The Lymphoma Epidemiology of Outcomes cohort study: Design, baseline characteristics, and early outcomes

To address the current and long-term unmet health needs of the growing population of non-Hodgkin lymphoma (NHL) patients, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/). A total of 7735 newly diagnosed patients aged 18 years and older with NHL were prospectively enrolled from 7/1/2015 to 5/31/2020 at 8 academic centers in the United States. The median age at diagnosis was 62 years (range, 18-99). Participants came from 49 US states and included 538 Black/African-Americans (AA), 822 Hispanics (regardless of race), 3386 women, 716 age <40 years, and 1513 rural residents. At study baseline, we abstracted clinical, pathology, and treatment data; banked serum/plasma (N = 5883, 76.0%) and germline DNA (N = 5465, 70.7%); constructed tissue microarrays for four major NHL subtypes (N = 1189); and collected quality of life (N = 5281, 68.3%) and epidemiologic risk factor (N = 4489, 58.0%) data. Through August 2022, there were 1492 deaths. Compared to population-based SEER data (2015-2019), LEO participants had a similar distribution of gender, AA race, Hispanic ethnicity, and NHL subtype, while LEO was underrepresented for patients who were Asian and aged 80 years and above. Observed overall survival rates for LEO at 1 and 2 years were similar to population-based SEER rates for indolent B-cell (follicular and marginal zone) and T-cell lymphomas, but were 10%-15% higher than SEER rates for aggressive B-cell subtypes (diffuse large B-cell and mantle cell). The LEO cohort is a robust and comprehensive national resource to address the role of clinical, tumor, host genetic, epidemiologic, and other biologic factors in NHL prognosis and survivorship.

Translating prognostic quantification of c-MYC and BCL2 from tissue microarrays to whole slide images in diffuse large B-cell lymphoma using deep learning

BACKGROUND

c-MYC and BCL2 positivity are important prognostic factors for diffuse large B-cell lymphoma. However, manual quantification is subject to significant intra- and inter-observer variability. We developed an automated method for quantification in whole-slide images of tissue sections where manual quantification requires evaluating large areas of tissue with possibly heterogeneous staining. We train this method using annotations of tumor positivity in smaller tissue microarray cores where expression and staining are more homogeneous and then translate this model to whole-slide images.

METHODS

Our method applies a technique called attention-based multiple instance learning to regress the proportion of c-MYC-positive and BCL2-positive tumor cells from pathologist-scored tissue microarray cores. This technique does not require annotation of individual cell nuclei and is trained instead on core-level annotations of percent tumor positivity. We translate this model to scoring of whole-slide images by tessellating the slide into smaller core-sized tissue regions and calculating an aggregate score. Our method was trained on a public tissue microarray dataset from Stanford and applied to whole-slide images from a geographically diverse multi-center cohort produced by the Lymphoma Epidemiology of Outcomes study.

RESULTS

In tissue microarrays, the automated method had Pearson correlations of 0.843 and 0.919 with pathologist scores for c-MYC and BCL2, respectively. When utilizing standard clinical thresholds, the sensitivity/specificity of our method was 0.743 / 0.963 for c-MYC and 0.938 / 0.951 for BCL2. For double-expressors, sensitivity and specificity were 0.720 and 0.974. When translated to the external WSI dataset scored by two pathologists, Pearson correlation was 0.753 & 0.883 for c-MYC and 0.749 & 0.765 for BCL2, and sensitivity/specificity was 0.857/0.991 & 0.706/0.930 for c-MYC, 0.856/0.719 & 0.855/0.690 for BCL2, and 0.890/1.00 & 0.598/0.952 for double-expressors. Survival analysis demonstrates that for progression-free survival, model-predicted TMA scores significantly stratify double-expressors and non double-expressors (p = 0.0345), whereas pathologist scores do not (p = 0.128).

CONCLUSIONS

We conclude that proportion of positive stains can be regressed using attention-based multiple instance learning, that these models generalize well to whole slide images, and that our models can provide non-inferior stratification of progression-free survival outcomes.

Automated Deep Learning-Based Diagnosis and Molecular Characterization of Acute Myeloid Leukemia Using Flow Cytometry

The current flow cytometric analysis of blood and bone marrow samples for diagnosis of acute myeloid leukemia (AML) relies heavily on manual intervention in the processing and analysis steps, introducing significant subjectivity into resulting diagnoses and necessitating highly trained personnel. Furthermore, concurrent molecular characterization via cytogenetics and targeted sequencing can take multiple days, delaying patient diagnosis and treatment. Attention-based multi-instance learning models (ABMILMs) are deep learning models that make accurate predictions and generate interpretable insights regarding the classification of a sample from individual events/cells; nonetheless, these models have yet to be applied to flow cytometry data. In this study, we developed a computational pipeline using ABMILMs for the automated diagnosis of AML cases based exclusively on flow cytometric data. Analysis of 1820 flow cytometry samples shows that this pipeline provides accurate diagnoses of acute leukemia (area under the receiver operating characteristic curve [AUROC] 0.961) and accurately differentiates AML vs B- and T-lymphoblastic leukemia (AUROC 0.965). Models for prediction of 9 cytogenetic aberrancies and 32 pathogenic variants in AML provide accurate predictions, particularly for t(15;17)(PML::RARA) [AUROC 0.929], t(8;21)(RUNX1::RUNX1T1) (AUROC 0.814), and NPM1 variants (AUROC 0.807). Finally, we demonstrate how these models generate interpretable insights into which individual flow cytometric events and markers deliver optimal diagnostic utility, providing hematopathologists with a data visualization tool for improved data interpretation, as well as novel biological associations between flow cytometric marker expression and cytogenetic/molecular variants in AML. Our study is the first to illustrate the feasibility of using deep learning-based analysis of flow cytometric data for automated AML diagnosis and molecular characterization.

Early cellular mechanisms of type I interferon-driven susceptibility to tuberculosis

Mycobacterium tuberculosis (Mtb) causes 1.6 million deaths annually. Active tuberculosis correlates with a neutrophil-driven type I interferon (IFN) signature, but the cellular mechanisms underlying tuberculosis pathogenesis remain poorly understood. We found that interstitial macrophages (IMs) and plasmacytoid dendritic cells (pDCs) are dominant producers of type I IFN during Mtb infection in mice and non-human primates, and pDCs localize near human Mtb granulomas. Depletion of pDCs reduces Mtb burdens, implicating pDCs in tuberculosis pathogenesis. During IFN-driven disease, we observe abundant DNA-containing neutrophil extracellular traps (NETs) described to activate pDCs. Cell-type-specific disruption of the type I IFN receptor suggests that IFNs act on IMs to inhibit Mtb control. Single-cell RNA sequencing (scRNA-seq) indicates that type I IFN-responsive cells are defective in their response to IFNγ, a cytokine critical for Mtb control. We propose that pDC-derived type I IFNs act on IMs to permit bacterial replication, driving further neutrophil recruitment and active tuberculosis disease.

Immunosuppression is a conserved driver of tuberculosis susceptibility

Mycobacterium tuberculosis ( Mtb ) causes 1.6 million deaths a year 1 . However, no individual mouse model fully recapitulates the hallmarks of human tuberculosis disease. Here we report that a comparison across three different susceptible mouse models identifies Mtb -induced gene signatures that predict active TB disease in humans significantly better than a signature from the standard C57BL/6 mouse model. An increase in lung myeloid cells, including neutrophils, was conserved across the susceptible mouse models, mimicking the neutrophilic inflammation observed in humans 2,3 . Myeloid cells in the susceptible models and non-human primates exhibited high expression of immunosuppressive molecules including the IL-1 receptor antagonist, which inhibits IL-1 signaling. Prior reports have suggested that excessive IL-1 signaling impairs Mtb control 4-6 . By contrast, we found that enhancement of IL-1 signaling via deletion of IL-1 receptor antagonist promoted bacterial control in all three susceptible mouse models. IL-1 signaling enhanced cytokine production by lymphoid and stromal cells, suggesting a mechanism for IL-1 signaling in promoting Mtb control. Thus, we propose that myeloid cell expression of immunosuppressive molecules is a conserved mechanism exacerbating Mtb disease in mice, non-human primates, and humans.

Profiling endogenous, environmental, and infectious disease mutational signatures in blastic plasmacytoid dendritic cell neoplasms

BACKGROUND

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematopoietic disease derived from plasmacytoid dendritic lineage cells. The disease typically shows skin as well as frequent bone marrow and peripheral blood involvement. However, the pathogenesis of this disease is still not well understood. While somatic point mutations and genetic rearrangements have been described in BPDCN, the types and origins of these mutations and relationships to other cancer types is not well understood.

MATERIALS AND METHODS

To probe the origins of BPDCN, we analyzed the exome sequence data of 9 tumor-normal pair cases of BPDCN. We utilized SignatureAnalyzer, SigProfiler and a custom microbial analysis pipeline to understand the relevance of endogenous and environmental mutagenic processes.

RESULTS

Our results identified a significant tobacco exposure and aging genetic signature as well as signatures related to nucleotide excision repair deficiency, ultra violet (UV) exposure, and endogenous deamination in BPDCN. We also assessed the samples for microbial infectious disease organisms but did not find a link to a microbial etiology.

CONCLUSION

The identification of a tobacco exposure and aging genetic signature in patients with BPDCN suggests that environmental and endogenous genetic changes may be central to the oncogenesis of BPDCN.

Automated Deep Learning-Based Diagnosis and Molecular Characterization of Acute Myeloid Leukemia using Flow Cytometry

Current flow cytometric analysis of blood and bone marrow samples for diagnosis of acute myeloid leukemia (AML) relies heavily on manual intervention in both the processing and analysis steps, introducing significant subjectivity into resulting diagnoses and necessitating highly trained personnel. Furthermore, concurrent molecular characterization via cytogenetics and targeted sequencing can take multiple days, delaying patient diagnosis and treatment. Attention-based multi-instance learning models (ABMILMs) are deep learning models which make accurate predictions and generate interpretable insights regarding the classification of a sample from individual events/cells; nonetheless, these models have yet to be applied to flow cytometry data. In this study, we developed a computational pipeline using ABMILMs for the automated diagnosis of AML cases based exclusively on flow cytometric data. Analysis of 1,820 flow cytometry samples shows that this pipeline provides accurate diagnoses of acute leukemia [AUROC 0.961] and accurately differentiates AML versus B- and T-lymphoblastic leukemia [AUROC 0.965]. Models for prediction of 9 cytogenetic aberrancies and 32 pathogenic variants in AML provide accurate predictions, particularly for t(15;17)(PML::RARA) [AUROC 0.929], t(8;21)(RUNX1::RUNX1T1) [AUROC 0.814], and NPM1 variants [AUROC 0.807]. Finally, we demonstrate how these models generate interpretable insights into which individual flow cytometric events and markers deliver optimal diagnostic utility, providing hematopathologists with a data visualization tool for improved data interpretation, as well as novel biological associations between flow cytometric marker expression and cytogenetic/molecular variants in AML. Our study is the first to illustrate the feasibility of using deep learning-based analysis of flow cytometric data for automated AML diagnosis and molecular characterization.

Regulation of antigen-specific T cell infiltration and spatial architecture in multiple myeloma and premalignancy

Entry of antigen-specific T cells into human tumors is critical for immunotherapy, but the underlying mechanisms are poorly understood. Here, we combined high-dimensional spatial analyses with in vitro and in vivo modeling to study the mechanisms underlying immune infiltration in human multiple myeloma (MM) and its precursor monoclonal gammopathy of undetermined significance (MGUS). Clustered tumor growth was a feature of MM but not MGUS biopsies, and this growth pattern was reproduced in humanized mouse models. MM biopsies exhibited intralesional as well as spatial heterogeneity, with coexistence of T cell-rich and T cell-sparse regions and the presence of areas of T cell exclusion. In vitro studies demonstrated that T cell entry into MM clusters was regulated by agonistic signals and CD2-CD58 interactions. Upon adoptive transfer, antigen-specific T cells localized to the tumor site but required in situ DC-mediated antigen presentation for tumor entry. C-type lectin domain family 9 member A-positive (CLEC9A+) DCs appeared to mark portals of entry for gradients of T cell infiltration in MM biopsies, and their proximity to T cell factor 1-positive (TCF1+) T cells correlated with disease state and risk status. These data illustrate a role for tumor-associated DCs and in situ activation in promoting the infiltration of antigen-specific T cells in MM and provide insights into spatial alterations in tumor/immune cells with malignant evolution.

An Automated Pipeline for Differential Cell Counts on Whole-Slide Bone Marrow Aspirate Smears

The pathologic diagnosis of bone marrow disorders relies in part on the microscopic analysis of bone marrow aspirate (BMA) smears and the manual counting of marrow nucleated cells to obtain a differential cell count (DCC). This manual process has significant limitations, including the analysis of only a small subset of optimal slide areas and nucleated cells, as well as interobserver variability due to differences in cell selection and classification. To address these shortcomings, we developed an automated machine learning-based pipeline for obtaining 11-component DCCs on whole-slide BMAs. This pipeline uses a sequential process of identifying optimal BMA regions with high proportions of marrow nucleated cells, detecting individual cells within these optimal areas, and classifying these cells into 1 of 11 DCC components. Convolutional neural network models were trained on 396,048 BMA region, 28,914 cell boundary, and 1,510,976 cell class images from manual annotations. The resulting automated pipeline produced 11-component DCCs that demonstrated a high statistical and diagnostic concordance with manual DCCs among a heterogeneous group of testing BMA slides with varying pathologies and cellularities. Additionally, we demonstrated that an automated analysis can reduce the intraslide variance in DCCs by analyzing the whole slide and marrow nucleated cells within all optimal regions. Finally, the pipeline outputs of region classification, cell detection, and cell classification can be visualized using whole-slide image analysis software. This study demonstrates the feasibility of a fully automated pipeline for generating DCCs on scanned whole-slide BMA images, with the potential for improving the current standard of practice for utilizing BMA smears in the laboratory analysis of hematologic disorders.

Herpes simplex virus lymphadenitis is associated with tumor reduction in a chronic lymphocytic leukemia patient

BACKGROUND

Herpes simplex virus lymphadenitis (HSVL) is an unusual presentation of HSV reactivation in chronic lymphocytic leukemia (CLL) patients characterized by systemic symptoms and no herpetic lesions. The immune responses during HSVL have not been studied.

METHODS

Peripheral blood and lymph node samples of a patient with HSVL were obtained. HSV-2 viral load, antibody levels, B and T cell responses, cytokine levels, and tumor burden were measured.

RESULTS

This patient showed HSV-2 viremia for at least 6 weeks. During this period, she had a robust HSV-specific antibody response with neutralizing and antibody-dependent cellular phagocytosis activity. Activated (HLA-DR+, CD38+) CD4+ and CD8+ T cells increased 18-fold and HSV-specific CD8+ T cells were detected in the blood at higher numbers. HSV-specific B and T cell responses in the lymph node were also detected. Markedly elevated levels of pro-inflammatory cytokines in the blood were also observed. Surprisingly, a sustained decrease in CLL tumor burden without CLL-directed therapy was observed with this and also a prior episode of HSVL.

CONCLUSION

HSVL should be considered as part of the differential diagnosis in CLL patients who present with signs and symptoms of aggressive lymphoma transformation. An interesting finding was the sustained tumor control after 2 episodes of HSVL in this patient. This tumor burden reduction may be due to the HSV-specific response serving as an adjuvant for activating tumor-specific or bystander T cells. Studies in additional CLL patients are needed to confirm and extend these findings.

FUNDING

National Institutes of Health and Winship Cancer Institute.

Lightweight, open source, easy-use algorithm and web service for paraprotein screening using spatial frequency domain analysis of electrophoresis studies

Introduction

Methods

Results

Conclusions

Venetoclax sensitivity in multiple myeloma is associated with B-cell gene expression

Venetoclax is a highly potent, selective BCL2 inhibitor capable of inducing apoptosis in cells dependent on BCL2 for survival. Most myeloma is MCL1-dependent; however, a subset of myeloma enriched for translocation t(11;14) is codependent on BCL2 and thus sensitive to venetoclax. The biology underlying this heterogeneity remains poorly understood. We show that knockdown of cyclin D1 does not induce resistance to venetoclax, arguing against a direct role for cyclin D1 in venetoclax sensitivity. To identify other factors contributing to venetoclax response, we studied a panel of 31 myeloma cell lines and 25 patient samples tested for venetoclax sensitivity. In cell lines, we corroborated our previous observation that BIM binding to BCL2 correlates with venetoclax response and further showed that knockout of BIM results in decreased venetoclax sensitivity. RNA-sequencing analysis identified expression of B-cell genes as enriched in venetoclax-sensitive myeloma, although no single gene consistently delineated sensitive and resistant cells. However, a panel of cell surface makers correlated well with ex vivo prediction of venetoclax response in 21 patient samples and may serve as a biomarker independent of t(11;14). Assay for transposase-accessible chromatin sequencing of myeloma cell lines also identified an epigenetic program in venetoclax-sensitive cells that was more similar to B cells than that of venetoclax-resistant cells, as well as enrichment for basic leucine zipper domain-binding motifs such as BATF. Together, these data indicate that remnants of B-cell biology are associated with BCL2 dependency and point to novel biomarkers of venetoclax-sensitive myeloma independent of t(11;14).

Chromatin Accessibility Identifies Regulatory Elements Predictive of Gene Expression and Disease Outcome in Multiple Myeloma

PURPOSE

Multiple myeloma is a malignancy of plasma cells. Extensive genetic and transcriptional characterization of myeloma has identified subtypes with prognostic and therapeutic implications. In contrast, relatively little is known about the myeloma epigenome.

EXPERIMENTAL DESIGN

CD138+CD38+ myeloma cells were isolated from fresh bone marrow aspirate or the same aspirate after freezing for 1-6 months. Gene expression and chromatin accessibility were compared between fresh and frozen samples by RNA sequencing (RNA-seq) and assay for transpose accessible chromatin sequencing (ATAC-seq). Chromatin accessible regions were used to identify regulatory RNA expression in more than 700 samples from newly diagnosed patients in the Multiple Myeloma Research Foundation CoMMpass trial (NCT01454297).

RESULTS

Gene expression and chromatin accessibility of cryopreserved myeloma recapitulated that of freshly isolated samples. ATAC-seq performed on a series of biobanked specimens identified thousands of chromatin accessible regions with hundreds being highly coordinated with gene expression. More than 4,700 of these chromatin accessible regions were transcribed in newly diagnosed myelomas from the CoMMpass trial. Regulatory element activity alone recapitulated myeloma gene expression subtypes, and in particular myeloma subtypes with immunoglobulin heavy chain translocations were defined by transcription of distal regulatory elements. Moreover, enhancer activity predicted oncogene expression implicating gene regulatory mechanisms in aggressive myeloma.

CONCLUSIONS

These data demonstrate the feasibility of using biobanked specimens for retrospective studies of the myeloma epigenome and illustrate the unique enhancer landscapes of myeloma subtypes that are coupled to gene expression and disease progression.

Automated Serum Protein Electrophoresis Interpretation Using Machine Learning-Based Algorithm for Paraprotein Detection

Introduction

The laboratory diagnostic criteria for plasma cell neoplasms such as multiple myeloma include the presence of a monoclonal paraprotein which may be identified by serum protein electrophoresis (SPEP). To date, there are no high-sensitivity screening methods for automated detection of serum paraproteins using machine learning.

Methods

Cases from a plasma cell neoplasm registry (n=501) were manually labeled for paraprotein status. Each case included categorical features for 31 laboratory results commonly reported in myeloma. We applied fast Fourier transform to the gamma region of the SPEP curve and constructed features corresponding to cumulative magnitudes in the Fourier domain. Data were split into a 75% training set and a 25% test set. Using all feature domains independently, as well as combinations of select feature domains, we then trained three models: logistic regression, support vector machine, and random forest. Via 5-fold cross-validation, we tuned all models to a 95% sensitivity target and evaluated them by AUC, specificity, positive predictive value (PPV), F1 score, accuracy and likelihood ratio. We evaluated performance in plasma cell neoplasm and clinically heterogeneous test sets at low, medium, and high paraprotein concentrations, performing error analysis on each set.

Results

The logistic regression model using only Fourier domain features performed with the highest AUC (0.944). This model achieved sensitivity 0.962, PPV 0.667, specificity 0.569, F1 score 0.787, and accuracy 0.755. The model with the highest likelihood ratio while maintaining sensitivity over 0.90 achieves AUC 0.944, sensitivity 0.904, PPV 0.860, specificity 0.862, F1 score 0.899, and accuracy 0.900.

Stratification of sensitivity by paraprotein concentration showed the model achieves sensitivity 0.88 in samples with low paraprotein concentration (0.1 to 0.5 g/dL), and 1.0 in samples with medium (0.5 to 3.0 g/dL) and high (over 3.0 g/dL) concentrations. In the separate clinically heterogeneous test set, the overall sensitivity was 0.880 (0.870 for low, 0.885 for medium and 0.909 for high concentration samples). Error analysis on the misclassified samples with low paraprotein status showed that the algorithm may miss cases with low paraprotein concentration, as well as cases with paraproteins outside the gamma region.

Discussion and Conclusion

Our machine learning algorithm detects paraproteins with 94% sensitivity at over 0.85 specificity, PPV, and accuracy using the Fourier transformation of the SPEP gamma region. Future work to achieve higher sensitivity at similar specificity would allow clinical laboratories to use this as a screening method for paraprotein rule-out and drive efficiencies in laboratory workflows. Although we did not demonstrate it in this study, we believe that extending our model to include quantitative laboratory results that frequently accompany SPEP holds promise for increasing sensitivity within the scope of physicians standard clinical laboratory ordering practice. Additional strategies include deep learning models like convolutional and recurrent neural networks.

Clinician-ordered peripheral blood smears have low reimbursement and variable clinical value: a three-institution study, with suggestions for operational efficiency

Background

Peripheral blood smears are performed to evaluate a variety of hematologic and non-hematologic disorders. At the authors’ institutions, clinician requests for pathologist-performed blood smear reviews have increased in recent years. Blood smears may contribute significantly to pathologists’ workloads, yet their clinical value is variable, and professional reimbursement rates are low. This study aimed to identify clinical scenarios in which smear review is likely to provide value beyond automated laboratory testing.

Methods

Blood smear review practices at three institutions were examined, and the indications for and interpretations of clinician-initiated smears were reviewed to determine the percentage of smears with potential added clinical value. A smear review was classified as having added clinical value if the pathologist’s interpretation included a morphologic abnormality that had the potential to impact patient management, and that could not be diagnosed by automated complete blood count with white blood cell differential or automated iron studies alone.

Results

Among 515 consecutive clinician-requested smears performed during the study timeframes, 23% yielded interpretations with potential added clinical value. When sorted by indication, 25, 19, and 13% of smear reviews requested for white blood cell abnormalities, red blood cell abnormalities, and platelet abnormalities, respectively, had findings with potential added clinical value. The proportion of smears with potential clinical value differed significantly across these three categories (p = 0.0375).

Conclusions

Smear review ordering practices across three institutions resulted in a minority of smears with potential added clinical value. The likelihood of value varied according to the indication for which the smear was requested. Given this, efforts to improve the utilization and efficiency of smear review are worthwhile. Solutions are discussed, including engaging laboratory staff, educating clinicians, and modifying technology systems.

Machine-based detection and classification for bone marrow aspirate differential counts: initial development focusing on nonneoplastic cells

Bone marrow aspirate (BMA) differential cell counts (DCCs) are critical for the classification of hematologic disorders. While manual counts are considered the gold standard, they are labor intensive, time consuming, and subject to bias. A reliable automated counter has yet to be developed, largely due to the inherent complexity of bone marrow specimens. Digital pathology imaging coupled with machine learning algorithms represents a highly promising emerging technology for this purpose. Yet, training datasets for BMA cellular constituents, critical for building and validating machine learning algorithms, are lacking. Herein, we report our experience creating and employing such datasets to develop a machine learning algorithm to detect and classify BMA cells. Utilizing a web-based system that we developed for annotating and managing digital pathology images, over 10,000 cells from scanned whole slide images of BMA smears were manually annotated, including all classes that comprise the standard clinical DCC. We implemented a two-stage, detection and classification approach that allows design flexibility and improved classification accuracy. In a sixfold cross-validation, our algorithms achieved high overall accuracy in detection (0.959 ± 0.008 precision-recall AUC) and classification (0.982 ± 0.03 ROC AUC) using nonneoplastic samples. Testing on a small set of acute myeloid leukemia and multiple myeloma samples demonstrated similar detection and classification performance. In summary, our algorithms showed promising early results and represent an important initial step in the effort to devise a reliable, objective method to automate DCCs. With further development to include formal clinical validation, such a system has the potential to assist in disease diagnosis and prognosis, and significantly impact clinical practice.

Multiple myeloma immunoglobulin lambda translocations portend poor prognosis

Multiple myeloma is a malignancy of antibody-secreting plasma cells. Most patients benefit from current therapies, however, 20% of patients relapse or die within two years and are deemed high risk. Here we analyze structural variants from 795 newly-diagnosed patients as part of the CoMMpass study. We report translocations involving the immunoglobulin lambda (IgL) locus are present in 10% of patients, and indicative of poor prognosis. This is particularly true for IgL-MYC translocations, which coincide with focal amplifications of enhancers at both loci. Importantly, 78% of IgL-MYC translocations co-occur with hyperdiploid disease, a marker of standard risk, suggesting that IgL-MYC-translocated myeloma is being misclassified. Patients with IgL-translocations fail to benefit from IMiDs, which target IKZF1, a transcription factor that binds the IgL enhancer at some of the highest levels in the myeloma epigenome. These data implicate IgL translocation as a driver of poor prognosis which may be due to IMiD resistance.

Multiple myeloma is frequently characterised by translocation of genes next to the immunoglobulin heavy chain locus. In this study, the authors sequence a large cohort of high risk myeloma samples and find translocations of cMyc to the immunoglobulin heavy chain locus and this is associated with poor prognosis.

Oligoclonal T Cells Transiently Expand and Express Tim-3 and PD-1 Following Anti-CD19 CAR T Cell Therapy: A Case Report

Clinical trials of chimeric antigen receptor (CAR) T cells in hematologic malignancy associate remissions with two profiles of CAR T cell proliferation kinetics, which differ based upon costimulatory domain. Additional T cell intrinsic factors that influence or predict clinical response remain unclear. To address this gap, we report the case of a 68-year-old woman with refractory/relapsed diffuse large B cell lymphoma (DLBCL), treated with tisagenlecleucel (anti-CD19), with a CD137 costimulatory domain (4-1BB) on an investigational new drug application (#16944). For two months post-infusion, the patient experienced dramatic regression of subcutaneous nodules of DLBCL. Unfortunately, her CAR T exhibited kinetics unassociated with remission, and she died of DLBCL-related sequelae. Serial phenotypic analysis of peripheral blood alongside sequencing of the β-peptide variable region of the T cell receptor (TCRβ) revealed distinct waves of oligoclonal T cell expansion with dynamic expression of immune checkpoint molecules. One week prior to CAR T cell contraction, T cell immunoglobulin mucin domain 3 (Tim-3) and programmed cell death protein 1 (PD-1) exhibited peak expressions on both the CD8 T cell (Tim-3 ≈ 50%; PD-1 ≈ 17%) and CAR T cell subsets (Tim-3 ≈ 78%; PD-1 ≈ 40%). These correlative observations draw attention to Tim-3 and PD-1 signaling pathways in context of CAR T cell exhaustion.

Flt3L Treatment of Bone Marrow Donors Increases Graft Plasmacytoid Dendritic Cell Content and Improves Allogeneic Transplantation Outcomes

A higher number of donor plasmacytoid dendritic cells (pDCs) is associated with increased survival and reduced graft-versus-host disease (GVHD) in human recipients of unrelated donor bone marrow (BM) grafts, but not granulocyte colony-stimulating factor (G-CSF)-mobilized peripheral blood grafts. We show that in murine models, donor BM pDCs are associated with increased survival and decreased GVHD compared with G-CSF-mobilized pDCs. To increase the content of pDCs in BM grafts, we studied the effect of FMS-like tyrosine kinase 3 ligand (Flt3L) treatment of murine BM donors on transplantation outcomes. Flt3L treatment (300 μg/kg/day) resulted in a schedule-dependent increase in the content of pDCs in the BM. Mice treated on days -4 and -1 had a >5-fold increase in pDC content without significant changes in numbers of HSCs, T cells, B cells, and natural killer cells in the BM graft. In an MHC-mismatched murine transplant model, recipients of Flt3L-treated T cell-depleted (TCD) BM (TCD F-BM) and cytokine-untreated T cells had increased survival and decreased GVHD scores with fewer Th1 and Th17 polarized T cells post-transplantation compared with recipients of equivalent numbers of untreated donor TCD BM and T cells. Gene array analyses of pDCs from Flt3L-treated human and murine donors showed up-regulation of adaptive immune pathways and immunoregulatory checkpoints compared with pDCs from untreated BM donors. Transplantation of TCD F-BM plus T cells resulted in no loss of the graft-versus-leukemia (GVL) effect compared with grafts from untreated donors in 2 murine GVL models. Thus, Flt3L treatment of BM donors is a novel method for increasing the pDC content in allografts, improving survival, and decreasing GVHD without diminishing the GVL effect.

Is a 500-Cell Count Necessary for Bone Marrow Differentials?: A Proposed Analytical Method for Validating a Lower Cutoff

OBJECTIVES

By convention, 500 cells are counted for bone marrow aspirate differentials. Evidence supporting such a cutoff is lacking. We hypothesized that 300-cell counts could be sufficient.

METHODS

Cell count results from 165 cases, for which values were recorded at 300 and 500 cells, were analyzed. We tested for statistical differences and changes in diagnostic classification between the two cutoffs.

RESULTS

Three hundred cell counts did not produce diagnostically different results, particularly for myeloblasts and plasma cells, where cell percentages are critical for disease classification. Method comparison analysis did not reach statistical significance for any cell type when comparing the two methods. Bias plots showed narrow, even spread about the mean bias. Contingency table analysis yielded no significant diagnostic discrepancies.

CONCLUSIONS

Performing differential counts on 300 cells would produce clinically and statistically similar results to 500 cells. Reducing the cell number counted has potential cost/labor reductions without affecting quality of care.

Diagnosis of GATA2 haplo-insufficiency in a young woman prompted by pancytopenia with deficiencies of B-cell and dendritic cell development

BACKGROUND

GATA2 deficiency presents with a spectrum of phenotypes including increased susceptibility to viral and bacterial infections, multi-lineage cytopenias, aplastic anemia, leukemic transformation and lymphedema. Allogeneic transplantation is only curative therapy for GATA2 deficiency, but is associated with significant treatment related morbidity and mortality. Given the spectrum of clinical presentation, accurate diagnosis of GATA2 deficiency is necessary to identify patients early in their disease course when allogeneic bone marrow transplantation may be of clinical benefit.

CASE PRESENTATION

In this report, we present a GATA2 mutation diagnosed in 23-year-old woman presenting with pancytopenia, recurring oral blisters, fatigue and chronic pain. We describe markedly low levels of mature B-cells in the blood and bone marrow and the absence of detectable blood dendritic cells with normal serum immunoglobulin levels and normal numbers of marrow plasma cells. She was ultimately diagnosed with GATA2 haplo-insufficiency due to a GATA2 germ-line mutation and underwent a successful allogeneic bone marrow transplant from a 10/10 HLA matched unrelated donor.

CONCLUSIONS

The case illustrates the diagnostic difficulties in identifying GATA2 deficiencies and the importance of family history and genetic testing. GATA2 plays an important role in B-cell and dendritic cell development, and decreased numbers of those cells is a characteristic feature that should prompt consideration of GATA2 deficiency in a patient with pancytopenia. Maturation of B-cells to long-lived plasma cells is relatively unaffected in GATA2 deficiency. Allogeneic stem cell transplantation can correct immune-deficiencies and prevent leukemic transformation in patients with GATA2 deficiency.

Informatics Approaches to Address New Challenges in the Classification of Lymphoid Malignancies

Purpose

Lymphoid malignancies are remarkably heterogeneous, with variations in outcomes and clinical, biologic, and histologic presentation complicating classification according to the World Health Organization guidelines. Incorrect classification of lymphoid neoplasms can result in suboptimal therapeutic strategies for individual patients and confound the interpretation of clinical trials involving personalized, class-based treatments. This review discusses the potential role of pathology informatics in improving the classification accuracy and objectivity for lymphoid malignancies.

Design

We identified peer-reviewed publications examining pathology informatics approaches for the classification of lymphoid malignancies, reviewed developments in the lymphoma classification systems, and summarized computational methods for pathologic assessment that can impact practice.

Results

Computer-assisted pathology image analysis algorithms in lymphoma most commonly have been applied to follicular lymphoma to address biologic heterogeneity and subjectivity in the process of classification.

Conclusion

Objective methods are available to assist pathologists in lymphoma classification and grading, and have been demonstrated to provide measurable benefits in specific contexts. Future validation and extension of these approaches will require datasets that link high resolution pathology images available for image analysis algorithms with clinical variables and follow up outcomes.

Bortezomib-induced heat shock response protects multiple myeloma cells and is activated by heat shock factor 1 serine 326 phosphorylation

Proteasome inhibitors such as bortezomib are highly active in multiple myeloma by affecting signaling cascades and leading to a toxic buildup of misfolded proteins. Bortezomib-treated cells activate the cytoprotective heat shock response (HSR), including upregulation of heat shock proteins (HSPs). Here we inhibited the bortezomib-induced HSR by silencing its master regulator, Heat Shock Factor 1 (HSF1). HSF1 silencing led to bortezomib sensitization. In contrast, silencing of individual and combination HSPs, except HSP40β, did not result in significant bortezomib sensitization. However, HSP40β did not entirely account for increased bortezomib sensitivity upon HSF1 silencing. To determine the mechanism of HSF1 activation, we assessed phosphorylation and observed bortezomib-inducible phosphorylation in cell lines and patient samples. We determined that this bortezomib-inducible event is phosphorylation at serine 326. Prior clinical use of HSP inhibitors in combination with bortezomib has been disappointing in multiple myeloma therapy. Our results provide a rationale for targeting HSF1 activation in combination with bortezomib to enhance multiple myeloma treatment efficacy.

A Mimic of Posttransplant Lymphoproliferative Disease Following Liver Transplant

Generalized lymphadenopathy after organ transplant is a concerning finding, often indicating the devel-opment of lymphoma. We describe a 52-year-old liver transplant recipient who had clinical symptoms and imaging concerning for posttransplant lymphoproliferative disease. However, histologic evaluation of a lymph node biopsy revealed that the patient actually had a much rarer but relatively benign condition, Kikuchi-Fujimoto disease (histiocytic necrotizing lymphadenitis). We discuss the epidemiology, clinical symptoms, diagnosis, histologic features, and treatment of this uncommon mimic of posttransplant lymphoproliferative disease.

PD-1 and CTLA-4 up regulation on donor T cells is insufficient to prevent GvHD in allo-HSCT recipients

The expression of checkpoint blockade molecules PD-1, PD-L1, CTLA-4, and foxp3+CD25+CD4+ T cells (Tregs) regulate donor T cell activation and graft-vs-host disease (GvHD) in allogeneic hematopoietic stem cell transplant (allo-HSCT). Detailed kinetics of PD-1-, CTLA-4-, and PD-L1 expression on donor and host cells in GvHD target organs have not been well studied. Using an established GvHD model of allo-HSCT (B6 → CB6F1), we noted transient increases of PD-1- and CTLA-4-expressing donor CD4+ and CD8+ T cells on day 10 post transplant in spleens of allo-HSCT recipients compared with syngeneic HSCT (syn-HSCT) recipients. In contrast, expression of PD-1- and CTLA-4 on donor T cells was persistently increased in bone marrow (BM) of allo-HSCT recipients compared with syn-HSCT recipients. Similar differential patterns of donor T cell immune response were observed in a minor histocompatibility (miHA) mismatched transplant model of GvHD. Despite higher PD-1 and CTLA-4 expression in BM, numbers of foxp3+ T cells and Tregs were much lower in allo-HSCT recipients compared with syn-HSCT recipients. PD-L1-expressing host cells were markedly decreased concomitant with elimination of residual host hematopoietic elements in spleens of allo-HSCT recipients. Allo-HSCT recipients lacking PD-L1 rapidly developed increased serum inflammatory cytokines and lethal acute GvHD compared with wild-type (WT) B6 allo-HSCT recipients. These data suggest that increased expression of checkpoint blockade molecules PD-1 and CTLA-4 on donor T cells is not sufficient to prevent GvHD, and that cooperation between checkpoint blockade signaling by host cells and donor Tregs is necessary to limit GvHD in allo-HSCT recipients.

Multimodality Technologies in the Assessment of Hematolymphoid Neoplasms

Accurate assessment of tissues for hematolymphoid neoplasms requires an integrated multiparameter approach. Although morphologic examination by light microscopy remains the mainstay of initial assessment for hematolymphoid neoplasms, immunophenotypic analysis by immunohistochemistry and/or flow cytometry is essential to determine the pattern of differentiation and to detect minimal disease when morphology is inconclusive. In some cases, immunophenotypic analysis provides additional information for targeted immunotherapy and prognostication. Genotypic studies, including cytogenetics, fluorescence in situ hybridization, DNA microarray, polymerase chain reaction, and/or next-generation sequencing, are also imperative for subclassification of the genetically defined disease entities in the current World Health Organization classification of hematolymphoid neoplasms. Moreover, genotypic studies can establish clonality, stratify patients to determine appropriate treatment, and monitor patients for treatment response.

Identification of human plasma cells with a lamprey monoclonal antibody

Ab-producing plasma cells (PCs) serve as key participants in countering pathogenic challenges as well as being contributors to autoimmune and malignant disorders. Thus far, only a limited number of PC-specific markers have been identified. The characterization of the unique variable lymphocyte receptor (VLR) Abs that are made by evolutionarily distant jawless vertebrates prompted us to investigate whether VLR Abs could detect novel PC antigens that have not been recognized by conventional Abs. Here, we describe a monoclonal lamprey Ab, VLRB MM3, that was raised against primary multiple myeloma cells. VLRB MM3 recognizes a unique epitope of the CD38 ectoenzyme that is present on plasmablasts and PCs from healthy individuals and on most, but not all, multiple myelomas. Binding by the VLRB MM3 Ab coincides with CD38 dimerization and NAD glycohydrolase activity. Our data demonstrate that the lamprey VLRB MM3 Ab is a unique reagent for the identification of plasmablasts and PCs, with potential applications in the diagnosis and therapeutic intervention of PC or autoimmune disorders.

Successful treatment of severe immune hemolytic anemia after allogeneic stem cell transplantation with bortezomib: report of a case and review of literature

BACKGROUND

Immune hemolytic anemia is a well-known complication after allogeneic hematopoietic stem cell transplantation (HSCT). Posttransplant hemolytic anemia results in increased red blood cell transfusions and medical sequelae including iron overload.

CASE REPORT

We present a case report of immune hemolytic anemia that occurred after allogeneic HSCT from an ABO major-mismatched, HLA-matched unrelated donor. The patient had high anti-donor A type antibodies that were unresponsive to treatment with steroids and rituximab, resulting in persistent transfusion dependence. A detailed time course of anti-A titers, plasma cell content of the marrow, and B-cell content of the blood is presented. Treatment with bortezomib, a protease inhibitor, eliminated residual host-type plasma cells secreting anti-A and restored normal donor-derived erythropoiesis.

CONCLUSION

This report, and a review of literature for treatment of immune hemolytic anemia after allogeneic HSCT, supports the utility of bortezomib as plasma cell-targeted therapy in this setting.

DNA methylation profiling in human B cells reveals immune regulatory elements and epigenetic plasticity at Alu elements during B-cell activation

Memory is a hallmark of adaptive immunity, wherein lymphocytes mount a superior response to a previously encountered antigen. It has been speculated that epigenetic alterations in memory lymphocytes contribute to their functional distinction from their naive counterparts. However, the nature and extent of epigenetic alterations in memory compartments remain poorly characterized. Here we profile the DNA methylome and the transcriptome of B-lymphocyte subsets representing stages of the humoral immune response before and after antigen exposure in vivo from multiple humans. A significant percentage of activation-induced losses of DNA methylation mapped to transcription factor binding sites. An additional class of demethylated loci mapped to Alu elements across the genome and accompanied repression of DNA methyltransferase 3A. The activation-dependent DNA methylation changes were largely retained in the progeny of activated B cells, generating a similar epigenetic signature in downstream memory B cells and plasma cells with distinct transcriptional programs. These findings provide insights into the methylation dynamics of the genome during cellular differentiation in an immune response.

Examining racial differences in diffuse large B-cell lymphoma presentation and survival

We performed a retrospective cohort analysis of 701 (533 white and 144 black) patients with diffuse large B-cell lymphoma (DLBCL) treated at two referral centers in southern United States between 1981 and 2010. Median age of diagnosis for blacks was 50 years vs. 57 years for whites (p < 0.001). A greater percentage of blacks presented with elevated lactate dehydrogenase levels, B-symptoms and performance status ≥ 2. More whites (8%) than blacks (3%) had a positive family history of lymphoma (p = 0.048). There were no racial differences in the use of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone; 52% black vs. 47% white, p = 0.73). While black race predicted worse survival among patients treated with CHOP (hazard ratio [HR] 1.8, p < 0.001), treatment with R-CHOP was associated with improved survival irrespective of race (HR 0.61, p = 0.01). Future studies should examine biological differences that may underlie the observed racial differences in presentation and outcome.

Certification and role of local pathologists for diffuse large B-cell lymphoma (DLBCL) subtyping and eligibility determination in the phase II PYRAMID study

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Background: The role of local pathologists in promoting patient (pt) accrual and evaluating eligibility criteria involving a complicated immunohistochemical (IHC) algorithm has rarely been investigated. The phase II PYRAMID trial (NCT00931918) is assessing R-CHOP ± bortezomib for newly diagnosed pts with non-germinal-center B-cell (non-GCB) subtype DLBCL. In this trial, local pathologists were encouraged to perform DLBCL subtyping at the point of biopsy, identify suitable pts for the trial, and facilitate accrual. Methods: Determination of GCB vs non-GCB subtype is per the Hans method, an algorithm based on IHC for CD10, BCL-6, and IRF4/MUM1. In stage 1, pathologists demonstrated IHC subtyping proficiency by evaluating a tissue microarray (TMA) of 12 DLBCL cases; those with ≥80% of samples in agreement with central lab results were certified for determining trial eligibility. In stage 2, to broaden participation, pathologist certification occurred via teleconference outlining trial eligibility criteria, tissue subtyping requirements, and determining pathologists’ experience with the Hans method. Results: 182 pathologists have been certified for local subtyping, 50 via TMA and 132 by teleconference. 66/88 active study sites have ≥1 certified pathologist. Only 1 of the 10 top enrolling sites lacks a certified pathologist. 52% (84/162) of pts have been enrolled based on local pathologist subtyping prior to central lab confirmation. Discordance with central lab results occurred in 9/84 cases (11%). Enrollment rates pre- and post-local pathologist certification were 0.053 and 0.096 pts/site/month; an improvement of 81%. Trial accrual correlates with the presence of a certified local pathologist (p=0.0026). The rate of ineligible GCB cases sent for central lab testing was lower from sites with a certified pathologist (23% [69/299 cases] vs 38% [40/106 cases] for sites without). Conclusions: Engagement of local pathologists in trials requiring pathology selection can significantly improve accrual. This study demonstrates the effectiveness of various training modalities in improving selection by local pathologists using a complex IHC algorithm. Clinical trial information: NCT00931918.

Characteristics and outcomes of diffuse large B-cell lymphoma presenting in leukaemic phase

Diffuse large B-cell lymphoma (DLBCL) occasionally presents with circulating malignant cells. The clinical characteristics and long-term outcomes of these patients have not been described. Twenty-nine newly diagnosed DLBCL presenting in leukaemic phase were identified between 1996 and 2010, at two institutions. Median age was 48 years, and patients presented with leucocytosis, high lactate dehydrogenase levels, B symptoms, and high International Prognostic Index score. Extra nodal site involvement was observed in all patients and affected the bone marrow (100%), spleen (62%), pleura/lung (41%), liver (21%), bone (17%), bowels (7%) and cerebrospinal fluid (14%). Blood lymphomatous cells co-expressed CD19, CD20, CD22, CD38, CD45, HLA-DR and FMC7 in >90%, and kappa or lambda light chain restriction in >50%. Ninety per cent received rituximab and anthracycline-based chemotherapy. Overall, remission was complete in 54% and partial in 31%; 15% had resistant disease. Median follow-up was 47 months; 13 (45%) patients remain alive in complete remission. Median progression-free and overall survivals were 11·5 and 46·7 months, respectively. In summary, patients with DLBCL in leukaemic phase present with high tumour burden and frequent involvement of extra nodal sites. In this uncommon DLBCL subgroup, anthracycline-based regimens with rituximab are associated with early morbidity and mortality, but yield approximately 50% 4-year survival.

Flagellin, a TLR5 agonist, reduces graft-versus-host disease in allogeneic hematopoietic stem cell transplantation recipients while enhancing antiviral immunity

Graft-versus-host disease (GVHD) is a major cause of morbidity and mortality in patients treated with allogeneic hematopoietic stem cell transplantation (HSCT). Posttransplant immunosuppressive drugs incompletely control GVHD and increase susceptibility to opportunistic infections. In this study, we used flagellin, a TLR5 agonist protein (∼50 kDa) extracted from bacterial flagella, as a novel experimental treatment strategy to reduce both acute and chronic GVHD in allogeneic HSCT recipients. On the basis of the radioprotective effects of flagellin, we hypothesized that flagellin could ameliorate GVHD in lethally irradiated murine models of allogeneic HSCT. Two doses of highly purified flagellin (administered 3 h before irradiation and 24 h after HSCT) reduced GVHD and led to better survival in both H-2(b) → CB6F1 and H-2(K) → B6 allogeneic HSCT models while preserving >99% donor T cell chimerism. Flagellin treatment preserved long-term posttransplant immune reconstitution characterized by more donor thymic-derived CD4(+)CD25(+)Foxp3(+) regulatory T cells and significantly enhanced antiviral immunity after murine CMV infection. The proliferation index and activation status of donor spleen-derived T cells and serum concentration of proinflammatory cytokines in flagellin-treated recipients were reduced significantly within 4 d posttransplant compared with those of the PBS-treated control recipients. Allogeneic transplantation of radiation chimeras previously engrafted with TLR5 knockout hematopoietic cells showed that interactions between flagellin and TLR5 expressed on both donor hematopoietic and host nonhematopoietic cells were required to reduce GVHD. Thus, the peritransplant administration of flagellin is a novel therapeutic approach to control GVHD while preserving posttransplant donor immunity.

DNA methylation prevents CTCF-mediated silencing of the oncogene BCL6 in B cell lymphomas

Aberrant DNA methylation commonly occurs in cancer cells where it has been implicated in the epigenetic silencing of tumor suppressor genes. Additional roles for DNA methylation, such as transcriptional activation, have been predicted but have yet to be clearly demonstrated. The BCL6 oncogene is implicated in the pathogenesis of germinal center-derived B cell lymphomas. We demonstrate that the intragenic CpG islands within the first intron of the human BCL6 locus were hypermethylated in lymphoma cells that expressed high amounts of BCL6 messenger RNA (mRNA). Inhibition of DNA methyltransferases decreased BCL6 mRNA abundance, suggesting a role for these methylated CpGs in positively regulating BCL6 transcription. The enhancer-blocking transcription factor CTCF bound to this intronic region in a methylation-sensitive manner. Depletion of CTCF by short hairpin RNA in neoplastic plasma cells that do not express BCL6 resulted in up-regulation of BCL6 transcription. These data indicate that BCL6 expression is maintained during lymphomagenesis in part through DNA methylation that prevents CTCF-mediated silencing.

The role of CD11c expression in the diagnosis of mantle cell lymphoma

Flow cytometric immunophenotyping (FCI) aids in the differentiation of chronic lymphocytic leukemia (CLL) from mantle cell lymphoma (MCL); however, overlapping phenotypes may occur. CD11c expression has been reported in up to 90% of CLL cases but has rarely been reported in MCL. Whether CD11c can be used to exclude MCL has not been directly addressed. FCI reports were reviewed for 90 MCL cases (44 patients) and 355 CLL/small lymphocytic lymphoma (SLL) cases (158 patients). MCL cases were confirmed by cyclin D1 immunoreactivity and/or t(11;14) detection by karyotyping or fluorescence in situ hybridization. Cases with typical MCL immunophenotypes did not express CD11c. The 2 MCL cases displaying dim CD11c positivity (2 of 44 patients) expressed other markers not typical of MCL. CD11c was detected in 96 (27.0%) of 355 cases of CLL/SLL representing 53 of 158 patients. CD11c expression is rare in MCL and may aid in differentiation of CD5+ B-cell neoplasms, particularly when small samples limit further ancillary testing.

Activation, immune polarization, and graft-versus-leukemia activity of donor T cells are regulated by specific subsets of donor bone marrow antigen-presenting cells in allogeneic hemopoietic stem cell transplantation

We investigated the roles of specific subsets of donor APCs purified from bone marrow in donor T cell activation and graft-vs-leukemia (GvL) activity in murine models of hemopoietic stem cell transplantation. Lineage(-)CD11c(+) APC precursors were separated from donor bone marrow based on expression of CD11b. Transplanting lineage(-)CD11c(+)CD11b(-) APC (CD11b(-) APC) in combination with c-kit(+)Sca-1(+)lineage(-) hemopoietic stem cells (HSC) and congenic donor T cells led to increased donor CD4(+) and CD8(+) T cell proliferation and higher donor T cell chimerism than with transplanting grafts containing HSC, T cells, and lineage(-)CD11c(+)CD11b(+) APCs (CD11b(+) APC), or grafts containing only HSC and T cells. Transplanting CD11b(-) APCs induced Th1/type 1 cytotoxic T lymphocyte donor T cell immune polarization and enhanced GvL activity of donor T cells without increased graft-vs-host disease in both MHC- and minor histocompatibility Ag-mismatched murine hemopoietic stem cell transplantation models, whereas CD11b(+) APCs led to Th2/type 2 cytotoxic T lymphocyte donor T cell immune polarization. Donor CD11b(-) APCs were plasmacytoid dendritic cell progenitors (>90% CD317; PDCA-1(+)) and up-regulated CD80, CD86, and IL-12 during alloantigen presentation, whereas CD11b(+) APCs expressed Gr-1 and up-regulated expression of programmed death ligands-1 and 2 after activation. These results are the first to show that manipulation of the content of donor APCs in allogeneic HSC grafts can regulate donor T cell immunity and enhance GvL without increasing graft-vs-host disease activity.

Functional interaction of plasmacytoid dendritic cells with multiple myeloma cells: a therapeutic target

Multiple myeloma (MM) remains incurable despite novel therapies, suggesting the need for further identification of factors mediating tumorigenesis and drug resistance. Using both in vitro and in vivo MM xenograft models, we show that plasmacytoid dendritic cells (pDCs) in the bone marrow (BM) microenvironment both mediate immune deficiency characteristic of MM and promote MM cell growth, survival, and drug resistance. Microarray, cell signaling, cytokine profile, and immunohistochemical analysis delineate the mechanisms mediating these sequelae. Although pDCs are resistant to novel therapies, targeting toll-like receptors with CpG oligodeoxynucleotides both restores pDC immune function and abrogates pDC-induced MM cell growth. Our study therefore validates targeting pDC-MM interactions as a therapeutic strategy to overcome drug resistance in MM.

A new immunostain algorithm classifies diffuse large B-cell lymphoma into molecular subtypes with high accuracy

PURPOSE

Hans and coworkers previously developed an immunohistochemical algorithm with approximately 80% concordance with the gene expression profiling (GEP) classification of diffuse large B-cell lymphoma (DLBCL) into the germinal center B-cell-like (GCB) and activated B-cell-like (ABC) subtypes. Since then, new antibodies specific to germinal center B-cells have been developed, which might improve the performance of an immunostain algorithm.

EXPERIMENTAL DESIGN

We studied 84 cases of cyclophosphamide-doxorubicin-vincristine-prednisone (CHOP)-treated DLBCL (47 GCB, 37 ABC) with GCET1, CD10, BCL6, MUM1, FOXP1, BCL2, MTA3, and cyclin D2 immunostains, and compared different combinations of the immunostaining results with the GEP classification. A perturbation analysis was also applied to eliminate the possible effects of interobserver or intraobserver variations. A separate set of 63 DLBCL cases treated with rituximab plus CHOP (37 GCB, 26 ABC) was used to validate the new algorithm.

RESULTS

A new algorithm using GCET1, CD10, BCL6, MUM1, and FOXP1 was derived that closely approximated the GEP classification with 93% concordance. Perturbation analysis indicated that the algorithm was robust within the range of observer variance. The new algorithm predicted 3-year overall survival of the validation set [GCB (87%) versus ABC (44%); P < 0.001], simulating the predictive power of the GEP classification. For a group of seven primary mediastinal large B-cell lymphoma, the new algorithm is a better prognostic classifier (all "GCB") than the Hans' algorithm (two GCB, five non-GCB).

CONCLUSION

Our new algorithm is significantly more accurate than the Hans' algorithm and will facilitate risk stratification of DLBCL patients and future DLBCL research using archival materials.

Neutropenia in a patient treated with ipilimumab (anti-CTLA-4 antibody)

A 42-year-old white woman with a diagnosis of metastatic melanoma developed severe neutropenia during treatment with ipilimumab (anticytotoxic T-lymphocyte-associated antigen-4 antibody). Bone marrow aspiration and biopsy specimens revealed marked myeloid hypoplasia, with unremarkable erythropoiesis and megakaryopoiesis. The patient's neutropenia did not respond to therapy with a combination of colony stimulating factors and steroids; however, it rapidly improved after administration of intravenous immunoglobulin. Treatment with ipilimumab has not been reported to be associated with hematologic toxicities, and to our knowledge, no case of neutropenia has previously been reported. This report of acute grade 4 neutropenia associated with ipilimumab and clinically consistent with an autoimmune process emphasizes the importance of monitoring complete blood count during treatment with this new monoclonal antibody.

The Mi-2/NuRD complex associates with pericentromeric heterochromatin during S phase in rapidly proliferating lymphoid cells

Chromosomal replication results in the duplication not only of DNA sequence but also of the patterns of histone modification, DNA methylation, and nucleoprotein structure that constitute epigenetic information. Pericentromeric heterochromatin in human cells is characterized by unique patterns of histone and DNA modification. Here, we describe association of the Mi-2/NuRD complex with specific segments of pericentromeric heterochromatin consisting of Satellite II/III DNA located on human chromosomes 1, 9, and 16 in some but not all cell types. This association is linked in part to DNA replication and chromatin assembly and may suggest a role in these processes. Mi-2/NuRD accumulation is independent of Polycomb association and is characterized by a unique pattern of histone modification. We propose that Mi-2/NuRD constitutes an enzymatic component of a pathway for assembly and maturation of chromatin utilized by rapidly proliferating lymphoid cells for replication of constitutive heterochromatin.

Rational identification of a novel peptide for targeting nanocarriers to 9L glioma

Traditional therapies for high grade gliomas are limited in part by collateral damage to normal tissues. Selective delivery of therapies to tumors is, therefore, needed. Here, we report that liposomal nanocarriers coated with a novel oligopeptide enhance uptake by 9L gliosarcoma. A targeting nine amino acid peptide sequence (RSI) was identified by differential panning of random peptide phage display libraries on 9L cells and rat blood cells and plasma. Peptides were coupled to the surface of liposomal nanocarriers which were subsequently loaded with doxorubicin. The ability of RSI coated liposomes to facilitate drug uptake and cytotoxicity was compared with conventional liposomal nanocarriers and controls. In addition, plasma clearance profiles of the RSI peptide coupled liposomal nanocarriers were evaluated in adult immuno-competent rats. RSI peptide-coupled liposomal nanocarriers enhanced drug uptake by 9L cells by 500% compared with conventional liposomal nanocarriers, and significantly increased cytotoxicity. The plasma half-lives confirmed that the presence of the RSI peptide on the liposomal nanocarriers did not compromise circulation time in the blood in comparison with Stealth liposomal nanocarriers. These data suggest that phage-identified oligopeptides could lead to the development of new tumor selective nanocarriers.

The BCL6-associated transcriptional co-repressor, MTA3, is selectively expressed by germinal centre B cells and lymphomas of putative germinal centre derivation

Metastasis-associated protein 3 (MTA3) is a recently described cell-type specific component of the Mi-2-NURD transcriptional co-repressor complex that is expressed in breast epithelia and germinal centre B cells. In model B cell lines, MTA3 physically interacts with BCL6 and appears to be instrumental in maintenance of the germinal centre B cell transcriptional programme that precludes premature plasmacytic differentiation. Here, we report selective, in situ cell-type specific expression of MTA3 among lymphoid cells largely confined to the germinal centre B cell compartment. Centroblasts display greater expression than smaller, less proliferative centrocytes, with undetectable expression in quiescent plasma cells. Among B cell neoplasms, germinal centre B cell-like lymphomas likewise exhibit selective expression that generally escalates with increasing proliferative capacity. MTA3 protein expression was, in accord, highly predictive of the germinal centre B cell-like gene expression profile for diffuse large B cell lymphomas. Lastly, relative repression of a subset of known BCL6 targets, including BLIMP1 and p27kip1, was highest in diffuse large B cell lymphomas that co-expressed both MTA3 and BCL6 protein. Together, these novel data suggest a role for MTA3 in BCL6-mediated lymphomagenesis in germinal centre B cell-like neoplasms.

Chronic GvHD decreases antiviral immune responses in allogeneic BMT

Chronic graft-versus-host disease (cGvHD) is associated with functional immunodeficiency and an increased risk of opportunistic infections in allogeneic bone marrow transplantation (BMT). We used a parent to F1 model of allogeneic BMT to test the hypothesis that cGvHD leads to impaired antigen-specific antiviral immunity and compared BM transplant recipients with cGvHD to control groups of allogeneic BM transplant recipients without GvHD. Mice with and without cGvHD received a nonlethal dose of murine cytomegalovirus (MCMV) +100 days after transplantation. Recipients with cGvHD had more weight loss and higher viral loads in the spleen and liver. MCMV infection led to greater than 25-fold expansion of donor spleen-derived MCMV peptide-specific tetramer-positive CD8(+) T cells in blood of transplant recipients with and without cGvHD, but mice with cGvHD had far fewer antigen-specific T cells in peripheral tissues and secondary lymphoid organs. The immunosuppression associated with cGvHD was confirmed by vaccinating transplant recipients with and without cGvHD using a recombinant Listeria expressing MCMV early protein (Lm-MCMV). Secondary adoptive transfer of lymphocytes from donor mice with or without cGvHD into lymphopenic congenic recipients showed that cGvHD impaired tissue-specific homing of antigen-specific T cells. These results indicate that cGvHD causes an intrinsic immunosuppression and explain, in part, the functional immunodeficiency in allogeneic transplant recipients.