Bioinformatics Analysis to Identify Cell Adhesion Molecules in Cancer - Adhesion Molecules - page 319

proteins associated in modulating cell-cell and cell-matrix interactions, may play
an important role in organ-specii c metastasis. h ey also observed multiple cell
adhesion molecules that were dif erentially regulated between micrometastases
and macrometastases (Kakiuchi et al . 2003).
IDENTIFICATION OF NON-LINEAGE-SPECIFIC TUMOR
CAMs
High-throughput techniques and bioinformatics application is not limited to the
identii cation of markers specii c to one type of tumor tissue (lineage-specii c), for
example, CAMs specii c to breast or lung cancer. Kolonin et al . provide evidence
that phage display peptide library and bioinformatics analysis can be used to select
common peptides against the vasculature of multiple tumor types (Kolonin et al .
2006). h e US National Cancer Institute (NCI) established a panel of 60 cell lines
(NCI60) from multiple tumors in the late 1980s with an objective to develop a
model system for in vitro drug discovery (Shoemaker 2006). h is cell line panel is
being widely used as a rich source of information to understand the mechanisms
of action of various existing and experimental drugs (Shoemaker 2006). Kolonin
et al . used the NCI60 panel to screen a spectrum of peptides using a phage display
library that targeted the surface of NCI60 cells. h ey proi led an enriched spectrum
of peptides that preferentially bind to non-integrin cell surface molecules expressed
in NCI60 cell lines by selecting against an excess of a competing Arg-Gly-Asp
(RGD) synthetic integrin-binding peptide. Since tripeptide motifs were shown to
capture the protein-peptide interaction in the phage display library, the authors
surveyed the spectrum of tripeptides that resulted from the phage-display screen
using statistical and bioinformatics approaches to compare the dif erential binding
of phage-displayed peptides across the NCI60 panel. h ey found a unique set of
tripeptides with dif erential binding ai nity across the NCI60 cell lines (Kolonin
et al . 2006).
In order to infer the variation in peptide-binding specii city across the NCI60
cell lines, Kolonin et al . performed hierarchical cluster analysis of relative
tripeptide frequencies found among 7-mer peptides binding to each cell. h us,
cell lines within a given cluster share similar peptide frequencies. By associating
these frequencies with the distribution of tripeptides among the NCI-60 cell lines,
the authors suggested the existence of shared targeted surface receptor(s) that
are common to multiple tumor types. Later, they successfully predicted the lead
targeted receptors common to multiple tumor types correlating frequencies of the
peptides and the protein expression patterns available from NCI Molecular Target
Database (Table 1) f or the NCI60 cell lines. h us, their approach presents a simple
way to search drug-accessible tumor cell surface receptors (including CAMs) and
to i nd peptide ligands that can serve as ligands to target the receptors (Kolonin
et al . 2006).