© 2005 European Society for Medical Oncology
Keynote lecture |
Genomics and proteomics—the way forward
Departments of 1 Pathology and 4 Medical Hemato-Oncology, Stavanger University Hospital, Stavanger, Gade Institute, 2 University of Bergen, Norway; 3 Free University, Amsterdam, The Netherlands
The Post-Genomic Era is characterized by huge numbers. This will only increase in the future when more will become known about proteins, which not only outnumber the genes, but also can be functionally altered in various ways. These "big numbers" have two consequences. Studies, which were despisingly called Fishing Expeditions only a few years ago are now respectfully dubbed Discovery Science, which answers questions and generate new hypotheses. Secondly, it is not always easy to select the way forward in Genomics and Proteomics. Therefore emerging technologies are updated and the hallmarks of cancer cells briefly discussed. Promising applications for screening/early disease detection, diagnosis and tumour classification, prognostication, predictive response and tailoring therapy are described.
Strategic choices as to certain types of study, which diseases or organ sites should be analyzed or techniques used, are mainly political and very much determined by loco-regional and national interests. However, in post-genomic research the following practical points must be considered. To avoid non-informative noise, homogeneous groups (preferably of small lesions) should be analyzed. Adequate sampling will be even more important than in the past to minimize the risk of non-informative benign cells inclusion. Accurate, biologically relevant, well reproducible quantitative morphological information is of the utmost importance to define the lesions, as mixtures of functionally different cells will obscure important signals. RNA and proteins degrade quickly under hypoxic conditions, so that for reliable results the interval between tumour excision and freezing must be minimized and standardized. Promising results must always be independently validated as the use of relatively few patients combined with the enormous number of variables analyzed, carries a serious risk of selection bias and too optimistic results. An integrated collaboration structure of multiple disciplines becomes increasingly important.
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