Fibroblasts are important participants in inflammation. Although not leukocytes, their capacity to produce cytokines, chemokines, and other inflammatory factors locally in tissues suggests that they can contribute to inflammatory diseases. For example, fibroblasts in a rheumatoid arthritis (RA) joint are a dominant source of IL-6 and RANKL in the synovium, both of which are therapeutic targets for inflammation and bone erosion. Previously, we found that fibroblasts can be targeted by mAb directed against cadherin-11 (cad-11), a mesenchymal cadherin that fibroblasts selectively express. Targeting cad-11 significantly reduced inflammation as assessed by joint swelling and clinical inflammation scores. However, the mechanism by which anti–cad-11 reduced inflammation was not known. Here, we show that cad-11 engagement induces synovial fibroblasts to secret proinflammatory cytokines including IL-6. Cad-11 engagement strongly synergized with TNF-α and IL-1β in the induction of IL-6. Importantly, cad-11 activated MAP kinases and NF-κB for IL-6 induction. IL-6 levels in ankles of inflamed joints were reduced in cad-11 mutant mice compared to wild-type mice with inflammatory arthritis. Thus, we suggest that cad-11 modulates synovial fibroblasts to evoke inflammatory factors that may contribute to the inflammatory process in RA.

Tumor angiogenesis is essential for cancer growth and provides an attractive target for oncologic therapies. CT perfusion is an emerging imaging tool that provides both qualitative and quantitative information regarding tumor angiogenesis.

The accuracy in the diagnosis of metastatic colorectal cancer (mCRC) represents one of the challenges in the clinical management of patients. The detection of circulating tumour cells (CTC) is becoming a promising alternative to current detection techniques, as it focuses on one of the players of the metastatic disease and it should provide with more specific and sensitive detection rates. Here, we describe an improved method of detection of CTC from mCRC patients by combining immune-enrichment, optimal purification of RNA from very low cell numbers, and the selection of accurate PCR probes. As a result, we obtained a logistic model that combines GAPDH and VIL1 normalized to CD45 rendering powerful results in the detection of CTC from mCRC patients (AUROC value 0.8599). We further demonstrated the utility of this model at the clinical setting, as a reliable prognosis tool to determine progression-free survival in mCRC patients. Overall, we developed a strategy that ameliorates the specificity and sensitivity in the detection of CTC, resulting in a robust and promising logistic model for the clinical management of metastatic colorectal cancer patients.