scholarly journals A Single-Cell Transcriptome Profiling of Anterior Kidney Leukocytes From Nile Tilapia (Oreochromis niloticus)

2021 ◽  
Vol 12 ◽  
Author(s):  
Liting Wu ◽  
Along Gao ◽  
Lan Li ◽  
Jianlin Chen ◽  
Jun Li ◽  
...  
Keyword(s):  
T Cells ◽  
B Cells ◽  
B Cell ◽  
Single Cell ◽  
Nile Tilapia ◽  
Immune Cell ◽  
Cell Types ◽  
Cell Transcriptome ◽  
B Cell Subsets ◽  
Single Cell Transcriptome

Teleost fish anterior kidney (AK) is an important hematopoietic organ with multifarious immune cells, which have immune functions comparable to mammalian bone marrow. Myeloid and lymphoid cells locate in the AK, but the lack of useful specific gene markers and antibody-based reagents for the cell subsets makes the identification of the different cell types difficult. Single-cell transcriptome sequencing enables single-cell capture and individual library construction, making the study on the immune cell heterogeneity of teleost fish AK possible. In this study, we examined the transcriptional patterns of 11,388 AK leukocytes using 10× Genomics single-cell RNA sequencing (scRNA-seq). A total of 22 clusters corresponding to five distinct immune cell subsets were identified, which included B cells, T cells, granulocytes, macrophages, and dendritic cells (DCs). However, the subsets of myeloid cells (granulocytes, macrophages, and DCs) were not identified in more detail according to the known specific markers, even though significant differences existed among the clusters. Thereafter, we highlighted the B-cell subsets and identified them as pro/pre B cells, immature/mature B cells, activated B/plasmablasts, or plasma cells based on the different expressions of the transcription factors (TFs) and cytokines. Clustering of the differentially modulated genes by pseudo-temporal trajectory analysis of the B-cell subsets showed the distinct kinetics of the responses of TFs to cell conversion. Moreover, we classified the T cells and discovered that CD3+CD4−CD8−, CD3+CD4+CD8+, CD4+CD8−, and CD4−CD8+ T cells existed in AK, but neither CD4+CD8− nor CD4−CD8+ T cells can be further classified into subsets based on the known TFs and cytokines. Pseudotemporal analysis demonstrated that CD4+CD8− and CD4−CD8+ T cells belonged to different states with various TFs that might control their differentiation. The data obtained above provide a valuable and detailed resource for uncovering the leukocyte subsets in Nile tilapia AK, as well as more potential markers for identifying the myeloid and lymphoid cell types.

scholarly journals Selective Targeting of T and B Cell Populations by Alemtuzumab in the Treatment of Multiple Sclerosis

2017 ◽  
Vol 12 (02) ◽  
pp. 78
Author(s):  
Nikolaos C Grigoriadis ◽  
Keyword(s):  
Multiple Sclerosis ◽  
T Cells ◽  
B Cells ◽  
B Cell ◽  
Cell Types ◽  
Tolerability Profile ◽  
T And B Cells ◽  
Brain Volume Loss ◽  
Inflammatory Phenotype ◽  
B Cell Subsets

Upstream targeting of both T and B cells is a rational therapeutic approach in multiple sclerosis (MS) in view of how both cell types and the interaction between them contribute to MS pathophysiology. This article will discuss this new way of thinking in MS: the targeting of both T and B cells, with a focus on the recently developed therapy, alemtuzumab (Lemtrada®, Genzyme, UK). Alemtuzumab depletes T and B lymphocytes, mainly via complement-dependent cytolysis and antibody-dependent cytolysis; depletion of B cells is not an enduring effect compared with the depletion of T cells. After dosing, CD4+ and CD8+ T cells and CD19 B cells decrease initially but increase over the following 11 months. During repopulation after alemtuzumab treatment, there is a shift in the relative proportions of T cell and B cell subsets whereby proportions of regulatory T cells and memory-phenotype T cells are increased and the proportion of naive T cells is decreased. A switch from a pro- to an anti-inflammatory phenotype and cytokine profile caused by alemtuzumab may underpin the long-lasting suppression of MS activity that has been observed in clinical trials. Alemtuzumab treatment is also associated with a consistently good safety and tolerability profile. Further, alemtuzumab appears to promote neurorehabilitation by improving measures of physical functioning, disability, measures of quality of life, and brain volume loss. Alemtuzumab therefore has the potential to reduce disease burden and improve substantially the prognosis for patients with MS.

scholarly journals Immune Cell Profiling of COVID-19 Patients in the Recovery Stage by Single-Cell Sequencing

2020 ◽  
Author(s):  
Wen Wen ◽  
Wenru Su ◽  
Hao Tang ◽  
Wenqing Le ◽  
Xiaopeng Zhang ◽  
...  
Keyword(s):  
T Cells ◽  
B Cells ◽  
B Cell ◽  
Single Cell ◽  
Hospital Discharge ◽  
Immune Cell ◽  
Cell Receptor ◽  
B Cell Receptor ◽  
Early Recovery ◽  
Recovery Stage

AbstractCOVID-19, caused by SARS-CoV-2, has recently affected over 300,000 people and killed more than 10,000. The manner in which the key immune cell subsets change and their states during the course of COVID-19 remain unclear. Here, we applied single-cell technology to comprehensively characterize transcriptional changes in peripheral blood mononuclear cells during the recovery stage of COVID-19. Compared with healthy controls, in patients in the early recovery stage (ERS) of COVID-19, T cells decreased remarkably, whereas monocytes increased. A detailed analysis of the monocytes revealed that there was an increased ratio of classical CD14++ monocytes with high inflammatory gene expression as well as a greater abundance of CD14++IL1B+ monocytes in the ERS. CD4+ and CD8+ T cells decreased significantly and expressed high levels of inflammatory genes in the ERS. Among the B cells, the plasma cells increased remarkably, whereas the naïve B cells decreased. Our study identified several novel B cell-receptor (BCR) changes, such as IGHV3-23 and IGHV3-7, and confirmed isotypes (IGHV3-15, IGHV3-30, and IGKV3-11) previously used for virus vaccine development. The strongest pairing frequencies, IGHV3-23-IGHJ4, indicated a monoclonal state associated with SARS-CoV-2 specificity. Furthermore, integrated analysis predicted that IL-1β and M-CSF may be novel candidate target genes for inflammatory storm and that TNFSF13, IL-18, IL-2 and IL-4 may be beneficial for the recovery of COVID-19 patients. Our study provides the first evidence of an inflammatory immune signature in the ERS, suggesting that COVID-19 patients are still vulnerable after hospital discharge. Our identification of novel BCR signaling may lead to the development of vaccines and antibodies for the treatment of COVID-19.Highlights-The immune response was sustained for more than 7 days in the early recovery stage of COVID-19, suggesting that COVID-19 patients are still vulnerable after hospital discharge.-Single-cell analysis revealed a predominant subset of CD14++ IL1β+ monocytes in patients in the ERS of COVID-19.-Newly identified virus-specific B cell-receptor changes, such as IGHV3-23, IGHV3-7, IGHV3-15, IGHV3-30, and IGKV3-11, could be helpful in the development of vaccines and antibodies against SARS-CoV-2.-IL-1β and M-CSF were discovered as novel mediators of inflammatory cytokine storm, and TNFSF13, IL-2, IL-4, and IL-18 may be beneficial for recovery.

scholarly journals Dynamics of Adaptive Immune Cell and NK Cell Subsets in Patients With Ankylosing Spondylitis After IL-17A Inhibition by Secukinumab

2021 ◽  
Vol 12 ◽  
Author(s):  
Yutong Jiang ◽  
Mingcan Yang ◽  
Yanli Zhang ◽  
Yefei Huang ◽  
Jialing Wu ◽  
...  
Keyword(s):  
T Cells ◽  
Ankylosing Spondylitis ◽  
T Cell ◽  
B Cells ◽  
B Cell ◽  
Immune Cell ◽  
Nk Cell ◽  
Wilcoxon Test ◽  
Cell Distribution ◽  
B Cell Subsets

Background: Anti-IL-17A therapy is generally effectively applied in patients with Ankylosing Spondylitis (AS) to achieve and maintain remission. However, the influence of anti-IL-17A on the composition of the immune system is not apparent. Our prospective study was to explore the changes in immune imbalance regarding T cell, B cell and natural killer (NK) cell subsets after secukinumab treatment in AS patients.Methods: Immune cell distribution of 43 AS patients treated with secukinumab for 12 weeks and 47 healthy controls (HC) were evaluated. Flow cytometry using monoclonal antibodies against 25 surface markers was accomplished to explore the frequencies of lineage subsets. The differences between HC, AS pre-treatment, and post-treatment were compared using the paired Wilcoxon test, Mann-Whitney U test, and ANOVA.Results: AS patients had altered immune cell distribution regarding T cell and B cell subsets. Apart from activated differentiation of CD4+ T cell, CD8+ T cell and B cell, higher levels of cytotoxic T (Tc) two cells and Tc17 cells were noted in AS patients. We confirmed that helper T (Th) one cell became decreased; however, Th17 cells and T follicular helper (Tfh) 17 cells went increased in AS. After 12 weeks of secukinumab therapy, CRP and ASDAS became significantly decreased, and meanwhile, the proportions of Th1 cells, Tfh17 cells and classic switched B cells were changed towards those of HC. A decreased CRP was positively correlated with a decrease in the frequency of naïve CD8+ T cells (p = 0.039) and B cells (p = 0.007) after secukinumab treatment. An elevated level of T cells at baseline was detected in patients who had a good response to secukinumab (p = 0.005).Conclusion: Our study confirmed that AS patients had significant multiple immune cell dysregulation. Anti-IL-17A therapy (Secukinumab) could reverse partial immune cell imbalance.

scholarly journals Single-cell atlas of a non-human primate reveals new pathogenic mechanisms of COVID-19

2020 ◽  
Author(s):  
Lei Han ◽  
Xiaoyu Wei ◽  
Chuanyu Liu ◽  
Giacomo Volpe ◽  
Zhifeng Wang ◽  
...  
Keyword(s):  
Single Cell ◽  
Viral Entry ◽  
Immune Cell ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
List Type ◽  
Innate Immune Responses ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
Substantial Heterogeneity

ABSTRACTStopping COVID-19 is a priority worldwide. Understanding which cell types are targeted by SARS-CoV-2 virus, whether interspecies differences exist, and how variations in cell state influence viral entry is fundamental for accelerating therapeutic and preventative approaches. In this endeavor, we profiled the transcriptome of nine tissues from a Macaca fascicularis monkey at single-cell resolution. The distribution of SARS-CoV-2 facilitators, ACE2 and TMRPSS2, in different cell subtypes showed substantial heterogeneity across lung, kidney, and liver. Through co-expression analysis, we identified immunomodulatory proteins such as IDO2 and ANPEP as potential SARS-CoV-2 targets responsible for immune cell exhaustion. Furthermore, single-cell chromatin accessibility analysis of the kidney unveiled a plausible link between IL6-mediated innate immune responses aiming to protect tissue and enhanced ACE2 expression that could promote viral entry. Our work constitutes a unique resource for understanding the physiology and pathophysiology of two phylogenetically close species, which might guide in the development of therapeutic approaches in humans.Bullet pointsWe generated a single-cell transcriptome atlas of 9 monkey tissues to study COVID-19.ACE2+TMPRSS2+ epithelial cells of lung, kidney and liver are targets for SARS-CoV-2.ACE2 correlation analysis shows IDO2 and ANPEP as potential therapeutic opportunities.We unveil a link between IL6, STAT transcription factors and boosted SARS-CoV-2 entry.

scholarly journals Single-cell transcriptome analysis of the immunosuppressive effect of differential expression of tumor PD-L1 on responding TCR-T cells

2020 ◽  
Author(s):  
Renpeng Ding ◽  
Shang Liu ◽  
Shanshan Wang ◽  
Huanyi Chen ◽  
Fei Wang ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Tumor Cells ◽  
Cell Function ◽  
Immune Cell ◽  
Gene Clusters ◽  
Cellular Assays ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

AbstractPD-L1 expression levels in tumors do not consistently predict cancer patients’ response to PD-(L)1 inhibitors. We therefore evaluated how tumor PD-L1 levels affect the anti-PD-(L)1 efficacy and T cell function. We used MART-1-specific TCR-T cells (TCR-TMART-1) stimulated with MART-127-35 peptide-loaded MEL-526 tumor cells with different proportions of them expressing PD-L1 to perform cellular assays and high-throughput single-cell RNA sequencing. Compared to control T cells, TCR-TMART-1 were more sensitive to exhaustion and secreted lower pro-inflammatory but higher anti-inflammatory cytokines with increasing proportions of PD-L1+ tumor cells. The colocalization of T cells and tumor cells in gene clusters correlated negatively with the proportion of PD-L1+ tumor cells and positively with immune cell cytotoxicity. Moreover, elevated proportion of PD-L1+ tumor cells increased PD-L1 expression and decreased PD-1 expression on T cells and enhanced T cell death. The expression of PD-1 and PD-L1 in T cells and macrophages also correlated positively with COVID-19 severity.

scholarly journals Landscape Of M6a RNA Methylation Regulators and Tumor Microenvironment Cell-Infiltration Characterization In Gastroesophageal Adenocarcinomas

2021 ◽  
Author(s):  
Duanrui Liu ◽  
Jingyu Zhu ◽  
Zongming Wang ◽  
Yusong Fang ◽  
Mingjie Yuan ◽  
...  
Keyword(s):  
T Cells ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Rna Methylation ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Abstract Background: RNA N6-methyladenosine (m6A) modification plays a nonnegligible role in shaping individual tumor microenvironment (TME) characterizations. However, the landscape and relationship of m6A modification and TME cell infiltration remain unknown in gastroesophageal adenocarcinomas (GEA). Methods: We systematically examined the TME of GEA focusing on the distinct m6A modification patterns from the public databases. Intrinsic patterns of m6A modification were evaluated for associations with clinicopathological characteristics, underlying biological pathways, tumor immune cell infiltration, oncological outcomes and treatment responses. We generated a single-cell transcriptome atlas of the GEA sample inhouse to validate the role of the m6A modification pattern on TME.Results: We identified and validated the landscape of m6A regulators and tumor-infiltrating immune cells in GEA. Then, two distinct m6A modification patterns of GEA (cluster1/2 subgroup) were defined, and we correlated two subgroups with TME cell-infiltrating characteristics. Cluster2 subgroup correlates with a poorer prognosis, down-regulated PD-1 expression, higher risk scores and distinct immune cell infiltration. Additionally, PPI and WGCNA network analysis were integrated to identify key module genes closely related to immune infiltration of GEA to find immunotherapy markers. And COL4A1 and COL5A2 in brown module were significantly correlated to the prognosis, PD-1/L1 and CTLA-4 expression of GEA patients. Interesting, low COL5A2 expression was linked to an enhanced response to anti-PD-1 immunotherapy. Finally, a prognostic risk score was constructed using three m6A regulator-associated signatures that represented an independent prognosis factor for GEA. The single-cell transcriptome atlas of GEA sample validated the role of m6A modification pattern on TME and revealed that three m6A regulators are highly expressed in CD4+ T cells, CD8+ T cells, Tregs and Macrophages.Conclusions: Our work revealed m6A RNA methylation regulators are a type of vital participant in the malignant progression and TME diversity of GEA. m6A modification patterns of COL5A2 may be the potential biomarker contributes to predicting the response to anti-PD-1 immunotherapy.

scholarly journals Single-cell transcriptome analysis of fish immune cells provides insight into the evolution of vertebrate immune cell types

2017 ◽  
Vol 27 (3) ◽  
pp. 451-461 ◽  
Author(s):  
Santiago J. Carmona ◽  
Sarah A. Teichmann ◽  
Lauren Ferreira ◽  
Iain C. Macaulay ◽  
Michael J.T. Stubbington ◽  
...  
Keyword(s):  
Single Cell ◽  
Immune Cells ◽  
Transcriptome Analysis ◽  
Immune Cell ◽  
Cell Types ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
Insight Into

scholarly journals Teriflunomide treatment reduces B cells in patients with MS

2017 ◽  
Vol 4 (6) ◽  
pp. e403 ◽  
Author(s):  
Ilaria Gandoglia ◽  
Federico Ivaldi ◽  
Alice Laroni ◽  
Federica Benvenuto ◽  
Claudio Solaro ◽  
...  
Keyword(s):  
T Cells ◽  
B Cells ◽  
B Cell ◽  
Immune Cell ◽  
Nk Cell ◽  
Detectable Effect ◽  
Open Label ◽  
Regulatory B Cell ◽  
Cell Numbers ◽  
B Cell Subsets

Objective:To study the immunomodulatory effect of teriflunomide on innate and adaptive immune cell populations through a pilot, open-label, observational study in a cohort of patients with relapsing-remitting MS.Methods:Blood lymphocytes were isolated from 10 patients with MS before and after 3 or 12 months of treatment. Adaptive and innate immune cell subsets were analyzed by flow cytometry as follows: B cells (memory, regulatory, and mature subsets), T cells (effector and regulatory subsets), and natural killer (NK) cells (CD56dim and CD56bright subsets).Results:Our results show that teriflunomide significantly reduces absolute counts of total CD19+ B cells and mature and regulatory B-cell subsets. T cells were affected to a lesser extent, with a trend in reduction of absolute counts for both T effector CD4+ cells (Th1, Th17 and Th1/17) and T regulatory CD8+ and CD4+ cells. Teriflunomide had no detectable effect on NK-cell numbers.Conclusions:In our small cohort, teriflunomide treatment affects mainly and significantly on B-cell numbers, while having a milder effect on T-cell numbers. Larger cohorts are necessary to confirm these findings and understand the effect of teriflunomide on the functionality of these cells.

scholarly journals Single-Cell Transcriptome Profiling Unravels Distinct Peripheral Blood Immune Cell Signatures of RRMS and MOG Antibody-Associated Disease

2022 ◽  
Vol 12 ◽  
Author(s):  
Ju Liu ◽  
Xiaoyan Yang ◽  
Jiali Pan ◽  
Zhihua Wei ◽  
Peidong Liu ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Peripheral Blood ◽  
Immune Cell ◽  
Serum Antibody ◽  
Clinical Manifestations ◽  
Demyelinating Diseases ◽  
Inflammatory Monocytes ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Relapsing-remitting multiple sclerosis (RRMS) and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) are inflammatory demyelinating diseases of the central nervous system (CNS). Due to the shared clinical manifestations, detection of disease-specific serum antibody of the two diseases is currently considered as the gold standard for the diagnosis; however, the serum antibody levels are unpredictable during different stages of the two diseases. Herein, peripheral blood single-cell transcriptome was used to unveil distinct immune cell signatures of the two diseases, with the aim to provide predictive discrimination. Single-cell RNA sequencing (scRNA-seq) was conducted on the peripheral blood from three subjects, i.e., one patient with RRMS, one patient with MOGAD, and one patient with healthy control. The results showed that the CD19+ CXCR4+ naive B cell subsets were significantly expanded in both RRMS and MOGAD, which was verified by flow cytometry. More importantly, RRMS single-cell transcriptomic was characterized by increased naive CD8+ T cells and cytotoxic memory-like Natural Killer (NK) cells, together with decreased inflammatory monocytes, whereas MOGAD exhibited increased inflammatory monocytes and cytotoxic CD8 effector T cells, coupled with decreased plasma cells and memory B cells. Collectively, our findings indicate that the two diseases exhibit distinct immune cell signatures, which allows for highly predictive discrimination of the two diseases and paves a novel avenue for diagnosis and therapy of neuroinflammatory diseases.

Single Cell Profiling Reveals Unique CXCL13 Positive T Cell Subsets in the Tumor Microenvironment of Lymphocyte Rich Classic Hodgkin Lymphoma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 32-33
Author(s):  
Tomohiro Aoki ◽  
Lauren C. Chong ◽  
Katsuyoshi Takata ◽  
Katy Milne ◽  
Elizabeth Chavez ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
B Cells ◽  
Single Cell ◽  
Immune Cells ◽  
Research Funding ◽  
Immune Cell ◽  
Expression Patterns ◽  
The Other ◽  
Tfh Cells

Introduction: Classic Hodgkin lymphoma (CHL) features a unique crosstalk between malignant cells and different types of normal immune cells in the tumor-microenvironment (TME). On the basis of histomorphologic and immunophenotypic features of the malignant Hodgkin and Reed-Sternberg (HRS) cells and infiltrating immune cells, four histological subtypes of CHL are recognized: Nodular sclerosing (NS), Mixed cellularity, Lymphocyte-rich (LR) and Lymphocyte-depleted CHL. Recently, our group described the high abundance of various types of immunosuppressive CD4+ T cells including LAG3+ and/or CTLA4+ cells in the TME of CHL using single cell RNA sequencing (scRNAseq). However, the TME of LR-CHL has not been well characterized due to the rarity of the disease. In this study, we aimed at characterizing the immune cell profile of LR-CHL at single cell resolution. METHODS: We performed scRNAseq on cell suspensions collected from lymph nodes of 28 primary CHL patients, including 11 NS, 9 MC and 8 LR samples, with 5 reactive lymph nodes (RLN) serving as normal controls. We merged the expression data from all cells (CHL and RLN) and performed batch correction and normalization. We also performed single- and multi-color immunohistochemistry (IHC) on tissue microarray (TMA) slides from the same patients. In addition, an independent validation cohort of 31 pre-treatment LR-CHL samples assembled on a TMA, were also evaluated by IHC. Results: A total of 23 phenotypic cell clusters were identified using unsupervised clustering (PhenoGraph). We assigned each cluster to a cell type based on the expression of genes described in published transcriptome data of sorted immune cells and known canonical markers. While most immune cell phenotypes were present in all pathological subtypes, we observed a lower abundance of regulatory T cells (Tregs) in LR-CHL in comparison to the other CHL subtypes. Conversely, we found that B cells were enriched in LR-CHL when compared to the other subtypes and specifically, all four naïve B-cell clusters were quantitatively dominated by cells derived from the LR-CHL samples. T follicular helper (TFH) cells support antibody response and differentiation of B cells. Our data show the preferential enrichment of TFH in LR-CHL as compared to other CHL subtypes, but TFH cells were still less frequent compared to RLN. Of note, Chemokine C-X-C motif ligand 13 (CXCL13) was identified as the most up-regulated gene in LR compared to RLN. CXCL13, which is a ligand of C-X-C motif receptor 5 (CXCR5) is well known as a B-cell attractant via the CXCR5-CXCL13 axis. Analyzing co-expression patterns on the single cell level revealed that the majority of CXCL13+ T cells co-expressed PD-1 and ICOS, which is known as a universal TFH marker, but co-expression of CXCR5, another common TFH marker, was variable. Notably, classical TFH cells co-expressing CXCR5 and PD-1 were significantly enriched in RLN, whereas PD-1+ CXCL13+ CXCR5- CD4+ T cells were significantly enriched in LR-CHL. These co-expression patterns were validated using flow cytometry. Moreover, the expression of CXCR5 on naïve B cells in the TME was increased in LR-CHL compared to the other CHL subtypes We next sought to understand the spatial relationship between CXCL13+ T cells and malignant HRS cells. IHC of all cases revealed that CXCL13+ T cells were significantly enriched in the LR-CHL TME compared to other subtypes of CHL, and 46% of the LR-CHL cases showed CXCL13+ T cell rosettes closely surrounding HRS cells. Since PD-1+ T cell rosettes are known as a specific feature of LR-CHL, we confirmed co-expression of PD-1 in the rosetting cells by IHC in these cases. Conclusions: Our results reveal a unique TME composition in LR-CHL. LR-CHL seems to be distinctly characterized among the CHL subtypes by enrichment of CXCR5+ naïve B cells and CD4+ CXCL13+ PD-1+ T cells, indicating the importance of the CXCR5-CXCL13 axis in the pathogenesis of LR-CHL. Figure Disclosures Savage: BeiGene: Other: Steering Committee; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie: Honoraria; Roche (institutional): Research Funding; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie, Servier: Consultancy. Scott:Janssen: Consultancy, Research Funding; Celgene: Consultancy; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding; NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy. Steidl:AbbVie: Consultancy; Roche: Consultancy; Curis Inc: Consultancy; Juno Therapeutics: Consultancy; Bayer: Consultancy; Seattle Genetics: Consultancy; Bristol-Myers Squibb: Research Funding.

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