Biomedical Engineering Reference
In-Depth Information
sources of high-throughput data to identify CAMs with high therapeutic or
diagnostic potential. A few of the bioinformatics resources related to phage-display
assays and microarrays are provided in Table 1. Taken together, high-throughput
techniques and bioinformatics approaches to identify tumor-associated CAMs
could help guide the development of new drugs against dif erent types and stages
of cancer.
Abbreviations
BLAST
basic local alignment search tool
CAM
cell adhesion molecules
MANOVA
multivariate analysis of variance
MCAM
mammalian cell adhesion molecule
NCBI
National Center for Biological Information
NCI
National Cancer Institute
PCA
principal component analysis
RefSeq
Reference Sequence database
RELIC
Receptor Ligand Contacts
RGD
Arg-Gly-Asp peptides
SAGE
serial analysis of gene expression
SAGEmap
Serial Analysis of Gene Expression data repository
SEER
Survival Epidemiology and End Results
SEMA 5A
Semaphorin 5A
SRPVS
Similar enRiched Parikh Vector Searching
Key Facts
1. Cancer is one of the leading causes of death in humans.
2. Because most cancer deaths occur as a result of metastasis, developing
therapeutic options to inhibit metastasis would likely have major clinical
benei ts.
3. Inasmuch as cell adhesion molecules (CAMs) are involved in the release
and trai cking of tumor cells, it is important to elucidate the diverse
patterns by which CAMs are displayed on the surface of tumor cells and/
or host tissues, and to understand how those patterns guide tumor cells
from origin to destination.
4. Bioinformatics methods can be used to rei ne CAMs that play major roles
during various steps of tumor progression and metastasis.
