A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer.

BACKGROUND: Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics. METHODS: All patients of the FFPE biopsy cohort were treated by radical prostatectomy and median follow-up for biochemical recurrence (BCR) was 9 years. Based on the transcriptome data of 176 FFPE biopsies, we filtered ProstaTrend for genes susceptible to FFPE-associated degradation via regression analysis. ProstaTrend was additionally restricted to genes with concordant prognostic effects in the RNA-Seq TCGA prostate adenocarcinoma (PRAD) cohort to ensure robust and broad applicability. The prognostic relevance of the refined Transcriptomic Risk Score (TRS) was analyzed by Kaplan-Meier curves and Cox-regression models in our FFPE-biopsy cohort and 9 other public datasets from PCa patients with BCR as primary endpoint. In addition, we developed a prostate single-cell atlas of 41 PCa patients from 5 publicly available studies to analyze gene expression of ProstaTrend genes in different cell compartments. RESULTS: Validation of the TRS using the original ProstaTrend signature in the cohort of FFPE biopsies revealed a relevant impact of FFPE-associated degradation on gene expression and consequently no significant association with prognosis (Cox-regression, p-value > 0.05) in FFPE tissue. However, the TRS based on the new version of the ProstaTrend-ffpe signature, which included 204 genes (of originally 1396 genes), was significantly associated with BCR in the FFPE biopsy cohort (Cox-regression p-value < 0.001) and retained prognostic relevance when adjusted for Gleason Grade Groups. We confirmed a significant association with BCR in 9 independent cohorts including 1109 patients. Comparison of the prognostic performance of the TRS with 17 other prognostically relevant PCa panels revealed that ProstaTrend-ffpe was among the best-ranked panels. We generated a PCa cell atlas to associate ProstaTrend genes with cell lineages or cell types. Tumor-specific luminal cells have a significantly higher TRS than normal luminal cells in all analyzed datasets. In addition, TRS of epithelial and luminal cells was correlated with increased Gleason score in 3 studies. CONCLUSIONS: We developed a prognostic gene-expression signature for PCa that can be applied to FFPE biopsies and may be suitable to support clinical decision-making.

Characterization and evaluation of gene fusions as a measure of genetic instability and disease prognosis in prostate cancer.

BACKGROUND: Prostate cancer (PCa) is one of the most prevalent cancers worldwide. The clinical manifestations and molecular characteristics of PCa are highly variable. Aggressive types require radical treatment, whereas indolent ones may be suitable for active surveillance or organ-preserving focal therapies. Patient stratification by clinical or pathological risk categories still lacks sufficient precision. Incorporating molecular biomarkers, such as transcriptome-wide expression signatures, improves patient stratification but so far excludes chromosomal rearrangements. In this study, we investigated gene fusions in PCa, characterized potential novel candidates, and explored their role as prognostic markers for PCa progression. METHODS: We analyzed 630 patients in four cohorts with varying traits regarding sequencing protocols, sample conservation, and PCa risk group. The datasets included transcriptome-wide expression and matched clinical follow-up data to detect and characterize gene fusions in PCa. With the fusion calling software Arriba, we computationally predicted gene fusions. Following detection, we annotated the gene fusions using published databases for gene fusions in cancer. To relate the occurrence of gene fusions to Gleason Grading Groups and disease prognosis, we performed survival analyses using the Kaplan-Meier estimator, log-rank test, and Cox regression. RESULTS: Our analyses identified two potential novel gene fusions, MBTTPS2,L0XNC01::SMS and AMACR::AMACR. These fusions were detected in all four studied cohorts, providing compelling evidence for the validity of these fusions and their relevance in PCa. We also found that the number of gene fusions detected in a patient sample was significantly associated with the time to biochemical recurrence in two of the four cohorts (log-rank test, p-value < 0.05 for both cohorts). This was also confirmed after adjusting the prognostic model for Gleason Grading Groups (Cox regression, p-values < 0.05). CONCLUSIONS: Our gene fusion characterization workflow revealed two potential novel fusions specific for PCa. We found evidence that the number of gene fusions was associated with the prognosis of PCa. However, as the quantitative correlations were only moderately strong, further validation and assessment of clinical value is required before potential application.

Molecular characterization of Richter syndrome identifies de novo diffuse large B-cell lymphomas with poor prognosis.

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.

Focal structural variants revealed by whole genome sequencing disrupt the histone demethylase KDM4C in B-cell lymphomas.

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.

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.

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.

Secondary Treatment for Men with Localized Prostate Cancer: A Pooled Analysis of PRIAS and ERSPC-Rotterdam Data within the PIONEER Data Platform.

INTRODUCTION: Treatment choice for localized prostate cancer is complicated, as each treatment option comes with various pros and cons. It is well established that active surveillance (AS), may be ended with a change to curative treatment at the time of disease progression, but it is less clear whether secondary treatment after initial curative treatment is required. As part of the PIONEER project, we quantified the probabilities of treatment change. METHODS: A cohort study based on PRIAS and ERSPC-Rotterdam data was conducted. Patients were followed up for 10 years or until the 31st of December 2017. The primary outcome was the incidence of treatment change following initial treatment (i.e., a change to curative treatment following AS or secondary treatment after initial RP/RT). RESULTS: Over a period of 1 to 5 years after initial treatment, the cumulative incidence of treatment change ranged from 3.8% to 42.8% for AS, from 7.6% to 12.1% for radical prostatectomy (RP) and from no change to 5.3% for radiation therapy (RT). While the possibility of treatment change in AS is known, the numbers within a five-year period were substantial. For RP and RT, the rate of change to secondary treatment was lower, but still non-neglectable, with 5 (10)-year incidences up to 12% (20%) and 5% (16%), respectively. CONCLUSION: This is one of the first studies comparing the incidence of guideline-recommended treatment changes in men receiving different primary treatments (i.e., AS, RT, or RP) for localized prostate cancer (PCa).

Lupus erythematosus: correlation of clinical and histological findings and proposal for a modified disease classification.

BACKGROUND: Classification of lupus erythematosus (LE) is conflicting as it is carried out from different starting points. Whereas dermatological classifications categorize LE morphologically based on specific cutaneous lesions, rheumatologic classifications are based on symptomatic aspects. Indeed, LE is a systemic autoimmune disease with variable acuity and organ involvement. All cutaneous disease patterns may occur in both limited-cutaneous and systemic LE. PATIENTS AND METHODS: 76 LE-patients with complete clinical data, clinical photographs and biopsy of cutaneous manifestations as well as paraclinical findings were retrospectively analyzed. Based on a published two-dimensional classification system that considers disease-specific skin manifestations and final disease diagnosis separately, patients' diagnoses were revised and compared with those in medical records. In addition, the extent to which patients could be clustered by diagnosis based on their LE-specific skin manifestations, corresponding histopathological changes, and paraclinical data was investigated. RESULTS: After re-evaluation, the proportion of patients with limited-cutaneous LE decreased from 82% previously to 24%. More than two-thirds of patients indeed showed intermediate or systemic LE. Disease-specific skin manifestations, histologic characteristics and paraclinical data did not cluster with final diagnoses. CONCLUSIONS: First, the work underlines the systemic character of the disease. Second, a two-dimensional approach can help overcome classification difficulties in LE, as skin-morphologic and symptomatic aspects can be considered separately.

Distinct Immune Signatures Indicative of Treatment Response and Immune-Related Adverse Events in Melanoma Patients under Immune Checkpoint Inhibitor Therapy.

To identify potential early biomarkers of treatment response and immune-related adverse events (irAE), a pilot immune monitoring study was performed in stage IV melanoma patients by flow cytometric analysis of peripheral blood mononuclear cells (PBMC). Overall, 17 patients were treated with either nivolumab or pembrolizumab alone, or with a combination of nivolumab and ipilimumab every three weeks. Of 15 patients for which complete response assessment was available, treatment responders (n = 10) as compared to non-responders (n = 5) were characterized by enhanced PD-1 expression on CD8+ T cells immediately before treatment (median ± median absolute deviation/MAD 26.7 ± 10.4% vs. 17.2 ± 5.3%). Responders showed a higher T cell responsiveness after T cell receptor ex vivo stimulation as determined by measurement of programmed cell death 1 (PD-1) expression on CD3+ T cells before the second cycle of treatment. The percentage of CD8+ effector memory (CD8+CD45RA-CD45RO+CCR7-) T cells was higher in responders compared to non-responders before and immediately after the first cycle of treatment (median ± MAD 39.2 ± 7.3% vs. 30.5 ± 4.1% and 37.7 ± 4.6 vs. 24.0 ± 6.4). Immune-related adverse events (irAE) were accompanied by a higher percentage of activated CD4+ (CD4+CD38+HLADR+) T cells before the second treatment cycle (median ± MAD 14.9 ± 3.9% vs. 5.3 ± 0.4%). In summary, PBMC immune monitoring of immune-checkpoint inhibition (ICI) treatment in melanoma appears to be a promising approach to identify early markers of treatment response and irAEs.

Distinct Molecular Mechanisms of Altered HLA Class II Expression in Malignant Melanoma.

BACKGROUND: The human leukocyte antigen (HLA) class II molecules are constitutively expressed in some melanoma, but the underlying molecular mechanisms have not yet been characterized. METHODS: The expression of HLA class II antigen processing machinery (APM) components was determined in melanoma samples by qPCR, Western blot, flow cytometry and immunohistochemistry. Immunohistochemical and TCGA datasets were used for correlation of HLA class II expression to tumor grading, T-cell infiltration and patients' survival. RESULTS: The heterogeneous HLA class II expression in melanoma samples allowed us to characterize four distinct phenotypes. Phenotype I totally lacks constitutive HLA class II surface expression, which is inducible by interferon-gamma (IFN-γ); phenotype II expresses low basal surface HLA class II that is further upregulated by IFN-γ; phenotype III lacks constitutive and IFN-γ controlled HLA class II expression, but could be induced by epigenetic drugs; and in phenotype IV, lack of HLA class II expression is not recovered by any drug tested. High levels of HLA class II APM component expression were associated with an increased intra-tumoral CD4+ T-cell density and increased patients' survival. CONCLUSIONS: The heterogeneous basal expression of HLA class II antigens and/or APM components in melanoma cells is caused by distinct molecular mechanisms and has clinical relevance.

High-Resolution Cartography of the Transcriptome and Methylome Landscapes of Diffuse Gliomas.

Molecular mechanisms of lower-grade (II-III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendroglioma-like (IDH-O) tumors both carrying mutations(s) at the isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma resemblance. We generated detailed maps of the transcriptomes and DNA methylomes, revealing that cell functions divided into three major archetypic hallmarks: (i) increased proliferation in IDH-wt and, to a lesser degree, IDH-O; (ii) increased inflammation in IDH-A and IDH-wt; and (iii) the loss of synaptic transmission in all subtypes. Immunogenic properties of IDH-A are diverse, partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We analyzed details of coregulation between gene expression and DNA methylation and of the immunogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby, molecular cartography provides a graphical coordinate system that links gene-level information with glioma subtypes, their phenotypes, and clinical context.

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.

Mantle cell lymphomas with concomitant MYC and CCND1 breakpoints are recurrently TdT positive and frequently show high-grade pathological and genetic features.

Chromosomal breakpoints involving the MYC gene locus, frequently referred to as MYC rearrangements (MYC - R+), are a diagnostic hallmark of Burkitt lymphoma and recurrent in many other subtypes of B-cell lymphomas including follicular lymphoma, diffuse large B-cell lymphoma and other high-grade B-cell lymphomas and are associated with an aggressive clinical course. In remarkable contrast, in MCL, only few MYC - R+ cases have yet been described. In the current study, we have retrospectively analysed 16 samples (MYC - R+, n = 15, MYC - R-, n = 1) from 13 patients and describe their morphological, immunophenotypic and (molecular) genetic features and clonal evolution patterns. Thirteen out of fifteen MYC - R+ samples showed a non-classical cytology including pleomorphic (centroblastic, immunoblastic), anaplastic or blastoid. MYC translocation partners were IG-loci in 4/11 and non-IG loci in 7/11 analysed cases. The involved IG-loci included IGH in 3 cases and IGL in one case. PAX5 was the non-IG partner in 2/7 patients. The MYC - R+ MCL reported herein frequently displayed characteristics associated with an aggressive clinical course including high genomic-complexity (6/7 samples), frequent deletions involving the CDKN2A locus (7/10 samples), high Ki-67 proliferation index (12/13 samples) and frequent P53 expression (13/13 samples). Of note, in 4/14 samples, SOX11 was not or only focally expressed and 3/13 samples showed focal or diffuse TdT-positivity presenting a diagnostic challenge as these features could point to a differential diagnosis of diffuse large B-cell lymphoma and/or lymphoblastic lymphoma/leukaemia.

ProstaTrend-A Multivariable Prognostic RNA Expression Score for Aggressive Prostate Cancer.

BACKGROUND: Prostate cancer (PCa) is the most prevalent solid cancer among men in Western Countries. The clinical behavior of localized PCa is highly variable. Some cancers are aggressive leading to death, while others can even be monitored safely. Hence, there is a high clinical need for precise biomarkers for identification of aggressive disease in addition to established clinical parameters. OBJECTIVE: To develop an RNA expression-based score for the prediction of PCa prognosis that facilitates clinical decision making. DESIGN, SETTING, AND PARTICIPANTS: We assessed 233 tissue specimens of PCa patients with long-term follow-up data from fresh-frozen radical prostatectomies (RPs), from formalin-fixed and paraffin-embedded RP specimens and biopsies by transcriptome-wide next-generation sequencing and customized expression microarrays. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We applied Cox proportional hazard models to the cohorts from different platforms and specimen types. Evidence from these models was combined by fixed-effect meta-analysis to identify genes predictive of the time to death of disease (DoD). Genes were combined by a weighted median approach into a prognostic score called ProstaTrend and transferred for the prediction of biochemical recurrence (BCR) after RP in an independent cohort of The Cancer Genome Atlas (TCGA). RESULTS AND LIMITATIONS: ProstaTrend comprising ∼1400 genes was significantly associated with DoD in the training cohort of PCa patients treated by RP (leave-one-out cross-validation, Cox regression: p=2e-09) and with BCR in the TCGA validation cohort (Cox regression: p=3e-06). The prognostic impact persisted after multivariable Cox regression analysis adjusting for Gleason grading group (GG) ≥3 and resection status (p=0.001; DoD, training cohort) and for GG≥3, pathological stage ≥T3, and resection state (p=0.037; BCR, validation cohort). CONCLUSIONS: ProstaTrend is a transcriptome-based score that predicts DoD and BCR in cohorts of PCa patients treated with RP. PATIENT SUMMARY: ProstaTrend provides molecular patient risk stratification after radical prostatectomy.

The impact of SOCS1 mutations in diffuse large B-cell lymphoma.

Mutations in SOCS1 are frequent in primary mediastinal B-cell lymphoma and classical Hodgkin lymphoma. In the latter, SOCS1 mutations affect the length of the encoded protein (major mutations) and are associated with shorter patient survival. Two independent studies examined the prognostic impact of SOCS1 mutations in diffuse large B-cell lymphoma (DLBCL) and showed differing results. This may be due to the small number of included patients, the heterogeneity of patients' demographics and the distinct treatment schemes in these studies. To overcome the size limitations of these previous studies, we assessed SOCS1 mutations in the RICOVER-60 cohort. The cohort uniformly consists of elderly patients (aged 61-80 years) treated with the CHOP-14 scheme (cyclophosphamide, hydroxydaunorubicin, vincristine, prednisolone at 14-day intervals) with or without an additional rituximab treatment. Patient outcomes were analysed with regard to overall SOCS1 mutation frequency, major and minor mutations and a novel impact-based classifier - against the treatment modalities. Patients harbouring putative pathogenic SOCS1 mutations showed significant reduced overall survival within the CHOP plus rituximab group. Hence, putative pathogenic SOCS1 mutations seem to efface the beneficial effect of the therapeutic CD20 antibody. Comparing published data of whole exome and transcriptome sequencing of a large DLBCL cohort confirmed that predicted deleterious SOCS1 mutations forecast pre-eminent survival in early onset DLBCL.

A modular transcriptome map of mature B cell lymphomas.

BACKGROUND: Germinal center-derived B cell lymphomas are tumors of the lymphoid tissues representing one of the most heterogeneous malignancies. Here we characterize the variety of transcriptomic phenotypes of this disease based on 873 biopsy specimens collected in the German Cancer Aid MMML (Molecular Mechanisms in Malignant Lymphoma) consortium. They include diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt's lymphoma, mixed FL/DLBCL lymphomas, primary mediastinal large B cell lymphoma, multiple myeloma, IRF4-rearranged large cell lymphoma, MYC-negative Burkitt-like lymphoma with chr. 11q aberration and mantle cell lymphoma. METHODS: We apply self-organizing map (SOM) machine learning to microarray-derived expression data to generate a holistic view on the transcriptome landscape of lymphomas, to describe the multidimensional nature of gene regulation and to pursue a modular view on co-expression. Expression data were complemented by pathological, genetic and clinical characteristics. RESULTS: We present a transcriptome map of B cell lymphomas that allows visual comparison between the SOM portraits of different lymphoma strata and individual cases. It decomposes into one dozen modules of co-expressed genes related to different functional categories, to genetic defects and to the pathogenesis of lymphomas. On a molecular level, this disease rather forms a continuum of expression states than clearly separated phenotypes. We introduced the concept of combinatorial pattern types (PATs) that stratifies the lymphomas into nine PAT groups and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma signatures. Inflammation signatures in combination with healthy B cell and tonsil characteristics associate with better overall survival rates, while proliferation in combination with inflammation and plasma cell characteristics worsens it. A phenotypic similarity tree is presented that reveals possible progression paths along the transcriptional dimensions. Our analysis provided a novel look on the transition range between FL and DLBCL, on DLBCL with poor prognosis showing expression patterns resembling that of Burkitt's lymphoma and particularly on 'double-hit' MYC and BCL2 transformed lymphomas. CONCLUSIONS: The transcriptome map provides a tool that aggregates, refines and visualizes the data collected in the MMML study and interprets them in the light of previous knowledge to provide orientation and support in current and future studies on lymphomas and on other cancer entities.

MDM4 Is Targeted by 1q Gain and Drives Disease in Burkitt Lymphoma.

Oncogenic MYC activation promotes proliferation in Burkitt lymphoma, but also induces cell-cycle arrest and apoptosis mediated by p53, a tumor suppressor that is mutated in 40% of Burkitt lymphoma cases. To identify molecular dependencies in Burkitt lymphoma, we performed RNAi-based, loss-of-function screening in eight Burkitt lymphoma cell lines and integrated non-Burkitt lymphoma RNAi screens and genetic data. We identified 76 genes essential to Burkitt lymphoma, including genes associated with hematopoietic cell differentiation (FLI1, BCL11A) or B-cell development and activation (PAX5, CDKN1B, JAK2, CARD11) and found a number of context-specific dependencies including oncogene addiction in cell lines with TCF3/ID3 or MYD88 mutation. The strongest genotype-phenotype association was seen for TP53. MDM4, a negative regulator of TP53, was essential in TP53 wild-type (TP53wt) Burkitt lymphoma cell lines. MDM4 knockdown activated p53, induced cell-cycle arrest, and decreased tumor growth in a xenograft model in a p53-dependent manner. Small molecule inhibition of the MDM4-p53 interaction was effective only in TP53wt Burkitt lymphoma cell lines. Moreover, primary TP53wt Burkitt lymphoma samples frequently acquired gains of chromosome 1q, which includes the MDM4 locus, and showed elevated MDM4 mRNA levels. 1q gain was associated with TP53wt across 789 cancer cell lines and MDM4 was essential in the TP53wt-context in 216 cell lines representing 19 cancer entities from the Achilles Project. Our findings highlight the critical role of p53 as a tumor suppressor in Burkitt lymphoma and identify MDM4 as a functional target of 1q gain in a wide range of cancers that is therapeutically targetable. SIGNIFICANCE: Targeting MDM4 to alleviate degradation of p53 can be exploited therapeutically across Burkitt lymphoma and other cancers with wild-type p53 harboring 1q gain, the most frequent copy number alteration in cancer.

Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma.

Burkitt lymphoma (BL) is the most common B-cell lymphoma in children. Within the International Cancer Genome Consortium (ICGC), we performed whole genome and transcriptome sequencing of 39 sporadic BL. Here, we unravel interaction of structural, mutational, and transcriptional changes, which contribute to MYC oncogene dysregulation together with the pathognomonic IG-MYC translocation. Moreover, by mapping IGH translocation breakpoints, we provide evidence that the precursor of at least a subset of BL is a B-cell poised to express IGHA. We describe the landscape of mutations, structural variants, and mutational processes, and identified a series of driver genes in the pathogenesis of BL, which can be targeted by various mechanisms, including IG-non MYC translocations, germline and somatic mutations, fusion transcripts, and alternative splicing.

Stress-related hormones in association with periodontal condition in adolescents-results of the epidemiologic LIFE Child study.

OBJECTIVES: The aim of this study was to investigate the associations between blood levels of stress-related hormones and early signs of periodontal disease in children and adolescents. MATERIALS AND METHODS: Within the LIFE (Leipzig research center for civilization diseases) Child study, 498 adolescents (10 to 18 years) were included. Early signs of periodontal inflammation were measured by probing depth (PD) at six index teeth (16, 11, 26, 36, 31, 46). Blood levels of stress-related hormones (cortisol, dehydroepiandosterone-sulfate [DHEA-S]) and, additionally interleukine-6 (IL-6) were measured. Socioeconomic status, oral hygiene, orthodontic appliances, and nutritional status, recorded by body-mass-index-standard-deviation-score (BMI-SDS), were considered as confounding factors. Additionally, in 98 participants, an oral chairside active matrix metalloproteinase-8 (aMMP-8) test was performed. Statistical tests are the Mann-Whitney U tests, chi-squared tests and multivariate logistic regression model. RESULTS: IL-6, BMI-SDS as well as positive aMMP-8 test result were significantly associated with maximum PD > 3 mm (p < 0.05). However, no statistically significant associations between stress-related hormones (cortisol and DHEA-S) and presence of maximum PD > 3 mm were found (p > 0.05). Higher DHEA-S and BMI were associated with positive aMMP-8 result, even after adjusting for age and gender (p = 0.027, padj = 0.026). CONCLUSION: The results reveal no associations between PD and stress-related hormones cortisol and DHEA-S. aMMP-8 test result might be associated with DHEA-S level. Nutritional status seems to influence periodontal disease in adolescents. CLINICAL RELEVANCE: DHEA-S and BMI-SDS show associations with early signs of periodontal disease in adolescents aged 10 to 18 years. This association should be confirmed by the investigation of high-risk groups.