Identification and characterization of a molecular marker in epithelial ovarian cancer

Carcinomas that arise from the ovarian surface epithelium represent a great challenge in gynecologic oncology. Although the prognosis of ovarian cancer is influenced by many factors capable of predicting clinical outcome, including tumor stage, pathological grade, and amount of residual disease following primary surgery, the biological aspects of ovarian cancer are not completely understood, thus implying that there may be other predictive indicators that could be used independently or in conjunction with these factors to provide a clearer clinical picture. The identification of additional markers with biological relevance is desirable. To identify disease-associated peptides, a phage display random peptide library was used to screen immunoglobulins derived from a patient with ovarian cancer. One peptide was markedly enriched following three rounds of affinity selection. The presence of autoantibodies against the peptide was examined in a panel of ovarian cancer patients. Stage IV patients exhibited a high percentage of positive reactivity (59%). This was in contrast to stage III patients, who only displayed 7% positive reactivity. Antibodies against the peptide were affinity purified, and heat-shock protein 90 (Hsp90) was identified as the corresponding autoantigen. The expression profile of the identified antigen was determined. Hsp90 was expressed in all sections examined regardless of degree of anaplasia. This thesis shows that utilizing the humoral response to ovarian cancer can be used to identify a tumor antigen in ovarian cancer. The data show that certain antigens may be expressed in ovarian tumors independent of the disease stage or grade, whereas circulating antibodies against such epitopes are only found in a subset of patients. ^

Spatial and temporal aspects of synaptic plasticity

The notion that changes in synaptic efficacy underlie learning and memory processes is now widely accepted even if definitive proof of the synaptic plasticity and memory hypothesis is still lacking. When learning occurs, patterns of neural activity representing the occurrence of events cause changes in the strength of synaptic connections within the brain. Reactivation of these altered connections constitutes the experience of memory for these events and for other events with which they may be associated. These statements summarize a long-standing theory of memory formation that we refer to as the synaptic plasticity and memory hypothesis. Since activity-dependent synaptic plasticity is induced at appropriate synapses during memory formation, and is both necessary and sufficient for the information storage, we can speculate that a methodological study of the synapse will help us understand the mechanism of learning. Random events underlie a wide range of biological processes as diverse as genetic drift and molecular diffusion, regulation of gene expression and neural network function. Additionally spatial variability may be important especially in systems with nonlinear behavior. Since synapse is a complex biological system we expect that stochasticity as well as spatial gradients of different enzymes may be significant for induction of plasticity. ^ In that study we address the question "how important spatial and temporal aspects of synaptic plasticity may be". We developed methods to justify our basic assumptions and examined the main sources of variability of calcium dynamics. Among them, a physiological method to estimate the number of postsynaptic receptors as well as a hybrid algorithm for simulating postsynaptic calcium dynamics. Additionally we studied how synaptic geometry may enhance any possible spatial gradient of calcium dynamics and how that spatial variability affect plasticity curves. Finally, we explored the potential of structural synaptic plasticity to provide a metaplasticity mechanism specific for the synapse. ^