Potential and challenges of a human cytome project.
BACKGROUND
The elucidation of the molecular pathways from the 20-40.000 genes of the sequenced human genome via investigation of genetic networks and molecular pathways up to the cellular and organismal phenotypes is highly complex and time consuming.
The proposed upside-down research strategy of a human cytome project accesses the expressed molecular cell phenotypes by differential screening, for example of diseased versus healthy, or undifferentiated versus differentiated cells to obtain information on disease or differentiation related molecular hotspots at the single cell level. The genome serves as inventory of the biomolecular capacities of organisms while the mechanisms of genome realisation are initially entirely bypassed. Detected molecular hotspots are further investigated by backward directed systems biology, including molecular pathway modelling to elucidate disease related molecular pathways. New drug targets may be identified to specifically influence such pathways. Differential screening provides, in addition, individualized disease course predictions for everyday medicine, in form of "predictive medicine by cytomics." The early recognition of future disease complications enables an immediate application of preventive therapies. This is likely to lower disease related irreversible tissue destruction and adverse drug reactions and will allow to individually optimize patient therapy.


CONCLUSIONS
Immediate medical use, facilitated access to the detection of new drug targets, increased research speed and the stimulation for advanced technological developments represent major driving forces for the efforts to establish a human cytome project.
Max-Planck-Institut für Biochemie, Martinsried, Germany. valet@biochem.mpg.de
G
G
Valet
A
A
Tárnok
D003585:Cell Biology / Q000639:trends*; D019295:Computational Biology; D003592:Cytophotometry; D005544:Forecasting; D015894:Genome, Human; D016045:Human Genome Project; D006801:Humans; D011315:Preventive Medicine / Q000639:trends; D049490:Systems Biology