DNA – RNA – Protein transcription – translation Double stranded DNA A Microarrays: B A Splitting into two single strands An introduction to the bio- B technology mRNA Transcription from strand B A B E 1 E 2 E 3 E 4 Transcribed RNA RNA splicing results in an mRNA molecule E 1 E 2 E 3 E 4 mRNA is translated into protein Jan Komorowski Central dogma of molecular Gene expression patterns in Gene expression patterns in physiology and pathophysiology physiology and pathophysiology biology normal resting normal stimulated gastric cancer type A type B gastric mucosa gastric mucosa Jan Komorowski Jan Komorowski 1
Sample Gene Expression Why is gene expression worth Regulation studying? • Physiological and pathophysiological responses are associated with specific changes in cellular a gene expression • Insight into the specific patterns of gene c c expression associated with physiological and f f e pathophysiological responses and conditions b b enable hypotheses about gene function and medical diagnosis d � Physiology is the study of the body in a healthy state � Pathophysiology is the study of disease states. u u u u u u u u 2 4 Jan Komorowski 3 Jan Komorowski 1 5 7 8 6 Overview Pharmacogenomics • Genetic variability in drug response – Sensitivity of some individuals to debrisoquine: certain Cytochrome P450 gene mutations incapacitate the protein enzyme and cause poor drug metabolism, eventually leading to poisoning due to the extensive exposure to the drug. – Obtain a DNA test of the patient, make a decision based on his/her genetic make-up – Large DB’s of genetic and drug response data are commercially built for the discovery of genetically- based rules of drug selection (e.g. Genometrix Inc.) And much more! Jan Komorowski Jan Komorowski 2
Hybridization Image after scanning Jan Komorowski Jan Komorowski Extracting Data Hierarchical Cluster Analysis Experiments Fluorescence ratios Samples 1 2 3 4 5 6 Red > green: up-regulated Gene 1 Gene 7 Red = green Gene 6 Green > red : down-regulated Gene 8 Genes Not available Gene 3 200 10000 50.00 5.64 4800 4800 1.00 0.00 9000 300 0.03 -4.91 Cy5 Cy5 Cy3 Cy5 log ( ) Cy3 Cy3 Jan Komorowski Jan Komorowski 3
In a few words, Data analysis goals microarrays are … What to study? • Classes of experiments; changes in … devices for measuring expression levels in tissue samples with different e.g. diseases, treatments, relative gene expression levels environmental effects etc. of a large number of pre- • Classes of genes; expression profiles of genes with similar biological function selected genes • Both of the above Jan Komorowski Jan Komorowski Data analysis methods Example 96 normal and malignant • Unsupervised learning (clustering, class lymphocyte samples discovery); used to “discover” natural Almost 20 000 cDNA clones groups of genes/experiments e.g. Two sub-clusters of DLBCL – discover subclasses of a form of cancer that is were shown to include patients with significantly clinically homogenous different expected survival time! • Supervised learning; used to “learn” a model of a set of predefined classes of genes/experiments e.g. – diagnosis of cancer/subclasses of cancer Alizadeh et al., Distinct types of diffuse large B- cell lymphoma identified by gene expression profiling, Nature , 403:503-511, Jan Komorowski Jan Komorowski 2000. 4
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