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.

Evolution of SARS-CoV-2 in the Rhine-Neckar/Heidelberg Region 01/2021 - 07/2023.

In January 2021, the monitoring of circulating variants of SARS-CoV-2 was initiated in Germany under the Corona Surveillance Act, which was discontinued after July 2023. This initiative aimed to enhance pandemic containment, as specific amino acid changes, particularly in the spike protein, were associated with increased transmission and reduced vaccine efficacy. Our group conducted whole genome sequencing using the ARTIC protocol (currently V4) on Illumina's NextSeq 500 platform (and, starting in May 2023, on the MiSeq DX platform) for SARS-CoV-2 positive specimen from patients at Heidelberg University Hospital, associated hospitals, and the public health office in the Rhine-Neckar/Heidelberg region. In total, we sequenced 26,795 SARS-CoV-2-positive samples between January 2021 and July 2023. Valid sequences, meeting the requirements for upload to the German electronic sequencing data hub (DESH) operated by the Robert Koch Institute (RKI), were determined for 24,852 samples, and the lineage/clade could be identified for 25,912 samples. The year 2021 witnessed significant dynamics in the circulating variants in the Rhine-Neckar/Heidelberg region, including A.27.RN, followed by the emergence of B.1.1.7 (Alpha), subsequently displaced by B.1.617.2 (Delta), and the initial occurrences of B.1.1.529 (Omicron). By January 2022, B.1.1.529 had superseded B.1.617.2, dominating with over 90%. The years 2022 and 2023 were then characterized by the dominance of B.1.1.529 and its sublineages, particularly BA.5 and BA.2, and more recently, the emergence of recombinant variants like XBB.1.5. Since the global dominance of B.1.617.2, the identified variant distribution in our local study, apart from a time delay in the spread of new variants, can be considered largely representative of the global distribution. om a time delay in the spread of new variants, can be considered largely representative of the global distribution.

Hepatitis D infection induces IFN-ß-mediated NK cell activation and TRAIL-dependent cytotoxicity.

Background and aims: The co-infection of hepatitis B (HBV) patients with the hepatitis D virus (HDV) causes the most severe form of viral hepatitis and thus drastically worsens the course of the disease. Therapy options for HBV/HDV patients are still limited. Here, we investigated the potential of natural killer (NK) cells that are crucial drivers of the innate immune response against viruses to target HDV-infected hepatocytes. Methods: We established in vitro co-culture models using HDV-infected hepatoma cell lines and human peripheral blood NK cells. We determined NK cell activation by flow cytometry, transcriptome analysis, bead-based cytokine immunoassays, and NK cell-mediated effects on T cells by flow cytometry. We validated the mechanisms using CRISPR/Cas9-mediated gene deletions. Moreover, we assessed the frequencies and phenotype of NK cells in peripheral blood of HBV and HDV superinfected patients. Results: Upon co-culture with HDV-infected hepatic cell lines, NK cells upregulated activation markers, interferon-stimulated genes (ISGs) including the death receptor ligand tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), produced interferon (IFN)-γ and eliminated HDV-infected cells via the TRAIL-TRAIL-R2 axis. We identified IFN-ß released by HDV-infected cells as an important enhancer of NK cell activity. In line with our in vitro data, we observed activation of peripheral blood NK cells from HBV/HDV co-infected, but not HBV mono-infected patients. Conclusion: Our data demonstrate NK cell activation in HDV infection and their potential to eliminate HDV-infected hepatoma cells via the TRAIL/TRAIL-R2 axis which implies a high relevance of NK cells for the design of novel anti-viral therapies.

DNA-methylation signature accurately differentiates pancreatic cancer from chronic pancreatitis in tissue and plasma.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy. Differentiation from chronic pancreatitis (CP) is currently inaccurate in about one-third of cases. Misdiagnoses in both directions, however, have severe consequences for patients. We set out to identify molecular markers for a clear distinction between PDAC and CP. DESIGN: Genome-wide variations of DNA-methylation, messenger RNA and microRNA level as well as combinations thereof were analysed in 345 tissue samples for marker identification. To improve diagnostic performance, we established a random-forest machine-learning approach. Results were validated on another 48 samples and further corroborated in 16 liquid biopsy samples. RESULTS: Machine-learning succeeded in defining markers to differentiate between patients with PDAC and CP, while low-dimensional embedding and cluster analysis failed to do so. DNA-methylation yielded the best diagnostic accuracy by far, dwarfing the importance of transcript levels. Identified changes were confirmed with data taken from public repositories and validated in independent sample sets. A signature of six DNA-methylation sites in a CpG-island of the protein kinase C beta type gene achieved a validated diagnostic accuracy of 100% in tissue and in circulating free DNA isolated from patient plasma. CONCLUSION: The success of machine-learning to identify an effective marker signature documents the power of this approach. The high diagnostic accuracy of discriminating PDAC from CP could have tremendous consequences for treatment success, once the result from still a limited number of liquid biopsy samples would be confirmed in a larger cohort of patients with suspected pancreatic cancer.

Resolving therapy resistance mechanisms in multiple myeloma by multiomics subclone analysis.

Intratumor heterogeneity as a clinical challenge becomes most evident after several treatment lines, when multidrug-resistant subclones accumulate. To address this challenge, the characterization of resistance mechanisms at the subclonal level is key to identify common vulnerabilities. In this study, we integrate whole-genome sequencing, single-cell (sc) transcriptomics (scRNA sequencing), and chromatin accessibility (scATAC sequencing) together with mitochondrial DNA mutations to define subclonal architecture and evolution for longitudinal samples from 15 patients with relapsed or refractory multiple myeloma. We assess transcriptomic and epigenomic changes to resolve the multifactorial nature of therapy resistance and relate it to the parallel occurrence of different mechanisms: (1) preexisting epigenetic profiles of subclones associated with survival advantages, (2) converging phenotypic adaptation of genetically distinct subclones, and (3) subclone-specific interactions of myeloma and bone marrow microenvironment cells. Our study showcases how an integrative multiomics analysis can be applied to track and characterize distinct multidrug-resistant subclones over time for the identification of molecular targets against them.

Epigenetic signals that direct cell type-specific interferon beta response in mouse cells.

The antiviral response induced by type I interferon (IFN) via the JAK-STAT signaling cascade activates hundreds of IFN-stimulated genes (ISGs) across human and mouse tissues but varies between cell types. However, the links between the underlying epigenetic features and the ISG profile are not well understood. We mapped ISGs, binding sites of the STAT1 and STAT2 transcription factors, chromatin accessibility, and histone H3 lysine modification by acetylation (ac) and mono-/tri-methylation (me1, me3) in mouse embryonic stem cells and fibroblasts before and after IFNß treatment. A large fraction of ISGs and STAT-binding sites was cell type specific with promoter binding of a STAT1/2 complex being a key driver of ISGs. Furthermore, STAT1/2 binding to putative enhancers induced ISGs as inferred from a chromatin co-accessibility analysis. STAT1/2 binding was dependent on the chromatin context and positively correlated with preexisting H3K4me1 and H3K27ac marks in an open chromatin state, whereas the presence of H3K27me3 had an inhibitory effect. Thus, chromatin features present before stimulation represent an additional regulatory layer for the cell type-specific antiviral response.