2007•Journal of the Korean Gastric Cancer AssociationRequires access

Multiple Genetic Marker Analysis wih Using Quantitative RT-PCR in Gastric Cancer

Moon Won Yoo, Hyukjoon Lee, Soo Min Choi, Jieun Yu, Keun Hur, Young Kook Kim, Han Kwang Yang

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Abstract

Purpose: This study was aimed at evaluating the diagnostic validity of peritoneal dissemination of gastric cancer cells by performing multiple genetic marker analysis via quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) in gastric cancer cell lines and gastric cancer tissues. Materials and Methods: Quantitative RT-PCR was performed on 12 human gastric cancer cell lines and 10 gastric cancer tissues with four mRNAs of carcinoembryonic antigen (CEA), Cytokeratin 20 (CK20), dopa decarboxylase (DDC), and L-3-phosphoserine phosphatase (L3PP). Results: Out of the 12 human gastric cancer cell lines we tested, CEA was overexpressed in four cell lines (33%), CK20 in one (8%), DDC in six (50%) and L3PP was expessed in all the lines (100%). Out of the 10 gastric cancer tissues we tested, CEA was overexpressed in nine tissues, CK20 in eight, DOC in nine and L3PP was overexpressed in all the tissues. L3PP was overexpressed in all the gastric cancer cell lines and tissues, but the levels of overexpression were lower than those of CEA and DDC. Conclusion: Multiple genetic marker analysis can compensate for the weak points of single marker analysis when testing gastric cancer, and three mRNAs of CEA, DDC and L3PP can be used as candidate genes.

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Purpose: This study was aimed at evaluating the diagnostic validity of peritoneal dissemination of gastric cancer cells by performing multiple genetic marker analysis via quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) in gastric cancer cell lines and gastric cancer tissues. Materials and Methods: Quantitative RT-PCR was performed on 12 human gastric cancer cell lines and 10 gastric cancer tissues with four mRNAs of carcinoembryonic antigen (CEA), Cytokeratin 20 (CK20), dopa decarboxylase (DDC), and L-3-phosphoserine phosphatase (L3PP). Results: Out of the 12 human gastric cancer cell lines we tested, CEA was overexpressed in four cell lines (33%), CK20 in one (8%), DDC in six (50%) and L3PP was expessed in all the lines (100%). Out of the 10 gastric cancer tissues we tested, CEA was overexpressed in nine tissues, CK20 in eight, DOC in nine and L3PP was overexpressed in all the tissues. L3PP was overexpressed in all the gastric cancer cell lines and tissues, but the levels of overexpression were lower than those of CEA and DDC. Conclusion: Multiple genetic marker analysis can compensate for the weak points of single marker analysis when testing gastric cancer, and three mRNAs of CEA, DDC and L3PP can be used as candidate genes.

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Available abstract

Purpose: This study was aimed at evaluating the diagnostic validity of peritoneal dissemination of gastric cancer cells by performing multiple genetic marker analysis via quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) in gastric cancer cell lines and gastric cancer tissues. Materials and Methods: Quantitative RT-PCR was performed on 12 human gastric cancer cell lines and 10 gastric cancer tissues with four mRNAs of carcinoembryonic antigen (CEA), Cytokeratin 20 (CK20), dopa decarboxylase (DDC), and L-3-phosphoserine phosphatase (L3PP). Results: Out of the 12 human gastric cancer cell lines we tested, CEA was overexpressed in four cell lines (33%), CK20 in one (8%), DDC in six (50%) and L3PP was expessed in all the lines (100%). Out of the 10 gastric cancer tissues we tested, CEA was overexpressed in nine tissues, CK20 in eight, DOC in nine and L3PP was overexpressed in all the tissues. L3PP was overexpressed in all the gastric cancer cell lines and tissues, but the levels of overexpression were lower than those of CEA and DDC. Conclusion: Multiple genetic marker analysis can compensate for the weak points of single marker analysis when testing gastric cancer, and three mRNAs of CEA, DDC and L3PP can be used as candidate genes.

Key concepts: Medicine, Cancer, Real-time polymerase chain reaction, Computational biology, Internal medicine, Genetics, Gene, Biology

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