T-bet suppresses proliferation of malignant B cells in chronic lymphocytic leukemia.

The T-box transcription factor T-bet is known as a master regulator of T-cell response but its role in malignant B cells is not sufficiently explored. Here, we conducted single-cell resolved multi-omics analyses of malignant B cells from patients with chronic lymphocytic leukemia (CLL) and studied a CLL mouse model with genetic knockout of TBX21. We found that T-bet acts as a tumor suppressor in malignant B cells by decreasing their proliferation rate. NF-κB activity induced by inflammatory signals provided by the microenvironment, triggered T-bet expression which impacted on promoter proximal and distal chromatin co-accessibility and controlled a specific gene signature by mainly suppressing transcription. Gene set enrichment analysis identified a positive regulation of interferon signaling, and a negative control of proliferation by T-bet. In line, we showed that T-bet represses cell cycling and is associated with longer overall survival of CLL patients. Our study uncovers a novel tumor suppressive role of T-bet in malignant B cells via its regulation of inflammatory processes and cell cycling which has implications for stratification and therapy of CLL patients. Linking T-bet activity to inflammation explains the good prognostic role of genetic alterations in inflammatory signaling pathways in CLL.

Multimodal and spatially resolved profiling identifies distinct patterns of T cell infiltration in nodal B cell lymphoma entities.

The redirection of T cells has emerged as an attractive therapeutic principle in B cell non-Hodgkin lymphoma (B-NHL). However, a detailed characterization of lymphoma-infiltrating T cells across B-NHL entities is missing. Here we present an in-depth T cell reference map of nodal B-NHL, based on cellular indexing of transcriptomes and epitopes, T cell receptor sequencing, flow cytometry and multiplexed immunofluorescence applied to 101 lymph nodes from patients with diffuse large B cell, mantle cell, follicular or marginal zone lymphoma, and from healthy controls. This multimodal resource revealed quantitative and spatial aberrations of the T cell microenvironment across and within B-NHL entities. Quantitative differences in PD1+ TCF7- cytotoxic T cells, T follicular helper cells or IKZF3+ regulatory T cells were linked to their clonal expansion. The abundance of PD1+ TCF7- cytotoxic T cells was associated with poor survival. Our study portrays lymphoma-infiltrating T cells with unprecedented comprehensiveness and provides a unique resource for the investigation of lymphoma biology and prognosis.

Architecture of the Mass Spectrometry Data Management Pipeline in the SMART-CARE Project.

In the SMART-CARE project- a systems medicine approach to stratification of cancer recurrence in Heidelberg, Germany - a streamlined mass-spectrometry (MS) workflow for identification of cancer relapse was developed. This project has multiple partners from clinics, laboratories and computational teams. For optimal collaboration, consistent documentation and centralized storage, the linked data repository was designed. Clinical, laboratory and computational group members interact with this platform and store meta- and raw-data. The specific architectural choices, such as pseudonymization service, uploading process and other technical specifications as well as lessons learned are presented in this work. Altogether, relevant information in order to provide other research groups with a head-start for tackling MS data management in the context of systems medicine research projects is described.

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia.

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.

Large-File Raw Data Synchronization for openBIS Research Repositories.

In a systems medicine research consortium, openBIS is used as a research data repository. To facilitate efficient upload of large files, openBIS is complemented by a Nextcloud data cloud system. Using a Nextcloud client, raw mass spectrometry data is automatically imported into the repository in the background, enabling comprehensive data provenance.

Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis.

Metabolomic and proteomic analyses of human plasma and serum samples harbor the power to advance our understanding of disease biology. Pre-analytical factors may contribute to variability and bias in the detection of analytes, especially when multiple labs are involved, caused by sample handling, processing time, and differing operating procedures. To better understand the impact of pre-analytical factors that are relevant to implementing a unified proteomic and metabolomic approach in a clinical setting, we assessed the influence of temperature, sitting times, and centrifugation speed on the plasma and serum metabolomes and proteomes from six healthy volunteers. We used targeted metabolic profiling (497 metabolites) and data-independent acquisition (DIA) proteomics (572 proteins) on the same samples generated with well-defined pre-analytical conditions to evaluate criteria for pre-analytical SOPs for plasma and serum samples. Time and temperature showed the strongest influence on the integrity of plasma and serum proteome and metabolome. While rapid handling and low temperatures (4°C) are imperative for metabolic profiling, the analyzed proteomics data set showed variability when exposed to temperatures of 4°C for more than 2 h, highlighting the need for compromises in a combined analysis. We formalized a quality control scoring system to objectively rate sample stability and tested this score using external data sets from other pre-analytical studies. Stringent and harmonized standard operating procedures (SOPs) are required for pre-analytical sample handling when combining proteomics and metabolomics of clinical samples to yield robust and interpretable data on a longitudinal scale and across different clinics. To ensure an adequate level of practicability in a clinical routine for metabolomics and proteomics studies, we suggest keeping blood samples up to 2 h on ice (4°C) prior to snap-freezing as a compromise between stability and operability. Finally, we provide the methodology as an open-source R package allowing the systematic scoring of proteomics and metabolomics data sets to assess the stability of plasma and serum samples.

Phagocytosis by stroma confounds coculture studies.

Signals provided by the microenvironment can modify and circumvent pathway activities that are therapeutically targeted by drugs. Bone marrow stromal cell coculture models are frequently used to study the influence of the bone marrow niche on ex vivo drug response. Here, we show that mesenchymal stromal cells from selected donors and NKTert, a stromal cell line, which is commonly used for coculture studies with primary leukemia cells, extensively phagocytose apoptotic cells. This could lead to misinterpretation of results, especially if viability readouts of the target cells (e.g. leukemic cells) in such coculture models are based on the relative proportions of dead and alive cells. Future coculture studies which aim to investigate the impact of bone marrow stromal cells on drug response should take into account that stromal cells have the capacity to phagocytose apoptotic cells.

Data Management for Systems Medicine: The SMART-CARE Joint Environment.

For a research project on mass spectrometry, a streamlined, harmonized and robust analytical pipeline is built to predict tumor recurrence. By means of standardization all steps from sample collection, analysis, proteome, and metabolome analysis are harmonized. Challenges like non-central identificators and distributed data are overcome with a centralized high-performant IT-platform in combination with a pseudonymization service and harmonization.

Emerging protein kinase inhibitors for the treatment of multiple myeloma.

Introduction: Significant advances have been made during the last two decades in terms of new therapeutic options but also of innovative approaches to diagnosis and management of multiple myeloma (MM). While patient survival has been significantly prolonged, most patients relapse. Including the milestone approval of the first kinase inhibitor imatinib mesylate for CML in 2001, 48 small molecule protein kinase (PK) inhibitors have entered clinical practice until now. However, no PK inhibitor has been approved for MM therapy yet. Areas covered: This review article summarizes up-to-date knowledge on the pathophysiologic role of PKs in MM. Derived small molecules targeting receptor tyrosine kinases (RTKs), the Ras/Raf/MEK/MAPK- pathway, the PI3K/Akt/mTOR- pathway as well as Bruton tyrosine kinase (BTK), Aurora kinases (AURK), and cyclin-dependent kinases (CDKs) are most promising. Preclinical as well as early clinical data focusing on these molecules will be presented and critically reviewed. Expert opinion: Current MM therapy is directed against general vulnerabilities. Novel therapeutic strategies, inhibition of PKs in particular, are directed to target tumor-specific driver aberrations such as genetic abnormalities and microenvironment-driven deregulations. Results of ongoing Precision Medicine trials with PK inhibitors alone or in combination with other agents are eagerly awaited and hold the promise of once more improving MM patient outcome.