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Gastric cancer is the third most common cause
of cancer-related death in worldwide. It is crucial to tar-
get the key genes controlling pathogenesis in the early
stage of gastric cancer. This study describes an integrated
bioinformatics to identify molecular biomarkers for gas-
tric cancer in patients’ cancer tissues. We reports differ-
ently expression genes in large gastric cancer cohorts
from Gene Expression Ominus (GEO). Our findings re-
vealed that 433 genes were significantly different
expressed in human gastric cancer. Differently expression
gene profile in gastric cancer was further validated by
bioinformatic analyses, co-expression network construc-
tion. Based on the co-expression network and top-ranked
genes, we identified collagen type I alpha 2 (COL1A2)
which encodes the pro-alpha2 chain of type I collagen
whose triple helix comprises two alpha1 chains and one
alpha2 chain, was the key gene in a 37-gene network
that modulates cell motility by interacting with the cyto-
skeleton. Furthermore, the prognostic role of COL1A2
was determined by use of immunohistochemistry on hu-
man gastric cancer tissue. COL1A2 was highly expressed
in human gastric cancer as compared with normal gastric
tissues. Statistical analysis showed COL1A2 expression
level was significantly associated with histological type