Patients undergoing abdominal surgery often develop delirium, which greatly influences their postoperative course of clinical recovery and length of hospital stay (LOS).^1-3 Delirium affects 13% to 50% of patients undergoing noncardiac surgery,⁴ and the health care costs attributable to delirium are more than $164 billion per year in the United States.^5,6 Older surgical patients (≥65 years of age) have a particularly high risk for developing delirium, with detrimental effects on their recovery.⁶ Delirium has been associated with alterations in cholinergic activity, inflammatory processes induced by neural signaling, and excessive depth of anesthesia and sedation.^7,8 Delirium may also be precipitated by factors such as infection, malnutrition, electrolyte and fluid imbalances, anemia, and social isolation.^4,9,10 Nevertheless, 30% to 40% of cases of delirium are preventable¹¹; thus, implementing effective interventions to prevent incident delirium and reduce LOS is a clinical priority.

Connective tissue growth factor (CTGF) expression is elevated in advanced stages of breast cancer, but the regulatory role of CTGF in invasive breast cancer cell phenotypes is unclear. Presently, overexpression of CTGF in MCF-7 cells (MCF-7/CTGF cells) enhanced cellular migratory ability and spindle-like morphological alterations, as evidenced by actin polymerization and focal-adhesion-complex aggregation. Reducing the CTGF level in MDA-MB-231 (MDA231) cells by antisense CTGF cDNA (MDA231/AS cells) impaired cellular migration and promoted a change to an epithelial-like morphology. A neutralizing antibody against integrin αvβ3 significantly attenuated CTGF-mediated ERK1/2 activation and cellular migration, indicating that the integrin-αvβ3–ERK1/2 signaling pathway is crucial in mediating CTGF function. Moreover, the cDNA microarray analysis revealed CTGF-mediated regulation of the prometastatic gene S100A4. Transfection of MCF-7/CTGF cells with AS-S100A4 reversed the CTGF-induced cellular migratory ability, whereas overexpression of S100A4 in MDA231/AS cells restored their high migratory ability. Genetic and pharmacological manipulations suggested that the CTGF-mediated S100A4 upregulation was dependent on ERK1/2 activation, with expression levels of CTGF and S100A4 being closely correlated with human breast tumors. We conclude that CTGF plays a crucial role in migratory/invasive processes in human breast cancer by a mechanism involving activation of the integrin-αvβ3–ERK1/2–S100A4 pathway.

MicroRNAs (miRNAs) influence many biological processes, including cancer. They do so by posttranscriptionally repressing target mRNAs to which they have sequence complementarity. Although it has been postulated that miRNAs can regulate other miRNAs, this has never been shown experimentally to our knowledge. Here, we demonstrate that miR-107 negatively regulates the tumor suppressor miRNA let-7 via a direct interaction. miR-107 was found to be highly expressed in malignant tissue from patients with advanced breast cancer, and its expression was inversely correlated with let-7 expression in tumors and in cancer cell lines. Ectopic expression of miR-107 in human cancer cell lines led to destabilization of mature let-7, increased expression of let-7 targets, and increased malignant phenotypes. In contrast, depletion of endogenous miR-107 dramatically increased the stability of mature let-7 and led to downregulation of let-7 targets. Accordingly, miR-107 expression increased the tumorigenic and metastatic potential of a human breast cancer cell line in mice via inhibition of let-7 and upregulation of let-7 targets. By mutating individual sites within miR-107 and let-7, we found that miR-107 directly interacts with let-7 and that the internal loop of the let-7/miR-107 duplex is critical for repression of let-7 expression. Altogether, we have identified an oncogenic role for miR-107 and provide evidence of a transregulational interaction among miRNAs in human cancer development.

Purpose: This study was conducted to characterize gene expression profile of survival in patients with surgically curable gastric cancer by using an in-house membrane microarray and developing a survival prediction model. Materials and Methods: Data of cDNA microarrays were obtained from 18 pairs of cancerous and noncancerous gastric tissues. Nine patients who survived > 30 months were identified as good survival, and the other nine, who survived < 12 months, were identified as poor survival. Supervised analysis was performed to identify a gene expression profile by good and poor survival. Semiquantitative reverse transcriptase polymerase chain reaction (RT-PCR) was used to confirm the microarray data in 10 patients with sufficient RNA. Using these 10 patients and another 10 patients selected randomly from 40 newly enrolled patients as the training group, the RT-PCR status of the confirmed genes was used for predicting good versus poor survival. Finally, the prediction model was tested in the remaining 30 newly enrolled gastric cancer patients. Results: A survival prediction model consisting of three genes (CD36, SLAM, PIM-1) was developed. This model could correctly predict poor or good survival in 23 (76.7%) of 30 newly enrolled patients, and yielded a specificity of 80% and a sensitivity of 73.3%. The survival rate of the patients predicted to have good survival was significantly higher than that of those predicted to have poor survival in the test group as a whole (N = 30; P = .00531) and in stage III patients (n = 16; P = .04467). Conclusion: The semiquantitative RT-PCR gene expression profiling of three genes extracted from microarray study can accurately predict surgery-related outcome in gastric cancer patients.