Analysis of Human RSV Immunity at the Molecular Level: Learning from the Past and Present

Human RSV is one of the most prevalent viral pathogens of early childhood for which no vaccine is available. Herein we provide an analysis of RSV epitope data to examine its application to vaccine design and development. Our objective was to provide an overview of antigenic coverage, identify critical antibody and T cell determinants, and then analyze the cumulative RSV epitope data from the standpoint of functional responses using a combinational approach to characterize antigenic structure and epitope location. A review of the cumulative data revealed, not surprisingly, that the vast majority of epitopes have been defined for the two major surface antigens, F and G. Antibody and T cell determinants have been reported from multiple hosts, including those from human subjects following natural infection, however human data represent a minority of the data. A structural analysis of the major surface antigen, F, showed that the majority of epitopes defined for functional antibodies (neutralizing and/or protective) were either shown to bind pre-F or to be accessible in both pre- and post-F forms. This finding may have has implications for on-going vaccine design and development. These interpretations are in agreement with previous work and can be applied in the larger context of functional epitopes on the F protein. It is our hope that this work will provide the basis for further RSV-specific epitope discovery and investigation into the nature of antigen conformation in immunogenicity.     

In vitro induction of neoantigen-specific T cells in myelodysplastic syndrome,a disease with low mutational burden

Therapies that utilize immune checkpoint inhibition work by leveraging mutation-derived neoantigens and have shown greater clinical efficacy in tumors with higher mutational burden. Whether tumors with a low mutational burden are susceptible to neoantigen-targeted therapy has not been fully addressed. To examine the feasibility of neoantigen-specific adoptive T-cell therapy, the authors studied the T-cell response against somatic variants in five patients with myelodysplastic syndrome (MDS), a malignancy with a very low tumor mutational burden. DNA and RNA from tumor (CD34⁺) and normal (CD3⁺) cells isolated from the patients’ blood were sequenced to predict patient-specific MDS neopeptides. Neopeptides representing the somatic variants were used to induce and expand autologous T cells ex vivo, and these were systematically tested in killing assays to determine the proportion of neopeptides yielding neoantigen-specific T cells. The authors identified a total of 32 somatic variants (four to eight per patient) and found that 21 (66%) induced a peptide-specific T-cell response and 19 (59%) induced a T-cell response capable of killing autologous tumor cells. Of the 32 somatic variants, 11 (34%) induced a CD4⁺ response and 11 (34%) induced a CD8⁺ response that killed the tumor. These results indicate that in vitro induction of neoantigen-specific T cells is feasible for tumors with very low mutational burden and that this approach warrants investigation as a therapeutic option for such patients.     

Pattern classification of kinematic and kinetic running data to distinguish gender,shod/barefoot and injury groups with feature ranking

The identification of differences between groups is often important in biomechanics. This paper presents group classification tasks using kinetic and kinematic data from a prospective running injury study. Groups composed of gender, of shod/barefoot running and of runners who developed patellofemoral pain syndrome (PFPS) during the study, and asymptotic runners were classified.

The features computed from the biomechanical data were deliberately chosen to be generic. Therefore, they were suited for different biomechanical measurements and classification tasks without adaptation to the input signals. Feature ranking was applied to reveal the relevance of each feature to the classification task.

Data from 80 runners were analysed for gender and shod/barefoot classification, while 12 runners were investigated in the injury classification task. Gender groups could be differentiated with 84.7%, shod/barefoot running with 98.3%, and PFPS with 100% classification rate. For the latter group, one single variable could be identified that alone allowed discrimination.     

Epitope Predictions Indicate the Presence of Two Distinct Types of Epitope-Antibody-Reactivities Determined by Epitope Profiling of Intravenous Immunoglobulins

Epitope-antibody-reactivities (EAR) of intravenous immunoglobulins (IVIGs) determined for 75,534 peptides by microarray analysis demonstrate that roughly 9% of peptides derived from 870 different human protein sequences react with antibodies present in IVIG. Computational prediction of linear B cell epitopes was conducted using machine learning with an ensemble of classifiers in combination with position weight matrix (PWM) analysis. Machine learning slightly outperformed PWM with area under the curve (AUC) of 0.884 vs. 0.849. Two different types of epitope-antibody recognition-modes (Type I EAR and Type II EAR) were found. Peptides of Type I EAR are high in tyrosine, tryptophan and phenylalanine, and low in asparagine, glutamine and glutamic acid residues, whereas for peptides of Type II EAR it is the other way around. Representative crystal structures present in the Protein Data Bank (PDB) of Type I EAR are PDB 1TZI and PDB 2DD8, while PDB 2FD6 and 2J4W are typical for Type II EAR. Type I EAR peptides share predicted propensities for being presented by MHC class I and class II complexes. The latter interaction possibly favors T cell-dependent antibody responses including IgG class switching. Peptides of Type II EAR are predicted not to be preferentially presented by MHC complexes, thus implying the involvement of T cell-independent IgG class switch mechanisms. The high extent of IgG immunoglobulin reactivity with human peptides implies that circulating IgG molecules are prone to bind to human protein/peptide structures under non-pathological, non-inflammatory conditions. A webserver for predicting EAR of peptide sequences is available at www.sysmed-immun.eu/EAR.     

Properties of MHC Class I Presented Peptides That Enhance Immunogenicity

T-cells have to recognize peptides presented on MHC molecules to be activated and elicit their effector functions. Several studies demonstrate that some peptides are more immunogenic than others and therefore more likely to be T-cell epitopes. We set out to determine which properties cause such differences in immunogenicity. To this end, we collected and analyzed a large set of data describing the immunogenicity of peptides presented on various MHC-I molecules. Two main conclusions could be drawn from this analysis: First, in line with previous observations, we showed that positions P4–6 of a presented peptide are more important for immunogenicity. Second, some amino acids, especially those with large and aromatic side chains, are associated with immunogenicity. This information was combined into a simple model that was used to demonstrate that immunogenicity is, to a certain extent, predictable. This model (made available at http://tools.iedb.org/immunogenicity/) was validated with data from two independent epitope discovery studies. Interestingly, with this model we could show that T-cells are equipped to better recognize viral than human (self) peptides. After the past successful elucidation of different steps in the MHC-I presentation pathway, the identification of variables that influence immunogenicity will be an important next step in the investigation of T-cell epitopes and our understanding of cellular immune responses.     

Downregulation of AKT3 Increases Migration and Metastasis in Triple Negative Breast Cancer Cells by Upregulating S100A4

Background

Treatment of breast cancer patients with distant metastases represents one of the biggest challenges in today’s gynecological oncology. Therefore, a better understanding of mechanisms promoting the development of metastases is of paramount importance. The serine/threonine kinase AKT was shown to drive cancer progression and metastasis. However, there is emerging data that single AKT isoforms (i.e. AKT1, AKT2 and AKT3) have different or even opposing functions in the regulation of cancer cell migration in vitro, giving rise to the hypothesis that inhibition of distinct AKT isoforms might have undesirable effects on cancer dissemination in vivo.

Methods

The triple negative breast cancer cell line MDA-MB-231 was used to investigate the functional roles of AKT in migration and metastasis. AKT single and double knockdown cells were generated using isoform specific shRNAs. Migration was analyzed using live cell imaging, chemotaxis and transwell assays. The metastatic potential of AKT isoform knockdown cells was evaluated in a subcutaneous xenograft mouse model in vivo.

Results

Depletion of AKT3, but not AKT1 or AKT2, resulted in increased migration in vitro. This effect was even more prominent in AKT2,3 double knockdown cells. Furthermore, combined downregulation of AKT2 and AKT3, as well as AKT1 and AKT3 significantly increased metastasis formation in vivo. Screening for promigratory proteins revealed that downregulation of AKT3 increases the expression of S100A4 protein. In accordance, depletion of S100A4 by siRNA approach reverses the increased migration induced by knockdown of AKT3.

Conclusions

We demonstrated that knockdown of AKT3 can increase the metastatic potential of triple negative breast cancer cells. Therefore, our results provide a rationale for the development of AKT isoform specific inhibitors.