Connective tissue growth factor (CTGF) is a key signaling and regulatory molecule involved in different biological processes, such as cell proliferation, angiogenesis, and wound healing, as well as multiple pathologies, such as tumor development and tissue fibrosis. Although the underlying mechanisms of CTGF remain incompletely understood, a commonly accepted theory is that the interactions between different protein domains in CTGF and other various regulatory proteins and ligands contribute to its variety of functions. Here, we highlight the structure of each domain of CTGF and its biology functions in physiological conditions. We further summarized main diseases that are deeply influenced by CTGF domains and the potential targets of these diseases. Finally, we address the advantages and disadvantages of current drugs targeting CTGF and provide the perspective for the drug discovery of the next generation of CTGF inhibitors based on aptamers.

Duchenne muscular dystrophy (DMD) is a lethal, X-linked neuromuscular disorder caused by the absence of dystrophin protein, which is essential for muscle fiber integrity. Loss of dystrophin protein leads to recurrent myofiber damage, chronic inflammation, progressive fibrosis, and dysfunction of muscle stem cells. There is still no cure for DMD so far and the standard of care is principally limited to symptom relief through glucocorticoids treatments. Current therapeutic strategies could be divided into two lines. Dystrophin-targeted therapeutic strategies that aim at restoring the expression and/or function of dystrophin, including gene-based, cell-based and protein replacement therapies. The other line of therapeutic strategies aims to improve muscle function and quality by targeting the downstream pathological changes, including inflammation, fibrosis, and muscle atrophy. This review introduces the important developments in these two lines of strategies, especially those that have entered the clinical phase and/or have great potential for clinical translation. The rationale and efficacy of each agent in pre-clinical or clinical studies are presented. Furthermore, a meta-analysis of gene profiling in DMD patients has been performed to understand the molecular mechanisms of DMD.

Background Urothelial bladder cancer (BLCA) is one of the most common internal malignancies worldwide with poor prognosis. This study aims to explore effective prognostic biomarkers and construct a prognostic risk score model for patients with BLCA. Methods Weighted gene co-expression network analysis (WGCNA) was used for identifying the co-expression module related to the pathological stage of BLCA based on the RNA-Seq data retrieved from The Cancer Genome Atlas database. Prognostic biomarkers screened by Cox proportional hazard regression model and random forest were used to construct a risk score model that can predict the prognosis of patients with BLCA. The GSE13507 dataset was used as the independent testing dataset to test the performance of the risk score model in predicting the prognosis of patients with BLCA. Results WGCNA identified seven co-expression modules, in which the brown module consisted of 77 genes was most significantly correlated with the pathological stage of BLCA. Cox proportional hazard regression model and random forest identified TPST1 and P3H4 as prognostic biomarkers. Elevated TPST1 and P3H4 expressions were associated with the high pathological stage and worse survival. The risk score model based on the expression level of TPST1 and P3H4 outperformed pathological stage indicators and previously proposed prognostic models. Conclusion The gene co-expression network-based study could provide additional insight into the tumorigenesis and progression of BLCA, and our proposed risk score model may aid physicians in the assessment of the prognosis of patients with BLCA. Electronic supplementary material The online version of this article (10.1186/s41065-019-0100-1) contains supplementary material, which is available to authorized users.

Clinical studies in a range of cancers have detected elevated levels of the Wnt antagonist Dickkopf-1 (DKK1) in the serum or tumors of patients, and this was frequently associated with a poor prognosis. Our analysis of DKK1 gene profile using data from TCGA also proves the high expression of DKK1 in 14 types of cancers. Numerous preclinical studies have demonstrated the cancer-promoting effects of DKK1 in both in vitro cell models and in vivo animal models. Furthermore, DKK1 showed the ability to modulate immune cell activities as well as the immunosuppressive cancer microenvironment. Expression level of DKK1 is positively correlated with infiltrating levels of myeloid-derived suppressor cells (MDSCs) in 20 types of cancers, while negatively associated with CD8+ T cells in 4 of these 20 cancer types. Emerging experimental evidence indicates that DKK1 has been involved in T cell differentiation and induction of cancer evasion of immune surveillance by accumulating MDSCs. Consequently, DKK1 has become a promising target for cancer immunotherapy, and the mechanisms of DKK1 affecting cancers and immune cells have received great attention. This review introduces the rapidly growing body of literature revealing the cancer-promoting and immune regulatory activities of DKK1. In addition, this review also predicts that by understanding the interaction between different domains of DKK1 through computational modeling and functional studies, the underlying functional mechanism of DKK1 could be further elucidated, thus facilitating the development of anti-DKK1 drugs with more promising efficacy in cancer immunotherapy.