Tissue Microarrays for Analysis of Expression Patterns

Detta är en avhandling från Uppsala : Acta Universitatis Upsaliensis

Sammanfattning: Proteins are essential building blocks in every living cell, and since the complete human genome was sequenced in 2004, researchers have attempted to map the human proteome, which is the functional representation of the genome. One such initiative is the Human Protein Atlas programme (HPA), which generates monospecific antibodies towards all human proteins and uses these for high-throughput tissue profiling on tissue microarrays (TMAs). The results are publically available at the website www.proteinatlas.org.In this thesis, TMAs were used for analysis of expression patterns in various research areas. Different search queries in the HPA were tested and evaluated, and a number of potential biomarkers were identified, e.g. proteins exclusively expressed in islets of Langerhans, but not in exocrine glandular cells or other abdominal organs close to pancreas. The identified candidates were further analyzed on TMAs with pancreatic tissues from normal and diabetic individuals, and colocalization studies with insulin and glucagon revealed that several of the investigated proteins (DGCR2, GBF1, GPR44 and SerpinB10) appeared to be beta cell specific. Moreover, a set of proteins differentially expressed in lung cancer stroma was further analyzed on a clinical lung cancer cohort in the TMA format, and one protein (CD99) was significantly associated with survival. In addition, TMAs with tissue samples from different species were generated, e.g. for mapping of influenza virus attachment in various human and avian tissues. The results showed that the gull influenza virus H16N3 attached to human respiratory tract and eye, suggesting possible transmission of the virus between gull and human. TMAs were also used for analysis of protein expression differences between humans and other primates, and two proteins (TCF3 and SATB2) proved to be significantly differentially expressed on the human lineage at both the protein level and the RNA level.  In conclusion, this thesis exemplifies the potential of the TMA technology, which can be used for analysis of expression patterns in a large variety of research fields, such as biomarker discovery, influenza virus research or further understanding of human evolution.