Wiest, Matthew

Abstract Expression of macrophage receptor with collagenous structure (MARCO) by tumor-associated macrophages is associated with poor prognosis of multiple types of cancer. In this article, we report that cancer cells (e.g., breast cancer and glioblastoma cell lines) can upregulate surface MARCO expression on human macrophages not only via IL-6–induced STAT3 activation but also via sphingosine-1-phosphate receptor (S1PR)-mediated IL-6 and IL-10 expression followed by STAT3 activation. We further found that MARCO ligation induces activation of the MEK/ERK/p90RSK/CREB signaling cascade, leading to IL-10 expression followed by STAT3-dependent PD-L1 upregulation. Such MARCO-induced macrophage polarization is accompanied by increased expression of PPARG, IRF4, IDO1, CCL17, and CCL22. Ligation of surface MARCO can thus result in decreased T cell responses mainly by reduction of their proliferation. Taken together, cancer cell–induced MARCO expression and its intrinsic regulatory function within macrophages are, to our knowledge, new aspects of cancer immune evasion mechanisms that need to be further studied in the future.

Abstract Background Anti‐IgE (omalizumab) has been used for the treatment of moderate‐to‐severe asthma that is not controlled by inhaled steroids. Despite its success, it does not always provide patients with significant clinical benefits. Objective To investigate the transcriptional variations between omalizumab responders and non‐responders and to study the mechanisms of action of omalizumab. Methods The whole blood transcriptomes of moderate‐to‐severe adult asthma patients (N = 45:34 responders and 11 non‐responders) were analysed over the course of omalizumab treatment. Non‐asthmatic healthy controls (N = 17) were used as controls. Results Transcriptome variations between responders and non‐responders were identified using the genes significant (FDR < 0.05) in at least one comparison of each patient response status and time point compared with control subjects. Using gene ontology and network analysis, eight clusters of genes were identified. Longitudinal analyses of individual clusters revealed that responders could maintain changes induced with omalizumab treatment and become more similar to the control subjects, while non‐responders tend to remain more similar to their pre‐treatment baseline. Further analysis of an inflammatory gene cluster revealed that genes associated with neutrophil/eosinophil activities were up‐regulated in non‐responders and, more importantly, omalizumab did not significantly alter their expression levels. The application of modular analysis supported our findings and further revealed variations between responders and non‐responders. Conclusion and Clinical Relevance This study provides not only transcriptional variations between omalizumab responders and non‐responders, but also molecular insights for controlling asthma by omalizumab.