Periodic Reporting for period 1 - COSMIC (COmbatting disorders of adaptive immunity with Systems MedICine)
Reporting period: 2018-01-01 to 2019-12-31
EU countries face large health challenges to combat chronic diseases. Systems medicine, the integration of laboratory and computational approaches crossing research disciplines and sectors to solve clinical questions, will accelerate the translation of basic research into applications for improved diagnostics and personalized treatment.
COSMIC aims to deliver the next generation of leading systems medicine professionals having expertise, skills, and experience to successfully combat B-cell neoplasia (BCN) and rheumatoid arthritis (RA) both prototypical diseases originating from abnormal functioning of immune cells. These immune-related diseases pose a variety of challenges including (i) an incomplete understanding of the underlying molecular/cellular mechanisms, (ii) uncertain diagnosis/prognosis and (iii) variable treatment efficacies of existing drugs. This results in suboptimal patient management and a huge cost burden on healthcare systems.
The adaptive immune system is a key component of our defence against pathogens and comprises highly specialised cells and processes. Its humoral component is responsible for memory B-cell formation and high-afnity antibody production resulting from the germinal centres (GC), specialised anatomical sites for example found in lymph nodes. Incorrect functioning of the GC contributes to the emergence of B-cell clones expressing autoreactive antibodies or showing a malignant behaviour. Consequently, elucidating the cellular and molecular mechanisms of the GCR is essential to understand the ontogeny and evolution of BCN and RA.
Advancement in experimental technologies
To advance understanding of BCN and RA it is important that the B-cell repertoire from individual GCs can be measured. COSMIC made a major step by developing a methodology to isolate single GCs and determine their clonal B-cell composition. The next aim is to compare the clonal compositions of these normal GCs to GCs involved in lymphomagenesis. Similarly, significant advances have been made with the isolation of B-cells from GCs at several time points after immunization. This allows a comprehensive molecular characterisation of the genes expressed in these cells, which should give detailed insight in the mechanisms underlying lymphomagenesis. Experimental data will also help understanding the molecular basis for the initiation, maintenance, and termination of a GC and these date provide a stronger basis for the computational modelling.
Somatic hypermutation (SHM) of the B-cell receptor (BCR) genes are responsible for the B-cell composition of GC, which is critical for the production of high-affinity antibodies. It is, however, poorly understood why these mutations are not repaired by the B-cell. In COSMIC we have identified a mechanism that turns off faithful DNA repair to allow mutagenesis to happen and we gained further insight in mutagenic DNA repair. These findings have important implications for our understanding of B-cell transformation in the context of the GC. We also investigated the three-dimensional (3D) structure from antibodies produced in BCN, providing further insight into their function. We implemented the most up-to-date 3D prediction structure algorithms to construct the 3D antibody models from chronic lymphocytic leukemia (CLL). Knowledge of the structure of the antibody may assist in the development of a more robust prognostic stratification scheme in CLL.
Rheumatoid arthritis (RA)
Advancement in experimental technologies
Using nanopore long-read RNA sequencing, a critical method for full-length characterization of the transcriptome, we started to resolve the complexity in the GC B-cell transcriptome. The post-transcriptional regulation in positively selected GC B-cells has not been studied to reveal additional mechanisms or alterations in alternative isoforms, mRNA abundance, and polyadenylation so far. Further elucidation of these events is necessary to decipher the positive selection mechanism in order to develop advanced vaccine strategies and therapies for GC B-cell related malignancies. By proof-of-principle experiments, we were able to optimize subtle parameters in the experiment designs. We evaluated bioinformatics tools for alternative isoform analysis and how to assess the initial results. This will allow us to interrogate GC B-cells. Furthermore, a higher depth analysis will help us to find answers to the question arising from abnormal functions of GC reactions in BCN and RA.
Understanding rheumatoid arthritis
Based on previous observations on the presence of dominant B-cell clones in individuals at risk of developing RA, we focused on characterizing and phenotyping these clones in blood of individuals at-risk for developing RA. Results show that B-cell clones identified in blood correspond most to clones found in the plasma cell compartment and less to those in the memory B-cells compartment. We also studied a series of different B-cell clones with specificity for citrulline and type II collagen. These have been crystallized and are currently characterized functionally regarding induction of arthritis, pain and bone erosions. We have identified a new subset of B-cells with regulatory properties. It’s specific for CII and suppresses the immune response to CII. We are also validating a series of protective antibodies in mouse models aiming for therapy of RA. Some of the defined epitopes seem to be associated with protection against arthritis and antibodies to these epitopes proved to protect against arthritis in animal models.
Here we aim to develop new hypotheses about the role of the germinal center reaction (GCR) in B-cell neoplasia (BCN) and rheumatoid arthritis (RA). We have implemented complementary models to investigate disease mechanisms at the molecular and cellular levels together with the experimental groups in COSMIC. We developed a quantitative stochastic model of the GC with the goal of reproducing GC kinetics and shed light on the processes that underlie the emergence of clonal diversity and B-cell affinity maturation. We developed an agent-based models to develop theories about the GC onset and shutdown, and to understand glycosylation of ACPA B-cells in RA. In addition to the mechanistic models we developed interaction-based model to investigate disturbed networks in RA and BCN. Finally, we developed software (WASABI) that allows to infer gene regulatory networks from single cell gene expression data and started to develop protein interaction networks related to CLL and RA “effector” proteins.