A spatial portrait of the human sebaceous gland transcriptional program.

Sebaceous glands (SG) and their oily secretion (sebum) are indispensable for maintaining skin structure and function, and their deregulation causes skin disorders including but not limited to acne. Recent studies also indicate that sebum may have important immunomodulatory activities and may influence whole-body energy metabolism. However, the progressive transcriptional changes of sebocytes that lead to sebum production have never been characterized in detail. Here, we exploited the high cellular resolution provided by sebaceous hyperplasia and integrated spatial transcriptomics, pseudo time analysis, RNA velocity, and functional enrichment to map the landscape of sebaceous differentiation. Our results were validated by comparison with published SG transcriptome data and further corroborated by assessing the protein expression pattern of a subset of the transcripts in the public repository Human Protein Atlas. Departing from four sebocyte differentiation stages generated by unsupervised clustering, we demonstrate consecutive modulation of cellular functions associable with specific gene sets, from cell proliferation and oxidative phosphorylation via lipid synthesis to cell death. Both validation methods confirmed the biological significance of our results. Our report is complemented by a freely available and browsable online tool. Our data provide the first high-resolution spatial portrait of the SG transcriptional landscape and deliver starting points for experimentally assessing novel candidate molecules for regulating SG homeostasis in health and disease.

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections.

A crucial feature of life is its spatial organization and compartmentalization on the molecular, cellular, and tissue levels. Spatial transcriptomics (ST) technology has opened a new chapter of the sequencing revolution, emerging rapidly with transformative effects across biology. This technique produces extensive and complex sequencing data, raising the need for computational methods for their comprehensive analysis and interpretation. We developed the ST browser web tool for the interactive discovery of ST images, focusing on different functional aspects such as single gene expression, the expression of functional gene sets, as well as the inspection of the spatial patterns of cell-cell interactions. As a unique feature, our tool applies self-organizing map (SOM) machine learning to the ST data. Our SOM data portrayal method generates individual gene expression landscapes for each spot in the ST image, enabling its downstream analysis with high resolution. The performance of the spatial browser is demonstrated by disentangling the intra-tumoral heterogeneity of melanoma and the microarchitecture of the mouse brain. The integration of machine-learning-based SOM portrayal into an interactive ST analysis environment opens novel perspectives for the comprehensive knowledge mining of the organization and interactions of cellular ecosystems.

Single-cell transcriptomics reveals prominent expression of IL-14, IL-18, and IL-32 in psoriasis.

RATIONALE: Psoriasis is a chronic inflammatory skin disease involving different cytokines and chemokines. OBJECTIVES: Here we use single-cell transcriptomic analyses to identify relevant immune cell and nonimmune cell populations for an in-depth characterization of cell types and inflammatory mediators in this disease. METHODS: Psoriasis skin lesions of eight patients are analyzed using single-cell technology. Data are further validated by in situ hybridization (ISH) of human tissues, serum analyses of human samples and tissues of a murine model of psoriasis, and by in vitro cell culture experiments. RESULTS: Several different immune-activated cell types with particular cytokine patterns are identified such as keratinocytes, T-helper cells, dendritic cells, macrophages, and fibroblasts. Apart from well-known factors, IL-14 (TXLNA), IL-18, and IL-32 are identified with prominent expression in individual cell types in psoriasis. The percentage of inflammatory cellular subtypes expressing IL-14, IL-18, and IL-32 was significantly higher in psoriatic skin compared with healthy control skin. These findings were confirmed by ISH of human skin samples, in a murine model of psoriasis, in human serum samples, and in in vitro experiments. CONCLUSIONS: Taken together, we provide a differentiated view of psoriasis immune-cell phenotypes that support the role of IL-14, IL-18, and IL-32 in psoriasis pathogenesis.

A Short History of B-Cell HLA Epitopes.

Background: HLA epitopes are currently in the focus of transplantation immunogenetics. The main reason is the complexity of the HLA system with >38,000 alleles, the number of which increases steadily. These alleles are determined by the current state-of-the art typing methods like second- and third-generation sequencing. Screening for HLA antibodies is hampered by the lack of specific target beads with all possible alleles described. Summary: A way to circumvent the problem is to define HLA epitopes. The number of antibody-confirmed epitopes, on the other hand, was found to be 72 for HLA class I and 74 for HLA class II. Here, we elaborate on the current knowledge on these HLA epitopes. Absolute definitions of these structures are not yet available. Key Messages: Making use of eplets is a comparable way allowing statistical analyses. However, one should keep in mind that the results obtained are approximative or perhaps better associative. Continuous collaboration is needed for the full understanding of the HLA epitopes. The reactivity toward epitopes remains patient-specific.

Multilineage communication regulates human liver bud development from pluripotency.

Conventional two-dimensional differentiation from pluripotency fails to recapitulate cell interactions occurring during organogenesis. Three-dimensional organoids generate complex organ-like tissues; however, it is unclear how heterotypic interactions affect lineage identity. Here we use single-cell RNA sequencing to reconstruct hepatocyte-like lineage progression from pluripotency in two-dimensional culture. We then derive three-dimensional liver bud organoids by reconstituting hepatic, stromal, and endothelial interactions, and deconstruct heterogeneity during liver bud development. We find that liver bud hepatoblasts diverge from the two-dimensional lineage, and express epithelial migration signatures characteristic of organ budding. We benchmark three-dimensional liver buds against fetal and adult human liver single-cell RNA sequencing data, and find a striking correspondence between the three-dimensional liver bud and fetal liver cells. We use a receptor-ligand pairing analysis and a high-throughput inhibitor assay to interrogate signalling in liver buds, and show that vascular endothelial growth factor (VEGF) crosstalk potentiates endothelial network formation and hepatoblast differentiation. Our molecular dissection reveals interlineage communication regulating organoid development, and illuminates previously inaccessible aspects of human liver development.

Transcriptome profile of the sinoatrial ring reveals conserved and novel genetic programs of the zebrafish pacemaker.

BACKGROUND: Sinoatrial Node (SAN) is part of the cardiac conduction system, which controls the rhythmic contraction of the vertebrate heart. The SAN consists of a specialized pacemaker cell population that has the potential to generate electrical impulses. Although the SAN pacemaker has been extensively studied in mammalian and teleost models, including the zebrafish, their molecular nature remains inadequately comprehended. RESULTS: To characterize the molecular profile of the zebrafish sinoatrial ring (SAR) and elucidate the mechanism of pacemaker function, we utilized the transgenic line sqet33mi59BEt to isolate cells of the SAR of developing zebrafish embryos and profiled their transcriptome. Our analyses identified novel candidate genes and well-known conserved signaling pathways involved in pacemaker development. We show that, compared to the rest of the heart, the zebrafish SAR overexpresses several mammalian SAN pacemaker signature genes, which include hcn4 as well as those encoding calcium- and potassium-gated channels. Moreover, genes encoding components of the BMP and Wnt signaling pathways, as well as members of the Tbx family, which have previously been implicated in pacemaker development, were also overexpressed in the SAR. Among SAR-overexpressed genes, 24 had human homologues implicated in 104 different ClinVar phenotype entries related to various forms of congenital heart diseases, which suggest the relevance of our transcriptomics resource to studying human heart conditions. Finally, functional analyses of three SAR-overexpressed genes, pard6a, prom2, and atp1a1a.2, uncovered their novel role in heart development and physiology. CONCLUSION: Our results established conserved aspects between zebrafish and mammalian pacemaker function and revealed novel factors implicated in maintaining cardiac rhythm. The transcriptome data generated in this study represents a unique and valuable resource for the study of pacemaker function and associated heart diseases.

A Transcriptome-Wide Isoform Landscape of Melanocytic Nevi and Primary Melanomas Identifies Gene Isoforms Associated with Malignancy.

Genetic splice variants have become of central interest in recent years, as they play an important role in different cancers. Little is known about splice variants in melanoma. Here, we analyzed a genome-wide transcriptomic dataset of benign melanocytic nevi and primary melanomas (n = 80) for the expression of specific splice variants. Using kallisto, a map for differentially expressed splice variants in melanoma vs. benign melanocytic nevi was generated. Among the top genes with differentially expressed splice variants were Ras-related in brain 6B (RAB6B), a member of the RAS family of GTPases, Macrophage Scavenger Receptor 1 (MSR1), Collagen Type XI Alpha 2 Chain (COLL11A2), and LY6/PLAUR Domain Containing 1 (LYPD1). The Gene Ontology terms of differentially expressed splice variants showed no enrichment for functional gene sets of melanoma vs. nevus lesions, but between type 1 (pigmentation type) and type 2 (immune response type) melanocytic lesions. A number of genes such as Checkpoint Kinase 1 (CHEK1) showed an association of mutational patterns and occurrence of splice variants in melanoma. Moreover, mutations in genes of the splicing machinery were common in both benign nevi and melanomas, suggesting a common mechanism starting early in melanoma development. Mutations in some of these genes of the splicing machinery, such as Serine and Arginine Rich Splicing Factor A3 and B3 (SF3A3, SF3B3), were significantly enriched in melanomas as compared to benign nevi. Taken together, a map of splice variants in melanoma is presented that shows a multitude of differentially expressed splice genes between benign nevi and primary melanomas. The underlying mechanisms may involve mutations in genes of the splicing machinery.

Deciphering the Transcriptomic Heterogeneity of Duodenal Coeliac Disease Biopsies.

Coeliac disease (CD) is a clinically heterogeneous autoimmune disease with variable presentation and progression triggered by gluten intake. Molecular or genetic factors contribute to disease heterogeneity, but the reasons for different outcomes are poorly understood. Transcriptome studies of tissue biopsies from CD patients are scarce. Here, we present a high-resolution analysis of the transcriptomes extracted from duodenal biopsies of 24 children and adolescents with active CD and 21 individuals without CD but with intestinal afflictions as controls. The transcriptomes of CD patients divide into three groups-a mixed group presenting the control cases, and CD-low and CD-high groups referring to lower and higher levels of CD severity. Persistence of symptoms was weakly associated with subgroup, but the highest marsh stages were present in subgroup CD-high, together with the highest cell cycle rates as an indicator of virtually complete villous atrophy. Considerable variation in inflammation-level between subgroups was further deciphered into immune cell types using cell type de-convolution. Self-organizing maps portrayal was applied to provide high-resolution landscapes of the CD-transcriptome. We find asymmetric patterns of miRNA and long non-coding RNA and discuss the effect of epigenetic regulation. Expression of genes involved in interferon gamma signaling represent suitable markers to distinguish CD from non-CD cases. Multiple pathways overlay in CD biopsies in different ways, giving rise to heterogeneous transcriptional patterns, which potentially provide information about etiology and the course of the disease.

oposSOM-Browser: an interactive tool to explore omics data landscapes in health science.

BACKGROUND: oposSOM is a comprehensive, machine learning based open-source data analysis software combining functionalities such as diversity analyses, biomarker selection, function mining, and visualization. RESULTS: These functionalities are now available as interactive web-browser application for a broader user audience interested in extracting detailed information from high-throughput omics data sets pre-processed by oposSOM. It enables interactive browsing of single-gene and gene set profiles, of molecular 'portrait landscapes', of associated phenotype diversity, and signalling pathway activation patterns. CONCLUSION: The oposSOM-Browser makes available interactive data browsing for five transcriptome data sets of cancer (melanomas, B-cell lymphomas, gliomas) and of peripheral blood (sepsis and healthy individuals) at www.izbi.uni-leipzig.de/opossom-browser .

Toll-like receptor 4 is a therapeutic target for prevention and treatment of liver failure.

BACKGROUND & AIMS: Toll-like receptor 4 (TLR4) plays an essential role in mediating organ injury in acute liver failure (ALF) and acute-on-chronic liver failure (ACLF). Herein, we assess whether inhibiting TLR4 signaling can ameliorate liver failure and serve as a potential treatment. METHODS: Circulating TLR4 ligands and hepatic TLR4 expression were measured in plasma samples and liver biopsies from patients with cirrhosis. TAK-242 (TLR4 inhibitor) was tested in vivo (10 mg/kg intraperitoneally) in rodent models of ACLF (bile duct ligation + lipopolysaccharide [LPS]; carbon tetrachloride + LPS) and ALF (galactosamine + LPS) and in vitro on immortalized human monocytes (THP-1) and hepatocytes (HHL5). The in vivo therapeutic effect was assessed by coma-free survival, organ injury and cytokine release and in vitro by measuring IL-6, IL-1ß or cell injury (TUNEL), respectively. RESULTS: In patients with cirrhosis, hepatic TLR4 expression was upregulated and circulating TLR4 ligands were increased (p <0.001). ACLF in rodents was associated with a switch from apoptotic cell death in ALF to non-apoptotic forms of cell death. TAK-242 reduced LPS-induced cytokine secretion and cell death (p = 0.002) in hepatocytes and monocytes in vitro. In rodent models of ACLF, TAK-242 administration improved coma-free survival, reduced the degree of hepatocyte cell death in the liver (p <0.001) and kidneys (p = 0.048) and reduced circulating cytokine levels (IL-1ß, p <0.001). In a rodent model of ALF, TAK-242 prevented organ injury (p <0.001) and systemic inflammation (IL-1ß, p <0.001). CONCLUSION: This study shows that TLR4 signaling is a key factor in the development of both ACLF and ALF; its inhibition reduces the severity of organ injury and improves outcome. TAK-242 may be of therapeutic relevance in patients with liver failure. LAY SUMMARY: Toll-like receptor 4 (or TLR4) mediates endotoxin-induced tissue injury in liver failure and cirrhosis. This receptor sensitizes cells to endotoxins, which are produced by gram-negative bacteria. Thus, inhibiting TLR4 signaling with an inhibitor (TAK-242) ameliorates organ injury and systemic inflammation in rodent models of acute and acute-on-chronic liver failure.

Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome.

Colorectal cancer (CRC) arising in Lynch syndrome (LS) comprises tumours with constitutional mutations in DNA mismatch repair genes. There is still a lack of whole-genome and transcriptome studies of LS-CRC to address questions about similarities and differences in mutation and gene expression characteristics between LS-CRC and sporadic CRC, about the molecular heterogeneity of LS-CRC, and about specific mechanisms of LS-CRC genesis linked to dysfunctional mismatch repair in LS colonic mucosa and the possible role of immune editing. Here, we provide a first molecular characterization of LS tumours and of matched tumour-distant reference colonic mucosa based on whole-genome DNA-sequencing and RNA-sequencing analyses. Our data support two subgroups of LS-CRCs, G1 and G2, whereby G1 tumours show a higher number of somatic mutations, a higher amount of microsatellite slippage, and a different mutation spectrum. The gene expression phenotypes support this difference. Reference mucosa of G1 shows a strong immune response associated with the expression of HLA and immune checkpoint genes and the invasion of CD4+ T cells. Such an immune response is not observed in LS tumours, G2 reference and normal (non-Lynch) mucosa, and sporadic CRC. We hypothesize that G1 tumours are edited for escape from a highly immunogenic microenvironment via loss of HLA presentation and T-cell exhaustion. In contrast, G2 tumours seem to develop in a less immunogenic microenvironment where tumour-promoting inflammation parallels tumourigenesis. Larger studies on non-neoplastic mucosa tissue of mutation carriers are required to better understand the early phases of emerging tumours. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Homozygosity in any HLA locus is a risk factor for specific antibody production: the taboo concept 2.0.

Objective: In a cooperative study of the University Hospital Leipzig, University of Leipzig, and the Charité Berlin on kidney transplant patients, we analysed the occurrence of HLA-specific antibodies with respect to the HLA setup of the patients. We aimed at the definition of specific HLA antigens towards which the patients produced these antibodies. Methods: Patients were typed for the relevant HLA determinants using mainly the next-generation technology. Antibody screening was performed by the state-of-the-art multiplex-based technology using microspheres coupled with the respective HLA alleles of HLA class I and II determinants. Results: Patients homozygous for HLA-A*02, HLA-A*03, HLA-A*24, HLA-B*07, HLA-B*18, HLA-B*35, HLA-B*44, HLA-C*03, HLA-C*04, and HLA-C*07 in the class I group and HLA-DRB1*01, HLA-DRB1*03, HLA-DRB1*07, HLA-DRB1*15, HLA-DQA1*01, HLA-DQA1*05, HLA-DQB1*02, HLA-DQB1*03(7), HLA-DQB1*06, HLA-DPA1*01, and HLA-DPB1*04 in the class II group were found to have a significant higher antibody production compared to the heterozygous ones. In general, all HLA determinants are affected. Remarkably, HLA-A*24 homozygous patients can produce antibodies towards all HLA-A determinants, while HLA-B*18 homozygous ones make antibodies towards all HLA-B and selected HLA-A and C antigens, and are associated with an elevation of HLA-DRB1, parts of DQB1 and DPB1 alleles. Homozygosity for the HLA class II HLA-DRB1*01, and HLA-DRB1*15 seems to increase the risk for antibody responses against most of the HLA class I antigens (HLA-A, HLA-B, and HLA-C) in contrast to HLA-DQB1*03(7) where a lower risk towards few HLA-A and HLA-B alleles is found. The widely observed differential antibody response is therefore to be accounted to the patient's HLA type. Conclusion: Homozygous patients are at risk of producing HLA-specific antibodies hampering the outcome of transplantation. Including this information on the allocation procedure might reduce antibody-mediated immune reactivity and prevent graft loss in a patient at risk, increasing the life span of the transplanted organ.

Potential of a Bead-Based Multiplex Assay for SARS-CoV-2 Antibody Detection.

Serological assays for SARS-CoV-2 play a pivotal role in the definition of whether patients are infected, the understanding of viral epidemiology, the screening of convalescent sera for therapeutic and prophylactic purposes, and in obtaining a better understanding of the immune response towards the virus. The aim of this study was to investigate the performance of a bead-based multiplex assay. This assay allowed for the simultaneous testing of IgG antibodies against SARS-CoV-2 spike, S1, S2, RBD, and nucleocapsid moieties and S1 of seasonal coronaviruses hCoV-22E, hCoV-HKU1, hCoV-NL63, and hCoV-OC43, as well as MERS and SARS-CoV. We compared the bead-based multiplex assay with commercial ELISA tests. We tested the sera of 27 SARS-CoV-2 PCR-positive individuals who were previously tested with different ELISA assays. Additionally, we investigated the reproducibility of the results by means of multiple testing of the same sera. Finally, the results were correlated with neutralising assays. In summary, the concordance of the qualitative results ranged between 78% and 96% depending on the ELISA assay and the specific antigen. Repeated freezing-thawing cycles resulted in reduced mean fluorescence intensity, while the storage period had no influence in this respect. In our test cohort, we detected up to 36% of sera positive for the development of neutralising antibodies, which is in concordance with the bead-based multiplex and IgG ELISA.

Genetic Predisposition to SARS-CoV-2 Infection: Cytokine Polymorphism and Disease Transmission within Households.

We addressed the question of the influence of the molecular polymorphism of cytokines from different T helper subsets on the susceptibility to SARS-CoV-2 infection. From a cohort of 527 samples (collected from 26 May 2020 to 31 March 2022), we focused on individuals living in the same household (n = 58) with the SARS-CoV-2-infected person. We divided them into households with all individuals SARS-CoV-2 PCR positive (n = 29, households, 61 individuals), households with mixed PCR pattern (n = 24, 62) and negative households (n = 5, 15), respectively. TGF-ß1 and IL-6 were the only cytokines tested with a significant difference between the cohorts. We observed a shift toward Th2 and the regulatory Th17 and Treg subset regulation for households with all members infected compared to those without infection. These data indicate that the genetically determined balance between the cytokines acting on different T helper cell subsets may play a pivotal role in transmission of and susceptibility to SARS-CoV-2 infection. Contacts infected by their index persons were more likely to highly express TGF-ß1, indicating a reduced inflammatory response. Those not infected after contact had a polymorphism leading to a higher IL-6 expression. IL-6 acts in innate immunity, allergy and on the T helper cell differentiation, explaining the reduced susceptibility to SARS-CoV-2.

Individual Immune Response to SARS-CoV-2 Infection-The Role of Seasonal Coronaviruses and Human Leukocyte Antigen.

During the coronavirus pandemic, evidence is growing that the severity, susceptibility and host immune response to SARS-CoV-2 infection can be highly variable. Several influencing factors have been discussed. Here, we investigated the humoral immune response against SARS-CoV-2 spike, S1, S2, the RBD, nucleocapsid moieties and S1 of seasonal coronaviruses: hCoV-229E, hCoV-HKU1, hCoV-NL63 and hCoV-OC43, as well as MERS-CoV and SARS-CoV, in a cohort of 512 individuals. A bead-based multiplex assay allowed simultaneous testing for all the above antigens and the identification of different antibody patterns. Then, we correlated these patterns with 11 HLA loci. Regarding the seasonal coronaviruses, we found a moderate negative correlation between antibody levels against hCoV-229E, hCoV-HKU1 and hCoV-NL63 and the SARS-CoV-2 antigens. This could be an indication of the original immunological imprinting. High and low antibody response patterns were distinguishable, demonstrating the individuality of the humoral response towards the virus. An immunogenetical factor associated with a high antibody response (formation of ≥4 different antibodies) was the presence of HLA A*26:01, C*02:02 and DPB1*04:01 alleles, whereas the HLA alleles DRB3*01:01, DPB1*03:01 and DB1*10:01 were enriched in low responders. A better understanding of this variable immune response could enable more individualized protective measures.

Transcriptomic Maps of Colorectal Liver Metastasis: Machine Learning of Gene Activation Patterns and Epigenetic Trajectories in Support of Precision Medicine.

The molecular mechanisms of the liver metastasis of colorectal cancer (CRLM) remain poorly understood. Here, we applied machine learning and bioinformatics trajectory inference to analyze a gene expression dataset of CRLM. We studied the co-regulation patterns at the gene level, the potential paths of tumor development, their functional context, and their prognostic relevance. Our analysis confirmed the subtyping of five liver metastasis subtypes (LMS). We provide gene-marker signatures for each LMS, and a comprehensive functional characterization that considers both the hallmarks of cancer and the tumor microenvironment. The ordering of CRLMs along a pseudotime-tree revealed a continuous shift in expression programs, suggesting a developmental relationship between the subtypes. Notably, trajectory inference and personalized analysis discovered a range of epigenetic states that shape and guide metastasis progression. By constructing prognostic maps that divided the expression landscape into regions associated with favorable and unfavorable prognoses, we derived a prognostic expression score. This was associated with critical processes such as epithelial-mesenchymal transition, treatment resistance, and immune evasion. These factors were associated with responses to neoadjuvant treatment and the formation of an immuno-suppressive, mesenchymal state. Our machine learning-based molecular profiling provides an in-depth characterization of CRLM heterogeneity with possible implications for treatment and personalized diagnostics.

Integrated Multi-Omics Maps of Lower-Grade Gliomas.

Multi-omics high-throughput technologies produce data sets which are not restricted to only one but consist of multiple omics modalities, often as patient-matched tumour specimens. The integrative analysis of these omics modalities is essential to obtain a holistic view on the otherwise fragmented information hidden in this data. We present an intuitive method enabling the combined analysis of multi-omics data based on self-organizing maps machine learning. It "portrays" the expression, methylation and copy number variations (CNV) landscapes of each tumour using the same gene-centred coordinate system. It enables the visual evaluation and direct comparison of the different omics layers on a personalized basis. We applied this combined molecular portrayal to lower grade gliomas, a heterogeneous brain tumour entity. It classifies into a series of molecular subtypes defined by genetic key lesions, which associate with large-scale effects on DNA methylation and gene expression, and in final consequence, drive with cell fate decisions towards oligodendroglioma-, astrocytoma- and glioblastoma-like cancer cell lineages with different prognoses. Consensus modes of concerted changes of expression, methylation and CNV are governed by the degree of co-regulation within and between the omics layers. The method is not restricted to the triple-omics data used here. The similarity landscapes reflect partly independent effects of genetic lesions and DNA methylation with consequences for cancer hallmark characteristics such as proliferation, inflammation and blocked differentiation in a subtype specific fashion. It can be extended to integrate other omics features such as genetic mutation, protein expression data as well as extracting prognostic markers.

Classifying Germinal Center Derived Lymphomas-Navigate a Complex Transcriptional Landscape.

Classification of lymphoid neoplasms is based mainly on histologic, immunologic, and (rarer) genetic features. It has been supplemented by gene expression profiling (GEP) in the last decade. Despite the considerable success, particularly in associating lymphoma subtypes with specific transcriptional programs and classifier signatures of up- or downregulated genes, competing molecular classifiers were often proposed in the literature by different groups for the same classification tasks to distinguish, e.g., BL versus DLBCL or different DLBCL subtypes. Moreover, rarer sub-entities such as MYC and BCL2 "double hit lymphomas" (DHL), IRF4-rearranged large cell lymphoma (IRF4-LCL), and Burkitt-like lymphomas with 11q aberration pattern (mnBLL-11q) attracted interest while their relatedness regarding the major classes is still unclear in many respects. We explored the transcriptional landscape of 873 lymphomas referring to a wide spectrum of subtypes by applying self-organizing maps (SOM) machine learning. The landscape reveals a continuum of transcriptional states activated in the different subtypes without clear-cut borderlines between them and preventing their unambiguous classification. These states show striking parallels with single cell gene expression of the active germinal center (GC), which is characterized by the cyclic progression of B-cells. The expression patterns along the GC trajectory are discriminative for distinguishing different lymphoma subtypes. We show that the rare subtypes take intermediate positions between BL, DLBCL, and FL as considered by the 5th edition of the WHO classification of haemato-lymphoid tumors in 2022. Classifier gene signatures extracted from these states as modules of coregulated genes are competitive with literature classifiers. They provide functional-defined classifiers with the option of consenting redundant classifiers from the literature. We discuss alternative classification schemes of different granularity and functional impact as possible avenues toward personalization and improved diagnostics of GC-derived lymphomas.

The Transcriptome and Methylome of the Developing and Aging Brain and Their Relations to Gliomas and Psychological Disorders.

Mutually linked expression and methylation dynamics in the brain govern genome regulation over the whole lifetime with an impact on cognition, psychological disorders, and cancer. We performed a joint study of gene expression and DNA methylation of brain tissue originating from the human prefrontal cortex of individuals across the lifespan to describe changes in cellular programs and their regulation by epigenetic mechanisms. The analysis considers previous knowledge in terms of functional gene signatures and chromatin states derived from independent studies, aging profiles of a battery of chromatin modifying enzymes, and data of gliomas and neuropsychological disorders for a holistic view on the development and aging of the brain. Expression and methylation changes from babies to elderly adults decompose into different modes associated with the serial activation of (brain) developmental, learning, metabolic and inflammatory functions, where methylation in gene promoters mostly represses transcription. Expression of genes encoding methylome modifying enzymes is very diverse reflecting complex regulations during lifetime which also associates with the marked remodeling of chromatin between permissive and restrictive states. Data of brain cancer and psychotic disorders reveal footprints of pathophysiologies related to brain development and aging. Comparison of aging brains with gliomas supports the view that glioblastoma-like and astrocytoma-like tumors exhibit higher cellular plasticity activated in the developing healthy brain while oligodendrogliomas have a more stable differentiation hierarchy more resembling the aged brain. The balance and specific shifts between volatile and stable and between more irreversible and more plastic epigenomic networks govern the development and aging of healthy and diseased brain.

Transcriptional states of CAR-T infusion relate to neurotoxicity - lessons from high-resolution single-cell SOM expression portraying.

Anti-CD19 CAR-T cell immunotherapy is a hopeful treatment option for patients with B cell lymphomas, however it copes with partly severe adverse effects like neurotoxicity. Single-cell resolved molecular data sets in combination with clinical parametrization allow for comprehensive characterization of cellular subpopulations, their transcriptomic states, and their relation to the adverse effects. We here present a re-analysis of single-cell RNA sequencing data of 24 patients comprising more than 130,000 cells with focus on cellular states and their association to immune cell related neurotoxicity. For this, we developed a single-cell data portraying workflow to disentangle the transcriptional state space with single-cell resolution and its analysis in terms of modularly-composed cellular programs. We demonstrated capabilities of single-cell data portraying to disentangle transcriptional states using intuitive visualization, functional mining, molecular cell stratification, and variability analyses. Our analysis revealed that the T cell composition of the patient's infusion product as well as the spectrum of their transcriptional states of cells derived from patients with low ICANS grade do not markedly differ from those of cells from high ICANS patients, while the relative abundancies, particularly that of cycling cells, of LAG3-mediated exhaustion and of CAR positive cells, vary. Our study provides molecular details of the transcriptomic landscape with possible impact to overcome neurotoxicity.