Background:

Gastric carcinoma (GC) remains among the most frequent malignancies in Taiwan as well as in the world and also one of leading causes of cancer-related death. Accumulating evidence shows that chronic inflammation leads to the occurrence of cancers, including GC, via multiple mechanisms.

Cyclooxygenase-2 (COX-2) is a crucial enzyme in inflammatory process and is shown to be up-regulated in a variety of cancers. Therefore, COX-2 may play an important role in carcinogenesis. The hallmarks of cancer include continuing proliferation, evading apoptosis, prohibiting immunity, promoting angiogenesis, enhancing invasion and metastasis. We hypothesize that COX-2 induces carcinogenesis through multiple mechanistic strategies and interactions of multiple genes simultaneously.

Laser capture microdissection (LCM) for obtaining pure cancer cells and microarray technology and analysis are now generally accepted as powerful tools in genomic research, providing reliable microdissection of cancer cells and simultaneous analysis of whole genome.

Aim:

Use microarray technology to investigate patterns of genomic change related to differential COX-2 expression and their clinicopathological association in GC.

Materials:

GC cell lines are transfected with COX-2-expressing vector to establish cell lines with differential levels of COX-2 expression. Clinical specimens are obtained from surgical resection of GC proved by pathology at the Surgical Department of National Taiwan University Hospital, which COX-2 expression is evaluated by Western blotting and immunohistochemical staining.

Methods:

The present project will use microarray for analysis of genome clustering patterns of surgical tissue (GC cells procured by LCM) and GC cell lines based on differential COX-2 expression levels, to discover significantly positively or negatively associated gene clusterings which contain candidate genes for studies of carcinogenesis mechanisms and establishment of animal experiment models in another component project.

Execution:

In the first year of this 3-year project, we will establish GC cell lines expressing differential COX-2 levels by transfection of COX-2-expressing vector and focus on analyzing their genomes by microarray. We also start to collect surgical specimens of GC, record clinicopathological characteristics, procure cells by LCM and assess RNA quality, perform microarray experiments. In the second year, we will continue LCM, RNA extraction, and microarray experiments. In the third year, microarray experiment of a total of 60 pairs, including 30 high-COX-2 cases and 30 low-COX-2 cases, of tumor and non-tumoral tissues are completed. Final analysis is carried out to identify clustering, to select candidate genes, and investigate their relationship to clinicopathological characteristics, according to COX-2 expression. These genes are to be subjected to mechanism and animal studies. We expect a better understanding of patterns of gene clustering in differential COX-2 gene expression.

Background:

Gastric carcinoma (GC) remains among the most frequent malignancies in Taiwan as well as in the world and also one of leading causes of cancer-related death. Accumulating evidence shows that chronic inflammation leads to the occurrence of cancers, including GC, via multiple mechanisms.

Cyclooxygenase-2 (COX-2) is a crucial enzyme in inflammatory process and is shown to be up-regulated in a variety of cancers. Therefore, COX-2 may play an important role in carcinogenesis. The hallmarks of cancer include continuing proliferation, evading apoptosis, prohibiting immunity, promoting angiogenesis, enhancing invasion and metastasis. We hypothesize that COX-2 induces carcinogenesis through multiple mechanistic strategies and interactions of multiple genes simultaneously.

Laser capture microdissection (LCM) for obtaining pure cancer cells and microarray technology and analysis are now generally accepted as powerful tools in genomic research, providing reliable microdissection of cancer cells and simultaneous analysis of whole genome.

Aim:

Use microarray technology to investigate patterns of genomic change related to differential COX-2 expression and their clinicopathological association in GC.

Materials:

GC cell lines are transfected with COX-2-expressing vector to establish cell lines with differential levels of COX-2 expression. Clinical specimens are obtained from surgical resection of GC proved by pathology at the Surgical Department of National Taiwan University Hospital, which COX-2 expression is evaluated by Western blotting and immunohistochemical staining.

Methods:

The present project will use microarray for analysis of genome clustering patterns of surgical tissue (GC cells procured by LCM) and GC cell lines based on differential COX-2 expression levels, to discover significantly positively or negatively associated gene clusterings which contain candidate genes for studies of carcinogenesis mechanisms and establishment of animal experiment models in another component project.

Execution:

In the first year of this 3-year project, we will establish GC cell lines expressing differential COX-2 levels by transfection of COX-2-expressing vector and focus on analyzing their genomes by microarray. We also start to collect surgical specimens of GC, record clinicopathological characteristics, procure cells by LCM and assess RNA quality, perform microarray experiments. In the second year, we will continue LCM, RNA extraction, and microarray experiments. In the third year, microarray experiment of a total of 60 pairs, including 30 high-COX-2 cases and 30 low-COX-2 cases, of tumor and non-tumoral tissues are completed. Final analysis is carried out to identify clustering, to select candidate genes, and investigate their relationship to clinicopathological characteristics, according to COX-2 expression. These genes are to be subjected to mechanism and animal studies. We expect a better understanding of patterns of gene clustering in differential COX-2 gene expression.

Inclusion Criteria:

• surgical resected gastric cancer proved by pathology

Exclusion Criteria:

• Nil