An extensive amount of information is currently available to clinical specialists, ranging from details ofclinical symptoms to various types of biochemical data and outputs of imaging devices. Each type of dataprovides information that must be evaluated and assigned to a particular pathology during the diagnosticprocess. To streamline the diagnostic process in daily routine and avoid misdiagnosis, artificial intelligencemethods (especially computer aided diagnosis and artificial neural networks) can be employed. Theseadaptive learning algorithms can handle diverse types of medical data and integrate them into categorizedoutputs. In this paper, we briefly review and discuss the philosophy, capabilities, and limitations of artificialneural networks in medical diagnosis through selected examples

Copper is an endogenous metal ion that has been studied to prepare a new antitumoral agent with less side-effects. Copper is involved as a cofactor in several enzymes, in ROS production, in the promotion of tumor progression, metastasis, and angiogenesis, and has been found at high levels in serum and tissues of several types of human cancers. Under these circumstances, two strategies are commonly followed in the development of novel anticancer Copper-based drugs: the sequestration of free Copper ions and the synthesis of Copper complexes that trigger cell death. The latter strategy has been followed in the last 40 years and many reviews have covered the anticancer properties of a broad spectrum of Copper complexes, showing that the activity of these compounds is often multi factored. In this work, we would like to focus on the anticancer properties of mixed Cu(II) complexes bearing substituted or unsubstituted 1,10-phenanthroline based ligands and different classes of inorganic and organic auxiliary ligands. For each metal complex, information regarding the tested cell lines and the mechanistic studies will be reported and discussed. The exerted action mechanisms were presented according to the auxiliary ligand/s, the metallic centers, and the increasing complexity of the compound structures.

Prostate cancer is the most prevalent cancer in males in developed countries. Tumor suppressor candidate 3 (TUSC3) has been identified as a putative tumor suppressor gene in prostate cancer, though its function has not been characterized. TUSC3 shares homologies with the yeast oligosaccharyltransferase (OST) complex subunit Ost3p, suggesting a role in protein glycosylation. We provide evidence that TUSC3 is part of the OST complex and affects N-linked glycosylation in mammalian cells. Loss of TUSC3 expression in DU145 and PC3 prostate cancer cell lines leads to increased proliferation, migration and invasion as well as accelerated xenograft growth in a PTEN negative background. TUSC3 downregulation also affects endoplasmic reticulum (ER) structure and stress response, which results in increased Akt signaling. Together, our findings provide first mechanistic insight in TUSC3 function in prostate carcinogenesis in general and N-glycosylation in particular.

BACKGROUND.: Current prognostic information in ovarian cancer is based on tumor stage, tumor grade, and postoperative tumor size. Reliable molecular prognostic markers are scarce. In this article, the authors describe epigenetic events in a frequently deleted region on chromosome 8p22 that influence the expression of tumor suppressor candidate 3 (TUSC3), a putative tumor suppressor gene in ovarian cancer.METHODS.: Messenger RNA expression and promoter hypermethylation of TUSC3 were studied in ovarian cancer cell lines and in tumor samples from 2 large, independent ovarian cancer cohorts using polymerase chain reaction‐based methods.RESULTS.: The results indicated that TUSC3 expression is decreased significantly because of promoter methylation in malignant ovarian tumors compared with benign controls. Almost 33% of ovarian cancer samples had detectable TUSC3 promoter methylation. Furthermore, methylation status of the TUSC3 promoter had a significant and independent influence on progression‐free and overall survival.CONCLUSIONS.: TUSC3 hypermethylation predicted progression‐free and overall survival in ovarian cancer. The current observations suggested a role for N‐glycosylating events in ovarian cancer pathogenesis in general and identified the epigenetic silencing of TUSC3 as a prognostic factor in this disease. Cancer 2013. © 2012 American Cancer Society.