The Immune Landscape of Cancer

We performed an extensive immunogenomic anal-ysis of more than 10,000 tumors comprising 33diverse cancer types by utilizing data compiled byTCGA. Across cancer types, we identified six im-mune subtypes\u2014wound healing, IFN-gdominant,inflammatory, lymphocyte depleted, immunologi-cally quiet, and TGF-bdominant\u2014characterized bydifferences in macrophage or lymphocyte signa-tures, Th1:Th2 cell ratio, extent of intratumoral het-erogeneity, aneuploidy, extent of neoantigen load,overall cell proliferation, expression of immunomod-ulatory genes, and prognosis. Specific drivermutations correlated with lower (CTNNB1,NRAS,orIDH1) or higher (BRAF,TP53,orCASP8) leukocytelevels across all cancers. Multiple control modalitiesof the intracellular and extracellular networks (tran-scription, microRNAs, copy number, and epigeneticprocesses) were involved in tumor-immune cell inter-actions, both across and within immune subtypes.Our immunogenomics pipeline to characterize theseheterogeneous tumors and the resulting data areintended to serve as a resource for future targetedstudies to further advance the field

Psychometric properties of the Screen for Child Anxiety Related Emotional Disorders (SCARED) in Cypriot children and adolescents

The Screen for Child Anxiety Related Emotional Disorders (SCARED) is a 41-item self-report questionnaire that measures symptoms of DSM-IV anxiety disorders (panic/somatic, generalized anxiety, separation anxiety, social phobia) and school phobia in children and adolescents. This study examined the psychometric properties of the Greek translation of SCARED in a large community sample of children and adolescents (N = 1,072), aged 12 to 17 years, in the nonoccupied territory of Cyprus. A subsample of these participants (N = 108) was retested an average of 8 weeks after the initial assessment. The SCARED demonstrated high internal consistency (α = .92) and test-retest reliability (r = .84, over 8 weeks). The SCARED total scores correlated significantly with the internalizing factor of the Youth Self-Report, the Columbia Impairment Scale, and with the emotional subscale of the Strength and Difficulty Questionnaire. Confirmatory factor analyses revealed the same five-factor structure as the original SCARED. The SCARED proved to be a reliable and valid measure of anxiety symptoms in the Cypriot context

Impact of pregabalin treatment on pain, pain-related sleep interference and general well-being in patients with neuropathic pain: A non-interventional, multicentre, post-marketing study

Background and Objectives: Numerous controlled clinical trials have demonstrated the safety and efficacy of pregabalin in the treatment of neuropathic pain. The objectives of the present study were to assess the impact of pregabalin under real-world conditions on pain, pain-related sleep interference and general well-being, and to assess the tolerability and safety of pregabalin in patients diagnosed with neuropathic pain of central or peripheral origin. Methods: This was a non-interventional, multicentre study in which pregabalin was administered for 8 weeks, at the therapeutic dosages of 150600mg/day, to patients with a diagnosis of neuropathic pain. Pain intensity and pain-related sleep interference were measured using 11-point numerical rating scales, while well-being was assessed by documenting how often emotions associated with anxiety or depression were felt over the past week. Patient and Clinician Global Impression of Change (PGIC and CGIC) were assessed at the final visit. Results: In the 668 patients included in the full analysis set, there were significant (p < 0.0001) reductions in mean pain and pain-related sleep interference scores of 4.16 and 4.02, respectively. Indicators of general well-being showed improvement from baseline to final visit. The majority of patients were rated as much improved (43.7% and 36.7%) or very much improved (24.0% and 26.2%) on CGIC and PGIC scores, respectively. Discontinuation because of lack of efficacy occurred in 0.7% of 691 patients in the safety analysis set while discontinuation because of adverse events occurred in 5.1% of this population; 76.4% continued treatment after the study ended. Conclusion: Significant reductions in pain and pain-related sleep interference, combined with reductions in feelings of anxiety and depression, suggest that pregabalin under real-world conditions improves the overall health and wellbeing of patients with neuropathic pain. © 2011 Adis Data Information BV. All rights reserved

The Immune Landscape of Cancer

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes\u2014wound healing, IFN-\u3b3 dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-\u3b2 dominant\u2014characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field. Thorsson et al. present immunogenomics analyses of more than 10,000 tumors, identifying six immune subtypes that encompass multiple cancer types and are hypothesized to define immune response patterns impacting prognosis. This work provides a resource for understanding tumor-immune interactions, with implications for identifying ways to advance research on immunotherapy

The Immune Landscape of Cancer (Immunity (2018) 48 (812–832), (S1074-7613(18)30121-3), (10.1016/j.immuni.2018.03.023))

(Immunity 48, 812–830.e1–e14; April 17, 2018) In the originally published version of this article, the authors neglected to include Younes Mokrab and Aaron M. Newman as co-authors and misspelled the names of authors Charles S. Rabkin and Ilya Shmulevich. The author names have been corrected here and online. In addition, the concluding sentence of the subsection “Immune Signature Compilation” in the Method Details in the original published article was deemed unclear because it did not specify differences among the gene set scoring methods. The concluding sentences now reads “Gene sets from Bindea et al., Senbabaoglu et al., and the MSigDB C7 collection were scored using single-sample gene set enrichment (ssGSEA) analysis (Barbie et al., 2009), as implemented in the GSVA R package (Hänzelmann et al., 2013). All other signatures were scored using methods found in the associated citations.

Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

The RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of Te, Tiand nehave been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks