Pescadillo is a nucleolar protein that has been suggested to be involved in embryonic development and ribosome biogenesis. Deregulated expression of human pescadillo (PES1) was described in some tumors, but its precise roles in tumorigenesis remains unclear. In this study, we generated three monoclonal antibodies recognizing PES1 with high specificity and sensitivity, with which PES1 expression in human colon cancer was analyzed immunohistochemically. Out of 265 colon cancer tissues, 89 (33.6%) showed positive PES1 expression, which was significantly higher than in non-cancerous tissues (P<0.001). Silencing of PES1 in colon cancer cells resulted in decreased proliferation, reduced growth of xenografts, and cell cycle arrest in G1 phase, indicating PES1 functions as an oncogene. We then explored the mechanism by which PES1 expression is controlled in human colon cancers and demonstrated that c-Jun, but not JunB, JunD, c-Fos, or mutant c-Jun, positively regulated PES1 promoter transcription activity. In addition, we mapped −274/−264 region of PES1 promoter as the c-Jun binding sequence, which was validated by chromatin immunoprecipitation and electrophoretic mobility shift assays. Moreover, we demonstrated a positive correlation between c-Jun and PES1 expression in colon cancer cells and colon cancer tissues. Upstream of c-Jun, it was revealed that c-Jun NH2-terminal kinases (JNK) is essential for controlling PES1 expression. Our study, in the first place, uncovers the oncogenic role of PES1 in colon cancer and elucidates the molecular mechanism directing PES1 expression.

Although gastric cancer is the second leading cause of cancer death worldwide, specific and sensitive biomarkers that can be used for its diagnosis are still unavailable. Attempting to improve on current approaches to the serological diagnosis of gastric cancer, we subjected serum samples from 245 individuals (including 127 gastric cancer patients, 100 age-and sex-matched healthy individuals, nine benign gastric lesion patients and nine colorectal cancer patients) for analysis by surface-enhanced laser desorption/ionization (SELDI) mass spectrometry. Peaks were detected with Ciphergen SELDI software version 3.1.1 and analyzed with Biomarker Patterns' software 5.0. We developed a classifier for separating the gastric cancer groups from the healthy groups. Three protein masses with 1468, 3935 and 7560 m/z were selected as a potential 'fingerprint' for the detection of gastric cancer. It was able to distinguish the gastric cancer patients from the health volunteers with a sensitivity of 95.6% and a specificity of 92.0% in the training set. In the blinding set, it was capable of differentiating the gastric cancer samples from the others with a specificity of 88.0%, a sensitivity of 85.3%, and an accuracy of 86.4%. These values were all higher than those achieved in a parallel analysis by measuring serum carcinoembryonic antigen (CEA) and carbohydrate antigen (CA)19-9 together. Therefore, the decision tree analysis of serum proteomic patterns has the potential to be used in gastric cancer diagnosis. (Cancer Sci 2007; 98: 37-43)

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