Negligible In Vitro Recovery of Macromolecules from Microdialysis Using 100 kDa Probes and Dextran in Perfusion Fluid

Microdialysis is applied in neurointensive care to monitor cerebral glucose metabolism. If recoverable, macromolecules may also serve as biomarkers in brain disease and provide clues to their passage across the blood-brain barrier. Our study aimed to investigate the in vitro recovery of human micro- and macromolecules using microdialysis catheters and perfusion fluids approved for clinical use. In vitro microdialysis of a bulk solution containing physiological or supraphysiological concentrations of glucose, lactate, pyruvate, human IgG, serum albumin, and hemoglobin was performed using two different catheters and perfusion fluids. One had a membrane cut-off of 20 kDa and was used with a standard CNS perfusion fluid, and the other had a membrane cut-off of 100 kDa and was perfused with the same solution supplemented with dextran. The flow rate was 0.3 µl/min. We used both push and push-pull methods. Dialysate samples were collected at 2-h intervals for 6 h and analyzed for relative recovery of each substance. The mean relative recovery of glucose, pyruvate, and lactate was > 90% in all but two sets of experiments. In contrast, the relative recovery of human IgG, serum albumin, and hemoglobin from both bulk solutions was below the lower limit of quantification (LLOQ). Using a push-pull method, recovery of human IgG, serum albumin, and hemoglobin from a bulk solution with supraphysiological concentrations were above LLOQ but with low relative recovery (range 0.9%-1.6%). In summary, exchanging the microdialysis setup from a 20 kDa catheter with a standard perfusion fluid for a 100 kDa catheter with a perfusion solution containing dextran did not affect the relative recovery of glucose and its metabolites. However, it did not result in any useful recovery of the investigated macromolecules at physiological levels, either with or without a push-pull pump system.

JAK2V617F drives gut microbiota differences in patients with myeloproliferative neoplasms

BACKGROUND

Essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (MF) are myeloproliferative neoplasms (MPN). Inflammation is involved in the initiation, progression, and symptomology of the diseases. The gut microbiota impacts the immune system, infection control, and steady-state hematopoiesis.

METHODS

We analyzed the gut microbiota of 227 MPN patients and healthy controls (HCs) using next-generation sequencing. We expanded our previous results in PV and ET patients with additional PV, pre-MF, and MF patients which allowed us to compare MPN patients collectively, MPN sub-diagnoses, and MPN mutations (separately and combined) vs. HCs (N = 42) and compare within MPN sub-diagnoses and MPN mutation.

RESULTS

MPN patients had a higher observed richness (median, 245 [range, 49-659]) compared with HCs (191.5 [range, 111-300; p = .003]) and a lower relative abundance of taxa within the Firmicutes phylum; for example, Faecalibacterium (6% vs. 14%, p < .001). The microbiota of CALR-positive patients (N = 30) resembled that of HCs more than that of patients with JAK2V617F (N = 177). In JAK2V617F-positive patients, only minor differences in the gut microbiota were observed between MPN sub-diagnoses, illustrating the importance of this mutation.

CONCLUSION

The gut microbiota in MPN patients differs from HCs and is driven by JAK2V617F, whereas the gut microbiota in CALR patients resembles HCs more.

A multi-omics systems vaccinology resource to develop and test computational models of immunity

Systems vaccinology studies have identified factors affecting individual vaccine responses, but comparing these findings is challenging due to varying study designs. To address this lack of reproducibility, we established a community resource for comparing Bordetella pertussis booster responses and to host annual contests for predicting patients' vaccination outcomes. We report here on our experiences with the "dry-run" prediction contest. We found that, among 20+ models adopted from the literature, the most successful model predicting vaccination outcome was based on age alone. This confirms our concerns about the reproducibility of conclusions between different vaccinology studies. Further, we found that, for newly trained models, handling of baseline information on the target variables was crucial. Overall, multiple co-inertia analysis gave the best results of the tested modeling approaches. Our goal is to engage community in these prediction challenges by making data and models available and opening a public contest in August 2024.

Building flexible and robust analysis frameworks for molecular subtyping of cancers

Molecular subtyping is essential to infer tumor aggressiveness and predict prognosis. In practice, tumor profiling requires in-depth knowledge of bioinformatics tools involved in the processing and analysis of the generated data. Additionally, data incompatibility (e.g., microarray versus RNA sequencing data) and technical and uncharacterized biological variance between training and test data can pose challenges in classifying individual samples. In this article, we provide a roadmap for implementing bioinformatics frameworks for molecular profiling of human cancers in a clinical diagnostic setting. We describe a framework for integrating several methods for quality control, normalization, batch correction, classification and reporting, and develop a use case of the framework in breast cancer.

Coordinated Immune Cell Networks in the Bone Marrow Microenvironment Define the Graft versus Leukemia Response with Adoptive Cellular Therapy

Understanding how intra-tumoral immune populations coordinate to generate anti-tumor responses following therapy can guide precise treatment prioritization. We performed systematic dissection of an established adoptive cellular therapy, donor lymphocyte infusion (DLI), by analyzing 348,905 single-cell transcriptomes from 74 longitudinal bone-marrow samples of 25 patients with relapsed myeloid leukemia; a subset was evaluated by protein-based spatial analysis. In acute myelogenous leukemia (AML) responders, diverse immune cell types within the bone-marrow microenvironment (BME) were predicted to interact with a clonally expanded population of ZNF683 + GZMB + CD8+ cytotoxic T lymphocytes (CTLs) which demonstrated in vitro specificity for autologous leukemia. This population, originating predominantly from the DLI product, expanded concurrently with NK and B cells. AML nonresponder BME revealed a paucity of crosstalk and elevated TIGIT expression in CD8+ CTLs. Our study highlights recipient BME differences as a key determinant of effective anti-leukemia response and opens new opportunities to modulate cell-based leukemia-directed therapy.

Expression and splicing mediate distinct biological signals

BACKGROUND

Through alternative splicing, most human genes produce multiple isoforms in a cell-, tissue-, and disease-specific manner. Numerous studies show that alternative splicing is essential for development, diseases, and their treatments. Despite these important examples, the extent and biological relevance of splicing are currently unknown.

RESULTS

To solve this problem, we developed pairedGSEA and used it to profile transcriptional changes in 100 representative RNA-seq datasets. Our systematic analysis demonstrates that changes in splicing, on average, contribute to 48.1% of the biological signal in expression analyses. Gene-set enrichment analysis furthermore indicates that expression and splicing both convey shared and distinct biological signals.

CONCLUSIONS

These findings establish alternative splicing as a major regulator of the human condition and suggest that most contemporary RNA-seq studies likely miss out on critical biological insights. We anticipate our results will contribute to the transition from a gene-centric to an isoform-centric research paradigm.

ZNF683 marks a CD8+ T cell population associated with anti-tumor immunity following anti-PD-1 therapy for Richter syndrome

Unlike many other hematologic malignancies, Richter syndrome (RS), an aggressive B cell lymphoma originating from indolent chronic lymphocytic leukemia, is responsive to PD-1 blockade. To discover the determinants of response, we analyze single-cell transcriptome data generated from 17 bone marrow samples longitudinally collected from 6 patients with RS. Response is associated with intermediate exhausted CD8 effector/effector memory T cells marked by high expression of the transcription factor ZNF683, determined to be evolving from stem-like memory cells and divergent from terminally exhausted cells. This signature overlaps with that of tumor-infiltrating populations from anti-PD-1 responsive solid tumors. ZNF683 is found to directly target key T cell genes (TCF7, LMO2, CD69) and impact pathways of T cell cytotoxicity and activation. Analysis of pre-treatment peripheral blood from 10 independent patients with RS treated with anti-PD-1, as well as patients with solid tumors treated with anti-PD-1, supports an association of ZNF683high T cells with response.

Pronounced gut microbiota signatures in patients with JAK2V617F-positive essential thrombocythemia

Essential thrombocythemia (ET) is part of the Philadelphia chromosome-negative myeloproliferative neoplasms. It is characterized by an increased risk of thromboembolic events and also to a certain degree hypermetabolic symptoms. The gut microbiota is an important initiator of hematopoiesis and regulation of the immune system, but in patients with ET, where inflammation is a hallmark of the disease, it is vastly unexplored. In this study, we compared the gut microbiota via amplicon-based 16S rRNA gene sequencing of the V3-V4 region in 54 patients with ET according to mutation status Janus-kinase 2 (JAK2V617F)-positive vs JAK2V617F-negative patients with ET, and in 42 healthy controls (HCs). Gut microbiota richness was higher in patients with ET (median-observed richness, 283.5; range, 75-535) compared with HCs (median-observed richness, 191.5; range, 111-300; P < 0.001). Patients with ET had a different overall bacterial composition (beta diversity) than HCs (analysis of similarities [ANOSIM]; R = 0.063, P = 0.004). Patients with ET had a significantly lower relative abundance of taxa within the Firmicutes phylum compared with HCs (51% vs 59%, P = 0.03), and within that phylum, patients with ET also had a lower relative abundance of the genus Faecalibacterium (8% vs 15%, P < 0.001), an important immunoregulative bacterium. The microbiota signatures were more pronounced in patients harboring the JAK2V617F mutation, and highly similar to patients with polycythemia vera as previously described. These findings suggest that patients with ET may have an altered immune regulation; however, whether this dysregulation is induced in part by, or is itself inducing, an altered gut microbiota remains to be investigated. IMPORTANCE Essential thrombocythemia (ET) is a cancer characterized by thrombocyte overproduction. Inflammation has been shown to be vital in both the initiation and progression of other myeloproliferative neoplasms, and it is well known that the gut microbiota is important in the regulation of our immune system. However, the gut microbiota of patients with ET remains uninvestigated. In this study, we characterized the gut microbiota of patients with ET compared with healthy controls and thereby provide new insights into the field. We show that the gut microbiota of patients with ET differs significantly from that of healthy controls and the patients with ET have a lower relative abundance of important immunoregulative bacteria. Furthermore, we demonstrate that patients with JAK2V617F-positive ET have pronounced gut microbiota signatures compared with JAK2V617F-negative patients. Thereby confirming the importance of the underlying mutation, the immune response as well as the composition of the microbiota.

A systems vaccinology resource to develop and test computational models of immunity

Computational models that predict an individual's response to a vaccine offer the potential for mechanistic insights and personalized vaccination strategies. These models are increasingly derived from systems vaccinology studies that generate immune profiles from human cohorts pre- and post-vaccination. Most of these studies involve relatively small cohorts and profile the response to a single vaccine. The ability to assess the performance of the resulting models would be improved by comparing their performance on independent datasets, as has been done with great success in other areas of biology such as protein structure predictions. To transfer this approach to system vaccinology studies, we established a prototype platform that focuses on the evaluation of Computational Models of Immunity to Pertussis Booster vaccinations (CMI-PB). A community resource, CMI-PB generates experimental data for the explicit purpose of model evaluation, which is performed through a series of annual data releases and associated contests. We here report on our experience with the first such 'dry run' for a contest where the goal was to predict individual immune responses based on pre-vaccination multi-omic profiles. Over 30 models adopted from the literature were tested, but only one was predictive, and was based on age alone. The performance of new models built using CMI-PB training data was much better, but varied significantly based on the choice of pre-vaccination features used and the model building strategy. This suggests that previously published models developed for other vaccines do not generalize well to Pertussis Booster vaccination. Overall, these results reinforced the need for comparative analysis across models and datasets that CMI-PB aims to achieve. We are seeking wider community engagement for our first public prediction contest, which will open in early 2024.

An insulin hypersecretion phenotype precedes pancreatic β cell failure in MODY3 patient-specific cells

MODY3 is a monogenic hereditary form of diabetes caused by mutations in the transcription factor HNF1A. The patients progressively develop hyperglycemia due to perturbed insulin secretion, but the pathogenesis is unknown. Using patient-specific hiPSCs, we recapitulate the insulin secretion sensitivity to the membrane depolarizing agent sulfonylurea commonly observed in MODY3 patients. Unexpectedly, MODY3 patient-specific HNF1A^+/R272C β cells hypersecrete insulin both in vitro and in vivo after transplantation into mice. Consistently, we identified a trend of increased birth weight in human HNF1A mutation carriers compared with healthy siblings. Reduced expression of potassium channels, specifically the K_ATP channel, in MODY3 β cells, increased calcium signaling, and rescue of the insulin hypersecretion phenotype by pharmacological targeting ATP-sensitive potassium channels or low-voltage-activated calcium channels suggest that more efficient membrane depolarization underlies the hypersecretion of insulin in MODY3 β cells. Our findings identify a pathogenic mechanism leading to β cell failure in MODY3.

CCL22-based peptide vaccines induce anti-cancer immunity by modulating tumor microenvironment

CCL22 is a macrophage-derived immunosuppressive chemokine that recruits regulatory T cells through the CCL22:CCR4 axis. CCL22 was shown to play a key role in suppressing anti-cancer immune responses in different cancer types. Recently, we showed that CCL22-specific T cells generated from cancer patients could kill CCL22-expressing tumor cells and directly influence the levels of CCL22 in vitro. The present study aimed to provide a rationale for developing a CCL22-targeting immunotherapy. Vaccination with CCL22-derived peptides induced CCL22-specific T-cell responses in both BALB/c and C57BL/6 mice, assessed by interferon-γ secretion ex vivo. Anti-tumor efficacy of the peptides was evaluated in mouse models engrafted with syngeneic tumor models showing a reduced tumor growth and prolonged survival of the treated mice. Vaccination induced changes in the cellular composition of immune cells that infiltrated the tumor microenvironment assessed with multicolor flow cytometry. In particular, the infiltration of CD8⁺ cells and M1 macrophages increased, which increased the CD8/Treg and the M1/M2 macrophage ratio. This study provided preclinical evidence that targeting CCL22 with CCL22 peptide vaccines modulated the immune milieu in the tumor microenvironment. This modulation led to an augmentation of anti-tumor responses. This study provided a rationale for developing a novel immunotherapeutic modality in cancer.

Target isoforms are an overlooked challenge and opportunity in chimeric antigen receptor cell therapy

The development of novel chimeric antigen receptor (CAR) cell therapies is rapidly growing, with 299 new agents being reported and 109 new clinical trials initiated so far this year. One critical lesson from approved CD19-specific CAR therapies is that target isoform switching has been shown to cause tumour relapse, but little is known about the isoforms of CAR targets in solid cancers. Here we assess the protein isoform landscape and identify both the challenges and opportunities protein isoform switching present as CAR therapy is applied to solid cancers.

cyCombine allows for robust integration of single-cell cytometry datasets within and across technologies

Combining single-cell cytometry datasets increases the analytical flexibility and the statistical power of data analyses. However, in many cases the full potential of co-analyses is not reached due to technical variance between data from different experimental batches. Here, we present cyCombine, a method to robustly integrate cytometry data from different batches, experiments, or even different experimental techniques, such as CITE-seq, flow cytometry, and mass cytometry. We demonstrate that cyCombine maintains the biological variance and the structure of the data, while minimizing the technical variance between datasets. cyCombine does not require technical replicates across datasets, and computation time scales linearly with the number of cells, allowing for integration of massive datasets. Robust, accurate, and scalable integration of cytometry data enables integration of multiple datasets for primary data analyses and the validation of results using public datasets.

High CD34 surface expression in BCP-ALL predicts poor induction therapy response and is associated with altered expression of genes related to cell migration and adhesion

Minimal residual disease (MRD) constitutes the most important prognostic factor in B‐cell precursor acute lymphoblastic leukemia (BCP‐ALL). Flow cytometry is widely used in MRD assessment, yet little is known regarding the effect of different immunophenotypic subsets on outcome. In this study of 200 BCP‐ALL patients, we found that a CD34‐positive, CD38 dim‐positive, nTdT dim‐positive immunophenotype on the leukemic blasts was associated with poor induction therapy response and predicted an MRD level at the end of induction therapy (EOI) of ≥ 0.001. CD34 expression was strongly and positively associated with EOI MRD, whereas CD34‐negative patients had a low relapse risk. Further, CD34 expression increased from diagnosis to relapse. CD34 is a stemness‐associated cell‐surface molecule, possibly involved in cell adhesion/migration or survival. Accordingly, genes associated with stemness were overrepresented among the most upregulated genes in CD34‐positive leukemias, and protein–protein interaction networks showed an overrepresentation of genes associated with cell migration, cell adhesion, and negative regulation of apoptosis. The present work is the first to demonstrate a CD34‐negative immunophenotype as a good prognostic factor in ALL, whereas high CD34 expression is associated with poor therapy response and an altered gene expression profile reminiscent of migrating cancer stem‐like cells.

A Comparison of Tools for Copy-Number Variation Detection in Germline Whole Exome and Whole Genome Sequencing Data

Copy-number variations (CNVs) have important clinical implications for several diseases and cancers. Relevant CNVs are hard to detect because common structural variations define large parts of the human genome. CNV calling from short-read sequencing would allow single protocol full genomic profiling. We reviewed 50 popular CNV calling tools and included 11 tools for benchmarking in a reference cohort encompassing 39 whole genome sequencing (WGS) samples paired current clinical standard-SNP-array based CNV calling. Additionally, for nine samples we also performed whole exome sequencing (WES), to address the effect of sequencing protocol on CNV calling. Furthermore, we included Gold Standard reference sample NA12878, and tested 12 samples with CNVs confirmed by multiplex ligation-dependent probe amplification (MLPA). Tool performance varied greatly in the number of called CNVs and bias for CNV lengths. Some tools had near-perfect recall of CNVs from arrays for some samples, but poor precision. Several tools had better performance for NA12878, which could be a result of overfitting. We suggest combining the best tools also based on different methodologies: GATK gCNV, Lumpy, DELLY, and cn.MOPS. Reducing the total number of called variants could potentially be assisted by the use of background panels for filtering of frequently called variants.

TANTIGEN 2.0: a knowledge base of tumor T cell antigens and epitopes

We previously developed TANTIGEN, a comprehensive online database cataloging more than 1000 T cell epitopes and HLA ligands from 292 tumor antigens. In TANTIGEN 2.0, we significantly expanded coverage in both immune response targets (T cell epitopes and HLA ligands) and tumor antigens. It catalogs 4,296 antigen variants from 403 unique tumor antigens and more than 1500 T cell epitopes and HLA ligands. We also included neoantigens, a class of tumor antigens generated through mutations resulting in new amino acid sequences in tumor antigens. TANTIGEN 2.0 contains validated TCR sequences specific for cognate T cell epitopes and tumor antigen gene/mRNA/protein expression information in major human cancers extracted by Human Pathology Atlas. TANTIGEN 2.0 is a rich data resource for tumor antigens and their associated epitopes and neoepitopes. It hosts a set of tailored data analytics tools tightly integrated with the data to form meaningful analysis workflows. It is freely available at http://projects.met-hilab.org/tadb .

Peptide Vaccination Against PD-L1 With IO103 a Novel Immune Modulatory Vaccine in Multiple Myeloma: A Phase I First-in-Human Trial

Background

Immune checkpoint blockade with monoclonal antibodies targeting programmed death 1 (PD-1) and its ligand PD-L1 has played a major role in the rise of cancer immune therapy. We have identified naturally occurring self-reactive T cells specific to PD-L1 in both healthy donors and cancer patients. Stimulation with a PD-L1 peptide (IO103), activates these cells to exhibit inflammatory and anti-regulatory functions that include cytotoxicity against PD-L1-expressing target cells. This prompted the initiation of the present first-in-human study of vaccination with IO103, registered at clinicaltrials.org (NCT03042793).

Methods

Ten patients with multiple myeloma who were up to 6 months after high dose chemotherapy with autologous stem cell support, were enrolled. Subcutaneous vaccinations with IO103 with the adjuvant Montanide ISA 51 was given up to fifteen times during 1 year. Safety was assessed by the common toxicity criteria for adverse events (CTCAE). Immunogenicity of the vaccine was evaluated using IFNγ enzyme linked immunospot and intracellular cytokine staining on blood and skin infiltrating lymphocytes from sites of delayed-type hypersensitivity. The clinical course was described.

Results

All adverse reactions to the PD-L1 vaccine were below CTCAE grade 3, and most were grade 1-2 injection site reactions. The total rate of adverse events was as expected for the population. All patients exhibited peptide specific immune responses in peripheral blood mononuclear cells and in skin-infiltrating lymphocytes after a delayed-type hypersensitivity test. The clinical course was as expected for the population. Three of 10 patients had improvements of responses which coincided with the vaccinations.

Conclusion

Vaccination against PD-L1 was associated with low toxicity and high immunogenicity. This study has prompted the initiation of later phase trials to assess the vaccines efficacy.

Clinical Trial Registration

clinicaltrials.org, identifier NCT03042793.

Adoptive cell therapy in combination with checkpoint inhibitors in ovarian cancer

Immune therapy is a promising field within oncology but has been unsuccessful in ovarian cancer (OC). Still, there is rationale and evidence supporting immune therapy in OC. We investigated the potential for adoptive cell therapy (ACT) from in vitro expanded tumor-infiltrating lymphocytes (TILs) in combination with checkpoint inhibitors (ICI) and conducted immunological testing of ex vivo expanded TILs (REP-TILs).

Six patients with late-stage metastatic high-grade serous OC were treated with immune therapy consisting of ipilimumab followed by surgery to obtain TILs and infusion of REP-TILs, low-dose IL-2 and nivolumab.

One patient achieved a partial response and 5 others experienced disease stabilization for up to 12 months. Analysis of the REP-TILs with flow- and mass-cytometry show primarily activated and differentiated effector memory T cells. REP-TILs showed in vitro reactivity and expression of inhibitory receptors, such as LAG-3 and PD-1. Furthermore, our data indicate that addition of ipilimumab therapy improves the T cell fold expansion during production, increase the level of CD8 T cell tumor reactivity, and favorably affect the T cell phenotype.

We show that the combination of ICI and ACT is feasible and safe. With one partial response and one long-lasting SD, we demonstrated the potential of ACT in OC.

ATIM-01. NIVOLUMAB AND BEVACIZUMAB FOR RECURRENT GLIOBLASTOMA; A TRANSLATIONAL TRIAL IN PROGRESS

Glioblastoma multiforme (GBM) is an aggressive brain tumor with a poor prognosis. Standard of care at diagnosis is surgical resection, followed by radiation and temozolomide. Receiving this therapy, the median survival is 14.6 months [1]. We have no standard treatment for relapse and known options have limited effect. There is an urgent need for novel treatment interventions to improve clinical outcomes and quality of life. Recently, improved overall survival has been achieved with immune therapeutics in melanoma and renal cell carcinoma. Accordingly, it has been posited that immunotherapy may offer promise in other difficult cancers such as GBM [2]. We present our translational study; a phase II open label, two-armed translational study of Nivolumab and Bevacizumab for recurrent GBM, who have failed Stupp’s regime [1]. Patients are included in two arms depending on possibly salvage neurosurgical resection. Both arms receive Nivolumab and Bevacizumab administrated every second weekend, but the surgical arm also receive Nivolumab 7 days prior surgery. We expect 40 patients; 20 in each arm. Enrollment period is expected to 20 months, started October 2018. Our primary objective is to make preliminary assessment of immune related biomarkers, including PD-L1; therefore, we perform full genome sequencing on tumor biopsies from the surgical arm and on blood samples from both arms. We evaluate changes in the transcriptomic landscape caused by the check-point inhibition and relation to response as compared with baseline sequencing data, as well as the impact of tumor mutation burden and neoepitope load. We investigate the tumor microenvironment by harvesting tumor infiltrating lymphocytes and study the composition by flow-cytometry. The patients are evaluated by blood samples, FET-PET as wells as clinical examinations to evaluate PFS and OS. Overall the study will provide us with a unique possibility to investigate and thereof predict which patients will profit from the treatment.

Publisher Correction: Clonal analysis of Salmonella-specific effector T cells reveals serovar-specific and cross-reactive T cell responses

In the version of this article initially published, the first affiliation lacked 'MRC'; the correct name of the institution is 'MRC Weatherall Institute of Molecular Medicine'. Two designations (SP110Y and ST110H) were incorrect in the legend to Fig. 6f,h,i. The correct text is as follows: for panel f, "...loaded with either the CdtB(105-125)SP110Y (DRB4*SP110Y) or the CdtB(105-125)ST110H (DRB4*ST110H) peptide variants..."; for panel h, "...decorated by the DRB4*SP110Y tetramer (lower-right quadrant), the DRB4*ST110H (upper-left quadrant)..."; and for panel i, "...stained ex vivo with DRB4*SP110Y, DRB4*ST110H...". In Fig. 8e, the final six residues (LTEAFF) of the sequence in the far right column of the third row of the table were missing; the correct sequence is 'CASSYRRTPPLTEAFF'. In the legend to Fig. 8d, a designation (HLyE) was incorrect; the correct text is as follows: "(HlyE?)." Portions of the Acknowledgements section were incorrect; the correct text is as follows: "This work was supported by the UK Medical Research Council (MRC) (MR/K021222/1) (G.N., M.A.G., A.S., V.C., A.J.P.),...the Oxford Biomedical Research Centre (A.J.P., V.C.),...and core funding from the Singapore Immunology Network (SIgN) (E.W.N.) and the SIgN immunomonitoring platform (E.W.N.)." Finally, a parenthetical element was phrased incorrectly in the final paragraph of the Methods subsection "T cell cloning and live fluorescence barcoding"; the correct phrasing is as follows: "...(which in all cases included HlyE, CdtB, Ty21a, Quailes, NVGH308, and LT2 strains and in volunteers T5 and T6 included PhoN)...". Also, in Figs. 3c and 4a, the right outlines of the plots were not visible; in the legend to Fig. 3, panel letter 'f' was not bold; and in Fig. 8f, 'ND' should be aligned directly beneath DRB4 in the key and 'ND' should be removed from the diagram at right, and the legend should be revised accordingly as follows: "...colors indicate the HLA class II restriction (gray indicates clones for which restriction was not determined (ND)). Clonotypes are grouped on the basis of pathogen selectivity (continuous line), protein specificity (dashed line) and epitope specificity; for ten HlyE-specific clones (pixilated squares), the epitope specificity was not determined...". The errors have been corrected in the HTML and PDF versions of the article.

BioReader: a text mining tool for performing classification of biomedical literature

Background

Scientific data and research results are being published at an unprecedented rate. Many database curators and researchers utilize data and information from the primary literature to populate databases, form hypotheses, or as the basis for analyses or validation of results. These efforts largely rely on manual literature surveys for collection of these data, and while querying the vast amounts of literature using keywords is enabled by repositories such as PubMed, filtering relevant articles from such query results can be a non-trivial and highly time consuming task.

Results

We here present a tool that enables users to perform classification of scientific literature by text mining-based classification of article abstracts. BioReader (Biomedical Research Article Distiller) is trained by uploading article corpora for two training categories - e.g. one positive and one negative for content of interest - as well as one corpus of abstracts to be classified and/or a search string to query PubMed for articles. The corpora are submitted as lists of PubMed IDs and the abstracts are automatically downloaded from PubMed, preprocessed, and the unclassified corpus is classified using the best performing classification algorithm out of ten implemented algorithms.

Conclusion

BioReader supports data and information collection by implementing text mining-based classification of primary biomedical literature in a web interface, thus enabling curators and researchers to take advantage of the vast amounts of data and information in the published literature. BioReader outperforms existing tools with similar functionalities and expands the features used for mining literature in database curation efforts. The tool is freely available as a web service at http://www.cbs.dtu.dk/services/BioReader

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2607-x) contains supplementary material, which is available to authorized users.

Computational Methods for Identification of T Cell Neoepitopes in Tumors

Cancer immunotherapy has experienced several major breakthroughs in the past decade. Most recently, technical advances in next-generation sequencing methods have enabled discovery of tumor-specific mutations leading to protective T cell neoepitopes. Many of the successes are enabled by computational methods, which facilitate processing of raw data, mapping of mutations, and prediction of neoepitopes. In this book chapter, we provide an overview of the computational tasks related to the identification of neoepitopes, propose specific tools and best practices, and discuss strengths, weaknesses, and future challenges.

Using microarray-based subtyping methods for breast cancer in the era of high-throughput RNA sequencing

Breast cancer is a highly heterogeneous disease that can be classified into multiple subtypes based on the tumor transcriptome. Most of the subtyping schemes used in clinics today are derived from analyses of microarray data from thousands of different tumors together with clinical data for the patients from which the tumors were isolated. However, RNA sequencing (RNA‐Seq) is gradually replacing microarrays as the preferred transcriptomics platform, and although transcript abundances measured by the two different technologies are largely compatible, subtyping methods developed for probe‐based microarray data are incompatible with RNA‐Seq as input data. Here, we present an RNA‐Seq data processing pipeline, which relies on the mapping of sequencing reads to the probe set target sequences instead of the human reference genome, thereby enabling probe‐based subtyping of breast cancer tumor tissue using sequencing‐based transcriptomics. By analyzing 66 breast cancer tumors for which gene expression was measured using both microarrays and RNA‐Seq, we show that RNA‐Seq data can be directly compared to microarray data using our pipeline. Additionally, we demonstrate that the established subtyping method CITBCMST (Guedj et al., 2012), which relies on a 375 probe set‐signature to classify samples into the six subtypes basL, lumA, lumB, lumC, mApo, and normL, can be applied without further modifications. This pipeline enables a seamless transition to sequencing‐based transcriptomics for future clinical purposes.

TANTIGEN: a comprehensive database of tumor T cell antigens

Tumor T cell antigens are both diagnostically and therapeutically valuable molecules. A large number of new peptides are examined as potential tumor epitopes each year, yet there is no infrastructure for storing and accessing the results of these experiments. We have retroactively cataloged more than 1000 tumor peptides from 368 different proteins, and implemented a web-accessible infrastructure for storing and accessing these experimental results. All peptides in TANTIGEN are labeled as one of the four categories: (1) peptides measured in vitro to bind the HLA, but not reported to elicit either in vivo or in vitro T cell response, (2) peptides found to bind the HLA and to elicit an in vitro T cell response, (3) peptides shown to elicit in vivo tumor rejection, and (4) peptides processed and naturally presented as defined by physical detection. In addition to T cell response, we also annotate peptides that are naturally processed HLA binders, e.g., peptides eluted from HLA in mass spectrometry studies. TANTIGEN provides a rich data resource for tumor-associated epitope and neoepitope discovery studies and is freely available at http://cvc.dfci.harvard.edu/tantigen/ or http://projects.met-hilab.org/tadb (mirror).

Transcriptional changes induced by bevacizumab combination therapy in responding and non-responding recurrent glioblastoma patients

Background

Bevacizumab combined with chemotherapy produces clinical durable response in 25–30% of recurrent glioblastoma patients. This group of patients has shown improved survival and quality of life. The aim of this study was to investigate changes in gene expression associated with response and resistance to bevacizumab combination therapy.

Methods

Recurrent glioblastoma patients who had biomarker-accessible tumor tissue surgically removed both before bevacizumab treatment and at time of progression were included. Patients were grouped into responders (n = 7) and non-responders (n = 14). Gene expression profiling of formalin-fixed paraffin-embedded tumor tissue was performed using RNA-sequencing.

Results

By comparing pretreatment samples of responders with those of non-responders no significant difference was observed. In a paired comparison analysis of pre- and posttreatment samples of non-responders 1 gene was significantly differentially expressed. In responders, this approach revealed 256 significantly differentially expressed genes (72 down- and 184 up-regulated genes at the time of progression). Genes differentially expressed in responders revealed a shift towards a more proneural and less mesenchymal phenotype at the time of progression.

Conclusions

Bevacizumab combination treatment demonstrated a significant impact on the transcriptional changes in responders; but only minimal changes in non-responders. This suggests that non-responding glioblastomas progress chaotically without following distinct gene expression changes while responding tumors adaptively respond or progress by means of the same transcriptional changes. In conclusion, we hypothesize that the identified gene expression changes of responding tumors are associated to bevacizumab response or resistance mechanisms.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-017-3251-3) contains supplementary material, which is available to authorized users.

Angiotensinogen and HLA class II predict bevacizumab response in recurrent glioblastoma patients

BACKGROUND

Bevacizumab combination therapy is among the most frequently used treatments in recurrent glioblastoma and patients who achieve response to bevacizumab have improved survival as well as quality of life. Accordingly, the aim of this study was to identify predictive biomarkers for bevacizumab response in recurrent glioblastoma patients.

METHODS

The study included a total of 82 recurrent glioblastoma patients treated with bevacizumab combination therapy whom were both response and biomarker evaluable. Gene expression of tumor tissue was analyzed by using a customized NanoString platform covering 800 genes. Candidate gene predictors associated with response were analyzed by multivariate logistic and Cox regression analysis.

RESULTS

Two genes were independently associated with response: Low expression of angiotensinogen (2-fold decrease in AGT; OR = 2.44; 95% CI: 1.45-4.17; P = 0.0009) and high expression of a HLA class II gene (2-fold increase in HLA-DQA1; OR = 1.22; 95% CI: 1.01-1.47; P = 0.04). These two genes were included in a model that is able predict response to bevacizumab combination therapy in clinical practice. When stratified for a validated prognostic index, the predictive model for response was significantly associated with improved overall survival.

CONCLUSION

Two genes (low angiotensinogen and high HLA-class II expression) were predictive for bevacizumab response and were included in a predictive model for response. This model can be used in clinical practice to identify patients who will benefit from bevacizumab combination therapy.

A comprehensive profile of recurrent glioblastoma

In spite of relentless efforts to devise new treatment strategies, primary glioblastomas invariably recur as aggressive, therapy-resistant relapses and patients rapidly succumb to these tumors. Many therapeutic agents are first tested in clinical trials involving recurrent glioblastomas. Remarkably, however, fundamental knowledge on the biology of recurrent glioblastoma is just slowly emerging. Here, we review current knowledge on recurrent glioblastoma and ask whether and how therapies change intra-tumor heterogeneity, molecular traits and growth pattern of glioblastoma, and to which extent this information can be exploited for therapeutic decision-making. We conclude that the ability to characterize and predict therapy-induced changes in recurrent glioblastoma will determine, whether, one day, glioblastoma can be contained in a state of chronic disease.

Abstract A25: Predictive biomarkers for bevacizumab response in recurrent glioblastoma patients

BACKGROUND: Bevacizumab (BEV) plus chemotherapy has shown high response rates in recurrent glioblastoma (GBM) and patients who achieve response have an improved overall survival as well as quality of life. Recent retrospective analysis of the randomized phase III trial, AVAglio, indicate that patients with the proneural GBM subtype have a survival benefit when treated with BEV in combination with standard treatment. However, no validated biomarkers able to predict BEV response have been identified and the biology reflecting a clinical BEV response is poorly understood. The primary objective of this study was to evaluate the predictive and prognostic value of GBM subtypes in recurrent GBM patients treated with BEV therapy. The secondary objective was to identify biomarkers able to predict response to BEV therapy in recurrent GBM patients. METHODS: A total of 90 recurrent GBM patients treated with BEV combination treatment according to a previously published treatment protocol were included. Inclusion criteria: BEV plus irinotecan treatment in the period between May 2005-2011; available GBM tissue (according to WHO); response evaluable (RANO). RNA from tumor tissue was analyzed by the NanoString platform covering 800 genes. Raw data was assigned to molecular subtypes for each of the samples using the PAMR classifier model, previously trained on the AVAglio dataset. In order to identify novel candidate biomarkers able to predict response, differentially expressed genes (fold-change difference &gt; 1.5) between patients responding versus progressing on BEV were identified using a t-test. Biomarkers significantly (P&lt;0.05) associated with response in multivariate logistic regression analysis adjusted for recently validated clinical prognostic factors were selected for the final predictive model. RESULTS: Molecular subtypes were not associated with response or overall survival. However, two novel independent predictive biomarkers (gene1 down-regulated and gene2 up-regulated in responders) of BEV response and overall survival were identified. Results will be presented.

Citation Format: Thomas Urup, Signe Regner Michaelsen, Lars Rønn Olsen, Anders Toft, Ib Jarle Christensen, Kirsten Grunnet, Helle Broholm, Michael Kosteljanetz, Shohreh Issazadeh-Navikas, Hans Skovgaard Poulsen, Ulriik Lassen. Predictive biomarkers for bevacizumab response in recurrent glioblastoma patients. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr A25.

Software-supported USER cloning strategies for site-directed mutagenesis and DNA assembly

USER cloning is a fast and versatile method for engineering of plasmid DNA. We have developed a user friendly Web server tool that automates the design of optimal PCR primers for several distinct USER cloning-based applications. Our Web server, named AMUSER (Automated DNA Modifications with USER cloning), facilitates DNA assembly and introduction of virtually any type of site-directed mutagenesis by designing optimal PCR primers for the desired genetic changes. To demonstrate the utility, we designed primers for a simultaneous two-position site-directed mutagenesis of green fluorescent protein (GFP) to yellow fluorescent protein (YFP), which in a single step reaction resulted in a 94% cloning efficiency. AMUSER also supports degenerate nucleotide primers, single insert combinatorial assembly, and flexible parameters for PCR amplification. AMUSER is freely available online at http://www.cbs.dtu.dk/services/AMUSER/.

Depression and emotional stress is highly prevalent among women with recurrent pregnancy loss

STUDY QUESTION

Is the prevalence of psychological stress and moderate/severe depression higher for women with recurrent pregnancy loss (RPL) than pregnancy planners trying to conceive naturally?

SUMMARY ANSWER

Both psychological stress and major depression are significantly more common among women with RPL than in those trying to conceive naturally.

WHAT IS KNOWN ALREADY

RPL has a significant emotional impact on couples, especially the woman. Previous studies have shown inconclusive results.

STUDY DESIGN, SIZE, DURATION

In this cross-sectional study, we compared the prevalence of stress and depression among 301 women with RPL and 1813 women attempting to conceive naturally. We defined RPL as three or more pregnancy losses before 12 weeks' gestation. RPL patients were enrolled from 2010 to 2013 and the comparison group from 2011 to 2014.

PARTICIPANTS/MATERIALS, SETTING, METHODS

RPL patients completed an online questionnaire before their first consultation at the Danish RPL Unit. In addition, we included data from a comparison group of 1813 women who participated in the Soon Parents Study (www.SnartForældre.dk). The Major Depression Index (MDI) was used to assess symptoms of depression, and Cohen's Perceived Stress Scale (PSS) was used to measure stress. Relevant demographic data were also retrieved.

MAIN RESULTS AND THE ROLE OF CHANCE

Of the RPL patients, 26 (8.6%) had a score on the MDI corresponding to moderate/severe depression, as did 40 (2.2%) of the women in Soon Parents Study (adjusted odds ratio (OR) 5.53 (95% confidence interval (CI): 2.09; 14.61)). A high stress level, defined as ≥19 on the PSS scale, was reported by 124 (41.2%) of the patients and 420 (23.2%) in the comparison group (adjusted OR 1.59 (95% CI 1.03; 2.44)).

LIMITATIONS, REASONS FOR CAUTION

We used online questionnaires, and have no interview data. We were unaware if any of the women in the comparison group suffer from RPL.

WIDER IMPLICATIONS OF THE FINDINGS

This study should entail a heightened awareness of mental distress among care providers for women with RPL.

STUDY FUNDING/COMPETING INTERESTS

No specific funding was sought for this study. The Soon Parents Study is funded by National Institute of Child Health and Human Development (R01 HD060680-01A4). No authors have competing interests to declare.

TRIAL REGISTRATION NUMBER

N/A.

Bioinformatics for cancer immunotherapy target discovery

The mechanisms of immune response to cancer have been studied extensively and great effort has been invested into harnessing the therapeutic potential of the immune system. Immunotherapies have seen significant advances in the past 20 years, but the full potential of protective and therapeutic cancer immunotherapies has yet to be fulfilled. The insufficient efficacy of existing treatments can be attributed to a number of biological and technical issues. In this review, we detail the current limitations of immunotherapy target selection and design, and review computational methods to streamline therapy target discovery in a bioinformatics analysis pipeline. We describe specialized bioinformatics tools and databases for three main bottlenecks in immunotherapy target discovery: the cataloging of potentially antigenic proteins, the identification of potential HLA binders, and the selection epitopes and co-targets for single-epitope and multi-epitope strategies. We provide examples of application to the well-known tumor antigen HER2 and suggest bioinformatics methods to ameliorate therapy resistance and ensure efficient and lasting control of tumors.

Characterizing the human hematopoietic CDome

In this study, we performed extensive semi-automated data collection from the primary and secondary literature in an effort to characterize the expression of all membrane proteins within the CD scheme on hematopoietic cells. Utilizing over 6000 data points across 305 CD molecules on 206 cell types, we seek to give a preliminary characterization of the “human hematopoietic CDome.” We encountered severe gaps in the knowledge of CD protein expression, mostly resulting from incomplete and unstructured data generation, which we argue inhibit both basic research as well as therapies seeking to target membrane proteins. We detail these shortcomings and propose strategies to overcome these issues. Analyzing the available data, we explore the functional characteristics of the CD molecules both individually and across the groups of hematopoietic cells on which they are expressed. We compare protein and mRNA data for a subset of CD molecules, and explore cell functions in the context of CD protein expression. We find that the presence and function of CD molecules serve as good indicators for the overall function of the cells that express them, suggesting that increasing our knowledge about the cellular CDome may serve to stratify cells on a more functional level.

BlockLogo: visualization of peptide and sequence motif conservation

BlockLogo is a web-server application for the visualization of protein and nucleotide fragments, continuous protein sequence motifs, and discontinuous sequence motifs using calculation of block entropy from multiple sequence alignments. The user input consists of a multiple sequence alignment, selection of motif positions, type of sequence, and output format definition. The output has BlockLogo along with the sequence logo, and a table of motif frequencies. We deployed BlockLogo as an online application and have demonstrated its utility through examples that show visualization of T-cell epitopes and B-cell epitopes (both continuous and discontinuous). Our additional example shows a visualization and analysis of structural motifs that determine the specificity of peptide binding to HLA-DR molecules. The BlockLogo server also employs selected experimentally validated prediction algorithms to enable on-the-fly prediction of MHC binding affinity to 15 common HLA class I and class II alleles as well as visual analysis of discontinuous epitopes from multiple sequence alignments. It enables the visualization and analysis of structural and functional motifs that are usually described as regular expressions. It provides a compact view of discontinuous motifs composed of distant positions within biological sequences. BlockLogo is available at: http://research4.dfci.harvard.edu/cvc/blocklogo/ and http://met-hilab.bu.edu/blocklogo/.

Conservation analysis of dengue virus T-cell epitope-based vaccine candidates using Peptide block entropy

Broad coverage of the pathogen population is particularly important when designing CD8+ T-cell epitope vaccines against viral pathogens. Traditional approaches are based on combinations of highly conserved T-cell epitopes. Peptide block entropy analysis is a novel approach for assembling sets of broadly covering antigens. Since T-cell epitopes are recognized as peptides rather than individual residues, this method is based on calculating the information content of blocks of peptides from a multiple sequence alignment of homologous proteins rather than using the information content of individual residues. The block entropy analysis provides broad coverage of variant antigens. We applied the block entropy analysis method to the proteomes of the four serotypes of dengue virus (DENV) and found 1,551 blocks of 9-mer peptides, which cover 99% of available sequences with five or fewer unique peptides. In contrast, the benchmark study by Khan et al. (2008) resulted in 165 conserved 9-mer peptides. Many of the conserved blocks are located consecutively in the proteins. Connecting these blocks resulted in 78 conserved regions. Of the 1551 blocks of 9-mer peptides 110 comprised predicted HLA binder sets. In total, 457 subunit peptides that encompass the diversity of all sequenced DENV strains of which 333 are T-cell epitope candidates.

Hip fractures in a city in Northern Norway over 15 years: time trends, seasonal variation and mortality : the Harstad Injury Prevention Study

In this open population-based study from Northern Norway, there was no increase in hip fracture incidence in women and men from 1994 to 2008. Age-adjusted hip fracture rates was lower compared to reported rates from the Norwegian capital Oslo, indicating regional differences within the country.

INTRODUCTION

The aim of the present population-based study was to describe age- and sex-specific incidence of hip fractures in a Northern Norwegian city, compare rates with the Norwegian capital Oslo, describe time trends in hip fracture incidence, place of injury, seasonal variation and compare mortality after hip fracture between women and men.

METHODS

Data on hip fractures from 1994 to 2008 in women and men aged 50 years and above were obtained from the Harstad Injury Registry.

RESULTS

There were altogether 603 hip fractures in Harstad between 1994 and 2008. The annual incidenc rose exponentially from 5.8 to 349.2 per 10,000 in men, and from 8.7 to 582.2 per 10,000 in women from the age group 50-54 to 90+ years. The age-adjusted incidence rates were 101.0 and 37.4 in women and men, respectively, compared to 118.0 in women (p = 0.005) and 44.0 in men (p = 0.09) in Oslo. The age-adjusted incidence rates did not increase between 1994-1996 and 2006-2008. The majority of hip fractures occurred indoors and seasonal variation was significant in fractures occurring outdoors only. After adjusting for age at hip fracture, mortality after fracture was higher in men than in women 3, 6 and 12 months (p ≤ 0.002) after fracture.

CONCLUSIONS

There are regional differences in hip fracture incidence that cannot be explained by a north-south gradient in Norway. Preventive strategies must be targeted to indoor areas throughout the year and to outdoor areas in winter.

PHUSER (Primer Help for USER): a novel tool for USER fusion primer design

Uracil-Specific Exision Reagent (USER) fusion is a recently developed technique that allows for assembly of multiple DNA fragments in a few simple steps. However, designing primers for USER fusion is both tedious and time consuming. Here, we present the Primer Help for USER (PHUSER) software, a novel tool for designing primers specifically for USER fusion and USER cloning applications. We also present proof-of-concept experimental validation of its functionality. PHUSER offers quick and easy design of PCR optimized primers ensuring directionally correct fusion of fragments into a plasmid containing a customizable USER cassette. Designing primers using PHUSER ensures that the primers have similar annealing temperature (T(m)), which is essential for efficient PCR. PHUSER also avoids identical overhangs, thereby ensuring correct order of assembly of DNA fragments. All possible primers are individually analysed in terms of GC content, presence of GC clamp at 3'-end, the risk of primer dimer formation, the risk of intra-primer complementarity (secondary structures) and the presence of polyN stretches. Furthermore, PHUSER offers the option to insert linkers between DNA fragments, as well as highly flexible cassette options. PHUSER is publicly available at http://www.cbs.dtu.dk/services/phuser/.

Mental distress in the Danish general population

OBJECTIVE

To present data on mental distress in the Danish general population using recently validated Hopkins symptom checklist (SCL) subscales and compare with data from other countries. To evaluate associations between mental distress and biopsychosocial factors.

METHOD

Questionnaires were sent to a gender- and age-stratified random sample comprising 2040 Danes. Mean SCL subscale scores were calculated. Cases were defined in accordance with the traditional criteria, and Danish and US raw score cut-offs were compared. A multiple regression model was developed to describe associations between biopsychosocial factors and SCL scores.

RESULTS

The response rate was 58%. The Danish mean scores were significantly higher than reported for a US non-patient sample, and Danish raw score cut-offs for caseness were higher. The Danish scores were closer to Nordic mean scores. Age, gender, social status, somatic disorder and traumatic life events in the past year in work life as well as personal life were significantly associated with the level of mental distress. SCL scores were compared with scores on the Major Depression Inventory.

CONCLUSION

The SCL mean scores of the Danish general population were relatively high, but similar to data from the Nordic countries. Consequently, interpretation of the Danish SCL requires Danish norms and Danish cut-off scores for caseness.

Modafinil augmentation in depressed patients with partial response to antidepressants: a pilot study on self-reported symptoms covered by the Major Depression Inventory (MDI) and the Symptom Checklist (SCL-92)

Treatment-resistant depression, i.e. partial or non response to antidepressants in spite of various treatment attempts with optimized doses and combinations, is rather common. With residual symptoms such as tiredness, anhedonia and concentration disturbances, the treatment strategy has often been to use monoamino-oxidase inhibitors (MAOIs). Their use, however, is limited due to interaction problems. Modafinil is recently developed wake-promoting drug with only minor side-effects. Pilot studies indicate that it appears to have an augmentation effect in treatment-resistant depression. This open-label study performed in the private psychiatric practice setting is the first to make a comprehensive evaluation of the target patient profile based on patient-reported symptoms. Modafinil in doses of 100-400 mg was administered as augmentation to ongoing antidepressant therapy in patients with partial response and suffering from hypersomnia. The total number of patients was 21 and 43% of these were responders (i.e. had a score reduction of >50% on the Major Depression Inventory (MDI) as well as remitters, i.e. the remission rate was 43%. At endpoint, the responders had psychological distress scores on the Symptom Checklist (SCL-92) on the level of the general Danish population. Baseline characteristics for responders were lower scores on depression, hostility, anxiety, somatization, obsession and psychoticism. Modafinil thus appears to be an appropriate augmentation to antidepressant treatment, leading to a remission rate of 43%. However, the results from this open-label study need ot be confirmed in a placebo-controlled trial.

The SCL-90 and SCL-90R versions validated by item response models in a Danish community sample

OBJECTIVE

To evaluate the internal validity of the subscales of the combined SCL-90 and SCL-90R, the SCL-92, by item response analyses as compared with several previously reported factor analyses of this questionnaire in the literature.

METHOD

The SCL-92 questionnaire was mailed to an age- and gender-stratified random sample of Danish citizens. The sample comprised 2040 individuals. The internal structure of the nine factors of the SCL-92 questionnaire was evaluated by Mokken-Loevinger analysis and Rasch analysis.

RESULTS

In total, 1153 persons or 58% returned the questionnaire fully completed. Mokken analysis found all scales apart from the psychoticism scale acceptable. The Rasch analysis found most of the subscales to be robust. Minor problems were seen for the scales of phobic anxiety, obsession-compulsion and depression. Analysis of the Global Severity Index showed that the Rasch model was rejected for the full 92-item scale, but not for a scale consisting of the 63 items from the non-psychotic subscales. Spearman correlations among the subscales were all positive (range 0.34-0.79) and so were correlations between each of the subscales and the Global Severity Index (range 0.55-0.91).

CONCLUSION

In this sample from the Danish general population the non-psychotic subscales, i.e. the subscales covering psychological distress were observed to function well. In a general population sample, the 63 non-psychotic items primarily appear to reflect one broad dimension of distress.

Prevalence of major depression and stress indicators in the Danish general population

OBJECTIVE

To estimate the prevalence rate of major depression in the Danish general population by using the Major Depression Inventory (MDI), a validated self-rating scale fulfilling the symptomatic criteria in DSM-IV and ICD-10 for a depressive episode.

METHOD

A booklet containing the MDI and a number of questions on psychosocial factors was sent to 2040 randomly selected Danish citizens. The sample was age- and gender-stratified. Mean MDI scores were calculated. Logistic regression analysis was used in order to produce a model for the influence of psychosocial factors.

RESULTS

The response rate was 60%. The point prevalence of major depression was 3.3%. Among the tested predictors of depression were sociodemographic variables, alcohol and smoking habit, bodily pain, somatic diseases and traumatic life events. For a traumatic event in personal life over the past year odds ratio was 6.4 [2.7; 15.5], for overconsumption of alcohol odds ratio was 3.2 [1.5; 6.8]. While the gender difference in major depression rate was not found statistically significant, a significant (P < 0.05) gender difference of male to female of 1 : 2 was found when including minor depression. Of people identified as having a major depression only 13% were currently treated by a medical doctor.

CONCLUSION

Major depression has a high prevalence in the Danish general population and seems to be undertreated. The gender difference was only found statistically significant when including minor depression, indicating that the female predominance is less pronounced in the more severe depression states.

The internal and external validity of the Major Depression Inventory in measuring severity of depressive states

BACKGROUND

We have developed the Major Depression Inventory (MDI), consisting of 10 items, covering the DSM-IV as well as the ICD-10 symptoms of depressive illness. We aimed to evaluate this as a scale measuring severity of depressive states with reference to both internal and external validity.

METHOD

Patients representing the score range from no depression to marked depression on the Hamilton Depression Scale (HAM-D) completed the MDI. Both classical and modern psychometric methods were applied for the evaluation of validity, including the Rasch analysis.

RESULTS

In total, 91 patients were included. The results showed that the MDI had an adequate internal validity in being a unidimensional scale (the total score an appropriate or sufficient statistic). The external validity of the MDI was also confirmed as the total score of the MDI correlated significantly with the HAM-D (Pearson's coefficient 0.86, P < or = 0.01, Spearman 0.80, P < or = 0.01).

CONCLUSION

When used in a sample of patients with different states of depression the MDI has an adequate internal and external validity.

The sensitivity and specificity of the Major Depression Inventory, using the Present State Examination as the index of diagnostic validity

BACKGROUND

A self-rating inventory has been developed to measure DSM-IV and ICD-10 diagnoses of major (moderate to severe) depression by the patients' self-reported symptoms. This Major Depression Inventory (MDI) can be scored both according to the DSM-IV and the ICD-10 algorithms for depressive symptomatology and according to severity scales by the simple total sum of the items.

METHODS

The Schedule for Clinical Assessment in Neuropsychiatry (SCAN) was used as index of validity for the clinician's DSM-IV and ICD-10 diagnosis of major (moderate to severe) depression. The sensitivity and specificity of MDI was assessed in a sample of 43 subjects covering a spectrum of depressive symptoms.

RESULTS

The sensitivity of the MDI algorithms for major depression varied between 0.86 and 0.92. The specificity varied between 0.82 and 0.86. When using the total score of MDI the optimal cut-off score was estimated 26 and the total score was shown to be a sufficient statistic.

LIMITATIONS

The sample of subjects was limited. Patients with psychotic depression were not included.

CONCLUSION

The MDI was found to have a sensitivity and specificity which is acceptable. The questionnaire is brief and can be scored diagnostically by the DSM-IV and ICD-10 algorithms as well as by its simple total score.

Structure of the Escherichia coli GlmU pyrophosphorylase and acetyltransferase active sites

N-Acetylglucosamine-1-PO(4) uridyltransferase (GlmU) is a trimeric bifunctional enzyme that catalyzes the last two sequential reactions in the de novo biosynthetic pathway for UDP-GlcNAc. The X-ray crystal structure of Escherichia coli GlmU in complex with UDP-GlcNAc and CoA has been determined to 2.1 A resolution and reveals a two-domain architecture that is responsible for these two reactions. The C-terminal domain is responsible for the CoA-dependent acetylation of Glc-1-PO(4) to GlcNAc-1-PO(4) and displays the longest left-handed parallel beta-helix observed to date. The acetyltransferase active site defined by the binding site for CoA makes use of residues from all three subunits and is positioned beneath an open cavity large enough to accommodate the Glc-1-PO(4) acetyl acceptor. The N-terminal domain catalyzes uridyl transfer from UTP to GlcNAc-1-PO(4) to form the final products UDP-GlcNAc and pyrophosphate. This domain is composed of a central seven-stranded beta-sheet surrounded by six alpha-helices in a Rossmann fold-like topology. A Co(2+) ion binds to just one of the two independent pyrophosphorylase active sites present in the crystals studied here, each of which nonetheless binds UDP-GlcNAc. The conformational changes of the enzyme and sugar nucleotide that accompany metal binding may provide a window into the structural dynamics that accompany catalysis.

[Logbook. A possible method]

The European board of psychiatry recommends the use of a logbook and checklist. There has been discussion about the extent of registration--and the resources involved. We present a simple method of registering supervision. Trainees make a daily report of the amount of supervision received. The trial period was divided into two sections: March, April and May 1997; (training intensive) and June, July and August 1997; (holiday season). The trainees responded well to the logbook, the answering rate was 94.2% in the first period, 60.9% in the holiday season. Calculations based on the first period show that trainees receive supervision during 9.8% of their working hours (range 4.8-16.0). Twenty-nine percent of supervision is of the direct variety, where both trainer and trainee are present. This variety suffers during holiday season. This type of logbook provides an opportunity to be directed in training activities, with a minimum of resources involved.