Date of Award
9-10-2010
Document Type
Open Access Thesis
Degree Name
Medical Doctor (MD)
First Advisor
Jeffrey Sklar, M.D., Ph.D.
Abstract
TWO METHODS TO DETECT CLONAL POPULATIONS OF HUMAN CELLS IN SITU. Philip Hall, Jonathan Murphy, and Jeffrey Sklar, Department of Pathology, Yale University, School of Medicine, New Haven, CT. A molecular assay to detect clonal populations of human cells in situ would be potentially valuable for both investigational and diagnostic purposes. Two such methods are proposed, both utilizing fluorescence in situ hybridization (FISH). The first relies upon random monoallelic expression of genes (so-called allelic exclusion), in which a subset of human genes are normally expressed at a single allele in a fixed fraction of cells within a tissue, independent of the parental origin of the allele. It is hypothesized that application of FISH to assess the allelic expression patterns among one or more of these genes should be able to distinguish a monoclonal population of cells from a polyclonal one. The second method, specific for T-cells, relies upon VDJ segmental recombination at the T-cell receptor beta locus. With this method, our hypothesis is that analysis by FISH of the configuration of rearranged VDJ segments should be able to distinguish a monoclonal population of T cells from a polyclonal population. Both proposed assays were tested on benign tonsil and thymus tissue as well as on monoclonal cell pellets produced from neoplastic cell lines. In those analyses that could be completed, attempts to assess the expression pattern either of genes subject to random allelic exclusion or the determination of VDJ segmental recombination failed to distinguish monoclonality from polyclonality. Although unsuccessful, the failure of these attempts was due to technical limitations and not to fundamental problems with the underlying hypotheses.
Recommended Citation
Hall, Philip Scorza, "Two Methods to Detect Clonal Populations of Human Cells In Situ" (2010). Yale Medicine Thesis Digital Library. 94.
https://elischolar.library.yale.edu/ymtdl/94
This Article is Open Access
Comments
This is an Open Access Thesis.