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Cancers often overexpress multiple clinically relevant oncogenes, but it is not known if combinations of oncogenes in cellular subpopulations within a cancer influence clinical outcomes. Using quantitative multispectral imaging of the prognostically relevant oncogenes MYC, BCL2, and BCL6 in diffuse large B-cell lymphoma (DLBCL), we show that the percentage of cells with a unique combination MYC+BCL2+BCL6− (M+2+6−) consistently predicts survival across four independent cohorts (n = 449), an effect not observed with other combinations including M+2+6+. We show that the M+2+6− percentage can be mathematically derived from quantitative measurements of the individual oncogenes and correlates with survival in IHC (n = 316) and gene expression (n = 2,521) datasets. Comparative bulk/single-cell transcriptomic analyses of DLBCL samples and MYC/BCL2/BCL6-transformed primary B cells identify molecular features, including cyclin D2 and PI3K/AKT as candidate regulators of M+2+6− unfavorable biology. Similar analyses evaluating oncogenic combinations at single-cell resolution in other cancers may facilitate an understanding of cancer evolution and therapy resistance. Significance: Using single-cell–resolved multiplexed imaging, we show that selected subpopulations of cells expressing specific combinations of oncogenes influence clinical outcomes in lymphoma. We describe a probabilistic metric for the estimation of cellular oncogenic coexpression from IHC or bulk transcriptomes, with possible implications for prognostication and therapeutic target discovery in cancer. This article is highlighted in the In This Issue feature, p. 1027

Supplementary methods. Supplementary Figure 1. Phenotyping of B-cells in non-malignant tissues. A, Quantitation of marker positivity across ten tonsil and two reactive lymph node samples (rLN). Analysis is spatially resolved between the GC and extra-GC zones. B, Spatial map of cellular coordinates based on cell segmentation of images in Figure 1B. Marker-positivity is indicated, and a total proportion of positive and negative cells is depicted as a pie chart. These maps were used to derive sub-population phenotypes depicted in Figure 1C. Scale bar is 100μm. C, Proliferation analysis (i.e., Ki67-positivity) among sub-populations in five tonsil samples. Median with interquartile range, whiskers denote 10th and 90th percentile. Supplementary figure 2. Example pseudo-colored mfIHC images for MYC, BCL2, BCL6 cases in DLBCL. Images of a range of mean fluorescent intensities are shown with equal scaling for reference. Supplementary figure 3. Global distribution of MYC, BCL2 and BCL6 sub-populations within DLBCL cohorts. Heat-maps displaying the percentage extent of individual markers and each sub-population within the DLBCL NUH, CMMC, SGH and MDA cohorts. Hierarchical k-means clustering of patients according to sub-population extent is applied. Positivity shading for single markers ranges between 0-100% positivity, whereas shading for sub-populations reflects 0-50% positivity and remains fully saturated until 100%. IPI Risk Group - International Prognostic Index Risk Group, FISH - fluorescence in situ hybridization. Supplementary figure 4. Intra-tumor heterogeneity of sub-populations. A, Correlation of sub-population extent quantification between two biopsies of the same patient for which at least two tissue microarray (TMA) biopsies are available. Correlation is shown separately for lymph node and extranodal biopsies. Spearman rho is indicated for each correlation. Axes are in exponential and equivalent in all panels. B, Sub-population percentage extent quantification across multiple TMA cores (columns) of the same patient (rows). Pie charts are ordered according to decreasing cell numbers evaluated per core. All patients from the NUH cohort with at least five cores are evaluated. A heterogenous cluster is highlighted by the red box. Supplementary figure 5. Spatial heterogeneity of sub-population interactions. A, Conceptual schematic of pair correlation function (PCF) plots depicting a clustered distribution (left, green) and a random distribution (right, grey). Representative counterpart spatial maps are above each plot. B, PCF analysis for sub-populations to investigate spatial clustering (top). Mean results for two independent cohorts (shading is cohort standard deviation). An example tissue microarray core is shown as physical distance reference for spatial analyses (bottom left). Absolute number of neighboring cells expected within a given radius (data from 3500 randomly selected cells across all images, mean with standard deviation) (bottom right). C, Actual spatial map of sub-populations of an example DLBCL case (top). Extent of all sub-populations within the sample is shown on the left. Simulated, hypothetical random distribution of cells for the same case (middle). PCF analysis for the shown sample and its matched simulated random distribution (bottom). Scale bars in B and C are 100µm. D, Mean deviations from expected neighbor abundance (Δ%) summarizing cell-cell interactions between sub-populations for the sample shown in (C). E, Sub-population interaction matrices from spatially distinct biopsies (cores in tissue microarray) for example DLBCL patients. Biopsies of stable, spatially homogenous, sub-population interaction profiles are grouped (top), whereas biopsies of a differing, heterogenous, interaction profile are grouped separately (bottom). Supplementary figure 6. Global deviations from expected spatial neighbor abundance (Δ%). Hierarchical clustering (minimum variance method) of measured Δ% for all cases in the SGH and MDA cohorts. Extents of sub-populations are indicated for reference (top). For the MDA cohort, multiple biopsies (n = 1-3) from the same patient were included in the analysis to determine spatial interaction similarity across spatially distinct regions (bottom). Supplementary figure 7. Correlation of predicted MYC, BCL2 and BCL6 sub-population percentage extent based on single oncogene positivity and observed percentage extent in DLBCL cohorts. Spearman rho, axes are equivalent in all panels. Supplementary figure 8. Variance of M+2+6- percentage extent in the context of positivity calling across a 15% cut-off. A, M+2+6- scoring variance across multiple pathological imaging fields. All whole-tissue DLBCL sections from University of Palermo (UP), and samples from the NUH TMA with at least four fields scored per patient and a mean M+2+6- score above 5% are shown. Mean with SD. Ordinates between 50-100% are compressed for clarity. Dashed line denotes M+2+6- 15% positivity. B, Stability of M+2+6- case positivity calling across scoring increasing number of imaging fields. All cases from panel A with at least five fields scored in this study are shown. Only one case is called M+2+6- Low (

Cancers often overexpress multiple clinically relevant oncogenes, but it is not known if combinations of oncogenes in cellular subpopulations within a cancer influence clinical outcomes. Using quantitative multispectral imaging of the prognostically relevant oncogenes MYC, BCL2, and BCL6 in diffuse large B-cell lymphoma (DLBCL), we show that the percentage of cells with a unique combination MYC+BCL2+BCL6− (M+2+6−) consistently predicts survival across four independent cohorts (n = 449), an effect not observed with other combinations including M+2+6+. We show that the M+2+6− percentage can be mathematically derived from quantitative measurements of the individual oncogenes and correlates with survival in IHC (n = 316) and gene expression (n = 2,521) datasets. Comparative bulk/single-cell transcriptomic analyses of DLBCL samples and MYC/BCL2/BCL6-transformed primary B cells identify molecular features, including cyclin D2 and PI3K/AKT as candidate regulators of M+2+6− unfavorable biology. Similar analyses evaluating oncogenic combinations at single-cell resolution in other cancers may facilitate an understanding of cancer evolution and therapy resistance.Significance:Using single-cell–resolved multiplexed imaging, we show that selected subpopulations of cells expressing specific combinations of oncogenes influence clinical outcomes in lymphoma. We describe a probabilistic metric for the estimation of cellular oncogenic coexpression from IHC or bulk transcriptomes, with possible implications for prognostication and therapeutic target discovery in cancer.This article is highlighted in the In This Issue feature, p. 1027

Quantitative single-cell analysis of MYC, BCL2, and BCL6 protein expression in B cells in nonmalignant tissues and diffuse large B-cell lymphoma. A, Schematic workflow of a quantitative digital pathology experiment. B, Spectrally unmixed multiplexed fluorescent images for CD20, MYC, BCL2, and BCL6 and nuclear counterstaining in tonsil tissue. The germinal center (GC) and extragerminal center (extra-GC) zones are indicated. C, Spatial map of MYC/BCL2/BCL6 subpopulations, i.e., possible permutations of MYC/BCL2/BCL6-positivity and -negativity within the CD20-positive cell population in a tonsil image. D, Quantitation of subpopulation extent within CD20-positive cells in tonsils and reactive lymph nodes resolved spatially between the GC and extra-GC zones. E, Example of pseudocolored MYC/BCL2/BCL6/CD20 mfIHC staining in diffuse large B-cell lymphoma (DLBCL; left). Cell segmentation and single oncogene positivity masks are shown within the CD20-positive cell population (right). F, Summary of percentage extent of subpopulations across patients from National University Hospital (NUH), Chi-Mei Medical Center (CMMC), MD Anderson (MDA), and Singapore General Hospital (SGH). Relevant clinicopathologic features are indicated; see also Supplementary Fig. S3. Patients were ordered arbitrarily according to extent of the triple-positive M+2+6+ subpopulation extent. IPI Risk Group, International Prognostic Index Risk Group; FISH, fluorescence in situ hybridization. G, Intrapatient spatial stability of subpopulations – proportion of subpopulations measured across four spatially distinct biopsies from the same patient (rows). Biopsy comparison overview is shown across 11 representative example DLBCL patients (columns). See also Supplementary Fig. S4A and S4B for a correlation analysis for all patients with multiple biopsies available. H, Proliferation analysis (i.e., Ki-67-positivity) among subpopulations in DLBCL samples. Proliferative BCL6-positive subpopulations are grouped. Median with interquartile range, whiskers denote 10th and 90th percentile. Mann–Whitney test (BCL6-positive vs. -negative subpopulations). All scale bars, 100 μm.

Transcriptomic analysis of M+2+6− high cases and potential role of CCND2. A, Correlation of observed M+2+6− percentage extent in the BCA cohort with the cell-of-origin (COO) DLBCL90-COO signature. Bonferroni corrected Kruskal–Wallis test for ABC vs. others. B, Correlation of M+2+6− metric in GEP cohorts with COO signatures. Mean M+2+6− metric value per group per cohort is shown. Bonferroni corrected paired-samples t test. C, Correlation of the M+2+6− percentage extent and metric evaluated by mfIHC and mRNA inference, respectively, with genetic subtypes (LymphGen classification). D, Sankey plot of M+2+6− dichotomized grouping matched with molecular features. E, Volcano plot of pooled direct correlation of gene mRNA expression and M+2+6− metric across seven GEP cohorts. Genes highly correlated with M+2+6− metric across datasets at absolute Spearman rho ≥0.2 and FDR≤0.001 are shown (see also Supplementary Table S11). The abscissa is scaled exponentially. F, Differential gene expression between primary GC B cells overexpressing M+2+ and M+2+6+ (see also Supplementary Table S12). Analysis is generated from 4 biological replicates from each condition, from cells of independent donors. G, Genes highly enriched in M+2+6− cells: correlation of results from E and F. H,CCDN2 gene expression in GEP cohorts in patients dichotomized by M+2+6− 15% metric (left) and in primary B cells (right). Paired t test (left); mean with standard deviation and FDR (FDR as per Supplementary Table S12) for t test (right). I, Single-cell RNA-seq of GC primary B cells transduced either with BCL2 and MYC (MYC-transduced) or BCL2 and BCL6 (BCL6-transduced). Untransduced GC primary B cells are also included. Expression of CCND2 is indicated in color. J, Proliferation analysis of M+2+6+ primary GC B cells overexpressing cyclin D2 (CCND2) compared with M+2+6+ primary GC B cells transduced with an empty vector (EV). Analysis performed with 3 biological replicates for each condition, using cells from 3 independent patients; mean with standard deviation; t test. UMAP, Uniform Manifold Approximation and Projection.

Multivariate analysis of continuous M+2+6− percentage extent at 5% increments as a predictor of OS in the NUH, SGH, and MDA cohorts of DLBCL (Cox proportional hazards model)

Supplementary table 1. Per-patient mfIHC MYC, BCL2 and BCL6 single oncogene and subpopulation scores for normal tonsil tissue and reactive lymph node tissue. Supplementary table 2. Per-patient mfIHC MYC, BCL2 and BCL6 single oncogene and subpopulation scores for DLBCL tissue (NUH, CMMC, SGH, MDA, BCA and UP). Supplementary table 6. Inferred percentage extents of MYC, BCL2, BCL6 and sub-population metrics in GEP cohorts. Supplementary table 11. Correlation of M+2+6- metric with gene expression in GEP cohorts. Supplementary table 12. Differential gene expression analysis of primary germinal center (GC) B-cells with M+2+ and M+2+6+ overexpression. Supplementary table 13. Differentially expressed genes between M+2+6- and all other malignant cells in scRNA-seq samples of DLBCL. Dichotomized non-parametric comparison, Wilcoxon rank sum test. Supplementary table 14. Analysis of positive enrichment of Wikipathways terms between M+2+6- and all other malignant cells in scRNA-seq samples of DLBCL by gprofiler2.

MYC, BCL2, and BCL6 protein coexpression in DLBCL can be inferred from individual marker data. A, Schematic of possible relationships between expression of three oncogenes in a population of cells. The distribution of these oncogenes can either reflect interdependent expression, independent/stochastic expression, or mutually exclusive expression. These relationships result in the percentage extent of oncogenes in the tumor being either strongly positively correlated, not correlated, or strongly negatively correlated, respectively. Created with BioRender.com. B, Correlation of MYC, BCL2, and BCL6 percentage extent across patients in DLBCL cohorts. Spearman correlation; axes are equivalent in all panels. C, Good correlation between probabilistically predicted subpopulation percentage extent based on single oncogene positivity and observed percentage extent in the NUH cohort. Cases of double-hit lymphoma (DHL, MYC+BCL2+ translocations or MYC+BCL6+ translocations) or triple-hit lymphoma (THL) are highlighted. Spearman rho for each correlation is shown; axes are equivalent in all panels. Correlation for other cohorts can be found in Supplementary Fig. S7. D, Prospective evaluation of an optimal dichotomization cutoff for M+2+6− percentage extent in the BCA cohort. Univariate Cox PH model at 1% extent positivity increment, HR for death with 95% CI. HR scale is exponential. Optimal dichotomization cutoff is highlighted in blue. E, Kaplan–Meier OS analysis of the chromogenic IHC BCA cohort evaluation stratified into M+2+6− metric high and low groups across an absolute value of 15% M+2+6−metric. Log-rank test, shading denotes 95% confidence interval. CMMC, Chi-Mei Medical Center.

Validation of prognostic significance of the M+2+6− subpopulation metric in gene-expression datasets. A, Distribution of single oncogene positivity in DLBCL cohorts as assessed by mfIHC (see Supplementary Fig. S9A and S9B). B, Impact of subpopulation metrics in GEP datasets on OS. Pooled univariate Cox PH model analysis; metric was used as a continuous variable in the model at 5% increments. HR per 5% increment with 95% CI is shown; CI are proportional on both tails but are capped at the graph's edges. Pooled P values were Bonferroni corrected to adjust for multiple testing and are shown for each subpopulation. C, Kaplan–Meier OS analysis of GEP cohorts stratified uniformly across absolute 15% M+2+6− metric into -high and -low groups. Log-rank test, shading denotes 95% CI. Total patient numbers in each group are shown. CMMC, Chi-Mei Medical Center.

Prognostic significance of subpopulations after R-CHOP therapy. A, Pooled univariate Cox PH model analysis for MYC, BCL2, and BCL6 single oncogene and subpopulations percentage extent as predictors of OS across multiple DLBCL cohorts. Percentage extent was used as a continuous variable in the model at 5% increments (see Survival Analysis) for an unbiased comparison between the variables. Pooled P values were Bonferroni corrected for single oncogenes and subpopulations independently to adjust for multiple testing and are shown for each variable. Hazard ratio (HR) with 95% confidence interval (CI) per 5%-positivity increment is shown (see also Supplementary Table S4). B, Kaplan–Meier OS analysis of dichotomized into M+2+6− high and low groups. Log-rank test, shading denotes 95% CI. An optimal dichotomization cutoff was used for stratification; total patient numbers in each group are shown.

Prognostic values of MHC expression

IHC antibodies and cell line information

CREBBP mutations are highly recurrent in B-cell lymphomas and either inactivate its histone acetyltransferase (HAT) domain or truncate the protein. Herein, we show that these two classes of mutations yield different degrees of disruption of the epigenome, with HAT mutations being more severe and associated with inferior clinical outcome. Genes perturbed by CREBBP mutation are direct targets of the BCL6–HDAC3 onco-repressor complex. Accordingly, we show that HDAC3-selective inhibitors reverse CREBBP-mutant aberrant epigenetic programming, resulting in: (i) growth inhibition of lymphoma cells through induction of BCL6 target genes such as CDKN1A and (ii) restoration of immune surveillance due to induction of BCL6-repressed IFN pathway and antigen-presenting genes. By reactivating these genes, exposure to HDAC3 inhibitors restored the ability of tumor-infiltrating lymphocytes to kill DLBCL cells in an MHC class I and II–dependent manner, and synergized with PD-L1 blockade in a syngeneic model in vivo. Hence, HDAC3 inhibition represents a novel mechanism-based immune epigenetic therapy for CREBBP-mutant lymphomas.Significance:We have leveraged the molecular characterization of different types of CREBBP mutations to define a rational approach for targeting these mutations through selective inhibition of HDAC3. This represents an attractive therapeutic avenue for targeting synthetic vulnerabilities in CREBBP-mutant cells in tandem with promoting antitumor immunity.This article is highlighted in the In This Issue feature, p. 327

Supplementary Methods, Figures and Legends

Genetic backgrounds of MHC deficient cases

Genetic analysis in the MHC-I/II double-positive cases

We performed a genomic, transcriptomic, and immunophenotypic study of 347 patients with diffuse large B-cell lymphoma (DLBCL) to uncover the molecular basis underlying acquired deficiency of MHC expression. Low MHC-II expression defines tumors originating from the centroblast-rich dark zone of the germinal center (GC) that was associated with inferior prognosis. MHC-II–deficient tumors were characterized by somatically acquired gene mutations reducing MHC-II expression and a lower amount of tumor-infiltrating lymphocytes. In particular, we demonstrated a strong enrichment of EZH2 mutations in both MHC-I– and MHC-II–negative primary lymphomas, and observed reduced MHC expression and T-cell infiltrates in murine lymphoma models expressing mutant Ezh2Y641. Of clinical relevance, EZH2 inhibitors significantly restored MHC expression in EZH2-mutated human DLBCL cell lines. Hence, our findings suggest a tumor progression model of acquired immune escape in GC-derived lymphomas and pave the way for development of complementary therapeutic approaches combining immunotherapy with epigenetic reprogramming.Significance:We demonstrate how MHC-deficient lymphoid tumors evolve in a cell-of-origin–specific context. Specifically, EZH2 mutations were identified as a genetic mechanism underlying acquired MHC deficiency. The paradigmatic restoration of MHC expression by EZH2 inhibitors provides the rationale for synergistic therapies combining immunotherapies with epigenetic reprogramming to enhance tumor recognition and elimination.See related commentary by Velcheti et al., p. 472.This article is highlighted in the In This Issue feature, p. 453

EZH2 mutation data

Figures S1 - S16 Supplementary Methods

Gene expression analyses of clinical samples

Hodgkin lymphoma is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of noncancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding cross-talk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 Hodgkin lymphoma tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the Hodgkin lymphoma–specific immune microenvironment at single-cell resolution. Single-cell expression profiling identified a novel Hodgkin lymphoma–associated subset of T cells with prominent expression of the inhibitory receptor LAG3, and functional analyses established this LAG3+ T-cell population as a mediator of immunosuppression. Multiplexed spatial assessment of immune cells in the microenvironment also revealed increased LAG3+ T cells in the direct vicinity of MHC class II–deficient tumor cells. Our findings provide novel insights into TME biology and suggest new approaches to immune-checkpoint targeting in Hodgkin lymphoma.Significance:We provide detailed functional and spatial characteristics of immune cells in classic Hodgkin lymphoma at single-cell resolution. Specifically, we identified a regulatory T-cell–like immunosuppressive subset of LAG3+ T cells contributing to the immune-escape phenotype. Our insights aid in the development of novel biomarkers and combination treatment strategies targeting immune checkpoints.See related commentary by Fisher and Oh, p. 342.This article is highlighted in the In This Issue feature, p. 327

Supplementary Methods, Supplementary Figures 1-19, Supplementary References

Tables S1 - S13

MHC expression status in the cohort

Richter syndrome (RS) is the transformation of chronic lymphocytic leukemia (CLL) into aggressive lymphoma, most commonly diffuse large B-cell lymphoma (DLBCL). We characterize 58 primary human RS samples by genome-wide DNA methylation and whole-transcriptome profiling. Our comprehensive approach determines RS DNA methylation profile and unravels a CLL epigenetic imprint, allowing CLL-RS clonal relationship assessment without the need of the initial CLL tumor DNA. DNA methylation- and transcriptomic-based classifiers were developed, and testing on landmark DLBCL datasets identifies a poor-prognosis, activated B-cell-like DLBCL subset in 111/1772 samples. The classification robustly identifies phenotypes very similar to RS with a specific genomic profile, accounting for 4.3-8.3% of de novo DLBCLs. In this work, RS multi-omics characterization determines oncogenic mechanisms, establishes a surrogate marker for CLL-RS clonal relationship, and provides a clinically relevant classifier for a subset of primary “RS-type DLBCL” with unfavorable prognosis., publishedVersion

The Transport Layer Security (TLS) protocol is used to cryptographically secure network connections. To ensure authenticity, TLS uses certificates that are exchanged at the beginning of each new connection. Due to expiration or early revocation of certificates, the deployment of new certificates to devices in the field is necessary. In addition, a device must identify revoked certificates during connection establishment to abort the connection. This paper presents the implementation of these two functionalities within a Security Gateway for the power grid. The nature of embedded systems with their limited resources and requirements regarding dependability impact the device-specific implementation. With these features, the Security Gateway can be integrated into an existing Public-Key Infrastructure System.

Histone methylation-modifiers, such as EZH2 and KMT2D, are recurrently altered in B-cell lymphomas. To comprehensively describe the landscape of alterations affecting genes encoding histone methylation-modifiers in lymphomagenesis we investigated whole genome and transcriptome data of 186 mature B-cell lymphomas sequenced in the ICGC MMML-Seq project. Besides confirming common alterations of KMT2D (47% of cases), EZH2 (17%), SETD1B (5%), PRDM9 (4%), KMT2C (4%), and SETD2 (4%), also identified by prior exome or RNA-sequencing studies, we here found recurrent alterations to KDM4C in chromosome 9p24, encoding a histone demethylase. Focal structural variation was the main mechanism of KDM4C alterations, and was independent from 9p24 amplification. We also identified KDM4C alterations in lymphoma cell lines including a focal homozygous deletion in a classical Hodgkin lymphoma cell line. By integrating RNA-sequencing and genome sequencing data we predict that KDM4C structural variants result in loss-offunction. By functional reconstitution studies in cell lines, we provide evidence that KDM4C can act as a tumor suppressor. Thus, we show that identification of structural variants in whole genome sequencing data adds to the comprehensive description of the mutational landscape of lymphomas and, moreover, establish KDM4C as a putative tumor suppressive gene recurrently altered in subsets of B-cell derived lymphomas., publishedVersion

High programmed cell death 1 ligand 1 (PD-L1) protein expression and copy number alterations (CNAs) of the corresponding genomic locus 9p24.1 in Hodgkin- and Reed-Sternberg cells (HRSC) have been shown to be associated with favourable response to anti-PD-1 checkpoint inhibition in relapsed/refractory (r/r) classical Hodgkin lymphoma (cHL). In the present study, we investigated baseline 9p24.1 status as well as PD-L1 and major histocompatibility complex (MHC) class I and II protein expression in 82 biopsies from patients with early stage unfavourable cHL treated with anti-PD-1-based first-line treatment in the German Hodgkin Study Group (GHSG) NIVAHL trial (ClinicalTrials.gov Identifier: NCT03004833). All evaluated specimens showed 9p24.1 CNA in HRSC to some extent, but with high intratumoral heterogeneity and an overall smaller range of alterations than reported in advanced-stage or r/r cHL. All but two cases (97%) showed PD-L1 expression by the tumour cells in variable amounts. While MHC-I was rarely expressed in >50% of HRSC, MHC-II expression in >50% of HRSC was found more frequently. No obvious impact of 9p24.1 CNA or PD-L1 and MHC-I/II expression on early response to the highly effective anti-PD-1-based NIVAHL first-line treatment was observed. Further studies evaluating an expanded panel of potential biomarkers are needed to optimally stratify anti-PD-1 first-line cHL treatment.

With autonomous driving, the system complexity of vehicles will increase drastically. This requires new ap- proaches to ensure system safety. Looking at standards like ISO 26262 or ISO/PAS 21448 and their suggested methodologies, an increasing trend in the recent literature can be noticed to incorporate uncertainty. Often this is done by using Bayesian Networks as a framework to enable probabilistic reasoning. These models can also be used to represent causal relationships. Many publications claim to model cause-effect relations, yet rarely give a formal introduction of the implications and resulting possibilities such an approach may have. This paper aims to link the domains of causal reasoning and automotive system safety by investigating relations between causal models and approaches like FMEA, FTA, or GSN. First, the famous “Ladder of Causation” and its implications on causality are reviewed. Next, we give an informal overview of common hazard and reliability analysis techniques and associate them with probabilistic models. Finally, we analyse a mixed-model methodology called Hybrid Causal Logic, extend its idea, and build the concept of a causal shell model of automotive system safety.

Gray zone lymphoma (GZL), a B-cell lymphoma with features intermediate between large B-cell lymphoma (LBCL) and classic Hodgkin lymphoma (cHL), is a rare and poorly defined entity. Alongside GZL, a subset of Epstein-Barr virus (EBV)–positive diffuse large B-cell lymphoma (DLBCL) has been described with polymorphic/GZL-like morphology (polymorphic-EBV-L). To fill the important gap in our understanding of the pathogenic process underlying these entities, we performed a gene expression study of a large international cohort of GZL and polymorphic-EBV-L, combined with cHL and primary mediastinal large B-cell lymphoma (PMBCL) cases. In an unsupervised principal component analysis, GZL cases presented with intermediate scores in a spectrum between cHL and PMBCL, whereas polymorphic-EBV-L clustered distinctly. The main biological pathways underlying the GZL spectrum were related to cell cycle, reflecting tumor cell content, and extracellular matrix signatures related to the cellular tumor microenvironment. Differential expression analysis and phenotypic characterization of the tumor microenvironment highlighted the predominance of regulatory macrophages in GZL compared with cHL and PMBCL. Two distinct subtypes of GZL were distinguishable that were phenotypically reminiscent of PMBCL and DLBCL, and we observed an association of PMBCL-type GZL with clinical presentation in the “thymic” anatomic niche. In summary, gene expression profiling (GEP) enabled us to add precision to the GZL spectrum, describe the biological distinction compared with polymorphic-EBV-L, and distinguish cases with and without thymic involvement as 2 subgroups of GZL, namely PMBCL-like and DLBCL-like GZL.

With the rising complexity and processing power of modern computer systems, the amount of MCU on a single PCB also rises. These microcontrollers often need to communicate with each other to exchange payload and control information in a bidirectional manner. Today’s well-established communication protocols in MCUs either do not fit modern transmission speed requirements or do have an inappropriate master-slave attribute, which does not allow the communication partners to have equal bus access rights. Therefore, this paper introduces an extension of the Serial Peripheral Interface (SPI) to allow an equally distributed access right for the communication interface between two microcontrollers. It simultaneously does fit modern transmission speed requirements of a common network interface, so that the message transmission does not constitute a bottleneck in data processing. Besides the protocol design, we do also provide a first prototype implementation, which constitutes a proof of concept.

Modern compute architectures often consist of multiple CPU cores to achieve their performance, as physical properties put a limit on the execution speed of a single processor. This trend is also visible in the embedded and real-time domain, where programmers are forced to parallelize their software to keep deadlines. Additionally, embedded systems rely increasingly on modular applications, that can easily be adapted to different system loads and hardware configurations. To parallelize applications under these dynamic conditions, often dispatching frameworks like Threading Building Blocks (TBB) are used in the desktop and server segment. More recently, Embedded Multicore Building Blocks (EMB\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{document}) was developed as a task-based programming solution designed with the constraints of embedded systems in mind. In this paper, we discuss how task-based programming fits such systems by analyzing scheduler implementation variants, with a focus on classic work-stealing and the libraries TBB and EMB\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{document}. Based on the state of the art we introduce a novel resource-trading concept that allows static memory allocation in a work-stealing runtime holding strict space and time bounds. We conduct benchmarks between an early prototype of the concept, TBB and EMB\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{document}, showing that resource-trading does not introduce additional runtime overheads, while unfortunately also not improving on execution time variances.

Das klassische Hodgkin-Lymphom (cHL) ist auf histologischer Ebene gekennzeichnet durch ein quantitativ dominierendes Begleitinfiltrat, das in Abhangigkeit vom histologischen Subtyp und EBV(Epstein-Barr-Virus)-Status eine unterschiedliche Zusammensetzung aufweist. Derzeitig gultige pathogenetische Konzepte postulieren, dass die malignen Zellen in Form der sogenannten Hodgkin- bzw. Reed-Sternberg(HRS)-Zellen eine dominante Rolle in der Rekrutierung verschiedener Immunzellen einnehmen, die wiederum zum Uberleben der Tumorzellpopulation beitragen. Unterstutzt wird diese Hypothese durch genetische Analysen, die entscheidend dazu beigetragen haben, relevante Mechanismen zu identifizieren, mithilfe derer sich die HRS-Zellen einer wirksamen Immunantwort entziehen konnen. Neben einer reduzierten bzw. defekten Antigenprasentation bedingt durch strukturelle Chromosomenaberrationen und Mutationen in Komponenten bzw. Regulatoren der Haupthistokompatibilitatskomponenten Klasse I und II, kommen vor allem Kopienzahlzugewinne des 9p24.1-Lokus eine bedeutsame Rolle zu. Letztere resultieren zumeist in einer verstarkten Expression von Liganden des programmierten Zelltod-Proteins PD‑1, die durch die Interaktion mit diesem auf T‑Lymphozyten exprimierten Rezeptor zu einer Suppression der Immunantwort fuhren. Die Reversibilitat dieser inhibitorischen Rezeptor-Liganden-Wechselwirkung wird klinisch in Form sog. Checkpoint-Inhibitoren genutzt, die bei Patienten mit cHL, insbesondere auch in der Rezidivsituation, mit im Vergleich zu vielen anderen Tumorentitaten imposanten Ansprechraten uberzeugt haben. Ultimatives Ziel ist die Integration dieser Informationen in prognostische bzw. pradiktive Modelle, die eine rationale Risikostratifizierung und basierend darauf eine Selektion optimaler Therapieregime ermoglicht.

CREBBP mutations are highly recurrent in B-cell lymphomas and either inactivate its histone acetyltransferase (HAT) domain or truncate the protein. Herein, we show that these two classes of mutations yield different degrees of disruption of the epigenome, with HAT mutations being more severe and associated with inferior clinical outcome. Genes perturbed by CREBBP mutation are direct targets of the BCL6–HDAC3 onco-repressor complex. Accordingly, we show that HDAC3-selective inhibitors reverse CREBBP-mutant aberrant epigenetic programming, resulting in: (i) growth inhibition of lymphoma cells through induction of BCL6 target genes such as CDKN1A and (ii) restoration of immune surveillance due to induction of BCL6-repressed IFN pathway and antigen-presenting genes. By reactivating these genes, exposure to HDAC3 inhibitors restored the ability of tumor-infiltrating lymphocytes to kill DLBCL cells in an MHC class I and II–dependent manner, and synergized with PD-L1 blockade in a syngeneic model in vivo. Hence, HDAC3 inhibition represents a novel mechanism-based immune epigenetic therapy for CREBBP-mutant lymphomas. Significance: We have leveraged the molecular characterization of different types of CREBBP mutations to define a rational approach for targeting these mutations through selective inhibition of HDAC3. This represents an attractive therapeutic avenue for targeting synthetic vulnerabilities in CREBBP-mutant cells in tandem with promoting antitumor immunity. This article is highlighted in the In This Issue feature, p. 327

Classical Hodgkin lymphoma (cHL) is a common malignancy in children and adolescents. Although cHL is highly curable, treatment with chemotherapy and radiation often come at the cost of long-term toxicity and morbidity. Effective risk-stratification tools are needed to tailor therapy. Here, we used gene expression profiling (GEP) to investigate tumor microenvironment (TME) biology, to determine molecular correlates of treatment failure, and to develop an outcome model prognostic for pediatric cHL. A total of 246 formalin-fixed, paraffin-embedded tissue biopsies from patients enrolled in the Children’s Oncology Group trial AHOD0031 were used for GEP and compared with adult cHL data. Eosinophil, B-cell, and mast cell signatures were enriched in children, whereas macrophage and stromal signatures were more prominent in adults. Concordantly, a previously published model for overall survival prediction in adult cHL did not validate in pediatric cHL. Therefore, we developed a 9-cellular component model reflecting TME composition to predict event-free survival (EFS). In an independent validation cohort, we observed a significant difference in weighted 5-year EFS between high-risk and low-risk groups (75.2% vs 90.3%; log-rank P = .0138) independent of interim response, stage, fever, and albumin. We demonstrate unique disease biology in children and adolescents that can be harnessed for risk-stratification at diagnosis. This trial was registered at www.clinicaltrials.gov as #NCT00025259.

The presented work is part of the research project Energy Safe and Secure System Module (ES3M), which is funded by the Project Management J ̈ulich (PtJ) and the German Federal Ministry for Economic Affairs and Energy (BMWi) under funding code 0350042A Supervisory Control and Data Acquisition (SCADA) systems are used to control and monitor components within the energy grid, playing a significant role in the stability of the system. As a part of critical infrastructures, components in these systems have to fulfill a variety of different requirements regarding their dependability and must also undergo strict audit procedures in order to comply with all relevant standards. This results in a slow adoption of new functionalities. Due to the emerged threat of cyberattacks against critical infrastructures, extensive security measures are needed within these systems to protect them from adversaries and ensure a stable operation. In this work, a solution is proposed to integrate extensive security measures into current systems. By deploying additional security-gateways into the communication path between two nodes, security features can be integrated transparently for the existing components. The developed security-gateway is compliant to all regulatory requirements and features an internal architecture based on the separation-of-concerns principle to increase its security and longevity. The viability of the proposed solution has been verified in different scenarios, consisting of realistic field tests, security penetration tests and various performance evaluations.

Modulární sčítání se používá jako nelineární operace v ARX kódování, neboť splňuje požadavek zavedení nelinearity v kryptografickém primitivu a většina moderních počítačových architektur potřebuje pro jeho vyčíslení pouze jeden hodinový cyklus. Díky tomu jsou kódy ARX obzvláště rychlé v softwarových implementacích, ovšem za cenu snížení ochrany proti ztrátám informací z postranních kanálů pomocí booleovského maskování: nejznámější maskovaná sčítačka pro mikrokontroléry ARM Thumb vyžaduje 83 instrukcí pro přidání dvou 32bitových čísel. Náš přístup pak spočívá v použití režimu bitových řezů umožňujících 32 paralelních sčítání na 32bitovém mikrokontroléru. Ukazujeme, že i když vezmeme v úvahu náklady na vytvoření bitových řezů před a po kódování, je možné dosáhnout vyšší propustnosti na testovaných kódech (CRAX a ChaCha20) při provozu v režimu bitových řezů. Dále ukazujeme, že nedochází k žádnému úniku informací ani v simulovaných trasách napájení, ani v trasách napájení získaných ze skutečného hardwaru poté, co byla zavedena dostatečná opatření k ochraně proti únikům (ztrátám) dat z datových vedení. The modular addition is used as a non-linear operation in ARX ciphers because it achieves the requirement of introducing non-linearity in a cryptographic primitive while only taking one clock cycle to execute on most modern architectures. This makes ARX ciphers especially fast in software implementations, but comes at the cost of making it harder to protect against side-channel information leakages using Boolean masking: the best known 2-shares masked adder for ARM Thumb micro-controllers takes 83 instructions to add two 32-bit numbers together. Our approach is to operate in bitsliced mode, performing 32 additions in parallel on a 32-bit microcontroller. We show that, even after taking into account the cost of bitslicing before and after the encryption, it is possible to achieve a higher throughput on the tested ciphers (CRAX and ChaCha20) when operating in bitsliced mode. Furthermore, we prove that no first-order information leakage is happening in either simulated power traces and power traces acquired from real hardware, after sufficient countermeasures are put into place to guard against pipeline leakages.

Histone methylation-modifiers, like EZH2 and KMT2D, are recurrently altered in B-cell lymphomas. To comprehensively describe the landscape of alterations affecting genes encoding histone methylation-modifiers in lymphomagenesis we investigated whole genome and transcriptome data of 186 mature B-cell lymphomas sequenced in the ICGC MMML-Seq project. Besides confirming common alterations of KMT2D (47% of cases), EZH2 (17%), SETD1B (5%), PRDM9 (4%), KMT2C (4%), and SETD2 (4%) also identified by prior exome or RNAseq studies, we here unravel KDM4C in chromosome 9p24, encoding a histone demethylase, to be recurrently altered. Focal structural variation was the main mechanism of KDM4C alterations, which was independent from 9p24 amplification. We identified KDM4C alterations also in lymphoma cell lines including a focal homozygous deletion in a classical Hodgkin lymphoma cell line. By integrating RNAseq and genome sequencing data we predict KDM4C structural variants to result in loss-of-function. By functional reconstitution studies in cell lines, we provide evidence that KDM4C can act as tumor suppressor. Thus, we show that identification of structural variants in whole genome sequencing data adds to the comprehensive description of the mutational landscape of lymphomas and, moreover, establish KDM4C as putative tumor suppressive gene recurrently altered in subsets of B-cell derived lymphomas.