Increasing evidence has shown that CXCL1, 2, and 8 are frequently elevated in many types of human cancers, including pancreatic cancer. In addition, therapies targeting CXCL1, 2, and 8 in the treatment of cancers have been reported, and the down-regulation of CXCL1, 2, and 8 inhibited the invasion of tumor cells. Using in vitro function assays, we demonstrated that CAFs exhibit increased CXCL1, 2 and 8 expression in pancreatic cancer, contributing to the enhanced invasion-promoting capacity of these cells. Therefore, targeting CXC chemokine TMI 1 signaling between CAF and cancer cells through pharmacological inhibition might provide a promising therapy for pancreatic cancer. The results obtained in the present study showed that Chinese herbal medicine QYHJ could significant suppress the production of CAF-derived CXCL1, 2 and 8, thereby preventing pancreatic cancer cell invasion. Thus, in this study, we have demonstrated that CAFs exhibited an enhanced capacity for inducing pancreatic cancer cell migration and invasion compared with NFs, while QYHJ-treated CAFs exhibited decreased migration and invasion-promoting capacities in vitro. In addition, we showed that QYHJ significantly suppressed CAF proliferation activities and the production of CAF-derived CXCL1, 2 and 8. Taken together, these results suggested that suppressing the tumor-promoting capacity of CAFs through Chinese herbal medicine attenuates pancreatic cancer cell invasion. As powerful tools for facilitating the SB 204741 discovery of totally novel and unexpected functional roles of genes, gene expression microarrays have been applied to a range of applications in biomedical research and produce a large number of databanks containing various amounts of hidden biological information. The key resides in the ability to analyze large amounts of data to detect a panel of genes capable of discriminating diseases. This study proposed a modeling framework for establishing a robust classification model, for identification of disease-related genes. We utilized the proposed modeling approach for identification of genes involved in multiple sclerosis. Multiple sclerosis is characterized as an inflammatory disorder of the central nervous system in which focal lymphocytic infiltration leads to damage of myelin and axons. The trigger for multiple sclerosis is unclear so far, although it is generally evaluated as an autoimmune disease. At present the diagnosis of multiple sclerosis usually involves the tests of lumbar puncture or magnetic resonance imaging scan of the brain function. The diagnostic ways are either clinically invasive or expensive for multiple sclerosis patients.