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Background Automatic cell type identification is essential to alleviate a key bottleneck in scRNA-seq data analysis. While most existing classification tools show good sensitivity and specificity, they often fail to adequately not-classify cells that are missing in the used reference. Additionally, many tools do not scale to the continuously increasing size of current scRNA-seq datasets. Therefore, additional tools are needed to solve these challenges. Results scAnnotatR is a novel R package that provides a complete framework to classify cells in scRNA-seq datasets using pre-trained classifiers. It supports both Seurat and Bioconductor’s SingleCellExperiment and is thereby compatible with the vast majority of R-based analysis workflows. scAnnotatR uses hierarchically organised SVMs to distinguish a specific cell type versus all others. It shows comparable or even superior accuracy, sensitivity and specificity compared to existing tools while being able to not-classify unknown cell types. Moreover, scAnnotatR is the only of the best performing tools able to process datasets containing more than 600,000 cells. Conclusions scAnnotatR is freely available on GitHub ( https://github.com/grisslab/scAnnotatR ) and through Bioconductor (from version 3.14). It is consistently among the best performing tools in terms of classification accuracy while scaling to the largest datasets.

Tumor associated inflammation predicts response to immune checkpoint blockade in human melanoma. Current theories on regulation of inflammation center on anti-tumor T cell responses. Here we show that tumor associated B cells are vital to melanoma associated inflammation. Human B cells express pro- and anti-inflammatory factors and differentiate into plasmablast-like cells when exposed to autologous melanoma secretomes in vitro. This plasmablast-like phenotype can be reconciled in human melanomas where plasmablast-like cells also express T cell-recruiting chemokines CCL3, CCL4, CCL5. Depletion of B cells in melanoma patients by anti-CD20 immunotherapy decreases tumor associated inflammation and CD8 + T cell numbers. Plasmablast-like cells also increase PD-1 + T cell activation through anti-PD-1 blockade in vitro and their frequency in pretherapy melanomas predicts response and survival to immune checkpoint blockade. Tumor associated B cells therefore orchestrate and sustain melanoma inflammation and may represent a predictor for survival and response to immune checkpoint blockade therapy. The regulation of tumor inflammation is incompletely understood and the role of B cells is unclear. Here, the authors show that a specific subtype of B cells is induced in melanoma and required to recruit T lymphocytes and elicit inflammation.

Dupilumab, an IL4R-blocking antibody, has shown clinical efficacy for atopic dermatitis (AD) treatment. In addition to conjunctivitis/blepharitis, the de novo appearance of head/neck dermatitis is now recognized as a distinct side effect, occurring in up to 10% of patients. Histopathological features distinct from AD suggest a drug effect, but exact underlying mechanisms remain unknown. We profiled punch biopsies from dupilumab-associated head and neck dermatitis (DAHND) by using single-cell RNA sequencing and compared data with untreated AD and healthy control skin. We show that dupilumab treatment was accompanied by normalization of IL-4/IL-13 downstream activity markers such as CCL13, CCL17 , CCL18 and CCL26 . By contrast, we found strong increases in type 22-associated markers ( IL22, AHR ) especially in oligoclonally expanded T cells, accompanied by enhanced keratinocyte activation and IL-22 receptor upregulation. Taken together, we demonstrate that dupilumab effectively dampens conventional type 2 inflammation in DAHND lesions, with concomitant hyperactivation of IL22 -associated responses. Dupilumab-associated head and neck dermatitis has been described in a subset of patients treated with the IL4R-blocker dupilumab. Here the authors characterise the immune cell composition and single-cell transcriptome in comparison with untreated forms of atopic dermatitis in a small cohort showing increases in IL-22-associated genes.

Anti-PD-1 therapy is used as a front-line treatment for many cancers, but mechanistic insight into this therapy resistance is still lacking. Here we generate a humanized (Hu)-mouse melanoma model by injecting fetal liver-derived CD34 + cells and implanting autologous thymus in immune-deficient NOD- scid IL2Rγ null (NSG) mice. Reconstituted Hu-mice are challenged with HLA-matched melanomas and treated with anti-PD-1, which results in restricted tumor growth but not complete regression. Tumor RNA-seq, multiplexed imaging and immunohistology staining show high expression of chemokines, as well as recruitment of FOXP3 + Treg and mast cells, in selective tumor regions. Reduced HLA-class I expression and CD8 + /Granz B + T cells homeostasis are observed in tumor regions where FOXP3 + Treg and mast cells co-localize, with such features associated with resistance to anti-PD-1 treatment. Combining anti-PD-1 with sunitinib or imatinib results in the depletion of mast cells and complete regression of tumors. Our results thus implicate mast cell depletion for improving the efficacy of anti-PD-1 therapy. Immune checkpoint therapies (ICT) are promising for treating various cancers, but response rates vary. Here the authors show, in mouse models, that tumor-infiltrating mast cells colocalize with regulatory T cells, coincide with local reduction of MHC-I and CD8 T cells, and is associated with resistance to ICT, which can be reversed by c-kit inhibitor treatment.

Cancer-associated fibroblasts (CAFs) play a key role in cancer progression and treatment outcome. This study dissects the intra-tumoral diversity of CAFs in basal cell carcinoma, squamous cell carcinoma, and melanoma using molecular and spatial single-cell analysis. We identify three distinct CAF subtypes: myofibroblast-like RGS5+ CAFs, matrix CAFs (mCAFs), and immunomodulatory CAFs (iCAFs). Large-cohort tissue analysis reveals significant shifts in CAF subtype patterns with increasing malignancy. Two CAF subtypes exhibit immunomodulatory properties via different mechanisms. mCAFs sythesize extracellular matrix and may restrict T cell invasion in low-grade tumors via ensheathing tumor nests, while iCAFs are enriched in late-stage tumors, and express high levels of cytokines and chemokines to aid immune cell recruitment and activation. This is supported by the induction of an iCAF-like phenotype with immunomodulatory functions in primary healthy fibroblasts exposed to skin cancer cell secretomes. Thus, targeting CAF variants holds promise to enhance immunotherapy efficacy in skin cancers. Fibroblast heterogeneity in the tumor microenvironment can explain their multifaceted role in cancer. Here by single-cell transcriptomic analysis of basal cell carcinoma, squamous cell carcinoma and melanoma samples, the authors explore fibroblast heterogeneity in skin cancer and their potential to modulate the tumor-immune microenvironment.

The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets. The number of publicly available proteomics datasets is growing rapidly, but a standardized approach for describing the associated metadata is lacking. Here, the authors propose a format and a software pipeline to present and validate metadata, and integrate them into ProteomeXchange repositories.

A newly developed algorithm enabled clustering of all 256 million (66 million identified and 190 million unidentified) peptide MS/MS spectra available in the PRIDE Archive database, allowing the detection of millions of consistently unidentified spectra across different data sets, of which roughly 20% could be identified using multiple complementary analysis tools. Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average, 75% of spectra analyzed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large scale to shed light on these unidentified spectra. The Proteomics Identifications (PRIDE) Database Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in the PRIDE Archive, coming from hundreds of data sets, we were able to consistently characterize spectra into three distinct groups: (1) incorrectly identified, (2) correctly identified but below the set scoring threshold, and (3) truly unidentified. Using multiple complementary analysis approaches, we were able to identify ∼20% of the consistently unidentified spectra. The complete spectrum-clustering results are available through the new version of the PRIDE Cluster resource ( http://www.ebi.ac.uk/pride/cluster ). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra.

Background The adoption of whole genome and exome sequencing (WGS/WES) is expanding rapidly, yet variant interpretation remains a critical bottleneck, limiting diagnostic yield and delaying precision care. We present ACVI-Med (Accelerated Candidate Variant Interpretation in Medicine), an open-source, on-premise platform for comprehensive analysis of genomic data. Results ACVI-Med integrates phenotype-aware filtering, ACMG-guided variant classification, and secondary findings detection into a unified, containerized system built for reproducibility and deployment across diverse institutional environments. Designed for accessibility, ACVI-Med enables users without extensive bioinformatics expertise to interpret variants from VCF (Variant Call Format) files through a flexible interface supporting phenotype-driven filtering, ACMG-guided variant classification, and integration of population, clinical, and predictive annotations. The software incorporates modules for secondary findings detection, aligned with ACMG Secondary Findings v3.2 recommendations, extending its utility beyond primary variant analysis. ACVI-Med’s customizable filtering logic, real-time access to curated knowledge bases, and interactive visualization tools support transparent and reproducible genomic interpretation. Conclusion ACVI-Med is an open-source software for genomic variant interpretation. Unlike commercial solutions, ACVI-Med is cost-effective, containerized, and can be institutionally self-hosted, reducing barriers to adoption in research settings.

Transglutaminase 1 (TGM1) plays an essential role in skin barrier formation by cross-linking proteins in differentiated keratinocytes. Here, we established a protocol for the antibody-dependent detection of TGM1 protein and the parallel detection of TGM activity. TGM1 immunoreactivity initially increased and co-localized with membrane-associated TGM activity during keratinocyte differentiation. TGM activity persisted upon further differentiation of keratinocytes, whereas TGM1 immunoreactivity was lost under standard assay conditions. Pretreatment of tissue sections with the proteases trypsin or proteinase K enabled immunodetection of TGM1 in cornified keratinocytes, indicating that removal of other proteins was a prerequisite for TGM1 immunolabeling after cornification. The increase of TGM activity and subsequent loss of TGM1 immunoreactivity could be replicated in HEK293T cells transfected with TGM1, suggesting that protein cross-linking mediated by TGM1 itself may lead to reduced recognition of TGM1 by antibodies. To screen for proteins potentially regulating TGM1, we performed Virotrap experiments and identified the CAPNS1 subunit of calpain as an interaction partner of TGM1. Treatment of keratinocytes and TGM1-transfected HEK293T cells with chemical inhibitors of calpain suppressed transglutamination. Our findings suggest that calpain contributes to the control of TGM1-mediated transglutamination and proteins cross-linked by transglutamination mask epitopes of TGM1.

There is increasing evidence that tertiary lymphoid structures (TLS) control not only local adaptive B cell responses at melanoma tumor sites but also the cellular composition and function of other immune cells. In human melanoma, however, a comprehensive analysis of TLS phenotypes, density and spatial distribution at different disease stages is lacking. Here we used 7-color multiplex immunostaining of whole tissue sections from 103 human melanoma samples to characterize TLS phenotypes along the expression of established TLS-defining molecular and cellular components. TLS density and spatial distribution were determined by referring TLS counts to the tissue area within defined intra- and extratumoral perimeters around the invasive tumor front. We show that only a subgroup of primary human melanomas contains TLS. These TLS rarely formed germinal centers and mostly located intratumorally within 1 mm distance to the invasive tumor front. In contrast, melanoma metastases had a significantly increased density of secondary follicular TLS. They appeared preferentially in stromal areas within an extratumoral 1 mm distance to the invasive tumor front and their density varied over time and site of metastasis. Interestingly, secondary follicular TLS in melanoma often lacked BCL6 + lymphatic cells and canonical germinal center polarity with the formation of dark and light zone areas. Our work provides an integrated qualitative, quantitative and spatial analysis of TLS in human melanoma and shows disease progression- and site-associated changes in TLS phenotypes, density and spatial distribution. The frequent absence of canonical germinal center polarity in melanoma TLS highlights the induction of TLS maturation as a potential additive to future immunotherapy studies. Given the variable evaluation strategies used in previous TLS studies of human tumors, an important asset of this study is the standardized quantitative evaluation approach that provides a high degree of reproducibility.