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Deficient (d) DNA mismatch repair (MMR) is a biomarker predictive of better response to PD-1 blockade immunotherapy in solid tumors. dMMR can be caused by mutations in MMR genes or by protein inactivation, which can be detected by sequencing and immunohistochemistry, respectively. To investigate the role of dMMR in diffuse large B-cell lymphoma (DLBCL), MMR gene mutations and expression of MSH6, MSH2, MLH1, and PMS2 proteins were evaluated by targeted next-generation sequencing and immunohistochemistry in a large cohort of DLBCL patients treated with standard chemoimmunotherapy, and correlated with the tumor immune microenvironment characteristics quantified by fluorescent multiplex immunohistochemistry and gene-expression profiling. The results showed that genetic dMMR was infrequent in DLBCL and was significantly associated with increased cancer gene mutations and favorable immune microenvironment, but not prognostic impact. Phenotypic dMMR was also infrequent, and MMR proteins were commonly expressed in DLBCL. However, intratumor heterogeneity existed, and increased DLBCL cells with phenotypic dMMR correlated with significantly increased T cells and PD-1+ T cells, higher average nearest neighbor distance between T cells and PAX5+ cells, upregulated immune gene signatures, LE4 and LE7 ecotypes and their underlying Ecotyper-defined cell states, suggesting the possibility that increased T cells targeted only tumor cell subsets with dMMR. Only in patients with MYC¯ DLBCL, high MSH6/PMS2 expression showed significant adverse prognostic effects. This study shows the immunologic and prognostic effects of genetic/phenotypic dMMR in DLBCL, and raises a question on whether DLBCL-infiltrating PD-1+ T cells target only tumor subclones, relevant for the efficacy of PD-1 blockade immunotherapy in DLBCL.

Abstract Patients diagnosed with epithelial ovarian cancer (OC) have a 5-year survival rate of 49%. For early-stage disease, the 5-year survival rate is above 90%. However, advanced-stage disease accounts for most cases as patients with early stages often are asymptomatic or present with unspecific symptoms, highlighting the need for diagnostic tools for early diagnosis. Liquid biopsy is a minimal invasive blood-based approach that utilizes circulating tumor DNA (ctDNA) shed from tumor cells for real-time detection of tumor genetics and epigenetics. Increased DNA methylation of promoter regions is an early event during tumorigenesis, and the methylation can be detected in ctDNA, accentuating the promise of methylated ctDNA as a biomarker for OC diagnosis. Many studies have investigated multiple methylation biomarkers in ctDNA from plasma or serum for discriminating OC patients from patients with benign diseases of the ovaries and/or healthy females. This systematic review summarizes and evaluates the performance of the currently investigated DNA methylation biomarkers in blood-derived ctDNA for early diagnosis of OC. PubMed’s MEDLINE and Elsevier’s Embase were systematically searched, and essential results such as methylation frequency of OC cases and controls, performance measures, as well as preanalytical factors were extracted. Overall, 29 studies met the inclusion criteria for this systematic review. The most common method used for methylation analysis was methylation-specific PCR, with half of the studies using plasma and the other half using serum. RASSF1A, BRCA1, and OPCML were the most investigated gene-specific methylation biomarkers, with OPCML having the best performance measures. Generally, methylation panels performed better than single gene-specific methylation biomarkers, with one methylation panel of 103,456 distinct regions and 1,116,720 CpGs having better performance in both training and validation cohorts. However, the evidence is still limited, and the promising methylation panels, as well as gene-specific methylation biomarkers highlighted in this review, need validation in large, prospective cohorts with early-stage asymptomatic OC patients to assess the true diagnostic value in a clinical setting.

Abstract Background Multiple myeloma remains an incurable disease with multiple relapses due to residual myeloma cells in the bone marrow of patients after therapy. Presence of small number of cancer cells in the body after cancer treatment, called minimal residual disease, has been shown to be prognostic for progression-free and overall survival. However, for multiple myeloma, it is unclear whether patients attaining minimal residual disease negativity may be candidates for treatment discontinuation. We investigated, if longitudinal flow cytometry-based monitoring of minimal residual disease (flow-MRD) may predict disease progression earlier and with higher sensitivity compared to biochemical assessments. Methods Patients from the Nordic countries with newly diagnosed multiple myeloma enrolled in the European-Myeloma-Network-02/Hovon-95 (EMN02/HO95) trial and undergoing bone marrow aspiration confirmation of complete response, were eligible for this Nordic Myeloma Study Group (NMSG) substudy. Longitdudinal flow-MRD assessment of bone marrow samples was performed to identify and enumerate residual malignant plasma cells until observed clinical progression. Results Minimal residual disease dynamics were compared to biochemically assessed changes in serum free light chain and M-component. Among 20 patients, reaching complete response or stringent complete response during the observation period, and with ≥3 sequential flow-MRD assessments analysed over time, increasing levels of minimal residual disease in the bone marrow were observed in six cases, preceding biochemically assessed disease and clinical progression by 5.5 months and 12.6 months (mean values), respectively. Mean malignant plasma cells doubling time for the six patients was 1.8 months (95% CI, 1.4–2.3 months). Minimal malignant plasma cells detection limit was 4 × 10–5. Conclusions Flow-MRD is a sensitive method for longitudinal monitoring of minimal residual disease dynamics in multiple myeloma patients in complete response. Increasing minimal residual disease levels precedes biochemically assessed changes and is an early indicator of subsequent clinical progression. Trial registration NCT01208766

Abstract Multiple studies have demonstrated that diffuse large B-cell lymphoma (DLBCL) can be divided into subgroups based on their biology; however, these biological subgroups overlap clinically. Using machine learning, we developed an approach to stratify patients with DLBCL into four subgroups based on survival characteristics. This approach uses data from the targeted transcriptome to predict these survival subgroups. Using the expression levels of 180 genes, our model reliably predicted the four survival subgroups and was validated using independent groups of patients. Multivariate analysis showed that this patient stratification strategy encompasses various biological characteristics of DLBCL, and only TP53 mutations remained an independent prognostic biomarker. This novel approach for stratifying patients with DLBCL, based on the clinical outcome of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone therapy, can be used to identify patients who may not respond well to these types of therapy, but would otherwise benefit from alternative therapy and clinical trials.

Abstract Background Diffuse large B-cell lymphoma (DLBCL) is the most frequent lymphoid neoplasm among adults,and approximately 30–40% of patients will experience relapse while 5–10% will suffer from primary refractory disease caused by different mechanisms, including treatment-induced resistance. For refractory and relapsed DLBCL (rrDLBCL) patients, early detection and understanding of the mechanisms controlling treatment resistance are of great importance to guide therapy decisions. Here, we have focused on genetic variations in immune surveillance genes in diagnostic DLBCL (dDLBCL) and rrDLBCL patients to elaborate on the suitability of new promising immunotherapies. Methods Biopsies from 30 dDLBCL patients who did not progress or relapse during follow up and 17 rrDLBCL patients with refractory disease or who relapsed during follow up were analyzed by whole-exome sequencing, including matched individual germline samples to include only somatic genetic variants in downstream analysis of a curated list of 58 genes involved in major immune surveillance pathways. Results More than 70% of both dDLBCLs and rrDLBCLs harbored alterations in immune surveillance genes, but rrDLBCL tumor samples have a lower number of genes affected compared to dDLBCL tumor samples. Increased gene mutation frequencies in rrDLBCLs were observed in more than half of the affected immune surveillance genes than dDLBCLs. Conclusion Genetic variants in the antigen-presenting genes affect a higher number of rrDLBCL patients supporting an important role for these genes in tumor progression and development of refractory disease and relapse.

Abstract The XPO1 inhibitor selinexor was recently approved in relapsed/refractory DLBCL patients but only demonstrated modest anti-DLBCL efficacy, prompting us to investigate the prognostic effect of XPO1 in DLBCL patients and the rational combination therapies in high-risk DLBCL. High XPO1 expression (XPO1high) showed significant adverse prognostic impact in 544 studied DLBCL patients, especially in those with BCL2 overexpression. Therapeutic study in 30 DLBCL cell lines with various molecular and genetic background found robust cytotoxicity of selinexor, especially in cells with BCL2-rearranged (BCL2-R+) DLBCL or high-grade B-cell lymphoma with MYC/BCL2 double-hit (HGBCL-DH). However, expression of mutant (Mut) p53 significantly reduced the cytotoxicity of selinexor in overall cell lines and the BCL2-R and HGBCL-DH subsets, consistent with the favorable impact of XPO1high observed in Mut-p53-expressing patients. The therapeutic effect of selinexor in HGBCL-DH cells was significantly enhanced when combined with a BET inhibitor INCB057643, overcoming the drug resistance in Mut-p53-expressing cells. Collectively, these data suggest that XPO1 worsens the survival of DLBCL patients with unfavorable prognostic factors such as BCL2 overexpression and double-hit, in line with the higher efficacy of selinexor demonstrated in BCL2-R+ DLBCL and HGBCL-DH cell lines. Expression of Mut-p53 confers resistance to selinexor treatment, which can be overcome by combined INCB057643 treatment in HGBCL-DH cells. This study provides insight into the XPO1 significance and selinexor efficacy in DLBCL, important for developing combination therapy for relapsed/refractory DLBCL and HGBCL-DH.

Diffuse large B‐cell lymphoma (DLBCL) is characterized by extensive genetic heterogeneity, and this results in unpredictable responses to the current treatment, R‐CHOP, which consists of a cancer drug combination supplemented with the humanized CD20‐targeting monoclonal antibody rituximab. Despite improvements in the patient response rate through rituximab addition to the treatment plan, up to 40% of DLBCL patients end in a relapsed or refractory state due to inherent or acquired resistance to the regimen. Here, we employ a lentiviral genome‐wide clustered regularly interspaced short palindromic repeats library screening approach to identify genes involved in facilitating the rituximab response in cancerous B cells. Along with the CD20‐encoding MS4A1 gene, we identify genes related to B‐cell receptor (BCR) signaling as mediators of the intracellular signaling response to rituximab. More specifically, the B‐cell linker protein (BLNK) and Bruton's tyrosine kinase (BTK) genes stand out as pivotal genes in facilitating direct rituximab‐induced apoptosis through mechanisms that occur alongside complement‐dependent cytotoxicity (CDC). Our findings demonstrate that rituximab triggers BCR signaling in a BLNK‐ and BTK‐dependent manner and support the existing notion that intertwined CD20 and BCR signaling pathways in germinal center B‐cell‐like‐subtype DLBCL lead to programmed cell death.

Abstract Background Treatment resistance is a major clinical challenge of diffuse large B-cell lymphoma (DLBCL) where approximately 40% of the patients have refractory disease or relapse. Since DLBCL is characterized by great clinical and molecular heterogeneity, the purpose of the present study was to investigate whether miRNAs associated to single drug components of R-CHOP can improve robustness of individual markers and serve as a prognostic classifier. Methods Fifteen DLBCL cell lines were tested for sensitivity towards single drug compounds of the standard treatment R-CHOP: rituximab (R), cyclophosphamide (C), doxorubicin (H), and vincristine (O). For each drug, cell lines were ranked using the area under the dose-response curve and grouped as either sensitive, intermediate or resistant. Baseline miRNA expression data were obtained for each cell line in untreated condition, and differential miRNA expression analysis between sensitive and resistant cell lines identified 43 miRNAs associated to growth response after exposure towards single drugs of R-CHOP. Using the Affymetrix HG-U133 platform, expression levels of miRNA precursors were assessed in 701 diagnostic DLBCL biopsies, and miRNA-panel classifiers predicting disease progression were build using multiple Cox regression or random survival forest. Classifiers were validated and ranked by repeated cross-validation. Results Prognostic accuracies were assessed by Brier Scores and time-varying area under the ROC curves, which revealed better performance of multivariate Cox models compared to random survival forest models. The Cox model including miR-146a, miR-155, miR-21, miR-34a, and miR-23a~miR-27a~miR-24-2 cluster performed the best and successfully stratified GCB-DLBCL patients into high- and low-risk of disease progression. In addition, combination of the Cox miRNA-panel and IPI substantially increased prognostic performance in GCB classified patients. Conclusion As a proof of concept, we found that expression data of drug associated miRNAs display prognostic utility and adding these to IPI improves prognostic stratification of GCB-DLBCL patients treated with R-CHOP.

Abstract Background Diffuse large B-cell lymphoma (DLBCL) harbors somatic hypermutation (SHM) in the immunoglobulin heavy chain and light chain variable region genes, IGHV and IGK/LV. Recent studies have revealed that IGV SHM creates neoantigens that activate T-cell responses against B-cell lymphoma. Methods To determine the clinical relevance of IGV SHM in DLBCL treated with standard immunochemotherapy, we performed next-generation sequencing of the immunoglobulin variable regions and complementarity determining region 3 (CDR3) for 378 patients with de novo DLBCL. The prognostic effects of IGV SHM and ongoing SHM or intra-clonal heterogeneity were analyzed in the training (192 patients), validation (186 patients), and overall DLBCL cohorts. To gain mechanistic insight, we analyzed the predicted IG-derived neoantigens’ immunogenicity potential, determined by the major histocompatibility complex-binding affinity and the frequency-of-occurrence of T cell-exposed motifs (TCEMs) in a TCEM repertoire derived from human proteome, microbiome, and pathogen databases. Furthermore, IGV SHM was correlated with molecular characteristics of DLBCL and PD-1/L1 expression in the tumor microenvironment assessed by fluorescent multiplex immunohistochemistry. Results SHM was commonly found in IGHV and less frequently in IGK/LV. High levels of clonal IGHV SHM (SHMhigh) were associated with prolonged overall survival in DLBCL patients, particularly those without BCL2 or MYC translocation. In contrast, long heavy chain CDR3 length, the presence of IGHV ongoing SHM in DLBCL, and high clonal IGK/LV SHM in germinal center B-cell–like (GCB)-DLBCL were associated with poor prognosis. These prognostic effects were significant in both the training and validation sets. By prediction, the SHMhigh groups harbored more potentially immune-stimulatory neoantigens with high binding affinity and rare TCEMs. PD-1/L1 expression in CD8+ T cells was significantly lower in IGHV SHMhigh than in SHMlow patients with activated B-cell–like DLBCL, whereas PD-1 expression in CD4+ T cells and PD-L1 expression in natural killer cells were higher in IGK/LV SHMhigh than in SHMlow patients with GCB-DLBCL. PD-L1/L2 (9p24.1) amplification was associated with high IGHV SHM and ongoing SHM. Conclusions These results show for the first time that IGV SHMhigh and ongoing SHM have prognostic effects in DLBCL and potential implications for PD-1/PD-L1 blockade and neoantigen-based immunotherapies.

Human B-cell differentiation has been extensively investigated on genomic and transcriptomic grounds; however, no studies have accomplished so far detailed analysis of antigen-dependent maturation-associated human B-cell populations from a proteomic perspective. Here, we investigate for the first time the quantitative proteomic profiles of B-cells undergoing antigen-dependent maturation using a label-free LC-MS/MS approach applied on 5 purified B-cell subpopulations (naive, centroblasts, centrocytes, memory and plasma B-cells) from human tonsils (data are available via ProteomeXchange with identifier PXD006191). Our results revealed that the actual differences among these B-cell subpopulations are a combination of expression of a few maturation stage-specific proteins within each B-cell subset and maturation-associated changes in relative protein expression levels, which are related with metabolic regulation. The considerable overlap of the proteome of the 5 studied B-cell subsets strengthens the key role of the regulation of the stoichiometry of molecules associated with metabolic regulation and programming, among other signaling cascades (such as antigen recognition and presentation and cell survival) crucial for the transition between each B-cell maturation stage.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma with high mutation burdens but a low response rate to immune checkpoint inhibitors. In this study, we performed targeted next-generation sequencing and fluorescent multiplex immunohistochemistry, and investigated the clinical significance and immunological effect of mutation numbers in 424 DLBCL patients treated with standard immunochemotherapy. We found that KMT2D and TP53 nonsynonymous mutations (MUT) were significantly associated with increased nonsynonymous mutation numbers, and that high mutation numbers (MUThigh) were associated with significantly poorer clinical outcome in germinal center B-cell-like DLBCL with wild-type TP53. To understand the underlying mechanisms, we identified a gene-expression profiling signature and the association of MUThigh with decreased T cells in DLBCL patients with wild-type TP53. On the other hand, in overall cohort, MUThigh was associated with lower PD-1 expression in T cells and PD-L1 expression in macrophages, suggesting a positive role of MUThigh in immune responses. Analysis in a whole-exome sequencing dataset of 304 patients deposited by Chapuy et al. validated the correlation of MUT-KMT2D with genomic complexity and the significantly poorer survival associated with higher numbers of genomic single nucleotide variants in activated B-cell–like DLBCL with wild-type TP53. Together, these results suggest that KMT2D inactivation or epigenetic dysregulation has a role in driving DLBCL genomic instability, and that genomic complexity has adverse impact on clinical outcome in DLBCL patients with wild-type TP53 treated with standard immunochemotherapy. The oncoimmune data in this study have important implications for biomarker and therapeutic studies in DLBCL.

BackgroundHead and neck squamous cell carcinomas (HNSCC) are often diagnosed in advanced stages. In search of new diagnostic tools, focus has shifted towards the biological properties of the HNSCC, and the number of different biomarkers under investigation is rapidly growing.ObjectivesThe objective was to review the current literature regarding aberrantly methylated DNA found in peripheral blood plasma or serum in patients with HNSCC and to evaluate the diagnostic accuracy of these changes.MethodsThe inclusion criteria were clinical studies involving patients with verified HNSCC that reported findings of aberrantly methylated DNA in peripheral blood serum or plasma. We systematically searched PubMed, OVID Embase and Cochrane Library. In addition to the search, we performed forward and backward chaining in references and Web of Science. The protocol was registered in PROSPERO: CRD42019135406. Two authors independently extracted data. The quality and the risk of bias of the included studies were assessed by the QUADAS-2 tool.ResultsA total of 1,743 studies were found eligible for screening, while ultimately seven studies were included. All studies were found to have methodological weaknesses, mainly concerning patient selection bias. The best individual marker of HNSCC was Septin 9 in plasma with a sensitivity of 57% and a specificity of 95%.ConclusionsNone of the aberrantly methylated genes found in the retrieved studies are applicable as single diagnostic markers for HNSCC and the best gene-panels still lack diagnostic accuracy. Future studies may benefit from newer sequencing techniques but validation studies with well-designed cohorts are also needed in the process of developing epigenetic based diagnostic tests for HNSCC.

Acute myeloid leukaemia (AML) is characterised by phenotypic heterogeneity, which we hypothesise is a consequence of deregulated differentiation with transcriptional reminiscence of the normal compartment or cell-of-origin. Here, we propose a classification system based on normal myeloid progenitor cell subset-associated gene signatures (MAGS) for individual assignments of AML subtypes. We generated a MAGS classifier including the progenitor compartments CD34+/CD38- for haematopoietic stem cells (HSCs), CD34+/CD38+/CD45RA- for megakaryocyte-erythroid progenitors (MEPs), and CD34+/CD38+/CD45RA+ for granulocytic-monocytic progenitors (GMPs) using regularised multinomial regression with three discrete outcomes and an elastic net penalty. The regularisation parameters were chosen by cross-validation, and MAGS assignment accuracy was validated in an independent data set (N = 38; accuracy = 0.79) of sorted normal myeloid subpopulations. The prognostic value of MAGS assignment was studied in two clinical cohorts (TCGA: N = 171; GSE6891: N = 520) and had a significant prognostic impact. Furthermore, multivariate Cox regression analysis using the MAGS subtype, FAB subtype, cytogenetics, molecular genetics, and age as explanatory variables showed independent prognostic value. Molecular characterisation of subtypes by differential gene expression analysis, gene set enrichment analysis, and mutation patterns indicated reduced proliferation and overrepresentation of RUNX1 and IDH2 mutations in the HSC subtype; increased proliferation and overrepresentation of CEBPA mutations in the MEP subtype; and innate immune activation and overrepresentation of WT1 mutations in the GMP subtype. We present a differentiation-dependent classification system for AML subtypes with distinct pathogenetic and prognostic importance that can help identify candidates poorly responding to combination chemotherapy and potentially guide alternative treatments.

Abstract: Gene expression profiling (GEP) by microarrays of diffuse large B-cell lymphoma (DLBCL) has enabled the categorization of DLBCL into activated B-cell–like and germinal center B-cell–like subclasses. However, as this does not fully embrace the great diversity of B-cell subtypes, we recently developed a gene expression assay for B-cell–associated gene signature (BAGS) classification. To facilitate quick and easy-to-use BAGS profiling, we developed in this study the NanoString-based BAGS2Clinic assay. Microarray data from 4 different cohorts (n = 970) were used to select genes and train the assay. The locked assay was validated in an independent cohort of 88 sample biopsies. The assay showed good correspondence with the original BAGS classifier, with an overall accuracy of 84% (95% confidence interval, 72% to 93%) and a subtype-specific accuracy ranging between 80% and 99%. BAGS classification has the potential to provide valuable insight into tumor biology as well as differences in resistance to immuno- and chemotherapy that can lead to novel treatment strategies for DLBCL patients. BAGS2Clinic can facilitate this and the implementation of BAGS classification as a routine clinical tool to improve prognosis and treatment guidance for DLBCL patients.

PTEN loss has been associated with poorer prognosis in many solid tumors. However, such investigation in lymphomas is limited. In this study, PTEN cytoplasmic and nuclear expression, PTEN gene deletion, and PTEN mutations were evaluated in two independent cohorts of diffuse large B-cell lymphoma (DLBCL). Cytoplasmic PTEN expression was found in approximately 67% of total 747 DLBCL cases, more frequently in the activated B-cell–like subtype. Nuclear PTEN expression was less frequent and at lower levels, which significantly correlated with higher PTEN mRNA expression. Remarkably, loss of PTEN protein expression was associated with poorer survival only in DLBCL with AKT hyperactivation. In contrast, high PTEN expression was associated with Myc expression and poorer survival in cases without abnormal AKT activation. Genetic and epigenetic mechanisms for loss of PTEN expression were investigated. PTEN deletions (mostly heterozygous) were detected in 11.3% of DLBCL, and showed opposite prognostic effects in patients with AKT hyperactivation and in MYC rearranged DLBCL patients. PTEN mutations, detected in 10.6% of patients, were associated with upregulation of genes involved in central nervous system function, metabolism, and AKT/mTOR signaling regulation. Loss of PTEN cytoplasmic expression was also associated with TP53 mutations, higher PTEN-targeting microRNA expression, and lower PD-L1 expression. Remarkably, low PTEN mRNA expression was associated with down-regulation of a group of genes involved in immune responses and B-cell development/differentiation, and poorer survival in DLBCL independent of AKT activation. Collectively, multi-levels of PTEN abnormalities and dysregulation may play important roles in PTEN expression and loss, and that loss of PTEN tumor-suppressor function contributes to the poor survival of DLBCL patients with AKT hyperactivation.

Abstract: Stringent complete remission (sCR) of acute myeloid leukemia is defined as normal hematopoiesis after therapy. Less sCR, including non-sCR, was introduced as insufficient blood platelet, neutrophil, or erythrocyte recovery. These latter characteristics were defined retrospectively as postremission transfusion dependency and were suggested to be of prognostic value. In the present report, we evaluated the prognostic impact of achieving sCR and non-sCR in the Danish National Acute Leukaemia Registry, including 769 patients registered with classical CR (ie,

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoid malignancy in adults. Although significant progress has been made in recent years to treat DLBCL patients, 30%–40% of the patients eventually relapse or are refractory to first line treatment, calling for better therapeutic strategies for DLBCL. Long non-coding RNAs (lncRNAs) have emerged as a highly diverse group of non-protein coding transcripts with intriguing molecular functions in human disease, including cancer. Here, we review the current understanding of lncRNAs in the pathogenesis and progression of DLBCL to provide an overview of the field. As the current knowledge of lncRNAs in DLBCL is still in its infancy, we provide molecular signatures of lncRNAs in DLBCL cell lines to assist further lncRNA research in DLBCL.

Methods for clustering in unsupervised learning are an important part of the statistical toolbox in numerous scientific disciplines. Tewari, Giering, and Raghunathan (2011) proposed to use so-called Gaussian mixture copula models (GMCM) for general unsupervised learning based on clustering. Li, Brown, Huang, and Bickel (2011) independently discussed a special case of these GMCMs as a novel approach to meta-analysis in highdimensional settings. GMCMs have attractive properties which make them highly flexible and therefore interesting alternatives to other well-established methods. However, parameter estimation is hard because of intrinsic identifiability issues and intractable likelihood functions. Both aforementioned papers discuss similar expectation-maximization-like algorithms as their pseudo maximum likelihood estimation procedure. We present and discuss an improved implementation in R of both classes of GMCMs along with various alternative optimization routines to the EM algorithm. The software is freely available in the R package GMCM. The implementation is fast, general, and optimized for very large numbers of observations. We demonstrate the use of package GMCM through different applications.

BACKGROUND:Radiation-therapy (RT) induces mucositis, a clinically challenging condition with limited prophylactic interventions and no predictive tests. In this pilot study, we applied global gene-expression analysis on serial human oral mucosa tissue and blood cells from patients with tonsil squamous cell cancer (TSCC) to identify genes involved in mucositis pathogenesis. METHODS AND FINDINGS:Eight patients with TSCC each provided consecutive buccal biopsies and blood cells before, after 7 days of RT treatment, and 20 days following RT. We monitored clinical mucositis and performed gene-expression analysis on tissue samples. We obtained control tissue from nine healthy individuals. After RT, expression was upregulated in apoptosis inducer and inhibitor genes, EDA2R and MDM2, and in POLH, a DNA-repair polymerase. Expression was downregulated in six members of the histone cluster family, e.g., HIST1H3B. Gene expression related to proliferation and differentiation was altered, including MKI67 (downregulated), which encodes the Ki-67-proliferation marker, and KRT16 (upregulated), which encodes keratin16. These alterations were not associated with the clinical mucositis grade. However, the expression of LY6G6C, which encodes a surface immunoregulatory protein, was upregulated before treatment in three cases of clinical none/mild mucositis, but not in four cases of ulcerative mucositis. CONCLUSION:RT caused molecular changes related to apoptosis, DNA-damage, DNA-repair, and proliferation without a correlation to the severity of clinical mucositis. LY6G6C may be a potential protective biomarker for ulcerative mucositis. Based on these results, our study model of consecutive human biopsies will be useful in designing a prospective clinical validation trial to characterize molecular mucositis and identify predictive biomarkers.

Diagnostic and prognostic evaluation of chronic lymphocytic leukemia (CLL) involves blood cell counts, immunophenotyping, IgVH mutation status, and cytogenetic analyses. We generated B-cell associated gene-signatures (BAGS) based on six naturally occurring B-cell subsets within normal bone marrow. Our hypothesis is that by segregating CLL according to BAGS, we can identify subtypes with prognostic implications in support of pathogenetic value of BAGS. Microarray-based gene-expression samples from eight independent CLL cohorts (1,024 untreated patients) were BAGS-stratified into pre-BI, pre-BII, immature, naïve, memory, or plasma cell subtypes; the majority falling within the memory (24.5-45.8%) or naïve (14.5-32.3%) categories. For a subset of CLL patients (n = 296), time to treatment (TTT) was shorter amongst early differentiation subtypes (pre-BI/pre-BII/immature) compared to late subtypes (memory/plasma cell, HR: 0.53 [0.35-0.78]). Particularly, pre-BII subtype patients had the shortest TTT among all subtypes. Correlates derived for BAGS subtype and IgVH mutation (n = 405) revealed an elevated mutation frequency in late vs. early subtypes (71% vs. 45%, P < .001). Predictions for BAGS subtype resistance towards rituximab and cyclophosphamide varied for rituximab, whereas all subtypes were sensitive to cyclophosphamide. This study supports our hypothesis that BAGS-subtyping may be of tangible prognostic and pathogenetic value for CLL patients.

BACKGROUND:Toxicity of the oral and gastrointestinal mucosa induced by high-dose melphalan is a clinical challenge with no documented prophylactic interventions or predictive tests. The aim of this study was to describe molecular changes in human oral mucosa and to identify biomarkers correlated with the grade of clinical mucositis. METHODS AND FINDINGS:Ten patients with multiple myeloma (MM) were included. For each patient, we acquired three buccal biopsies, one before, one at 2 days, and one at 20 days after high-dose melphalan administration. We also acquired buccal biopsies from 10 healthy individuals that served as controls. We analyzed the biopsies for global gene expression and performed an immunohistochemical analysis to determine HLA-DRB5 expression. We evaluated associations between clinical mucositis and gene expression profiles. Compared to gene expression levels before and 20 days after therapy, at two days after melphalan treatment, we found gene regulation in the p53 and TNF pathways (MDM2, INPPD5, TIGAR), which favored anti-apoptotic defense, and upregulation of immunoregulatory genes (TREM2, LAMP3) in mucosal dendritic cells. This upregulation was independent of clinical mucositis. HLA-DRB1 and HLA-DRB5 (surface receptors on dendritic cells) were expressed at low levels in all patients with MM, in the subgroup of patients with ulcerative mucositis (UM), and in controls; in contrast, the subgroup with low-grade mucositis (NM) displayed 5-6 fold increases in HLA-DRB1 and HLA-DRB5 expression in the first two biopsies, independent of melphalan treatment. Moreover, different splice variants of HLA-DRB1 were expressed in the UM and NM subgroups. CONCLUSIONS:Our results revealed that, among patients with MM, immunoregulatory genes and genes involved in defense against apoptosis were affected immediately after melphalan administration, independent of the presence of clinical mucositis. Furthermore, our results suggested that the expression levels of HLA-DRB1 and HLA-DRB5 may serve as potential predictive biomarkers for mucositis severity.

The concept of the myeloma stem cell may have important therapeutic implications, yet its demonstration has been hampered by a lack of consistency in terms and definitions. Here, we summarize the current documentation and propose single-cell in vitro studies for future translational studies. By the classical approach, a CD19−/CD45low/−/CD38high/CD138+ malignant plasma cell, but not the CD19+/CD38low/− memory B cell compartment, is enriched for tumorigenic cells that initiate myeloma in xenografted immunodeficient mice, supporting that myeloma stem cells are present in the malignant PC compartment. Using a new approach, analysis of c-DNA libraries from CD19+/CD27+/CD38− single cells has identified clonotypic memory B cell, suggested to be the cell of origin. This is consistent with multiple myeloma being a multistep hierarchical process before or during clinical presentation. We anticipate that further characterization will require single cell geno- and phenotyping combined with clonogenic assays. To implement such technologies, we propose a revision of the concept of a myeloma stem cell by including operational in vitro assays to describe the cellular components of origin, initiation, maintenance, and evolution of multiple myeloma. These terms are in accordance with recent (2012) consensus statements on the definitions, assays, and nomenclature of cancer stem cells, which is technically precise without completely abolishing established terminology. We expect that this operational model will be useful for future reporting of parameters used to identify and characterize the multiple myeloma stem cells. We strongly recommend that these parameters include validated standard technologies, reproducible assays, and, most importantly, supervised prospective sampling of selected biomaterial which reflects clinical stages, disease spectrum, and therapeutic outcome. This framework is key to the characterization of the cellular architecture of multiple myeloma and its use in precision medicine.

BACKGROUND:Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. RESULTS:This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically. CONCLUSIONS:The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays.

Based on the current literature, we aimed to provide an overview on Human Papillomavirus prevalence in normal pregnancies and pregnancies with adverse outcome. We conducted a systematic literature search in PubMed and Embase. Data extracted from the articles and used for analysis included HPV prevalence, pregnancy outcome, geographical location, investigated tissue types, and HPV detection methods. The overall HPV prevalence in normal full-term pregnancies was found to be 17.5% (95% CI; 17.3–17.7) for cervix, 8.3% (95% CI; 7.6–9.1) for placental tissue, 5.7% (95% CI; 5.1–6.3) for amniotic fluid, and 10.9% (95% CI; 10.1–11.7) for umbilical cord blood. Summary estimates for HPV prevalence of spontaneous abortions and spontaneous preterm deliveries, in cervix (spontaneous abortions: 24.5%, and preterm deliveries: 47%, resp.) and placenta (spontaneous abortions: 24.9%, and preterm deliveries: 50%, resp.), were identified to be higher compared to normal full-term pregnancies (P

Diffuse large B-cell lymphoma (DLBCL) is characterized by great genetic and clinical heterogeneity which complicates prognostic prediction and influences treatment efficacy. The most common regimen, R-CHOP, consists of a combination of anthracycline- and immuno-based drugs including Rituximab. It remains elusive how and to which extent genetic variability impacts the response and potential tolerance to R-CHOP. Hence, an improved understanding of mechanisms leading to drug tolerance in B-cells is crucial, and modelling by genetic intervention directly in B-cells is fundamental in such investigations. Lentivirus-based gene vectors are widely used gene vehicles, which in B-cells are an attractive alternative to potentially toxic transfection-based methodologies. Here, we investigate the use of VSV-G-pseudotyped lentiviral vectors in B-cells for exploring the impact of microRNAs on tolerance to Rituximab. Notably, we find that robust lentiviral transduction of cancerous B-cell lines markedly and specifically enhances the resistance of transduced germinal center B-cells (GCBs) to Rituximab. Although Rituximab works partially through complement-mediated cell lysis, increased tolerance is not achieved through effects of lentiviral transduction on cell death mediated by complement. Rather, reduced levels of PARP1 and persistent high levels of CD43 in Rituximab-treated GCBs demonstrate anti-apoptotic effects of lentiviral transduction that may interfere with the outcome and interpretation of Rituximab tolerance studies. Our findings stress that caution should be exercised exploiting lentiviral vectors in studies of tolerance to therapeutics in DLBCL. Importantly, however, we demonstrate the feasibility of using the lentiviral gene delivery platform in studies addressing the impact of specific microRNAs on Rituximab responsiveness.

BACKGROUND:International collaborative research is a mechanism for improving the development of disease-specific therapies and for improving health at the population level. However, limited data are available to assess the trends in research output related to orphan diseases. METHODS AND FINDINGS:We used bibliometric mapping and clustering methods to illustrate the level of fragmentation in myeloma research and the development of collaborative efforts. Publication data from Thomson Reuters Web of Science were retrieved for 2005-2009 and followed until 2013. We created a database of multiple myeloma publications, and we analysed impact and co-authorship density to identify scientific collaborations, developments, and international key players over time. The global annual publication volume for studies on multiple myeloma increased from 1,144 in 2005 to 1,628 in 2009, which represents a 43% increase. This increase is high compared to the 24% and 14% increases observed for lymphoma and leukaemia. The major proportion (>90% of publications) was from the US and EU over the study period. The output and impact in terms of citations, identified several successful groups with a large number of intra-cluster collaborations in the US and EU. The US-based myeloma clusters clearly stand out as the most productive and highly cited, and the European Myeloma Network members exhibited a doubling of collaborative publications from 2005 to 2009, still increasing up to 2013. CONCLUSION AND PERSPECTIVE:Multiple myeloma research output has increased substantially in the past decade. The fragmented European myeloma research activities based on national or regional groups are progressing, but they require a broad range of targeted research investments to improve multiple myeloma health care.

Long noncoding RNAs (lncRNAs) have emerged as important regulators of diverse cellular processes, but their roles in the developing immune system are poorly understood. In this study, we analysed lncRNA expression during human B-cell development by array-based expression profiling of eleven distinct flow-sorted B-cell subsets, comprising pre-B1, pre-B2, immature, naive, memory, and plasma cells from bone marrow biopsies (n = 7), and naive, centroblast, centrocyte, memory, and plasmablast cells from tonsil tissue samples (n = 6), respectively. A remapping strategy was used to assign the array probes to 37630 gene-level probe sets, reflecting recent updates in genomic and transcriptomic databases, which enabled expression profiling of 19579 long noncoding RNAs, comprising 3947 antisense RNAs, 5277 lincRNAs, 7625 pseudogenes, and 2730 additional lncRNAs. As a first step towards inferring the functions of the identified lncRNAs in developing B-cells, we analysed their co-expression with well-characterized protein-coding genes, a method known as "guilt by association". By using weighted gene co-expression network analysis, we identified 272 lincRNAs, 471 antisense RNAs, 376 pseudogene RNAs, and 64 lncRNAs within seven sub-networks associated with distinct stages of B-cell development, such as early B-cell development, B-cell proliferation, affinity maturation of antibody, and terminal differentiation. These data provide an important resource for future studies on the functions of lncRNAs in development of the adaptive immune response, and the pathogenesis of B-cell malignancies that originate from distinct B-cell subpopulations.

We evaluated a lymphoid RNA standard prepared in our laboratory for spotted microarrays against the Universal Human Reference standard from Stratagene. Our goal was to determine if the Stratagene standard, which contains only two lymphoid cell lines out of a pool of 10 human cancer cell lines, had acceptable gene coverage to serve as a comprehensive standard for gene expression profiling of lymphoid tissues. Our lymphoid standard was prepared from thymus, spleen, tonsil, and cell lines representing immature B cells, plasma cells, and natural killer (NK) cells, thus covering the entire spectrum of lymphoid cells and most stromal elements present in specialized lymphoid tissues. The two standards were co-hybridized on oligonucleotide microarrays containing 17,260 genes, and both had fluorescence intensities above background for approximately 85% of the genes. Despite the limited representation of lymphoid cells in the Stratagene standard, only 4.2% genes exhibited expression differences greater than 2-fold including only 0.35% with differences greater than 4-fold. Although the lymphoid standard reflected a more comprehensive representation of immune system-associated genes, the Stratagene standard has the advantage of being commercially available, enabling easier comparison across laboratories and allowing comparative studies across a long period of time.

Human papillomavirus (HPV) is suggested to infect trophoblasts in the placenta, and HPV infections are reported to be more prevalent in pregnancies with adverse outcomes. Results are however controversial, and studies investigating the molecular consequences of placental HPV infections are lacking. We studied HPV DNA localization in the placenta in cases of spontaneous abortion/spontaneous preterm delivery as well as in elective abortion/normal full-term delivery. Using in vitro assays, we investigated downstream effects of HPV16 E6 and E7 expression in trophoblast cells at the gene expression level in order to gain increased biological insight into the interaction between HPV and the cellular host. Fluorescent in situ hybridization (FISH), combined with fluorescent immunohistochemistry (FIHC) to target the trophoblast marker CK7 clearly showed, that HPV DNA resides within syncytiotrophoblast cells in the placenta. In vitro HPV16 E6 and E7-transfected trophoblasts were analyzed by RNA sequencing, and results were validated by reverse transcription real time polymerase chain reaction (RT-qPCR) for selected genes in cell lines, as well as in patient material. We show that HPV16 E6 and E7 upregulate interferon-induced antiviral response genes ISG15 and IFIT1 in a human trophoblast cell line two-days post-transfection. This is a response that is not observed when assessing the gene expression levels of the same genes in HPV16-positive placenta samples. Investigations on viral activity find that HPV16 E6 and E7 are not transcribed in patients, possibly suggesting that HPV16 syncytiotrophoblast infection may be latent. We conclude that HPV localizes to syncytiotrophoblast cells of the placenta, and that active expression of HPV16 E6 and E7 induce an immediate interferon-induced antiviral response in trophoblast cells, which is not present in HPV-positive placenta samples, suggesting latent infection.

Diffuse large B-cell lymphoma can be classified by gene expression profiling into germinal center and activated B-cell subtypes with different prognoses after rituximab-CHOP. The importance of previously recognized prognostic markers, such as Bcl-2 protein expression and BCL2 gene abnormalities, has been questioned in the new therapeutic era. We analyzed Bcl-2 protein expression, and BCL2 and MYC gene abnormalities by interphase fluorescence in situ hybridization in 327 patients with de novo disease treated with rituximab-CHOP. Isolated BCL2 and MYC rearrangements were not predictive of outcome in our patients as a whole, but only in those with the germinal center subtype of lymphoma. The prognostic relevance of isolated MYC rearrangements was weaker than that of BCL2 isolated translocations, but was probably limited by the rarity of the rearrangements. Seven of eight patients with double hit lymphoma had the germinal center subtype with poor outcome. The germinal center subtype patients with isolated BCL2 translocations had significantly worse outcome than the patients without BCL2 rearrangements (P=0.0002), and their outcome was similar to that of patients with the activated B-cell subtype (P=0.30), but not as bad as the outcome of patients with double hit lymphoma (P

In a conceptual study of drug resistance we have used a preclinical model of malignant B-cell lines by combining drug induced growth inhibition and gene expression profiling. In the current report a melphalan resistance profile of 19 genes were weighted by microarray data from the MRC Myeloma IX trial and time to progression following high dose melphalan, to generate an individual melphalan resistance index. The resistance index was subsequently validated in the HOVON65/GMMG-HD4 trial data set to prove the concept. Biologically, the assigned resistance indices were differentially distributed among translocations and cyclin D expression classes. Clinically, the 25% most melphalan resistant, the intermediate 50% and the 25% most sensitive patients had a median progression free survival of 18, 32 and 28 months, respectively (log-rank P-value = 0.05). Furthermore, the median overall survival was 45 months for the resistant group and not reached for the intermediate and sensitive groups (log-rank P-value = 0.003) following 38 months median observation. In a multivariate analysis, correcting for age, sex and ISS-staging, we found a high resistance index to be an independent variable associated with inferior progression free survival and overall survival. This study provides clinical proof of concept to use in vitro drug screen for identification of melphalan resistance gene signatures for future functional analysis.

BackgroundRecent reports indicate that in vitro drug screens combined with gene expression profiles (GEP) of cancer cell lines may generate informative signatures predicting the clinical outcome of chemotherapy. In multiple myeloma (MM) a range of new drugs have been introduced and now challenge conventional therapy including high dose melphalan. Consequently, the generation of predictive signatures for response to melphalan may have a clinical impact. The hypothesis is that melphalan screens and GEPs of B-cell cancer cell lines combined with multivariate statistics may provide predictive clinical information.Materials and methodsMicroarray based GEPs and a melphalan growth inhibition screen of 59 cancer cell lines were downloaded from the National Cancer Institute database. Equivalent data were generated for 18 B-cell cancer cell lines. Linear discriminant analyses (LDA), sparse partial least squares (SPLS) and pairwise comparisons of cell line data were used to build resistance signatures from both cell line panels. A melphalan resistance index was defined and estimated for each MM patient in a publicly available clinical data set and evaluated retrospectively by Cox proportional hazards and Kaplan-Meier survival analysis.Principal findingsBoth cell line panels performed well with respect to internal validation of the SPLS approach but only the B-cell panel was able to predict a significantly higher risk of relapse and death with increasing resistance index in the clinical data sets. The most sensitive and resistant cell lines, MOLP-2 and RPMI-8226 LR5, respectively, had high leverage, which suggests their differentially expressed genes to possess important predictive value.ConclusionThe present study presents a melphalan resistance index generated by analysis of a B-cell panel of cancer cell lines. However, the resistance index needs to be functionally validated and correlated to known MM biomarkers in independent data sets in order to better understand the mechanism underlying the preparedness to melphalan resistance.

Aggressive NK-cell leukemia is a rare malignancy with neoplastic proliferation of natural killer cells. It often presents with constitutional symptoms, a rapid declining clinical course, and a poor prognosis with a median survival of a few months. The disease is usually resistant to cytotoxic agents, and no treatment has emerged as the standard of care for these patients. We report a case of an 18-year-old male who obtains complete remission following two lines of combination chemotherapy. We describe in details our regimens for induction chemotherapy and perform a review of existing literature concerning treatment of aggressive NK-cell leukemia.