Identification of a radiosensitivity signature using integrative metaanalysis of published microarray data for NCI-60 cancer cells

被引:118
作者
Kim, Han Sang [1 ,2 ]
Kim, Sang Cheol [3 ]
Kim, Sun Jeong [1 ]
Park, Chan Hee [1 ]
Jeung, Hei-Cheul [1 ,2 ]
Kim, Yong Bae [4 ]
Ahn, Joong Bae [1 ,2 ]
Chung, Hyun Cheol [1 ,2 ,5 ]
Rha, Sun Young [1 ,2 ,5 ]
机构
[1] Yonsei Univ, Coll Med, Canc Metastasis Res Ctr, Seoul 120749, South Korea
[2] Yonsei Univ, Coll Med, Dept Internal Med, Seoul 120749, South Korea
[3] Korea Res Inst Biosci & Biotechnol, Korean Bioinformat Ctr, Taejon, South Korea
[4] Yonsei Canc Ctr, Dept Radiat Oncol, Seoul, South Korea
[5] Yonsei Univ, Coll Med, Brain Korea Project Med Sci 21, Seoul 120749, South Korea
基金
新加坡国家研究基金会;
关键词
Radiosensitivity; NCI-60; Microarray; Adhesion; Clonogenic assay; GENE-EXPRESSION PROFILES; BREAST-CANCER; RADIOTHERAPY; SENSITIVITY; PREDICTION; LINES; CHEMOSENSITIVITY; INHIBITION; BIOLOGY;
D O I
10.1186/1471-2164-13-348
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: In the postgenome era, a prediction of response to treatment could lead to better dose selection for patients in radiotherapy. To identify a radiosensitive gene signature and elucidate related signaling pathways, four different microarray experiments were reanalyzed before radiotherapy. Results: Radiosensitivity profiling data using clonogenic assay and gene expression profiling data from four published microarray platforms applied to cancer cell panel were used. The survival fraction at 2 Gy (SF2, range from 0 to 1) was calculated as a measure of radiosensitivity and a linear regression model was applied to identify genes or a gene set with a correlation between expression and radiosensitivity (SF2). Radiosensitivity signature genes were identified using significant analysis of microarrays (SAM) and gene set analysis was performed using a global test using linear regression model. Using the radiation-related signaling pathway and identified genes, a genetic network was generated. According to SAM, 31 genes were identified as common to all the microarray platforms and therefore a common radiosensitivity signature. In gene set analysis, functions in the cell cycle, DNA replication, and cell junction, including adherence and gap junctions were related to radiosensitivity. The integrin, VEGF, MAPK, p53, JAK-STAT and Wnt signaling pathways were overrepresented in radiosensitivity. Significant genes including ACTN1, CCND1, HCLS1, ITGB5, PFN2, PTPRC, RAB13, and WAS, which are adhesion-related molecules that were identified by both SAM and gene set analysis, and showed interaction in the genetic network with the integrin signaling pathway. Conclusions: Integration of four different microarray experiments and gene selection using gene set analysis discovered possible target genes and pathways relevant to radiosensitivity. Our results suggested that the identified genes are candidates for radiosensitivity biomarkers and that integrin signaling via adhesion molecules could be a target for radiosensitization.
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页数:10
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