Systemic treatment of children and adolescents with atopic dermatitis aged >= 2 years: a Delphi consensus project mapping expert opinion in Northern Europe

Background Paediatric atopic dermatitis (AD) can be burdensome, affecting mental health and impairing quality of life for children and caregivers. Comprehensive guidelines exist for managing paediatric AD, but practical guidance on using systemic therapy is limited, particularly for new therapies including biologics and Janus kinase (JAK) inhibitors, recently approved for various ages in this indication. Objectives This expert consensus aimed to provide practical recommendations within this advancing field to enhance clinical decision-making on the use of these and other systemics for children and adolescents aged >= 2 years with moderate-to-severe AD. Methods Nineteen physicians from Northern Europe were selected for their expertise in managing childhood AD. Using a two-round Delphi process, they reached full or partial consensus on 37 statements. Results Systemic therapy is recommended for children aged >= 2 years with a clear clinical diagnosis of severe AD and persistent disease uncontrolled after optimizing non-systemic therapy. Systemic therapy should achieve long-term disease control and reduce short-term interventions. Recommended are cyclosporine A for short-term use (all ages) and dupilumab or methotrexate for long-term use (ages >= 6 years). Consensus was not reached on the best long-term systemics for children aged 2-6 years, although new systemic therapies will likely become favourable: New biologics and JAK inhibitors will soon be approved for this age group, and more trial and real-world data will become available. Conclusions This article makes practical recommendations on the use of systemic AD treatments for children and adolescents, to supplement international and regional guidelines. It considers the systemic medication that was available for children and adolescents with moderate-to-severe AD at the time this consensus project was done: azathioprine, cyclosporine A, dupilumab, methotrexate, mycophenolate mofetil and oral glucocorticosteroids. We focus on the geographically similar Northern European countries, whose healthcare systems, local preferences for AD management and reimbursement structures nonetheless differ significantly.</p

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

MCL1 is deregulated in subgroups of diffuse large B-cell lymphoma.

Myeloid cell leukemia-1 (MCL1) is an anti-apoptotic member of the BCL2 family that is deregulated in various solid and hematological malignancies. However, its role in the molecular pathogenesis of diffuse large B-cell lymphoma (DLBCL) is unclear. We analyzed gene expression profiling data from 350 DLBCL patient samples and detected that activated B-cell-like (ABC) DLBCLs express MCL1 at significantly higher levels compared with germinal center B-cell-like DLBCL patient samples (P=2.7 × 10(-10)). Immunohistochemistry confirmed high MCL1 protein expression predominantly in ABC DLBCL in an independent patient cohort (n=249; P=0.001). To elucidate molecular mechanisms leading to aberrant MCL1 expression, we analyzed array comparative genomic hybridization data of 203 DLBCL samples and identified recurrent chromosomal gains/amplifications of the MCL1 locus that occurred in 26% of ABC DLBCLs. In addition, aberrant STAT3 signaling contributed to high MCL1 expression in this subtype. Knockdown of MCL1 as well as treatment with the BH3-mimetic obatoclax induced apoptotic cell death in MCL1-positive DLBCL cell lines. In summary, MCL1 is deregulated in a significant fraction of ABC DLBCLs and contributes to therapy resistance. These data suggest that specific inhibition of MCL1 might be utilized therapeutically in a subset of DLBCLs

Practical algorithm to inform clinical decision‐making in the topical treatment of atopic dermatitis

Atopic dermatitis is a chronic relapsing, inflammatory skin disorder associated with skin barrier dysfunction, the prevalence of which has increased dramatically in developing countries. In this article, we propose a treatment algorithm for patients with mild-tomoderate and severe atopic dermatitis flares in daily clinical practice. An international panel of 15 dermatology and allergy experts from eight countries was formed to develop a practical algorithm for the treatment of patients with atopic dermatitis, with a particular focus on topical therapies. In cases of mild-to-moderate atopic dermatitis involving sensitive skin areas, the topical calcineurin inhibitor pimecrolimus should be applied twice daily at the first signs of atopic dermatitis. For other body locations, patients should apply a topical calcineurin inhibitor, either pimecrolimus or tacrolimus, twice daily at the first signs of atopic dermatitis, such as pruritus, or twice weekly in previously affected skin areas. Emollients should be used regularly. Patients experiencing acute atopic dermatitis flares in sensitive skin areas should apply a topical corticosteroid twice daily or alternate once-daily topical corticosteroid/topical calcineurin inhibitor until symptoms improve. Following improvement, topical corticosteroid therapy should be discontinued and patients switched to a topical calcineurin inhibitor. Maintenance therapy should include the use of pimecrolimus once daily for sensitive areas and tacrolimus for other body locations. This treatment algorithm can help guide clinical decision-making in the treatment of atopic dermatitis

Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry

To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90)+HLA-DRAhi sublining fibroblasts, IL1B+ pro-inflammatory monocytes, ITGAX+TBX21+ autoimmune-associated B cells and PDCD1+ peripheral helper T (TPH) cells and follicular helper T (TFH) cells. We defined distinct subsets of CD8+ T cells characterized by GZMK+, GZMB+, and GNLY+ phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1+HLA-DRAhi fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis.</p