Genomic and functional profiling of gastric cancer

Helicobacter pylori infection is a risk factor for gastric cancer, which is a major health issue worldwide. Gastric cancer has a poor prognosis due to the unnoticeable progression of the disease and surgery is the only available treatment in gastric cancer. Therefore, gastric cancer patients would greatly benefit from identifying biomarker genes that would improve diagnostic and prognostic prediction and provide targets for molecular therapies. DNA copy number amplifications are the hallmarks of cancers in various anatomical locations. Mechanisms of amplification predict that DNA double-strand breaks occur at the margins of the amplified region. The first objective of this thesis was to identify the genes that were differentially expressed in H. pylori infection as well as the transcription factors and signal transduction pathways that were associated with the gene expression changes. The second objective was to identify putative biomarker genes in gastric cancer with correlated expression and copy number, and the last objective was to characterize cancers based on DNA copy number amplifications. DNA microarrays, an in vitro model and real-time polymerase chain reaction were used to measure gene expression changes in H. pylori infected AGS cells. In order to identify the transcription factors and signal transduction pathways that were activated after H. pylori infection, gene expression profiling data from the H. pylori experiments and a bioinformatics approach accompanied by experimental validation were used. Genome-wide expression and copy number microarray analysis of clinical gastric cancer samples and immunohistochemistry on tissue microarray were used to identify putative gastric cancer genes. Data mining and machine learning techniques were applied to study amplifications in a cross-section of cancers. FOS and various stress response genes were regulated by H. pylori infection. H. pylori regulated genes were enriched in the chromosomal regions that are frequently changed in gastric cancer, suggesting that molecular pathways of gastric cancer and premalignant H. pylori infection that induces gastritis are interconnected. 16 transcription factors were identified as being associated with H. pylori infection induced changes in gene expression. NF-κB transcription factor and p50 and p65 subunits were verified using elecrophoretic mobility shift assays. ERBB2 and other genes located in 17q12- q21 were found to be up-regulated in association with copy number amplification in gastric cancer. Cancers with similar cell type and origin clustered together based on the genomic localization of the amplifications. Cancer genes and large genes were co-localized with amplified regions and fragile sites, telomeres, centromeres and light chromosome bands were enriched at the amplification boundaries. H. pylori activated transcription factors and signal transduction pathways function in cellular mechanisms that might be capable of promoting carcinogenesis of the stomach. Intestinal and diffuse type gastric cancers showed distinct molecular genetic profiles. Integration of gene expression and copy number microarray data allowed the identification of genes that might be involved in gastric carcinogenesis and have clinical relevance. Gene amplifications were demonstrated to be non-random genomic instabilities. Cell lineage, properties of precursor stem cells, tissue microenvironment and genomic map localization of specific oncogenes define the site specificity of DNA amplifications, whereas labile genomic features define the structures of amplicons. These conclusions suggest that the definition of genomic changes in cancer is based on the interplay between the cancer cell and the tumor microenvironment.

A Probabilistic Approach to the Primary Visual Cortex

What can the statistical structure of natural images teach us about the human brain? Even though the visual cortex is one of the most studied parts of the brain, surprisingly little is known about how exactly images are processed to leave us with a coherent percept of the world around us, so we can recognize a friend or drive on a crowded street without any effort. By constructing probabilistic models of natural images, the goal of this thesis is to understand the structure of the stimulus that is the raison d etre for the visual system. Following the hypothesis that the optimal processing has to be matched to the structure of that stimulus, we attempt to derive computational principles, features that the visual system should compute, and properties that cells in the visual system should have. Starting from machine learning techniques such as principal component analysis and independent component analysis we construct a variety of sta- tistical models to discover structure in natural images that can be linked to receptive field properties of neurons in primary visual cortex such as simple and complex cells. We show that by representing images with phase invariant, complex cell-like units, a better statistical description of the vi- sual environment is obtained than with linear simple cell units, and that complex cell pooling can be learned by estimating both layers of a two-layer model of natural images. We investigate how a simplified model of the processing in the retina, where adaptation and contrast normalization take place, is connected to the nat- ural stimulus statistics. Analyzing the effect that retinal gain control has on later cortical processing, we propose a novel method to perform gain control in a data-driven way. Finally we show how models like those pre- sented here can be extended to capture whole visual scenes rather than just small image patches. By using a Markov random field approach we can model images of arbitrary size, while still being able to estimate the model parameters from the data.

Boundaries in Action : An Activity-theoretical Study of Development, Learning, and Change in Health Care Organization for Patients with Multiple and Chronic Illnesses

This study examines boundaries in health care organizations. Boundaries are sometimes considered things to be avoided in everyday living. This study suggests that boundaries can be important temporally and spatially emerging locations of development, learning, and change in inter-organizational activity. Boundaries can act as mediators of cultural and social formations and practices. The data of the study was gathered in an intervention project during the years 2000-2002 in Helsinki in which the care of 26 patients with multiple and chronic illnesses was improved. The project used the Change Laboratory method that represents a research assisted method for developing work. The research questions of the study are: (1) What are the boundary dynamics of development, learning, and change in health care for patients with multiple and chronic illnesses? (2) How do individual patients experience boundaries in their health care? (3) How are the boundaries of health care constructed and reconstructed in social interaction? (4) What are the dynamics of boundary crossing in the experimentation with the new tools and new practice? The methodology of the study, the ethnography of the multi-organizational field of activity, draws on cultural-historical activity theory and anthropological methods. The ethnographic fieldwork involves multiple research techniques and a collaborative strategy for raising research data. The data of this study consists of observations, interviews, transcribed intervention sessions, and patients' health documents. According to the findings, the care of patients with multiple and chronic illnesses emerges as fragmented by divisions of a patient and professionals, specialties of medicine and levels of health care organization. These boundaries have a historical origin in the Finnish health care system. As an implication of these boundaries, patients frequently experience uncertainty and neglect in their care. However, the boundaries of a single patient were transformed in the Change Laboratory discussions among patients, professionals and researchers. In these discussions, the questioning of the prevailing boundaries was triggered by the observation of gaps in inter-organizational care. Transformation of the prevailing boundaries was achieved in implementation of the collaborative care agreement tool and the practice of negotiated care. However, the new tool and practice did not expand into general use during the project. The study identifies two complementary models for the development of health care organization in Finland. The 'care package model', which is based on productivity and process models adopted from engineering and the 'model of negotiated care', which is based on co-configuration and the public good.