Plasticity and lineage commitment of individual TH1 cells are determined by stable T-bet expression quantities.

T helper 1 (TH1) cell identity is defined by the expression of the lineage-specifying transcription factor T-bet. Here, we examine the influence of T-bet expression heterogeneity on subset plasticity by leveraging cell sorting of distinct in vivo-differentiated TH1 cells based on their quantitative expression of T-bet and interferon-γ. Heterogeneous T-bet expression states were regulated by virus-induced type I interferons and were stably maintained even after secondary viral infection. Exposed to alternative differentiation signals, the sorted subpopulations exhibited graded levels of plasticity, particularly toward the TH2 lineage: T-bet quantities were inversely correlated with the ability to express the TH2 lineage-specifying transcription factor GATA-3 and TH2 cytokines. Reprogramed TH1 cells acquired graded mixed TH1 + TH2 phenotypes with a hybrid epigenetic landscape. Continuous presence of T-bet in differentiated TH1 cells was essential to ensure TH1 cell stability. Thus, innate cytokine signals regulate TH1 cell plasticity via an individual cell-intrinsic rheostat to enable T cell subset adaptation to subsequent challenges.

A mini-review on perturbation modelling across single-cell omic modalities.

Recent advances in single-cell omics technology have transformed the landscape of cellular and molecular research, enriching the scope and intricacy of cellular characterisation. Perturbation modelling seeks to comprehensively grasp the effects of external influences like disease onset or molecular knock-outs or external stimulants on cellular physiology, specifically on transcription factors, signal transducers, biological pathways, and dynamic cell states. Machine and deep learning tools transform complex perturbational phenomena in algorithmically tractable tasks to formulate predictions based on various types of single-cell datasets. However, the recent surge in tools and datasets makes it challenging for experimental biologists and computational scientists to keep track of the recent advances in this rapidly expanding filed of single-cell modelling. Here, we recapitulate the main objectives of perturbation modelling and summarise novel single-cell perturbation technologies based on genetic manipulation like CRISPR or compounds, spanning across omic modalities. We then concisely review a burgeoning group of computational methods extending from classical statistical inference methodologies to various machine and deep learning architectures like shallow models or autoencoders, to biologically informed approaches based on gene regulatory networks, and to combinatorial efforts reminiscent of ensemble learning. We also discuss the rising trend of large foundational models in single-cell perturbation modelling inspired by large language models. Lastly, we critically assess the challenges that underline single-cell perturbation modelling while pointing towards relevant future perspectives like perturbation atlases, multi-omics and spatial datasets, causal machine learning for interpretability, multi-task learning for performance and explainability as well as prospects for solving interoperability and benchmarking pitfalls.

Creating cloud platforms for supporting FAIR data management in biomedical research projects.

Biomedical research projects are becoming increasingly complex and require technological solutions that support all phases of the data lifecycle and application of the FAIR principles. At the Berlin Institute of Health (BIH), we have developed and established a flexible and cost-effective approach to building customized cloud platforms for supporting research projects. The approach is based on a microservice architecture and on the management of a portfolio of supported services. On this basis, we created and maintained cloud platforms for several international research projects. In this article, we present our approach and argue that building customized cloud platforms can offer multiple advantages over using multi-project platforms. Our approach is transferable to other research environments and can be easily adapted by other projects and other service providers.

Immunotherapy drives mesenchymal tumor cell state shift and TME immune response in glioblastoma patients.

BACKGROUND: Glioblastoma is a highly aggressive type of brain tumor for which there is no curative treatment available. Immunotherapies have shown limited responses in unselected patients, and there is an urgent need to identify mechanisms of treatment resistance to design novel therapy strategies. METHODS: Here we investigated the phenotypic and transcriptional dynamics at single-cell resolution during nivolumab immune checkpoint treatment of glioblastoma patients. RESULTS: We present the integrative paired single-cell RNA-seq analysis of 76 tumor samples from patients in a clinical trial of the PD-1 inhibitor nivolumab and untreated patients. We identify a distinct aggressive phenotypic signature in both tumor cells and the tumor microenvironment in response to nivolumab. Moreover, nivolumab-treatment was associated with an increased transition to mesenchymal stem-like tumor cells, and an increase in TAMs and exhausted and proliferative T cells. We verify and extend our findings in large external glioblastoma dataset (n = 298), develop a latent immune signature and find 18% of primary glioblastoma samples to be latent immune, associated with mesenchymal tumor cell state and TME immune response. Finally, we show that latent immune glioblastoma patients are associated with shorter overall survival following immune checkpoint treatment (P = .0041). CONCLUSIONS: We find a resistance mechanism signature in one fifth of glioblastoma patients associated with a tumor-cell transition to a more aggressive mesenchymal-like state, increase in TAMs and proliferative and exhausted T cells in response to immunotherapy. These patients may instead benefit from neuro-oncology therapies targeting mesenchymal tumor cells.

Proteomic and transcriptomic profiling of brainstem, cerebellum and olfactory tissues in early- and late-phase COVID-19.

Neurological symptoms, including cognitive impairment and fatigue, can occur in both the acute infection phase of coronavirus disease 2019 (COVID-19) and at later stages, yet the mechanisms that contribute to this remain unclear. Here we profiled single-nucleus transcriptomes and proteomes of brainstem tissue from deceased individuals at various stages of COVID-19. We detected an inflammatory type I interferon response in acute COVID-19 cases, which resolves in the late disease phase. Integrating single-nucleus RNA sequencing and spatial transcriptomics, we could localize two patterns of reaction to severe systemic inflammation, one neuronal with a direct focus on cranial nerve nuclei and a separate diffuse pattern affecting the whole brainstem. The latter reflects a bystander effect of the respiratory infection that spreads throughout the vascular unit and alters the transcriptional state of mainly oligodendrocytes, microglia and astrocytes, while alterations of the brainstem nuclei could reflect the connection of the immune system and the central nervous system via, for example, the vagus nerve. Our results indicate that even without persistence of severe acute respiratory syndrome coronavirus 2 in the central nervous system, local immune reactions are prevailing, potentially causing functional disturbances that contribute to neurological complications of COVID-19.

Genetic Characterization of Primary Mediastinal B-Cell Lymphoma: Pathogenesis and Patient Outcomes.

PURPOSE: Primary mediastinal large B-cell lymphoma (PMBCL) is a rare aggressive lymphoma predominantly affecting young female patients. Large-scale genomic investigations and genetic markers for risk stratification are lacking. PATIENTS AND METHODS: To elucidate the full spectrum of genomic alterations, samples from 340 patients with previously untreated PMBCL were investigated by whole-genome (n = 20), whole-exome (n = 78), and targeted (n = 308) sequencing. Statistically significant prognostic variables were identified using a multivariable Cox regression model and confirmed by L1/L2 regularized regressions. RESULTS: Whole-genome sequencing revealed a commonly disrupted p53 pathway with nonredundant somatic structural variations (SVs) in TP53-related genes (TP63, TP73, and WWOX) and identified novel SVs facilitating immune evasion (DOCK8 and CD83). Integration of mutation and copy-number data expanded the repertoire of known PMBCL alterations (eg, ARID1A, P2RY8, and PLXNC1) with a previously unrecognized role for epigenetic/chromatin modifiers. Multivariable analysis identified six genetic lesions with significant prognostic impact. CD58 mutations (31%) showed the strongest association with worse PFS (hazard ratio [HR], 2.52 [95% CI, 1.50 to 4.21]; P < .001) and overall survival (HR, 2.33 [95% CI, 1.14 to 4.76]; P = .02). IPI high-risk patients with mutated CD58 demonstrated a particularly poor prognosis, with 5-year PFS and OS rates of 41% and 58%, respectively. The adverse prognostic significance of the CD58 mutation status was predominantly observed in patients treated with nonintensified regimens, indicating that dose intensification may, to some extent, mitigate the impact of this high-risk marker. By contrast, DUSP2-mutated patients (24%) displayed durable responses (PFS: HR, 0.2 [95% CI, 0.07 to 0.55]; P = .002) and prolonged OS (HR, 0.11 [95% CI, 0.01 to 0.78]; P = .028). Upon CHOP-like treatment, these patients had very favorable outcome, with 5-year PFS and OS rates of 93% and 98%, respectively. CONCLUSION: This large-scale genomic characterization of PMBCL identified novel treatment targets and genetic lesions for refined risk stratification. DUSP2 and CD58 mutation analyses may guide treatment decisions between rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone and dose-adjusted etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin, and rituximab.

Mutational topography reflects clinical neuroblastoma heterogeneity.

Neuroblastoma is a pediatric solid tumor characterized by strong clinical heterogeneity. Although clinical risk-defining genomic alterations exist in neuroblastomas, the mutational processes involved in their generation remain largely unclear. By examining the topography and mutational signatures derived from all variant classes, we identified co-occurring mutational footprints, which we termed mutational scenarios. We demonstrate that clinical neuroblastoma heterogeneity is associated with differences in the mutational processes driving these scenarios, linking risk-defining pathognomonic variants to distinct molecular processes. Whereas high-risk MYCN-amplified neuroblastomas were characterized by signs of replication slippage and stress, homologous recombination-associated signatures defined high-risk non-MYCN-amplified patients. Non-high-risk neuroblastomas were marked by footprints of chromosome mis-segregation and TOP1 mutational activity. Furthermore, analysis of subclonal mutations uncovered differential activity of these processes through neuroblastoma evolution. Thus, clinical heterogeneity of neuroblastoma patients can be linked to differences in the mutational processes that are active in their tumors.

Genome-wide DNA methylation sequencing identifies epigenetic perturbations in the upper airways under long-term exposure to moderate levels of ambient air pollution.

While the link between exposure to high levels of ambient particulate matter (PM) and increased incidences of respiratory and cardiovascular diseases is widely recognized, recent epidemiological studies have shown that low PM concentrations are equally associated with adverse health effects. As DNA methylation is one of the main mechanisms by which cells regulate and stabilize gene expression, changes in the methylome could constitute early indicators of dysregulated signaling pathways. So far, little is known about PM-associated DNA methylation changes in the upper airways, the first point of contact between airborne pollutants and the human body. Here, we focused on cells of the upper respiratory tract and assessed their genome-wide DNA methylation pattern to explore exposure-associated early regulatory changes. Using a mobile epidemiological laboratory, nasal lavage samples were collected from a cohort of 60 adults that lived in districts with records of low (Simmerath) or moderate (Stuttgart) PM10 levels in Germany. PM10 concentrations were verified by particle measurements on the days of the sample collection and genome-wide DNA methylation was determined by enzymatic methyl sequencing at single-base resolution. We identified 231 differentially methylated regions (DMRs) between moderately and lowly PM10 exposed individuals. A high proportion of DMRs overlapped with regulatory elements, and DMR target genes were involved in pathways regulating cellular redox homeostasis and immune response. In addition, we found distinct changes in DNA methylation of the HOXA gene cluster whose methylation levels have previously been linked to air pollution exposure but also to carcinogenesis in several instances. The findings of this study suggest that regulatory changes in upper airway cells occur at PM10 levels below current European thresholds, some of which may be involved in the development of air pollution-related diseases.

Global hypomethylation in childhood asthma identified by genome-wide DNA-methylation sequencing preferentially affects enhancer regions.

BACKGROUND: Childhood asthma is a result of a complex interaction of genetic and environmental components causing epigenetic and immune dysregulation, airway inflammation and impaired lung function. Although different microarray based EWAS studies have been conducted, the impact of epigenetic regulation in asthma development is still widely unknown. We have therefore applied unbiased whole genome bisulfite sequencing (WGBS) to characterize global DNA-methylation profiles of asthmatic children compared to healthy controls. METHODS: Peripheral blood samples of 40 asthmatic and 42 control children aged 5-15 years from three birth cohorts were sequenced together with paired cord blood samples. Identified differentially methylated regions (DMRs) were categorized in genotype-associated, cell-type-dependent, or prenatally primed. Network analysis and subsequent natural language processing of DMR-associated genes was complemented by targeted analysis of functional translation of epigenetic regulation on the transcriptional and protein level. RESULTS: In total, 158 DMRs were identified in asthmatic children compared to controls of which 37% were related to the eosinophil content. A global hypomethylation was identified affecting predominantly enhancer regions and regulating key immune genes such as IL4, IL5RA, and EPX. These DMRs were confirmed in n = 267 samples and could be linked to aberrant gene expression. Out of the 158 DMRs identified in the established phenotype, 56 were perturbed already at birth and linked, at least in part, to prenatal influences such as tobacco smoke exposure or phthalate exposure. CONCLUSION: This is the first epigenetic study based on whole genome sequencing to identify marked dysregulation of enhancer regions as a hallmark of childhood asthma.

Robust methylation-based classification of brain tumours using nanopore sequencing.

BACKGROUND: DNA methylation-based classification of cancer provides a comprehensive molecular approach to diagnose tumours. In fact, DNA methylation profiling of human brain tumours already profoundly impacts clinical neuro-oncology. However, current implementation using hybridisation microarrays is time consuming and costly. We recently reported on shallow nanopore whole-genome sequencing for rapid and cost-effective generation of genome-wide 5-methylcytosine profiles as input to supervised classification. Here, we demonstrate that this approach allows us to discriminate a wide spectrum of primary brain tumours. RESULTS: Using public reference data of 82 distinct tumour entities, we performed nanopore genome sequencing on 382 tissue samples covering 46 brain tumour (sub)types. Using bootstrap sampling in a cohort of 55 cases, we found that a minimum set of 1000 random CpG features is sufficient for high-confidence classification by ad hoc random forests. We implemented score recalibration as a confidence measure for interpretation in a clinical context and empirically determined a platform-specific threshold in a randomly sampled discovery cohort (N = 185). Applying this cut-off to an independent validation series (n = 184) yielded 148 classifiable cases (sensitivity 80.4%) and demonstrated 100% specificity. Cross-lab validation demonstrated robustness with concordant results across four laboratories in 10/11 (90.9%) cases. In a prospective benchmarking (N = 15), the median time to results was 21.1 h. CONCLUSIONS: In conclusion, nanopore sequencing allows robust and rapid methylation-based classification across the full spectrum of brain tumours. Platform-specific confidence scores facilitate clinical implementation for which prospective evaluation is warranted and ongoing.

5'isomiR-183-5p|+2 elicits tumor suppressor activity in a negative feedback loop with E2F1.

BACKGROUND: MicroRNAs (miRNAs) and isomiRs play important roles in tumorigenesis as essential regulators of gene expression. 5'isomiRs exhibit a shifted seed sequence compared to the canonical miRNA, resulting in different target spectra and thereby extending the phenotypic impact of the respective common pre-miRNA. However, for most miRNAs, expression and function of 5'isomiRs have not been studied in detail yet. Therefore, this study aims to investigate the functions of miRNAs and their 5'isomiRs. METHODS: The expression of 5'isomiRs was assessed in The Cancer Genome Atlas (TCGA) breast cancer patient dataset. Phenotypic effects of miR-183 overexpression in triple-negative breast cancer (TNBC) cell lines were investigated in vitro and in vivo by quantifying migration, proliferation, tumor growth and metastasis. Direct targeting of E2F1 by miR-183-5p|+2 was validated with a 3'UTR luciferase assay and linked to the phenotypes of isomiR overexpression. RESULTS: TCGA breast cancer patient data indicated that three variants of miR-183-5p are highly expressed and upregulated, namely miR-183-5p|0, miR-183-5p|+1 and miR-183-5p|+2. However, TNBC cell lines displayed reduced proliferation and invasion upon overexpression of pre-miR-183. While invasion was reduced individually by all three isomiRs, proliferation and cell cycle progression were specifically inhibited by overexpression of miR-183-5p|+2. Proteomic analysis revealed reduced expression of E2F target genes upon overexpression of this isomiR, which could be attributed to direct targeting of E2F1, specifically by miR-183-5p|+2. Knockdown of E2F1 partially phenocopied the effect of miR-183-5p|+2 overexpression on cell proliferation and cell cycle. Gene set enrichment analysis of TCGA and METABRIC patient data indicated that the activity of E2F strongly correlated with the expression of miR-183-5p, suggesting transcriptional regulation of the miRNA by a factor of the E2F family. Indeed, in vitro, expression of miR-183-5p was regulated by E2F1. Hence, miR-183-5p|+2 directly targeting E2F1 appears to be part of a negative feedback loop potentially fine-tuning its activity. CONCLUSIONS: This study demonstrates that 5'isomiRs originating from the same arm of the same pre-miRNA (i.e. pre-miR-183-5p) may exhibit different functions and thereby collectively contribute to the same phenotype. Here, one of three isomiRs was shown to counteract expression of the pre-miRNA by negatively regulating a transcriptional activator (i.e. E2F1). We speculate that this might be part of a regulatory mechanism to prevent uncontrolled cell proliferation, which is disabled during cancer progression.

The genomic and transcriptional landscape of primary central nervous system lymphoma.

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Molecular drivers of PCNSL have not been fully elucidated. Here, we profile and compare the whole-genome and transcriptome landscape of 51 CNS lymphomas (CNSL) to 39 follicular lymphoma and 36 DLBCL cases outside the CNS. We find recurrent mutations in JAK-STAT, NFkB, and B-cell receptor signaling pathways, including hallmark mutations in MYD88 L265P (67%) and CD79B (63%), and CDKN2A deletions (83%). PCNSLs exhibit significantly more focal deletions of HLA-D (6p21) locus as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis are significantly enriched in PCNSL. TERT gene expression is significantly higher in PCNSL compared to activated B-cell (ABC)-DLBCL. Transcriptome analysis clearly distinguishes PCNSL and systemic DLBCL into distinct molecular subtypes. Epstein-Barr virus (EBV)+ CNSL cases lack recurrent mutational hotspots apart from IG and HLA-DRB loci. We show that PCNSL can be clearly distinguished from DLBCL, having distinct expression profiles, IG expression and translocation patterns, as well as specific combinations of genetic alterations.

MYCN mediates cysteine addiction and sensitizes neuroblastoma to ferroptosis.

Aberrant expression of MYC transcription factor family members predicts poor clinical outcome in many human cancers. Oncogenic MYC profoundly alters metabolism and mediates an antioxidant response to maintain redox balance. Here we show that MYCN induces massive lipid peroxidation on depletion of cysteine, the rate-limiting amino acid for glutathione (GSH) biosynthesis, and sensitizes cells to ferroptosis, an oxidative, non-apoptotic and iron-dependent type of cell death. The high cysteine demand of MYCN-amplified childhood neuroblastoma is met by uptake and transsulfuration. When uptake is limited, cysteine usage for protein synthesis is maintained at the expense of GSH triggering ferroptosis and potentially contributing to spontaneous tumor regression in low-risk neuroblastomas. Pharmacological inhibition of both cystine uptake and transsulfuration combined with GPX4 inactivation resulted in tumor remission in an orthotopic MYCN-amplified neuroblastoma model. These findings provide a proof of concept of combining multiple ferroptosis targets as a promising therapeutic strategy for aggressive MYCN-amplified tumors.

SSAM-lite: A Light-Weight Web App for Rapid Analysis of Spatially Resolved Transcriptomics Data.

The combination of a cell's transcriptional profile and location defines its function in a spatial context. Spatially resolved transcriptomics (SRT) has emerged as the assay of choice for characterizing cells in situ. SRT methods can resolve gene expression up to single-molecule resolution. A particular computational problem with single-molecule SRT methods is the correct aggregation of mRNA molecules into cells. Traditionally, aggregating mRNA molecules into cell-based features begins with the identification of cells via segmentation of the nucleus or the cell membrane. However, recently a number of cell-segmentation-free approaches have emerged. While these methods have been demonstrated to be more performant than segmentation-based approaches, they are still not easily accessible since they require specialized knowledge of programming languages and access to large computational resources. Here we present SSAM-lite, a tool that provides an easy-to-use graphical interface to perform rapid and segmentation-free cell-typing of SRT data in a web browser. SSAM-lite runs locally and does not require computational experts or specialized hardware. Analysis of a tissue slice of the mouse somatosensory cortex took less than a minute on a laptop with modest hardware. Parameters can interactively be optimized on small portions of the data before the entire tissue image is analyzed. A server version of SSAM-lite can be run completely offline using local infrastructure. Overall, SSAM-lite is portable, lightweight, and easy to use, thus enabling a broad audience to investigate and analyze single-molecule SRT data.

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy.

Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished 'classical' from 'basal-like' tumors with more aggressive clinical behavior. We derive PDAC organoids from 18 primary tumors and two matched liver metastases, and show that 'classical' and 'basal-like' cells coexist in individual organoids. By single-cell transcriptome analysis of PDAC organoids and primary PDAC, we identify distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. Cell states are connected by a differentiation hierarchy, with 'classical' cells concentrated at the endpoint. In an imaging-based drug screen, expression of 'classical' subtype genes correlates with better drug response. Our results thus uncover a functional hierarchy of PDAC cell states linked to transcriptional tumor subtypes, and support the use of PDAC organoids as a clinically relevant model for in vitro studies of tumor heterogeneity.

Cell segmentation-free inference of cell types from in situ transcriptomics data.

Multiplexed fluorescence in situ hybridization techniques have enabled cell-type identification, linking transcriptional heterogeneity with spatial heterogeneity of cells. However, inaccurate cell segmentation reduces the efficacy of cell-type identification and tissue characterization. Here, we present a method called Spot-based Spatial cell-type Analysis by Multidimensional mRNA density estimation (SSAM), a robust cell segmentation-free computational framework for identifying cell-types and tissue domains in 2D and 3D. SSAM is applicable to a variety of in situ transcriptomics techniques and capable of integrating prior knowledge of cell types. We apply SSAM to three mouse brain tissue images: the somatosensory cortex imaged by osmFISH, the hypothalamic preoptic region by MERFISH, and the visual cortex by multiplexed smFISH. Here, we show that SSAM detects regions occupied by known cell types that were previously missed and discovers new cell types.

CATCH: A Prospective Precision Oncology Trial in Metastatic Breast Cancer.

PURPOSE: CATCH (Comprehensive Assessment of clinical feaTures and biomarkers to identify patients with advanced or metastatic breast Cancer for marker driven trials in Humans) is a prospective precision oncology program that uses genomics and transcriptomics to guide therapeutic decisions in the clinical management of metastatic breast cancer. Herein, we report our single-center experience and results on the basis of the first 200 enrolled patients of an ongoing trial. METHODS: From June 2017 to March 2019, 200 patients who had either primary metastatic or progressive disease, with any number of previous treatment lines and at least one metastatic site accessible to biopsy, were enrolled. DNA and RNA from tumor tissue and corresponding blood-derived nontumor DNA were profiled using whole-genome and transcriptome sequencing. Identified actionable alterations were brought into clinical context in a multidisciplinary molecular tumor board (MTB) with the aim of prioritizing personalized treatment recommendations. RESULTS: Among the first 200 enrolled patients, 128 (64%) were discussed in the MTB, of which 64 (50%) were subsequently treated according to MTB recommendation. Of 53 evaluable patients, 21 (40%) achieved either stable disease (n = 13, 25%) or partial response (n = 8, 15%). Furthermore, 16 (30%) of those patients showed improvement in progression-free survival of at least 30% while on MTB-recommended treatment compared with the progression-free survival of the previous treatment line. CONCLUSION: The initial phase of this study demonstrates that precision oncology on the basis of whole-genome and RNA sequencing is feasible when applied in the clinical management of patients with metastatic breast cancer and provides clinical benefit to a substantial proportion of patients.

Mutational mechanisms shaping the coding and noncoding genome of germinal center derived B-cell lymphomas.

B cells have the unique property to somatically alter their immunoglobulin (IG) genes by V(D)J recombination, somatic hypermutation (SHM) and class-switch recombination (CSR). Aberrant targeting of these mechanisms is implicated in lymphomagenesis, but the mutational processes are poorly understood. By performing whole genome and transcriptome sequencing of 181 germinal center derived B-cell lymphomas (gcBCL) we identified distinct mutational signatures linked to SHM and CSR. We show that not only SHM, but presumably also CSR causes off-target mutations in non-IG genes. Kataegis clusters with high mutational density mainly affected early replicating regions and were enriched for SHM- and CSR-mediated off-target mutations. Moreover, they often co-occurred in loci physically interacting in the nucleus, suggesting that mutation hotspots promote increased mutation targeting of spatially co-localized loci (termed hypermutation by proxy). Only around 1% of somatic small variants were in protein coding sequences, but in about half of the driver genes, a contribution of B-cell specific mutational processes to their mutations was found. The B-cell-specific mutational processes contribute to both lymphoma initiation and intratumoral heterogeneity. Overall, we demonstrate that mutational processes involved in the development of gcBCL are more complex than previously appreciated, and that B cell-specific mutational processes contribute via diverse mechanisms to lymphomagenesis.

Lipomatous Solitary Fibrous Tumors Harbor Rare NAB2-STAT6 Fusion Variants and Show Up-Regulation of the Gene PPARG, Encoding for a Regulator of Adipocyte Differentiation.

Solitary fibrous tumors (SFTs) harbor activating NAB2-STAT6 gene fusions. Different variants of the NAB2-STAT6 gene fusion have been associated with distinct clinicopathologic features. Lipomatous SFTs are a morphologic variant of SFTs, characterized by a fat-forming tumor component. Our aim was to evaluate NAB2-STAT6 fusion variants and to further study the molecular genetic features in a cohort of lipomatous SFTs. A hybrid-capture-based next-generation sequencing panel was employed to detect NAB2-STAT6 gene fusions at the RNA level. In addition, the RNA expression levels of 507 genes were evaluated using this panel, and were compared with a control cohort of nonlipomatous SFTs. Notably, 5 of 11 (45%) of lipomatous SFTs in the current series harbored the uncommon NAB2 exon 4-STAT6 exon 4 gene fusion variant, which is observed in only 0.9% to 1.4% of nonlipomatous SFTs. Furthermore, lipomatous SFTs displayed significant differences in gene expression compared with their nonlipomatous counterparts, including up-regulation of the gene peroxisome proliferator activated receptor-γ (PPARG). Peroxisome proliferator activated receptor-γ is a nuclear receptor regulating adipocyte differentiation, providing a possible explanation for the fat-forming component in lipomatous SFTs. In summary, the current study provides a possible molecular genetic basis for the distinct morphologic features of lipomatous SFTs.