The high death rate of pancreatic cancer is attributed to the lack of reliable methods for early detection and underlying molecular mechanisms of its aggressive pathogenesis. Although MUC13, a newly identified transmembrane mucin, is known to be aberrantly expressed in ovarian and gastro-intestinal cancers, its role in pancreatic cancer is unknown. Herein, we investigated the expression profile and functions of MUC13 in pancreatic cancer progression. The expression profile of MUC13 in pancreatic cancer was investigated using a recently generated monoclonal antibody (clone PPZ0020) and pancreatic tissue microarrays. The expression of MUC13 was significantly (P < 0.005) higher in cancer samples compared with normal/nonneoplastic pancreatic tissues. For functional analyses, full-length MUC13 was expressed in MUC13 null pancreatic cancer cell lines, MiaPaca and Panc1. MUC13 overexpression caused a significant (P < 0.05) increase in cell motility, invasion, proliferation, and anchorage-dependent or -independent clonogenicity while decreasing cell–cell and cell-substratum adhesion. Exogenous MUC13 expression significantly (P < 0.05) enhanced pancreatic tumor growth and reduced animal survival in a xenograft mouse model. These tumorigenic characteristics correlated with the upregulation/phosphorylation of HER2, p21-activated kinase 1 (PAK1), extracellular signal-regulated kinase (ERK), Akt, and metastasin (S100A4), and the suppression of p53. Conversely, suppression of MUC13 in HPAFII pancreatic cancer cells by short hairpin RNA resulted in suppression of tumorigenic characteristics, repression of HER2, PAK1, ERK, and S100A4, and upregulation of p53. MUC13 suppression also significantly (P < 0.05) reduced tumor growth and increased animal survival. These results imply a role of MUC13 in pancreatic cancer and suggest its potential use as a diagnostic and therapeutic target.

MUC13, a transmembrane mucin, is normally expressed in gastrointestinal and airway epithelium. Its aberrant expression has been correlated with gastric colon and cancer. However, the expression and functions of MUC13 in ovarian cancer are unknown. In the present study, the expression profile and functions of MUC13 were analyzed to elucidate its potential role in ovarian cancer diagnosis and pathogenesis. A recently generated monoclonal antibody (clone PPZ0020) was used to determine the expression profile of MUC13 by immunohistochemistry using ovarian cancer tissue microarrays and 56 additional epithelial ovarian cancer (EOC) samples. The expression of MUC13 was significantly (P < 0.005) higher in cancer samples compared with the normal ovary/benign tissues. Among all ovarian cancer types, MUC13 expression was specifically present in EOC. For the functional analyses, a full-length MUC13 gene cloned in pcDNA3.1 was expressed in a MUC13 null ovarian cancer cell line, SKOV-3. Here, we show that the exogenous MUC13 expression induced morphologic changes, including scattering of cells. These changes were abrogated through c-Jun NH 2 kinase (JNK) chemical inhibitor (SP600125) or JNK2 siRNA. Additionally, a marked reduction in cell-cell adhesion and significant (P < 0.05) increases in cell motility, proliferation, and tumorigenesis in a xenograft mouse model system were observed upon exogenous MUC13 expression. These cellular characteristics were correlated with up-regulation of HER2, p21-activated kinase 1, and p38 protein expression. Our findings show the aberrant expression of MUC13 in ovarian cancer and that its expression alters the cellular characteristics of SKOV-3 cells. This implies a significant role of MUC13 in ovarian cancer.

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In this article, acceptance sampling plans are developed for the Burr type XII distribution percentiles when the life test is truncated at a pre-specified time. The minimum sample size necessary to ensure the specified life percentile is obtained under a given customer's risk. The operating characteristic values (tables) of the sampling plans as well as producer's risk are presented. The R package named spBurr is developed to implement the sampling plans. Two real datasets regarding the oil breakdown of an insulating fluid under high test voltage and the first failure times of small electric carts used for internal transportation and delivery are given as illustration.

The problem of detecting a shift in the percentile of a Birnbaum-Saunders population in a process monitoring situation is considered. For example, such problems may arise when the quality characteristic of interest is tensile strength or breaking stress. The parametric bootstrap method is used to develop a quality control chart for monitoring percentiles when process measurements have a Birnbaum-Saunders distribution. Through extensive Monte Carlo simulations, we investigate the behavior and performance of the proposed bootstrap percentile charts. Average run lengths of the proposed percentile chart are also investigated. Illustrative examples with the data concerning the tensile strength of the aluminum sheeting are presented. Copyright

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