Biomedical Engineering Reference
In-Depth Information
important for the development of diagnostic markers and anticancer therapies. In
the post-genomic era, biomarkers can be screened using whole genome approaches
using high-throughput technologies and by interpreting the voluminous data
generated from these technologies. However, our limited ability to interpret the
voluminous data is complemented by bioinformatics approaches. We summarize
recently developed bioinformatics methods that are being used to identify and
predict the functional CAMs involved in various processes of tumor progression
and metastasis.
INTRODUCTION
Tumor formation and metastasis are multistep processes during which malignant
cells acquire the potential for unlimited replication, increased proliferation and
enhanced angiogenesis leading to tissue invasion and metastasis. h ey acquire
these abilities by becoming sensitive to growth signals, insensitive to anti-growth
signals and resistant to apoptosis (Hanahan and Weinberg 2000). In addition to
dysregulated proliferation, apoptosis and angiogenesis, an essential process during
tumor formation and metastasis is the change in the ability of cancer cells to adhere
to one another, to neighboring stromal cells or to the extracellular matrix. h is
selective process of cell-cell or cell-matrix interactions is typically mediated by
high ai nity binding of cell adhesion molecules (CAMs) to neighboring cells or the
extracellular matrix (Lukas and Dvorak 2004, Stein
et al
. 2005)
*
. h e central role
of CAMs in a wide variety of processes during tumor progression and metastasis
makes their study applicable in a diverse array of tumor types.
Both gene expression and the functional attributes of CAMs dif er depending
on cell type. Primary tumors with the capability to metastasize express unique
CAMs that bind to counterpart CAMs expressed on the surface of endothelial cells
present in the target organ's vasculature. h rough this mechanism, the interacting
CAMs anchor the metastatic cells to the target organ (Sadanandam
et al
. 2007).
Recent evidence suggests that CAMs play a major role in the sensitivity of tumor
cells to various drugs, and the sensitivity is mediated through suppression of
apoptotic pathways in cancer cells (Stein
et al
. 2005). While high-throughput
technologies such as phage-display peptide library screening and microarrays
allow one to study a wide range of CAMs, bioinformatics techniques are needed
to distill large volumes of data so that those CAMs with a functional role in tumor
progression and metastasis can be identii ed. Once identii ed, the key players can
help guide the development of clinical diagnostic tools and anticancer therapies.
Here, we review the current high-throughput molecular techniques and the
pertinent bioinformatics methods.
*
CAMs are a subset of cell surface molecules. Hence, methods used to identify cell surface molecules
were discussed in the context of CAM identii cation.
