Abstract
Abstract 3602: Radiation pharmacogenomics: an integrative analysis approach to identify biomarkers using the human lymphoblastoid cell lines
Cancer research (Chicago, Ill.), Vol.70(8_Supplement), pp.3602-3602
04/15/2010
DOI: 10.1158/1538-7445.AM10-3602
Abstract
Abstract
Background Radiation therapy is used to treat half of the all cancer patients. Response to radiation therapy varies widely, in terms of both response and toxicity related events. Previous studies suggested almost 80% of the variation in normal tissue response to radiation treatment was likely to be due to genetic factors. Therefore, we performed a genome-wide association study (GWAS) to identify biomarkers that might help predict radiation response using a the “Human Variation Panel” lymphoblastoid cell lines (LCLs) that consists 287 ethnically defined cell lines.
Method Basal gene expression level, 1.3 million genome-wide SNP data were obtained for 287 human LCLs using Affymetrix U133 plus 2.0 GeneChip, Illumina HumanHap 550K, 510S BeadChips and Affymetix SNP Array 6.0. Radiation cytotoxicity assay was also performed to obtain the area under radiation dose response curve (AUC), a summary measure for cytotoxicity for the same cell lines. Functional validation of candidate genes, selected based on the integrated analysis of SNP, expression and AUC data, was performed in multiple cancer cell lines using specific siRNAs followed by MTS and colony formation assays.
Results 27 loci, containing at least 2 SNPs of p values <10−4 within 50kb were associated with radiation AUC. 270 expression probe sets were associated with radiation AUC (p< 10−3). The integrated analysis of 27 loci, 54,000 basal expression probe sets and radiation AUC identified 50 unique SNPs associated with AUC were also associated with gene expression of 39 unique annotated genes. In addition, these 39 genes were associated with radiation AUC with p values <10−3. Based on the GWAS and integrated analysis of SNP, expression array and radiation AUC data, 22 genes were selected for functional validation studies using siRNA knock down followed by MTS and colony formation assays in multiple tumor cell lines. C13orf34 (Bora), MAD2L1, PLK4, TPD52 significantly altered the radiation sensitivity in at least 2 cancer cell lines for both MTS and colony formation assays (p<0.05). Knock down of DEPDC1B, a gene containing 2 SNPs at the 3′-end that was significantly related with Bora gene expression level (p<10−4) significantly desensitized cancer cells to radiation treatment. Both microarray data and QRT-PCR analysis indicated that expression levels for those two genes were significantly correlated. Conclusion Our results using the lymphoblastoid cell lines might help identify novel biomarkers that contribute to variation in response to radiation therapy and help understand the mechanisms underlying the association.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3602.
Details
- Title: Subtitle
- Abstract 3602: Radiation pharmacogenomics: an integrative analysis approach to identify biomarkers using the human lymphoblastoid cell lines
- Creators
- Junmei Hou - Mayo ClinicNifang Niu - Mayo ClinicYuxin Qin - Mayo ClinicBrooke L. Fridley - Mayo Clinic in FloridaKrishna Kalari - Mayo Clinic in FloridaGregory Jenkins - Mayo Clinic in FloridaAnthony Batzler - Mayo Clinic in FloridaLiewei Wang - Mayo Clinic
- Resource Type
- Abstract
- Publication Details
- Cancer research (Chicago, Ill.), Vol.70(8_Supplement), pp.3602-3602
- Publisher
- AMER ASSOC CANCER RESEARCH
- DOI
- 10.1158/1538-7445.AM10-3602
- ISSN
- 0008-5472
- eISSN
- 1538-7445
- Language
- English
- Date published
- 04/15/2010
- Academic Unit
- Stead Family Department of Pediatrics; Medical Genetics and Genomics
- Record Identifier
- 9984701744102771
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