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miRNA signature associated with outcome of gastric cancer patients following chemotherapy
Authors:Chang Hee Kim  Hark K Kim  R Luke Rettig  Joseph Kim  Eunbyul T Lee  Olga Aprelikova  Il J Choi  David J Munroe  Jeffrey E Green
Institution:1. Department of Computer Science and Information Engineering, Ching Yun University, No. 229, Jiansing Road, 320, Jhongli City, Taoyuan County, Taiwan
2. Department of Computer Science and Information Engineering, National Cheng Kung University, No. 1, University Road, 701, Tainan City, Taiwan
3. Department of Biochemistry, Kaoshiung Medical University, Shih-Chuan 1st Road, 807, Kaohsiung, Taiwan
Abstract:

Background

Resistance to chemotherapy severely limits the effectiveness of chemotherapy drugs in treating cancer. Still, the mechanisms and critical pathways that contribute to chemotherapy resistance are relatively unknown. This study elucidates the chemoresistance-associated pathways retrieved from the integrated biological interaction networks and identifies signature genes relevant for chemotherapy resistance.

Methods

An integrated network was constructed by collecting multiple metabolic interactions from public databases and the k-shortest path algorithm was implemented to identify chemoresistant related pathways. The identified pathways were then scored using differential expression values from microarray data in chemosensitive and chemoresistant ovarian and lung cancers. Finally, another pathway database, Reactome, was used to evaluate the significance of genes within each filtered pathway based on topological characteristics.

Results

By this method, we discovered pathways specific to chemoresistance. Many of these pathways were consistent with or supported by known involvement in chemotherapy. Experimental results also indicated that integration of pathway structure information with gene differential expression analysis can identify dissimilar modes of gene reactions between chemosensitivity and chemoresistance. Several identified pathways can increase the development of chemotherapeutic resistance and the predicted signature genes are involved in drug resistant during chemotherapy. In particular, we observed that some genes were key factors for joining two or more metabolic pathways and passing down signals, which may be potential key targets for treatment.

Conclusions

This study is expected to identify targets for chemoresistant issues and highlights the interconnectivity of chemoresistant mechanisms. The experimental results not only offer insights into the mode of biological action of drug resistance but also provide information on potential key targets (new biological hypothesis) for further drug-development efforts.
Keywords:
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