ANCA-associated vasculitis is the most frequent cause of crescentic GN. To define new molecular and/or cellular biomarkers of this disease in the kidney, we performed microarray analyses of renal biopsy samples from patients with ANCA-associated crescentic GN. Expression profiles were correlated with clinical data in a prospective study of patients with renal ANCA disease. CC chemokine ligand 18 (CCL18), acting through CC chemokine receptor 8 (CCR8) on mononuclear cells, was identified as the most upregulated chemotactic cytokine in patients with newly diagnosed ANCA-associated crescentic GN. Macrophages and myeloid dendritic cells in the kidney were detected as CCL18-producing cells. The density of CCL18 + cells correlated with crescent formation, interstitial inflammation, and impairment of renal function. CCL18 protein levels were higher in sera of patients with renal ANCA disease compared with those in sera of patients with other forms of crescentic GN. CCL18 serum levels were higher in patients who suffered from ANCA-associated renal relapses compared with those in patients who remained in remission. Using a murine model of crescentic GN, we explored the effects of the CCL18 murine functional analog CCL8 and its receptor CCR8 on kidney function and morphology. Compared with wild-type mice, Ccr8 2/2 mice had significantly less infiltration of pathogenic mononuclear phagocytes. Furthermore, Ccr8 2/2 mice maintained renal function better and had reduced renal tissue injury. In summary, our data indicate that CCL18 drives renal inflammation through CCR8-expressing cells and could serve as a biomarker for disease activity and renal relapse in ANCA-associated crescentic GN.
Mouse models are important tools to decipher the molecular mechanisms of mammary carcinogenesis and to mimic the respective human disease. Despite sharing common phenotypic and genetic features, the proper translation of murine models to human breast cancer remains a challenging task. In a previous study we showed that in the SV40 transgenic WAP-T mice an active Met-pathway and epithelial-mesenchymal characteristics distinguish low-and high-grade mammary carcinoma. To assign these murine tumors to corresponding human tumors we here incorporated the analysis of expression of transcription factor (TF) coding genes and show that thereby a more accurate interspecies translation can be achieved. We describe a novel cross-species translation procedure and demonstrate that expression of unsupervised selected TFs, such as ELF5, HOXA5 and TFCP2L1, can clearly distinguish between the human molecular breast cancer subtypes-or as, for example, expression of TFAP2B between yet unclassified subgroups. By integrating different levels of information like histology, gene set enrichment, expression of differentiation markers and TFs we conclude that tumors in WAP-T mice exhibit similarities to both, human basal-like and non-basal-like subtypes. We furthermore suggest that the low-and high-grade WAP-T tumor phenotypes might arise from distinct cells of tumor origin. Our results underscore the importance of TFs as common cross-species denominators in the regulatory networks underlying mammary carcinogenesis.Breast cancer is the most often diagnosed tumor disease of women worldwide. Despite significant progress in early diagnosis and therapy, the mortality of breast cancer patients remains high, underscoring the need for novel therapeutic approaches and preclinical mouse models. 1 An important prerequisite for the development of new targeted therapies is an understanding of the molecular pathways leading to breast cancer development and progression. Such understanding is complicated by the histopathological, molecular and clinical heterogeneity of breast cancer. 2 Genetically engineered mouse models (GEMM) are a valuable resource for examining breast cancer in genetically defined, immune-competent environments. GEMM provide important tools for gaining insight into the molecular biology of breast cancer and the relationship to morphology and clinical behavior. They facilitate to identify influences of specific individual molecular factors and pathways on breast cancer development and progression-information that is difficult to obtain from retrospective analyses of human tumor samples. The limitations of GEMM are species-specific differences in mammary gland biology impeding a seamless translation of the GEMM derived insights to the human disease. Traditionally, the match of breast cancer phenotypes across different species -mouse model to human disease-is led by histology, expression of differentiation markers (e.g., cytokeratins) and of defined ''intrinsic'' gene expression signatures such as proliferation, stem cell or mesenchymal...
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