Molecular consequences of peripheral Influenza A infection on cell populations in the murine hypothalamus

Infection with Influenza A virus (IAV) causes the well-known symptoms of the flu, including fever, loss of appetite, and excessive sleepiness. These responses, mediated by the brain, will normally disappear once the virus is cleared from the system, but a severe respiratory virus infection may cause long-lasting neurological disturbances. These include encephalitis lethargica and narcolepsy. The mechanisms behind such long lasting changes are unknown. The hypothalamus is a central regulator of the homeostatic response during a viral challenge. To gain insight into the neuronal and non-neuronal molecular changes during an IAV infection, we intranasally infected mice with an H1N1 virus and extracted the brain at different time points. Using single-nucleus RNA sequencing (snRNA-seq) of the hypothalamus, we identify transcriptional effects in all identified cell populations. The snRNA-seq data showed the most pronounced transcriptional response at 3 days past infection, with a strong downregulation of genes across all cell types. General immune processes were mainly impacted in microglia, the brain resident immune cells, where we found increased numbers of cells expressing pro-inflammatory gene networks. In addition, we found that most neuronal cell populations downregulated genes contributing to the energy homeostasis in mitochondria and protein translation in the cytosol, indicating potential reduced cellular and neuronal activity. This might be a preventive mechanism in neuronal cells to avoid intracellular viral replication and attack by phagocytosing cells. The change of microglia gene activity suggest that this is complemented by a shift in microglia activity to provide increased surveillance of their surroundings

Bispecific T cell-engager targeting oncofetal chondroitin sulfate induces complete tumor regression and protective immune memory in mice

Abstract Background The malaria protein VAR2CSA binds oncofetal chondroitin sulfate (ofCS), a unique chondroitin sulfate, expressed on almost all mammalian cancer cells. Previously, we produced a bispecific construct targeting ofCS and human T cells based on VAR2CSA and anti-CD3 (V-aCD3Hu). V-aCD3Hu showed efficacy against xenografted tumors in immunocompromised mice injected with human immune cells at the tumor site. However, the complex effects potentially exerted by the immune system as a result of the treatment cannot occur in mice without an immune system. Here we investigate the efficacy of V-aCD3Mu as a monotherapy and combined with immune checkpoint inhibitors in mice with a fully functional immune system. Methods We produced a bispecific construct consisting of a recombinant version of VAR2CSA coupled to an anti-murine CD3 single-chain variable fragment. Flow cytometry and ELISA were used to check cell binding capabilities and the therapeutic effect was evaluated in vitro in a killing assay. The in vivo efficacy of V-aCD3Mu was then investigated in mice with a functional immune system and established or primary syngeneic tumors in the immunologically “cold” 4T1 mammary carcinoma, B16-F10 malignant melanoma, the pancreatic KPC mouse model, and in the immunologically “hot” CT26 colon carcinoma model. Results V-aCD3Mu had efficacy as a monotherapy, and the combined treatment of V-aCD3Mu and an immune checkpoint inhibitor showed enhanced effects resulting in the complete elimination of solid tumors in the 4T1, B16-F10, and CT26 models. This anti-tumor effect was abscopal and accompanied by a systemic increase in memory and activated cytotoxic and helper T cells. The combined treatment also led to a higher percentage of memory T cells in the tumor without an increase in regulatory T cells. In addition, we observed partial protection against re-challenge in a melanoma model and full protection in a breast cancer model. Conclusions Our findings suggest that V-aCD3Mu combined with an immune checkpoint inhibitor renders immunologically “cold” tumors “hot” and results in tumor elimination. Taken together, these data provide proof of concept for the further clinical development of V-aCD3 as a broad cancer therapy in combination with an immune checkpoint inhibitor

Additional file 1 of Bispecific T cell-engager targeting oncofetal chondroitin sulfate induces complete tumor regression and protective immune memory in mice

Additional file 1: Sup. Fig. 1. (A) ELISA showing binding of V-aCD3Mu (Coupled)(Kd = 38.8, Bmax = 3.31), rVAR2 (Kd and Bmax not determined), and V-aCD3Mu (Fused)(Kd = 14.2, Bmax = 3.36) to CSPG on a decorin backbone. Data is representative of a minimum of two separate experiments. (B) Solid 4T1 tumors 50-100 mm3 in size were treated with either PBS (n=5), V-aCD3Mu (Coupled) + CpG (n=8), or V-aCD3Mu (Fused) + CpG (n=8) on day 10, 12, 14, and 17 after tumor injection. Numbers in parentheses indicate the number of animals with complete tumor regression out of all mice in the group. Sup. Fig. 2. (A) Gating strategy on splenocytes and PBMCs in flow cytometry used to determine binding of rVAR2, aCD3Mu, V-aCD3Mu, aCD3Hu, and anti-V5 antibodies to T cells and non-T cell splenocytes/PBMCs. The gating is single cells lymphocytes live cells CD4+ and/or CD8+ cells as T cells and CD4-CD8- cells as non-T cells. The geometric MFI of the anti-penta-HIS antibodies conjugated to Alexa Flour 488 was then used to evaluate the binding of the HIS-tagged proteins. (B) Binding of aCD3Mu (Kd = 4.96, Bmax = 1.05), rVAR2 (Kd = NR, Bmax = 0.46), and V-aCD3Mu (Kd = 1.24, Bmax = 3.38) to murine recombinant CD3 in ELISA with aCD4Mu as a negative control (left). Means and standard deviations are shown. Right pane shows CSA inhibition of binding at 120 nM (right). Each dot represents one data point. Sup. Fig. 3. Cytokines measured from 4T1 and splenocyte co-culture supernatants using ELISA. Mouse splenocytes were incubated with 4T1 cancer cells together with 200 nM of the indicated protein. Sup. Fig. 4. (A) Survival curves for mice with indicated tumors treated as described in Fig. 4. The cut-off for all Kaplan-Meier plots is a tumor volume of $$\ge$$ ≥ 400 mm3. Mice were censored if they had to be excluded from the study prematurely due to reasons other than tumor size. Log-rank test was used for statistical analysis. *p < 0.05. (B) Bioluminescence in vivo imaging of C57BL/6 mice following orthotopic implantation of 5x104 Luciferase+ primary pancreatic cancer cells (CHX2000) derived from KPC mice (LSL-KrasG12D/+; p53f/f; Pdx1-Cre). Sup. Fig. 5. (A-C) Survival curves for mice treated as described in Fig. 5. The cut-off for all Kaplan-Meier plots is a tumor volume of $$\ge$$ ≥ 400 mm3. Mice were censored if they had to be excluded from the study prematurely due to reasons other than tumor size. Log-rank test was used for statistical analysis. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Sup. Fig. 6. (A) Treatment schedule until day 14 when spleens and tumors were harvested for flow cytometry and the subsequent gating strategy on splenocytes to evaluate different cell types in C-D. (B) Percentage of live cells relative to the PBS group in the spleen. Both CD8+ and CD4+ T cells that are CD69+, CD44hi, CD8+CD25+, or Tregs are shown. (C) UMAPs of splenocytes from all four treatment groups with clustering performed in ClusterExplorer. Cell types in clusters are explained below. Statistics were performed using one-way ANOVA with Dunnett’s post hoc test for comparison of all treatment groups to the PBS group. P values are indicated if significant or important for reading the figure. (D) Correlations between the tumor size and �8+CD69+ (p=0.67) and �4+CD69+ (p=0.14) of all live single cells in the tumor evaluated by simple linear regression. Sup. Fig. 7. Binding of mouse antibodies to 4T1 cells and B16-F10 cells in flow cytometry. Serum from C57BL/6 mice treated as described in materials and methods was diluted as illustrated on the figure and incubated with 200.000 4T1 or B16-F10 cells. Soluble CSA was added if indicated for 1 hour before detection with an anti-mouse IgG antibody conjugated to FITC