How organ size is controlled in mammals is not currently understood. In Drosophila the Hippo signaling pathway functions to suppress growth in imaginal discs and has been suggested to control organ size. To investigate the role of hippo signaling in regulation of mammalian organ size we have generated conditional alleles of Sav1 , mst1 , and mst2 , orthologs of Drosophila Salvador and hippo , respectively. Specific deletion of both mst1 and mst2 in hepatocytes results in significantly enlarged livers due to excessive proliferation. By the age of 5–6 months, mst1/2 conditional mutant livers have multiple foci of liver tumors, indicating that the combined activities of mst1 and mst2 act as redundant tumor suppressors in hepatocytes. Similar findings were obtained with liver-specific deletion of Sav1 , a second core Hippo signaling component that facilitates activation of mst1 and mst2 . Tumors from sav1 mutants exhibited varied morphology, suggesting a mixed-lineage origin of tumor-initiating cells. Transcriptional profiling of liver tissues from both mst1/2 and sav1 conditional mutants revealed a network of Hippo signaling regulated genes with specific enrichment for genes involved in immune and inflammatory responses. Histological and immunological characterization of mst1/2 double mutant liver tissues revealed abundant accumulation of adult facultative stem cells termed oval cells in periductal regions. Because oval cells induction is commonly associated with liver injury and tumor formation, it is likely that these cells contribute to the enlarged livers and hepatomas that we observe in sav1 and mst1/2 mutants. Taken together, our results demonstrate that the Hippo signaling pathway is a critical regulator of mammalian liver growth and a potent suppressor of liver tumor formation.

Purpose: Despite continual efforts to develop a prognostic model of gastric cancer by using clinical and pathologic parameters, a clinical test that can discriminate patients with good outcomes from those with poor outcomes after gastric cancer surgery has not been established. We aim to develop practical biomarker-based risk score that can predict relapse of gastric cancer after surgical treatment.Experimental Design: Microarray technologies were used to generate and analyze gene expression profiling data from 65 gastric cancer patients to identify biomarker genes associated with relapse. The association of expression patterns of identified genes with relapse and overall survival was validated in independent gastric cancer patients.Results: We uncovered two subgroups of gastric cancer that were strongly associated with the prognosis. For the easy translation of our findings into practice, we developed a scoring system based on the expression of six genes that predicted the likelihood of relapse after curative resection. In multivariate analysis, the risk score was an independent predictor of relapse in a cohort of 96 patients. We were able to validate the robustness of the six-gene signature in an additional independent cohort.Conclusions: The risk score derived from the six-gene set successfully prognosticated the relapse of gastric cancer patients after gastrectomy.