A generally applicable translational strategy identifies S100A4 as a candidate gene in allergy

S100A4-neutralizing antibody suppresses spontaneous tumor progression, pre-metastatic niche formation and alters T-cell polarization balance

Background

The tumor microenvironment plays a determinative role in stimulating tumor progression and metastasis. Notably, tumor-stroma signals affect the pattern of infiltrated immune cells and the profile of tumor-released cytokines. Among the known molecules that are engaged in stimulating the metastatic spread of tumor cells is the S100A4 protein. S100A4 is known as an inducer of inflammatory processes and has been shown to attract T-cells to the primary tumor and to the pre-metastatic niche. The present study aims to examine the immunomodulatory role of S100A4 in vivo and in vitro and assess the mode of action of 6B12, a S100A4 neutralizing antibody.

Methods

The therapeutic effect of the 6B12 antibody was evaluated in two different mouse models. First, in a model of spontaneous breast cancer we assessed the dynamics of tumor growth and metastasis. Second, in a model of metastatic niche formation we determined the expression of metastatic niche markers. The levels of cytokine expression were assessed using antibody as well as PCR arrays and the results confirmed by qRT-PCR and ELISA. T-cell phenotyping and in vitro differentiation analyses were performed by flow cytometry.

Results

We show that the S100A4 protein alters the expression of transcription factor and signal transduction pathway genes involved in the T-cell lineage differentiation. T-cells challenged with S100A4 demonstrated reduced proportion of Th1-polarized cells shifting the Th1/Th2 balance towards the Th2 pro-tumorigenic phenotype. The 6B12 antibody restored the Th1/Th2 balance. Furthermore, we provide evidence that the 6B12 antibody deploys its anti-metastatic effect, by suppressing the attraction of T-cells to the site of primary tumor and pre-metastatic niche. This was associated with delayed primary tumor growth, decreased vessel density and inhibition of metastases.

Conclusion

The S100A4 blocking antibody (6B12) reduces tumor growth and metastasis in a model of spontaneous breast cancer. The 6B12 antibody treatment inhibits T cell accumulation at the primary and pre-metastatic tumor sites. The 6B12 antibody acts as an immunomodulatory agent and thus supports the view that the 6B12 antibody is a promising therapeutic candidate to fight cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1034-2) contains supplementary material, which is available to authorized users.

Modules, networks and systems medicine for understanding disease and aiding diagnosis

Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms. For example, in allergy a module was used to find a novel candidate gene that was validated by functional and clinical studies. Such analyses play important roles in systems medicine. This is an emerging discipline that aims to gain a translational understanding of the complex mechanisms underlying common diseases. In this review, we will explain and provide examples of how network-based analyses of omics data, in combination with functional and clinical studies, are aiding our understanding of disease, as well as helping to prioritize diagnostic markers or therapeutic candidate genes. Such analyses involve significant problems and limitations, which will be discussed. We also highlight the steps needed for clinical implementation.

Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment

Background

Translational research typically aims to identify and functionally validate individual, disease-specific genes. However, reaching this aim is complicated by the involvement of thousands of genes in common diseases, and that many of those genes are pleiotropic, that is, shared by several diseases.

Methods

We integrated genomic meta-analyses with prospective clinical studies to systematically investigate the pathogenic, diagnostic and therapeutic roles of pleiotropic genes. In a novel approach, we first used pathway analysis of all published genome-wide association studies (GWAS) to find a cell type common to many diseases.

Results

The analysis showed over-representation of the T helper cell differentiation pathway, which is expressed in T cells. This led us to focus on expression profiling of CD4⁺ T cells from highly diverse inflammatory and malignant diseases. We found that pleiotropic genes were highly interconnected and formed a pleiotropic module, which was enriched for inflammatory, metabolic and proliferative pathways. The general relevance of this module was supported by highly significant enrichment of genetic variants identified by all GWAS and cancer studies, as well as known diagnostic and therapeutic targets. Prospective clinical studies of multiple sclerosis and allergy showed the importance of both pleiotropic and disease specific modules for clinical stratification.

Conclusions

In summary, this translational genomics study identified a pleiotropic module, which has key pathogenic, diagnostic and therapeutic roles.