From Antibody Repertoires to Cell-Cell Interactions to Molecular Networks: Bridging Scales in the Germinal Center

Harnessing Variability Signatures and Biological Noise May Enhance Immunotherapies' Efficacy and Act as Novel Biomarkers for Diagnosing and Monitoring Immune-Associated Disorders

Lack of response to immunotherapies poses a significant challenge in treating immune-mediated disorders and cancers. While the mechanisms associated with poor responsiveness are not well defined and change between and among subjects, the current methods for overcoming the loss of response are insufficient. The Constrained Disorder Principle (CDP) explains biological systems based on their inherent variability, bounded by dynamic boundaries that change in response to internal and external perturbations. Inter and intra-subject variability characterize the immune system, making it difficult to provide a single therapeutic regimen to all patients and even the same patients over time. The dynamicity of the immune variability is also a significant challenge for personalizing immunotherapies. The CDP-based second-generation artificial intelligence system is an outcome-based dynamic platform that incorporates personalized variability signatures into the therapeutic regimen and may provide methods for improving the response and overcoming the loss of response to treatments. The signatures of immune variability may also offer a method for identifying new biomarkers for early diagnosis, monitoring immune-related disorders, and evaluating the response to treatments.

IL-12 induces a B cell-intrinsic IL-12/IFNγ feed-forward loop promoting extrafollicular B cell responses

While some infections elicit germinal centers, others produce only extrafollicular responses. The mechanisms controlling these dichotomous fates are poorly understood. We identify IL-12 as a cytokine switch, acting directly on B cells to promote extrafollicular and suppress germinal center responses. IL-12 initiates a B cell-intrinsic feed-forward loop between IL-12 and IFNγ, amplifying IFNγ production, which promotes proliferation and plasmablast differentiation from mouse and human B cells, in synergy with IL-12. IL-12 sustains the expression of a portion of IFNγ-inducible genes. Together, they also induce unique gene changes, reflecting both IFNγ amplification and cooperative effects between both cytokines. In vivo, cells lacking both IL-12 and IFNγ receptors are more impaired in plasmablast production than those lacking either receptor alone. Further, B cell-derived IL-12 enhances both plasmablast responses and T helper 1 cell commitment. Thus, B cell-derived IL-12, acting on T and B cells, determines the immune response mode, with implications for vaccines, pathogen protection and autoimmunity.

A multiscale spatial modeling framework for the germinal center response

The germinal center response or reaction (GCR) is a hallmark event of adaptive humoral immunity. Unfolding in the B cell follicles of the secondary lymphoid organs, a GC culminates in the production of high-affinity antibody-secreting plasma cells along with memory B cells. By interacting with follicular dendritic cells (FDC) and T follicular helper (Tfh) cells, GC B cells exhibit complex spatiotemporal dynamics. Driving the B cell dynamics are the intracellular signal transduction and gene regulatory network that responds to cell surface signaling molecules, cytokines, and chemokines. As our knowledge of the GC continues to expand in depth and in scope, mathematical modeling has become an important tool to help disentangle the intricacy of the GCR and inform novel mechanistic and clinical insights. While the GC has been modeled at different granularities, a multiscale spatial simulation framework - integrating molecular, cellular, and tissue-level responses - is still rare. Here, we report our recent progress toward this end with a hybrid stochastic GC framework developed on the Cellular Potts Model-based CompuCell3D platform. Tellurium is used to simulate the B cell intracellular molecular network comprising NF-κB, FOXO1, MYC, AP4, CXCR4, and BLIMP1 that responds to B cell receptor (BCR) and CD40-mediated signaling. The molecular outputs of the network drive the spatiotemporal behaviors of B cells, including cyclic migration between the dark zone (DZ) and light zone (LZ) via chemotaxis; clonal proliferative bursts, somatic hypermutation, and DNA damage-induced apoptosis in the DZ; and positive selection, apoptosis via a death timer, and emergence of plasma cells in the LZ. Our simulations are able to recapitulate key molecular, cellular, and morphological GC events, including B cell population growth, affinity maturation, and clonal dominance. This novel modeling framework provides an open-source, customizable, and multiscale virtual GC simulation platform that enables qualitative and quantitative in silico investigations of a range of mechanistic and applied research questions on the adaptive humoral immune response in the future.

A Multiscale Spatial Modeling Framework for the Germinal Center Response

The germinal center response or reaction (GCR) is a hallmark event of adaptive humoral immunity. Unfolding in the B cell follicles of the secondary lymph organs, a GC culminates in the production of high-affinity antibody-secreting plasma cells along with memory B cells. By interacting with follicular dendritic cells (FDC) and T follicular helper (Tfh) cells, GC B cells exhibit complex spatiotemporal dynamics. Driving the B cell dynamics are the intracellular signal transduction and gene regulatory network that responds to cell surface signaling molecules, cytokines, and chemokines. As our knowledge of the GC continues to expand in depth and in scope, mathematical modeling has become an important tool to help disentangle the intricacy of the GCR and inform novel mechanistic and clinical insights. While the GC has been modeled at different granularities, a multiscale spatial simulation framework - integrating molecular, cellular, and tissue-level responses - is still rare. Here, we report our recent progress toward this end with a hybrid stochastic GC framework developed on the Cellular Potts Model-based CompuCell3D platform. Tellurium is used to simulate the B cell intracellular molecular network comprising NF-κB, FOXO1, MYC, AP4, CXCR4, and BLIMP1 that responds to B cell receptor (BCR) and CD40-mediated signaling. The molecular outputs of the network drive the spatiotemporal behaviors of B cells, including cyclic migration between the dark zone (DZ) and light zone (LZ) via chemotaxis; clonal proliferative bursts, somatic hypermutation, and DNA damage-induced apoptosis in the DZ; and positive selection, apoptosis via a death timer, and emergence of plasma cells in the LZ. Our simulations are able to recapitulate key molecular, cellular, and morphological GC events including B cell population growth, affinity maturation, and clonal dominance. This novel modeling framework provides an open-source, customizable, and multiscale virtual GC simulation platform that enables qualitative and quantitative in silico investigations of a range of mechanic and applied research questions in future.

Spatial biology analysis reveals B cell follicles in secondary lymphoid structures may regulate anti-tumor responses at initial melanoma diagnosis

Introduction

B cells are key regulators of immune responses in melanoma. We aimed to explore differences in the histologic location and activation status of B cell follicles in sentinel lymph nodes (SLN) of melanoma patients.

Methods

Flow cytometry was performed on fresh tumor draining lymph nodes (LN). Paraffin slides from a separate cohort underwent NanoString Digital Spatial Profiling (DSP)®. After staining with fluorescent markers for CD20 (B cells), CD3 (T cells), CD11c (antigen presenting cells) and a nuclear marker (tumor) was performed, regions of interest (ROI) were selected based on the location of B cell regions (B cell follicles). A panel of 68 proteins was then analyzed from the ROIs.

Results

B cell percentage trended higher in patients with tumor in LN (n=3) compared to patients with nSLN (n=10) by flow cytometry. B cell regions from a separate cohort of patients with tumor in the (pSLN) (n=8) vs. no tumor (nSLN) (n=16) were examined with DSP. Within B cell regions of the SLN, patients with pSLN had significantly higher expression of multiple activation markers including Ki-67 compared to nSLN patients. Among 4 patients with pSLN, we noted variability in arrangement of B cell follicles which were either surrounding the tumor deposit or appeared to be infiltrating the tumor. The B cell follicle infiltrative pattern was associated with prolonged recurrence free survival.

Conclusion

These data suggest a role for B cell follicles in coordinating effective adaptive immune responses in melanoma when low volume metastatic disease is present in tumor draining LN.