Department of Computer Science/The University of Chicago

                   Ryerson Hall -- 1100 E. 58th Street

                 C O L L O Q U I U M   A N N O U N C E M E N T

DATE:      	Monday, 4 October 1999

TIME:             3 p.m.

PLACE:          Ryerson 251 (followed by coffee/tea in Ryerson 258)

SPEAKER:   	John Quackenbush
		The Institute for Genomic Research, Rockville, MD 

TITLE:          	Whole Genome Functional Analysis in Humans
		Using DNA Microarrays

ABSTRACT:
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A goal of the Human Genome Project is identification of the complete set of
human genes and the role played by these genes in development and disease.
Microarrays provide the opportunity to study gene expression patterns on a
genomic scale. Thousands of DNA clones are arrayed on a microscope slide
and relative expression levels of the genes they encode are determined by
measuring fluorescence intensity of labeled RNA hybridized to the arrays.
The data provided by microarray analysis promises functional information on
a genomic scale, allowing a significant fraction of the genes in any
organism to be assayed in a single experiment. Further, they provide a
means of identifying candidate genes that may play a role in human disease
development and progression.

In the US, Colon cancer is the second most common cause of deaths related
to cancer in the United States. Despite significant advances in therapy,
poor prognosis of colon cancer metastasis results in high mortality. Unlike
tumorigenesis, which requires presence of mutated genes, metastasis is
mostly a result of altered gene expression. Using DNA microarrays, we have
begun a study of gene expression changes in colon tumor metastasis. To do
this, we 
assembled a collection of DNA clones representing more than 40,000 distinct
genes, developed laboratory hardware and protocols, and created databases
and data analysis tools necessary to analyze differential expression.
High-density DNA microarrays containing more than 19,200 PCR amplified
clones have been used to study differential expression patterns between
cell lines of low metastatic (KM12C) and highly metastatic (KM12L4A,
KM12SM) potential. Statistical analysis of measured expression ratios
suggests genes that may be of prognostic or diagnostic value and provide a
more complete understanding of gene function and regulation with respect to
cancer metastasis.

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