Combined inhibition of IL-1, IL-33 and IL-36 signalling by targeting IL1RAP ameliorates skin and lung fibrosis in preclinical models of systemic sclerosis.

BACKGROUND: The interleukin (IL)-1 receptor accessory protein (IL1RAP) is an essential coreceptor required for signalling through the IL-1, IL-33 and IL-36 receptors. Here, we investigate the antifibrotic potential of the combined inhibition of these cytokines by an anti-IL1RAP antibody to provide a scientific background for clinical development in systemic sclerosis (SSc). METHODS: The expression of IL1RAP-associated signalling molecules was determined by data mining of publicly available RNA sequencing (RNAseq) data as well as by imaging mass cytometry. The efficacy of therapeutic dosing of anti-IL1RAP antibodies was determined in three complementary mouse models: sclerodermatous chronic graft-versus-host disease (cGvHD), bleomycin-induced dermal fibrosis model and topoisomerase-I (topo)-induced fibrosis. RESULTS: SSc skin showed upregulation of IL1RAP and IL1RAP-related signalling molecules on mRNA and protein level compared with normal skin. IL-1, IL-33 and IL-36 all regulate distinct gene sets related to different pathophysiological processes in SSc. The responses of human fibroblasts and endothelial cells to IL-1, IL-33 and IL-36 were completely blocked by treatment with an anti-IL1RAP antibody in vitro. Moreover, anti-IL1RAP antibody treatment reduced dermal and pulmonary fibrosis in cGvHD-induced, bleomycin-induced and topoisomerase-induced fibrosis. Importantly, RNAseq analyses revealed effects of IL1RAP inhibition on multiple processes related to inflammation and fibrosis that are also deregulated in human SSc skin. CONCLUSION: This study provides the first evidence for the therapeutic benefits of targeting IL1RAP in SSc. Our findings have high translational potential as the anti-IL1RAP antibody CAN10 has recently entered a phase one clinical trial.

Tumor tissue protein signatures reflect histological grade of breast cancer.

Histological grade is one of the most commonly used prognostic factors for patients diagnosed with breast cancer. However, conventional grading has proven technically challenging, and up to 60% of the tumors are classified as histological grade 2, which represents a heterogeneous cohort less informative for clinical decision making. In an attempt to study and extend the molecular puzzle of histologically graded breast cancer, we have in this pilot project searched for additional protein biomarkers in a new space of the proteome. To this end, we have for the first time performed protein expression profiling of breast cancer tumor tissue, using recombinant antibody microarrays, targeting mainly immunoregulatory proteins. Thus, we have explored the immune system as a disease-specific sensor (clinical immunoproteomics). Uniquely, the results showed that several biologically relevant proteins reflecting histological grade could be delineated. In more detail, the tentative biomarker panels could be used to i) build a candidate model classifying grade 1 vs. grade 3 tumors, ii) demonstrate the molecular heterogeneity among grade 2 tumors, and iii) potentially re-classify several of the grade 2 tumors to more like grade 1 or grade 3 tumors. This could, in the long-term run, lead to improved prognosis, by which the patients could benefit from improved tailored care.

A Multicenter Trial Defining a Serum Protein Signature Associated with Pancreatic Ductal Adenocarcinoma.

Background. Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with rapid tumor progression and poor prognosis. This study was motivated by the lack of sensitive and specific PDAC biomarkers and aimed to identify a diagnostic, serum protein signature for PDAC. Methods. To mimic a real life test situation, a multicenter trial comprising a serum sample cohort, including 338 patients with either PDAC or other pancreatic diseases (OPD) and controls with nonpancreatic conditions (NPC), was analyzed on 293-plex recombinant antibody microarrays targeting immunoregulatory and cancer-associated antigens. Results. Serum samples collected from different hospitals were analyzed and showed that (i) sampling from five different hospitals could not be identified as a preanalytical variable and (ii) a multiplexed biomarker signature could be identified, utilizing up to 10 serum markers that could discriminate PDAC from controls, with sensitivities and specificities in the 91-100% range. The first protein profiles associated with the location of the primary tumor in the pancreas could also be identified. Conclusions. The results demonstrate that robust enough serum signatures could be identified in a multicenter trial, potentially contributing to the development of a multiplexed biomarker immunoassay for improved PDAC diagnosis.