Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Breast Cancer, Expression Profiles and Binary Regression in 7000 Dimensions Computational Diagnostics We are a new research group in the department of Computational Molecular Biology at the Max Planck Institute for Molecular Genetics in Berlin-Dahlem. Our group is part of the Berlin Center for Genome Based Bioinformatics and participates in the NGFN ( National Genome Research Network ). Rainer Spang, Harry Zuzan, Carrie Blanchette, Erich Huang, Holly Dressman, Jeff Marks, Joe Nevins, Mike West Duke Medical Center & Duke University Estrogen Receptor Status •7000 genes Research •49 breast tumors A comprehensive understanding of the mostly subtle differences in gene expression in patient specific cell samples is crucial for elucidating the molecular characteristics of diseases as well as for the optimal choice of treatment. Large scale gene expression profiling allow for a systematic investigation of the molecular characteristics of diseases. Recently, there was tremendous progress in the development of technologies that allows for the parallel measurement of expression levels for tens of thousands of genes. However, it is still very challenging to interpret the data, and use it in clinical decision processes. •25 ER+ The focus of this group is to develop statistical methodology for the use of gene expression profiles in medical diagnostics. We aim to identify pattern in expression profiles that improve or facilitate diagnosis, help to predict clinical outcome or refine common diagnostic schemes. Members Stefan Bentink Web: www.molgen.mpg.de/~bentink email: [email protected] •24 ER- 7000 Numbers Are More Numbers Than We Need Overfitting: We Can Not Identify a Model Informative Priors •There are many different models that assign high probabilities for ER+ tumors and low probabilities for ER- tumors in the training set •For a new patient we find among these models some that support that she is ER+ and others that predict she is ER- Likelihood Prior Posterior Fon:(++49 +30) 8413 - 1352 Claudio Lottaz Prior Choice Web: www.molgen.mpg.de/~lottaz email: [email protected] Fon: (++49 +30) 8413 - 1352 Center Orientation Not to wide not to narrow Florian Markowetz auto adjusting model Web: www.molgen.mpg.de/~markowet hyper-parameters with their own priors email: [email protected] Fon: (++49 +30) 8413 - 1352 Rainer Spang (head) Assumptions on the model correspond to assumptions on the diagnosis orthogonal super-genes Web: www.molgen.mpg.de/~spang email: [email protected] Fon: (++49 +30) 8413 - 1352 Which Genes Have Driven the Prediction ? Stefanie Scheid Web: www.molgen.mpg.de/~scheid email: [email protected] Gene Weight nuclear factor 3 alpha 0.853 cysteine rich heart protein 0.842 estrogen receptor 0.840 Publications intestinal trefoil factor 0.840 x box binding protein 1 0.835 Prediction and uncertainty in the analysis of gene expression profiles gata 3 0.818 Rainer Spang, Carrie Blanchette, Harry Zuzan, Jeffrey R. Marks, Joseph Nevins and Mike West ps 2 0.818 liv1 0.812 Fon: (++49 +30) 8413 - 1352 Proceedings of the German Conference on Bioinformatics GCB 2001 ... many many more ... ... Predicting the clinical status of human breast cancer by using gene expression profiles West M, Blanchette C, Dressman H, Huang E, Ishida S, Spang R, Zuzan H, Olson JA Jr, Marks JR, Nevins JR. Proc Natl Acad Sci U S A. 2001 Sep 25;98(20):11462-7 Role for E2F in control of both DNA replication and mitotic functions as revealed from DNA microarray analysis Ishida S, Huang E, Zuzan H, Spang R, Leone G, West M, Nevins JR. Mol Cell Biol. 2001 Jul;21(14):4684-99 What are the additional assumptions that came in by the prior? •The model can not be dominated by only a few super-genes ( genes! ) •The diagnosis is done based on global changes in the expression profiles influenced by many genes •The assumptions are neutral with respect to the individual diagnosis