Calcyclin-binding protein contributes to cholangiocarcinoma progression by inhibiting ubiquitination of MCM2.

Background: Cholangiocarcinoma (CCA) represents the epithelial cell cancer with high aggressiveness whose five-year survival rate is poor with standard treatment. Calcyclin-binding protein (CACYBP) shows aberrant expression within several malignant tumors, but the role of CACYBP in CCA remains unknown. Methods: Immunohistochemical (IHC) analysis was used to identify CACYBP overexpression in clinical samples of CCA patients. Moreover, its correlation with clinical outcome was revealed. Furthermore, CACYBP's effect on CCA cell growth and invasion was investigated in vitro and in vivo using loss-of-function experiments. Results: CACYBP showed up-regulation in CCA, which predicts the dismal prognostic outcome. CACYBP had an important effect on in-vitro and in-vivo cancer cell proliferation and migration. Additionally, knockdown of CACYBP weakened protein stability by promoting ubiquitination of MCM2. Accordingly, MCM2 up-regulation partly reversed CACYBP deficiency's inhibition against cancer cell viability and invasion. Thus, MCM2 might drive CCA development by Wnt/ß-catenin pathway. Conclusions: CACYBP exerted a tumor-promoting role in CCA by suppressing ubiquitination of MCM2 and activating Wnt/ß-catenin pathway, hence revealing that it may be the possible therapeutic target for CCA treatment.

A novel machine learning derived RNA-binding protein gene-based score system predicts prognosis of hepatocellular carcinoma patients.

BACKGROUND: Although the expression of RNA-binding protein (RBP) genes in hepatocellular carcinoma (HCC) varies and is associated with tumor progression, there has been no overview study with multiple cohorts and large samples. The HCC-associated RBP genes need to be more accurately identified, and their clinical application value needs to be further explored. METHODS: First, we used the robust rank aggregation (RRA) algorithm to extract HCC-associated RBP genes from nine HCC microarray datasets and verified them in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and International Cancer Genome Consortium (ICGC) Japanese liver cancer (ICGC-LIRI-JP) cohort. In addition, the copy number variation (CNV), single-nucleotide variant (SNV), and promoter-region methylation data of HCC-associated RBP genes were analyzed. Using the random forest algorithm, we constructed an RBP gene-based prognostic score system (RBP-score). We then evaluated the ability of RBP-score to predict the prognosis of patients. The relationships between RBP-score and other clinical characteristics of patients were analyzed. RESULTS: The RRA algorithm identified 30 RBP mRNAs with consistent expression patterns across the nine HCC microarray datasets. These 30 RBP genes were defined as HCC-associated RBP genes. Their mRNA expression patterns were further verified in the TCGA-LIHC and ICGC-LIRI-JP cohorts. Among these 30 RBP genes, some showed significant copy number gain or loss, while others showed differences in the methylation levels of their promoter regions. Some RBP genes were risk factors or protective factors for the prognosis of patients. We extracted 10 key HCC-associated RBP genes using the random forest algorithm and constructed an RBP-score system. RBP-score effectively predicted the overall survival (OS) and disease-free survival (DFS) of HCC patients and was associated with the tumor, node, metastasis (TNM) stage, α-fetoprotein (AFP), and metastasis risk. The clinical value of RBP-score was validated in datasets from different platforms. Cox analysis suggested that a high RBP-score was an independent risk factor for poor prognosis in HCC patients. We also successfully established a combined RBP-score+TNM LASSO-Cox model that more accurately predicted the prognosis. CONCLUSION: The RBP-score system constructed based on HCC-associated RBP genes is a simple and highly effective prognostic evaluation tool. It is suitable for different subgroups of HCC patients and has cross-platform characteristics. Combining RBP-score with the TNM staging system or other clinical parameters can lead to an even greater clinical benefit. In addition, the identified HCC-associated RBP genes may serve as novel targets for HCC treatment.