BackgroundOvarian cancer is a common type of malignant neoplasm. Its prognosis is poor because the disease is not well understood. Abnormal lipometabolism in peroxisomes is involved in tumor progression and hydroxysteroid dehydrogenase-like 2 (HSDL2), localized in peroxisomes, might be a regulatory factor in lipometabolism. However, the role of HSDL2 in ovarian cancer progression remains unknown.Material/MethodsHSDL2 expression was detected by qPCR and immunohistochemistry in ovarian tumor samples and qPCR in human ovarian cancer cell lines. Cell proliferation was measured by Celigo and MTT assay. Cell cycle distribution and apoptosis were determined using flow cytometry. Giemsa staining was used for analyzing colony formation. Cell motility was performed using Transwell migration and invasion assays. Tumorigenesis in nude mice was also detected.ResultsHSDL2 expression was upregulated in human ovarian cancer samples and in 3 human ovarian cancer cell lines: SKOV3, HO8910, and OVCAR-3. Higher expression of HSDL2 in ovarian tumor samples was associated with more progressed tumors (P=0.03) and lymphatic metastases (P=0.03). HSDL2 down-regulation by lentiviral-mediated HSDL2 knockdown suppressed cell proliferation, colony formation, and cell motility, while it promoted cell apoptosis and resulted in cell cycle arrest at the G0/G1 phase in human ovarian cancer cell lines OVCAR-3 and SKOV3. HSDL2 knockdown also inhibited tumorigenesis in mouse models.ConclusionsThis study shows that HSDL2 upregulation is associated with ovarian cancer progression. HSDL2 knockdown inhibited cell proliferation, colony formation, motility, and tumorigenesis. It induced apoptosis and cell cycle arrest and might therefore serve as a potential target for ovarian cancer therapy.
AIM: To investigate the relationship between inactivation of p16 gene and gastric carcinoma, and the mechanism of inactivation of p16 gene in gastric carcinogenesis. METHODS:40 fresh tumor tissue specimens were taken from primary gastric cancer patients. Expression of P16 protein was detected by immunohistochemical method. Deletion and point mutation of p16 gene were analyzed by polymerase chain reaction (PCR) and DNA sequencing, respectively. RESULTS:The frequency of loss of P16 protein expression in the gastric cancer tissue, adjacent nontumor tissue, and distal normal tissue was 77.5 % (31/40), 55.0 % (22/40), and 17.5 % (7/40), respectively (P<0.005). Homozygous deletion of exon 1 and exon 3 was observed in two and three cases, respectively, giving an overall frequency of homozygous deletion of 12.5 %. All five cases had diffuse type gastric carcinoma. No p16 gene point mutation was detected. CONCLUSION:
As an effective biclustering model, order-preserving submatrix (OPSM) has been widely applied to biological gene expression data mining, which can capture the general tendency of the gene expression under some experimental conditions. Recently, biologists hope to find deep OPSMs with long patterns and comparatively fewer support rows, which are important for the interpretation of gene regulatory networks. However, the traditional exact mining algorithms based on Apriori principle could not deal with the deep OPSM problem, which often take a large minimum support threshold for pattern pruning, and inevitably miss some significant deep OPSMs. In this paper, a new exact algorithm is proposed for mining deep OPSMs. Firstly all the common subsequences shared by every two rows are found out, then the row sets corresponding to the same common subsequences are formed. Finally all the deep OPSMs with support beyond the given threshold will be obtained. Experiments have been done in both real and synthetic data sets, and the results show that this new algorithm is capable of mining all the deep OPSMs over a small support. Under different thresholds of minimum support, this algorithm reveals better performance than the traditional sequential pattern mining algorithms.
Salvianolic acid B (Sal B) has previously reported anti-hepatic fibrosis effects, though it is not clear if it can inhibit hepatic fibrosis by regulating the hedgehog (Hh) signaling pathway. The aim of the present study was to explore the roles and mechanism of Sal B in preventing and treating liver fibrosis in rats. The study also aimed to determine the role of the Hh signaling pathway in this process. A rat model of liver fibrosis was induced through the subcutaneous injection of 50% carbon tetrachloride, followed by treatment with Sal B. After gavage, blood was collected to detect serum markers of liver injury. The degree of liver fibrosis and tissue damage was assessed using histopathological analysis. Western blotting and reverse transcription-quantitative PCR were used to detect the expression levels of TGF-β1 and Hh signaling pathway-related genes, including Sonic hedgehog (Shh) protein, membrane protein receptor protein patched homolog 1 (Ptch1), membrane protein receptor Smoothened (Smo) and transcription factor glioma-associated oncogene homolog 1 (Gli1). Serum alanine aminotransferase, aspartate aminotransferase and total bilirubin levels were decreased, whilst levels of albumin were increased in rats with liver fibrosis that were treated with Sal B (P<0.05). Additionally, significant increases in TGF-β1, Shh, Ptch1, Smo, Gli1 and α-smooth muscle actin expression levels were observed in the liver tissues of rats with hepatic fibrosis (P<0.05). However, Sal B treatment significantly reduced the expression levels of these proteins (P<0.05). In conclusion, the results of the present study suggested that the Hh signaling pathway may be activated during the process of rat liver fibrosis. Thus, Sal B may exert its anti-hepatic fibrosis effects, at least in part, by inhibiting the activation of the Hh signaling pathway.
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