Target Discovery and Validation Reviews and Protocols

Target Discovery and Validation 3
Fig. 1. Overexpression of green fluorescent protein-tagged centrosome/spindle pole
associated protein in HEK293T cells (DNA, blue; CSPPegfp, green; and α-tubulin, red).
Expressed sequence tag (EST)-derived expression analysis and SAGE are
based on the principle that frequency of sequence tag samples from a pool of
cDNA is directly proportional to the expression levels of the corresponding
gene. Chapter 4, Volume 1, showed that SAGE could potentially be used to
identify prognostic and therapeutic targets in human pancreatic cancer.
The rapidly growing gene expression databases and improvement in bioinformatics
tools set the stage for a new in silico strategy to discover therapeutic
targets (2,6). Numerous gene expression studies in several cancer types
can be downloaded from public databases. Notably, ESTs derived from
diverse normal and tumor cDNA libraries offer an attractive starting point for
cancer gene discovery. However, it is worth noting that although the in silico
detection of gene variants holds great promise, it is subjected to the same limitations
of all bioinformatics approaches in that the results need experimental
validation to avoid false leads derived from noisy data. Chapter 2, Volume 1,
highlights the strengths of in silico studies to identify diagnostic, prognostic,
and therapeutic targets in several cancer types. One of the identified genes,
SIM2, was validated in vitro and in vivo, and it could predict prostate cancer
development. Interestingly, its knockdown induced apoptosis in cancer cells
but not in normal cells.