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An integrative approach to identifying cancer chemoresistance-associated pathways

Authors
  • Chao, Shih-Yi1
  • Chiang, Jung-Hsien2
  • Huang, A-Mei3
  • Chang, Woan-Shan2
  • 1 Ching Yun University, Department of Computer Science and Information Engineering, No. 229, Jiansing Road, Jhongli City, Taoyuan County, 320, Taiwan , Jhongli City (Taiwan)
  • 2 National Cheng Kung University, Department of Computer Science and Information Engineering, No. 1, University Road, Tainan City, 701, Taiwan , Tainan City (Taiwan)
  • 3 Kaoshiung Medical University, Department of Biochemistry, Shih-Chuan 1st Road, Kaohsiung, 807, Taiwan , Kaohsiung (Taiwan)
Type
Published Article
Journal
BMC Medical Genomics
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Mar 24, 2011
Volume
4
Issue
1
Identifiers
DOI: 10.1186/1755-8794-4-23
Source
Springer Nature
Keywords
License
Yellow

Abstract

BackgroundResistance 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.MethodsAn 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.ResultsBy 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.ConclusionsThis 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.

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