T cells were merged into CD4 T cells; NK cells resting and NK cells activated were merged into NK cells; dendritic cells resting and dendritic cells activated were merged into DC cells; while mast cells resting and mast cell activated were merged into mast cells.The online analytic tool, CIBERSORT (Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts), was used according to the instruction provided by the developers.hiCD45 and loCD45 groups with the threshold (FPKM = 7.5) based on its bimodal distribution of RNA-seq data . Gene expression levels were normalized based on actin expression and samples were divided into higher ratio (above the upper quartile) and lower ratio (below the lower quartile) groups based on RNA-seq data. For other parameters, the samples were divided into lower cell fraction  and higher cell fraction  groups based on their data distribution of estimated cell fraction .For CD45 expression, the NB samples were divided into Gene set enrichment analysis version 2.3.0n = 3), intermediate (n = 6), and high (n = 6) risk NB. Diagnosis and staging were performed according to Children’s Oncology Group protocols. Biopsies were taken at the time of diagnosis and prior to initiation of any therapy. Specimen collection was obtained with the appropriate research consent (and assents when applicable) and was approved by the Institutional Review Board, CNMC, Washington D.C. (Pro00004284).Tumor specimens were obtained from 15 patients diagnosed with low  washing for 5 min. Sections were incubated overnight at 4°C with primary antibodies diluted in blocking buffer (PBS with 5% serum). The following primary antibodies were used: CD4 ; CD45 . Isotype-matched antibodies were used for negative controls. After washing with PBS, each section was incubated with 1:200 diluted biotinylated secondary antibodies  for 1 h at room temperature. Secondary antibody was detected with Vectastain ABC reagent , and 3′3′diaminobenzidine substrate (Sigma). Slides were washed in tap water for 5 min and then counterstained with hematoxylin (Sigma) for 30 s. Following counterstaining, slides were washed in tap water for 5 min, dehydrated (95 and 100% ethanol), transferred to 100% xylene, and mounted. Brightfield immunohistochemical images were acquired with a Nikon Eclipse E800 microscope (Nikon Corp.). Images were taken at magnifications of ×100.Thirty to forty randomly selected fields in each stained specimen were imaged under ×100 magnification. Quantification of positive staining intensity was achieved using Olympus cellSens imaging software (version 1.7). The positive staining intensity and the area of tumor tissue were measured. The positive staining intensity in each field was measured using a manual threshold setting. Measurements were made by the same person who was blinded to the clinical stage or characteristics of the tumor specimen. Data are presented as the mean positive staining intensity of all the fields for each specimen.2 test for contingency table. In the graphs, y-axis error bars represent SEM as indicated. Statistical calculations were performed using GraphPad Prism software  or R Software.The specific tests used to analyze each set of experiments are indicated in the figure legends. Data were analyzed using an unpaired Mann–Whitney test to compare between two groups, and χMYCN amplification among patients in the TARGET database. The patients with or without MYCN amplification are similar in age at diagnosis, gender distribution  and separation of the two groups suggest that lack of statistical significance may be due to a limited number of hiCD45 samples as the TARGET samples are biased toward high-risk group stratification. Combining MYCN non-amplification and hiCD45 parameters identified a group of NB patients with better survival   Figure C.hiCD8B and loCD8B NB patients show nearly identical overall survival . When the staining of CD45 and CD4 was integrated digitally, it is clear that high-risk NB samples (including MYCN amplified and non-amplified) had reduced CD4 and CD45 staining .CD4 T cells can be divided into regulatory and effector T cells. Since our preliminary analysis suggest no correlation between Treg subsets (data not shown), we focused on effector CD4 cells. CD4 T cells differentiated into multiple functional subsets including Th0, Th1, Th2, Th9, and Th17 among others, each characterized by their cytokine profiles and their master transcriptional regulators. Since most master regulators are prominently expressed in cancer cells, we decide to use their characteristic cytokines to discern the functional subsets associated with NB prognosis. As shown in Figures in silico analysis from a sequence database, we investigated NB from the perspective of immune cell transcript infiltrates and the association with outcome. It was clear that CD4 transcripts were associated with better outcomes in which a high transcript was associated with improved survival. This correlated with immunohistochemistry for CD4 cellular infiltrates in which tumors with poor prognosis and high risk had a lower CD4 cellular infiltrate in tumors. Though it is established in a number of tumor types that components of immune infiltration into the tumor plays a critical role in cancer prognosis  and was approved by the Institutional Review Board, CNMC, Washington D.C. (Pro00004284). All information obtained was protected and de-identified.PengZ mined data, performed analysis, and manuscript preparation. XW performed experiments and manuscript preparation. MB performed experiments. CD and PanZ reviewed data and manuscript preparation. YL and AS formulated concept, reviewed data, and manuscript preparation.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer MG and handling editor declared their shared affiliation.