Secretomic analysis of extracellular vesicles originating from polyomavirus-negative and polyomavirus-positive Merkel cell carcinoma cell lines.

Extracellular vesicles or exosomes constitute an evolutionarily conserved mechanism of intercellular signaling. Exosomes are gaining an increasing amount of attention due to their role in pathologies, including malignancy, their importance as prognostic and diagnostic markers, and their potential as a therapeutic tool. Merkel cell carcinoma (MCC) is an aggressive form of skin cancer with a poor prognosis. Because an effective systemic treatment for this cancer type is currently not available, an exosome-based therapy was proposed. However, comprehensive secretome profiling has not been performed for MCC. To help unveil the putative contribution of exosomes in MCC, we studied the protein content of MCC-derived exosomes. Since approximately 80% of all MCC cases contain Merkel cell polyomavirus (MCPyV), the secretomes of two MCPyV-negative and two MCPyV-positive MCC cell lines were compared. We identified with high confidence 164 exosome-derived proteins common for all four cell lines that were annotated in ExoCarta and Vesiclepedia databases. These include proteins implicated in motility, metastasis and tumor progression, such as integrins and tetraspanins, intracellular signaling molecules, chaperones, proteasomal proteins, and translation factors. Additional virus-negative and virus-positive MCC cell lines should be examined to identify highly representative exosomal proteins that may provide reliable prognostic and diagnostic biomarkers, as well as targets for treatment in the future. Data are available via ProteomeXchange with identifier PXD004198.

S6 kinase signaling: tamoxifen response and prognostic indication in two breast cancer cohorts.

Detection of signals in the mammalian target of rapamycin (mTOR) and the estrogen receptor (ER) pathways may be a future clinical tool for the prediction of adjuvant treatment response in primary breast cancer. Using immunohistological staining, we investigated the value of the mTOR targets p70-S6 kinase (S6K) 1 and 2 as biomarkers for tamoxifen benefit in two independent clinical trials comparing adjuvant tamoxifen with no tamoxifen or 5 years versus 2 years of tamoxifen treatment. In addition, the prognostic value of the S6Ks was evaluated. We found that S6K1 correlated with proliferation, HER2 status, and cytoplasmic AKT activity, whereas high protein expression levels of S6K2 and phosphorylated (p) S6K were more common in ER-positive, and low-proliferative tumors with pAKT-s473 localized to the nucelus. Nuclear accumulation of S6K1 was indicative of a reduced tamoxifen effect (hazard ratio (HR): 1.07, 95% CI: 0.53-2.81, P=0.84), compared with a significant benefit from tamoxifen treatment in patients without tumor S6K1 nuclear accumulation (HR: 0.42, 95% CI: 0.29-0.62, P<0.00001). Also S6K1 and S6K2 activation, indicated by pS6K-t389 expression, was associated with low benefit from tamoxifen (HR: 0.97, 95% CI: 0.50-1.87, P=0.92). In addition, high protein expression of S6K1, independent of localization, predicted worse prognosis in a multivariate analysis, P=0.00041 (cytoplasm), P=0.016 (nucleus). In conclusion, the mTOR-activated kinases S6K1 and S6K2 interfere with proliferation and response to tamoxifen. Monitoring their activity and intracellular localization may provide biomarkers for breast cancer treatment, allowing the identification of a group of patients less likely to benefit from tamoxifen and thus in need of an alternative or additional targeted treatment.

A validated gene regulatory network and GWAS identifies early regulators of T cell-associated diseases.

Early regulators of disease may increase understanding of disease mechanisms and serve as markers for presymptomatic diagnosis and treatment. However, early regulators are difficult to identify because patients generally present after they are symptomatic. We hypothesized that early regulators of T cell-associated diseases could be found by identifying upstream transcription factors (TFs) in T cell differentiation and by prioritizing hub TFs that were enriched for disease-associated polymorphisms. A gene regulatory network (GRN) was constructed by time series profiling of the transcriptomes and methylomes of human CD4(+) T cells during in vitro differentiation into four helper T cell lineages, in combination with sequence-based TF binding predictions. The TFs GATA3, MAF, and MYB were identified as early regulators and validated by ChIP-seq (chromatin immunoprecipitation sequencing) and small interfering RNA knockdowns. Differential mRNA expression of the TFs and their targets in T cell-associated diseases supports their clinical relevance. To directly test if the TFs were altered early in disease, T cells from patients with two T cell-mediated diseases, multiple sclerosis and seasonal allergic rhinitis, were analyzed. Strikingly, the TFs were differentially expressed during asymptomatic stages of both diseases, whereas their targets showed altered expression during symptomatic stages. This analytical strategy to identify early regulators of disease by combining GRNs with genome-wide association studies may be generally applicable for functional and clinical studies of early disease development.

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

The identification of diagnostic markers and therapeutic candidate genes in common diseases is complicated by the involvement of thousands of genes. We hypothesized that genes co-regulated with a key gene in allergy, IL13, would form a module that could help to identify candidate genes. We identified a T helper 2 (TH2) cell module by small interfering RNA-mediated knockdown of 25 putative IL13-regulating transcription factors followed by expression profiling. The module contained candidate genes whose diagnostic potential was supported by clinical studies. Functional studies of human TH2 cells as well as mouse models of allergy showed that deletion of one of the genes, S100A4, resulted in decreased signs of allergy including TH2 cell activation, humoral immunity, and infiltration of effector cells. Specifically, dendritic cells required S100A4 for activating T cells. Treatment with an anti-S100A4 antibody resulted in decreased signs of allergy in the mouse model as well as in allergen-challenged T cells from allergic patients. This strategy, which may be generally applicable to complex diseases, identified and validated an important diagnostic and therapeutic candidate gene in allergy.