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| Status |
Public on May 29, 2008 |
| Title |
Genetic Analysis of Human Traits In-Vitro: Drug Response and Gene Expression in Lymphoblastoid Cell Lines |
| Platform organism |
Homo sapiens |
| Sample organisms |
Pan troglodytes; Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
Lymphoblastoid cell lines (LCLs), originally collected as renewable sources of DNA, are now being used as a model system to study genotype-phenotype relationships in human cells. These cell lines have been used to search for genetic variants that are associated with drug response as well as with more basic cellular traits such as RNA levels. In setting out to extend such studies by searching for genetic variants contributing to drug response, we observed that phenotypes in LCLs were, in our lab and others, significantly affected by experimental confounders (i.e. in vitro growth rate, metabolic state, and relative levels of the Epstein-Barr virus used to transform the cells). As we did not find any SNPs associated with genome-wide significance to drug response, we evaluated whether incorporating RNA expression levels (and eQTLs) in the analysis could increase power to detect such effects. As previously shown, cis-acting eQTLs were detectable for a sizeable fraction of RNAs and baseline levels of many RNAs predicted response to several drugs. However, we found only limited evidence that SNPs influenced drug response through their effect on expression of RNA. Efforts to use LCLs to map genes underlying cellular traits will require great care to control experimental confounders, unbiased methods for integrating and interpreting such multi-dimensional data, and much larger sample sizes than have been applied to date.
Keywords: baseline RNA expression
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| Overall design |
We studied 269 cell lines densely genotyped by the International HapMap Project [31]. Cell lines were cultured and characterized at baseline for a variety of cellular phenotypes including growth rate, ATP levels, mitochondrial DNA copy number, EBV copy number, and measures of B-cell relevant cell surface receptors and cytokine levels. Each cell line was exposed in 384-well plates to a range of doses for each of seven drugs selected based on their divergent mechanisms of action and importance in clinical use for treatment of B-cell diseases, focusing on anti-cancer agents: 5-fluorouracil (5FU), methotrexate (MTX), simvastatin, SAHA, 6-mercaptopurine (6MP), rapamycin, and bortezomib. Drug response was measured using Celltiter Glo, an ATP-activated intracellular luminescent marker that, when compared to mock-treated control wells, can represent relative levels of cellular viability and metabolic activity. RNA was collected at baseline and RNA transcript levels were measured genome-wide on the Affymetrix platform. Baseline characterization and plating for drug response experiments was performed using batches of 90 cell lines from each HapMap analysis panel (CEU, JPT / CHB, and YRI) on each of three experiment days. The order of cell lines within each panel was randomized to avoid inducing artificial intra-familial correlation. Each drug was tested at a range of doses around the expected IC50 as reported for the drug by the NCI DTP; each dose of drug was tested in two wells per plate and on two separate plates. These replicate measurements for each cell line allowed assessment of intra-experimental variation. To evaluate day-to-day (i.e. inter-experimental) variation in all traits, a subset of 90 cell lines (30 from each of the three HapMap panels) was grown from a fresh aliquot and the entire experiment was repeated. To evaluate the effect of technical error on measured RNA levels, a set of 22 RNAs previously expression profiled (using Illumina HumanChip) at Wellcome Trust Sanger Institute (WTSI) (generously provided by Emmanouil T. Dermatsakis) was included in expression profiling at the Broad on Affymetrix arrays. Data can be downloaded from the Broad Institute web site: (http://www.broad.mit.edu/~yelensky/cell_lines_paper/). Please see Materials and Methods for details of QC, normalization, etc.
Note - Roman Yelensky (12/22/2009): A recent application of novel micro-array experiment QC methods by the scientific community (Lude Franke) has revealed the possibility of a mixup of a handful of RNA samples in the CHB/JPT population subset. Specifically, it has been suggested that RNA data for sample pairs:
- NA18609 and NA18971
- NA18592 and NA18605
- NA18637 and NA18966
- NA18550 and NA18635
- NA18994 and NA18524
may have been accidentally swapped. While we cannot verify whether a swap indeed occurred, users of the dataset are encouraged to also consider this alternate sample mapping (e.g. the array for NA18609 is actually NA18971 and vice versa) in their analyses.
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| Contributor(s) |
Yelensky R, Choy E, Altshuler D, Daly M |
| Citation(s) |
19043577 |
| Submission date |
May 28, 2008 |
| Last update date |
Aug 10, 2018 |
| Contact name |
Roman Yelensky |
| E-mail(s) |
ryelensky@gmail.com
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| Organization name |
MGH
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| Street address |
Massachusetts General Hospital Department of Molecular Biology 185 Cambridge St., Simches Ctr., CPZN-6818
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| City |
Boston |
| State/province |
MA |
| ZIP/Postal code |
02114-2790 |
| Country |
USA |
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| Platforms (1) |
| GPL96 |
[HG-U133A] Affymetrix Human Genome U133A Array |
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| Samples (374)
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| Relations |
| BioProject |
PRJNA106213 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE11582_RAW.tar |
771.4 Mb |
(http)(custom) |
TAR (of CEL) |
| Processed data included within Sample table |
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