Identification of a radiosensitivity signature using integrative metaanalysis of published microarray data for NCI-60 cancer cells.
Identification of a radiosensitivity signature using integrative metaanalysis of published microarray data for NCI-60 cancer cells.
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DOI：
10.1186/1471-2164-13-348
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发表时间：
2012-07-30
期刊：
影响因子：
4.4
通讯作者：
Rha SY
中科院分区：
文献类型：
--
作者：
Kim HS;Kim SC;Kim SJ;Park CH;Jeung HC;Kim YB;Ahn JB;Chung HC;Rha SY
在后基因组时代，对治疗反应的预测可能会导致更好的剂量选择患者在放疗。为了鉴定放射敏感基因特征并阐明相关信号通路，在放射治疗前重新分析了四种不同的微阵列实验。使用来自应用于NCI-60癌细胞组的四个公开的微阵列平台的使用克隆形成测定的放射敏感性分析数据和基因表达分析数据。计算2戈伊下的存活分数（SF 2，范围从0到1）作为放射敏感性的量度，并且应用线性回归模型来鉴定表达与放射敏感性（SF 2）之间具有相关性的基因或基因集。使用微阵列的显著性分析（SAM）鉴定放射敏感性标签基因，并且使用使用线性回归模型的全局检验进行基因集分析。利用辐射相关的信号通路和已确定的基因，形成了一个遗传网络。根据SAM，31个基因被鉴定为所有微阵列平台共有的，因此是一个共同的辐射敏感性特征。在基因集分析中，细胞周期、DNA复制和细胞连接（包括粘附和间隙连接）中的功能与放射敏感性相关。整合素、VEGF、MAPK、p53、JAK-STAT和Wnt信号通路在放射敏感性中占主导地位。重要基因包括ACTN 1、CCND 1、HCLS 1、ITGB 5、PFN 2、PTPRC、RAB 13和WAS，它们是通过SAM和基因集分析鉴定的粘附相关分子，并在遗传网络中与整合素信号通路相互作用。整合四个不同的微阵列实验和基因选择，使用基因集分析发现可能的靶基因和途径相关的辐射敏感性。我们的研究结果表明，所确定的基因是放射敏感性生物标志物的候选者，并且通过粘附分子的整合素信号传导可能是放射增敏的靶点。
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. Radiosensitivity profiling data using clonogenic assay and gene expression profiling data from four published microarray platforms applied to NCI-60 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. 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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影响因子：
11.2
作者：
Watanabe, T;Komuro, Y;Nagawa, H
通讯作者：
Nagawa, H
影响因子：
64.8
作者：
Jirawatnotai S;Hu Y;Michowski W;Elias JE;Becks L;Bienvenu F;Zagozdzon A;Goswami T;Wang YE;Clark AB;Kunkel TA;van Harn T;Xia B;Correll M;Quackenbush J;Livingston DM;Gygi SP;Sicinski P
通讯作者：
Sicinski P
DOI：
10.1073/pnas.091062498
发表时间：
2001-04-24
影响因子：
11.1
作者：
Tusher, VG;Tibshirani, R;Chu, G
通讯作者：
Chu, G
DOI：
10.1016/j.ijrobp.2010.06.023
发表时间：
2010-11-15
期刊：
International journal of radiation oncology, biology, physics
影响因子：
--
作者：
Spitzner M;Emons G;Kramer F;Gaedcke J;Rave-Fränk M;Scharf JG;Burfeind P;Becker H;Beissbarth T;Ghadimi BM;Ried T;Grade M
通讯作者：
Grade M
影响因子：
4.6
作者：
Kim, In Ah;Kim, Jin Ho;Park, Charn Il
通讯作者：
Park, Charn Il