Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform

Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies

Factors associated with psychotropic drug use among community-dwelling older persons: A review of empirical studies

BACKGROUND: In the many descriptive studies on prescribed psychotropic drug use by community-dwelling older persons, several sociodemographic and other factors associated with drug use receive inconsistent support. METHOD: Empirical reports with data on at least benzodiazepine or antidepressant drug use in samples of older persons published between 1990 and 2001 (n = 32) were identified from major databases and analyzed to determine which factors are most frequently associated with psychotropic drug use in multivariate analyses. Methodological aspects were also examined. RESULTS: Most reports used probability samples of users and non-users and employed cross-sectional designs. Among variables considered in 5 or more reports, race, proximity to health centers, medical consultations, sleep complaints, and health perception were virtually always associated to drug use. Gender, mental health, and physical health status were associated in about two-thirds of reports. Associations with age, marital status, medication coverage, socioeconomic status, and social support were usually not observed. CONCLUSIONS: The large variety of methods to operationalize drug use, mental health status, and social support probably affected the magnitude of observed relationships. Employing longitudinal designs and distinguishing short-term from long-term use, focusing on samples of drug users exclusively, defining drug use and drug classes more uniformly, and utilizing measures of psychological well-being rather than only of distress, might clarify the nature of observed associations and the direction of causality. Few studies tested specific hypotheses. Most studies focused on individual characteristics of respondents, neglecting the potential contribution of health care professionals to the phenomenon of psychotropic drug use among seniors