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Biomedical subjects

Kan-kan Wang

Publications and source records attributed to Kan-kan Wang.

2 recordsLinked to original sources

[Analysis of gene expression profile of G1/S transition in gastric cancer cell cycle].

OBJECTIVE: To detect the variation of gene expression profile of G1/S transition and elucidate the role of related genes regulating cell cycle from G1 to S phase in gastric cancer. METHODS: Nocodazole-thymidine and double thymidine methods were used to synchronize gastric cells at G2/M and G1/S point, cDNA microarray chips was applied to examine the gene expression profile at G1 early and late phase, S early and late phase during the cell cycle, hierarchy analysis was conducted by a professional software package. RESULTS: A total of 2001 genes were detected available, 959 genes appeared to be upregulated or downregulated, including 147 genes upregulated at G1 late phase. These 147 genes are involved in DNA metabolism, transcription and translation,posttranslational modification, ubiquitination, signal transduction etc, which all affected cell cycle from different aspects. CONCLUSION: Complex multiple gene processes, such as DNA metabolism, transcription and translation, posttranslational modification, ubiquitination, signal transduction etc,are implicated in and also essential for G1/S transition during gastric cancer cell cycle, part of these genes are significantly associate with overproliferation in gastric cancer.

Cell Division↗

[Establishment of CPP-SOM integrated cDNA microarray technology].

OBJECTIVE: To get an insight into the molecular mechanisms of diseases development and targeted therapy at the transcriptome level and search for potential therapeutic targets. METHODS: The present researchers established a cDNA microarray platform and applied component plane presentation integrated self-organizing map (CPP-SOM) to the microarray data obtained from a differentiation model, all trans retinoic acid-induced differentiation in NB4 cells. RESULTS: The platform included 12630 unique clones, including 9436 known genes. By CPP-SOM, the researchers were able to not only well classify the regulated genes into functionally distinct categories but also depict transcriptional changes throughout the process of the development of diseases or drug treatment. CONCLUSION: The platform has proven to be steady and reliable, and the CPP-SOM could serve as an important and good tool for analysis of microarray data.

Cell Line, Tumor↗