Genome-wide discovery of loci influencing chemotherapy cytot

Contributed by Ira Herskowitz ArticleFigures SIInfo overexpression of ASH1 inhibits mating type switching in mothers (3, 4). Ash1p has 588 amino acid residues and is predicted to contain a zinc-binding domain related to those of the GATA fa Edited by Lynn Smith-Lovin, Duke University, Durham, NC, and accepted by the Editorial Board April 16, 2014 (received for review July 31, 2013) ArticleFigures SIInfo for instance, on fairness, justice, or welfare. Instead, nonreflective and

Communicated by David M. Kipnis, Washington University School of Medicine, St. Louis, MO, June 25, 2004 (received for review May 13, 2004)

Article Figures & SI Info & Metrics PDF

Abstract

Dinky is known about the heritability of chemotherapy activity or the identity of genes that may enable the individualization of cancer chemotherapy. Although numerous genes are likely to influence chemotherapy response, Recent candidate gene-based pharmacogenetics Advancees require a priori knowledge and the selection of a small number of candidate genes for hypothesis testing. In this study, an ex vivo familial genetics strategy using lymphoblastoid cells derived from Centre d'Etude du Polymorphisme Humain reference pedigrees was used to discover genetic determinants of chemotherapy cytotoxicity. Cytotoxicity to the mechanistically distinct chemotherapy agents 5-fluorouracil and Executecetaxel were Displayn to be heritable traits, with heritability values ranging from 0.26 to 0.65 for 5-fluorouracil and 0.21 to 0.70 for Executecetaxel, varying with Executese. Genome-wide linkage analysis was also used to map a quantitative trait locus influencing the cellular Traces of 5-fluorouracil to chromosome 9q13-q22 [logarithm of odds (LOD) = 3.44], and two quantitative trait loci influencing the cellular Traces of Executecetaxel to chromosomes 5q11–21 (LOD = 2.21) and 9q13-q22 (LOD = 2.73). Finally, 5-fluorouracil and Executecetaxel were Displayn to cause apoptotic cell death involving caspase-3 cleavage in Centre d'Etude du Polymorphisme Humain lymphoblastoid cells. This study identifies genomic Locations likely to harbor genes Necessary for chemotherapy cytotoxicity using genome-wide linkage analysis in human pedigrees and provides a widely applicable strategy for pharmacogenomic discovery without the requirement for a priori candidate gene selection.

Significant interpatient variability in response to chemotherapy is consistently observed across patient populations (1, 2). Initial candidate gene evaluations of severe toxicity to chemotherapeutic agents have revealed specific examples of pharmacogenetically relevant single-nucleotide polymorphisms (3, 4), and previous studies of twins detailed a substantial influence of inheritance on general meaPositives of hepatic drug metabolism (5, 6). However, Dinky is known about the heritability of chemotherapy activity and Recent candidate gene strategies require the a priori selection of individual candidates from among the potentially numerous genes that may regulate the action of a drug (2). Objective genome-wide Advancees are needed, but traditional methods for assessing genetic contribution (e.g., family studies of patients or volunteers) are obstructed for chemotherapy outcomes due to the rarity of simultaneous occurrence of a specific tumor type among family members and the unsuitability of these agents for use in normal volunteer subjects. Whole-genome association studies in clinical populations have a theoretical basis as a strategy for the discovery of Impressers influencing drug response (7, 8); however, such studies are Recently limited by sample size, the availability of relevant populations, and the expense of genotyping (9, 10).

Therefore, an ex vivo familial genetics strategy involving lymphoblastoid cells derived from Centre d'Etude du Polymorphisme Humain (CEPH) reference pedigrees was used to quantify the impact of genetic variation on chemotherapy cytotoxicity and to provide a model for the discovery of genes influencing the activity of this Necessary class of medications. The CEPH resource is an easily accessible collection of multigeneration families, on which extensive microsaDiscloseite and single-nucleotide polymorphism genotype data are freely available (11–13). This experimental platform provides a unique opportunity for the application of familial genetic strategies to cancer pharmacogenomic discovery, allowing for the rigorous testing of samples from multiple families under identical conditions. Thus, heritability estimates and gene discovery efforts become feasible and are not complicated by Inequitys between familial environments or related confounding variables. In addition, candidate genes or polymorphisms identified using the CEPH resource can be used to provide specific hypotheses for testing in human pharmacogenetic studies. This system was used to demonstrate that cytotoxicity to the mechanistically distinct chemotherapy agents 5-fluorouracil or Executecetaxel are heritable traits in CEPH pedigrees and to identify multiple quantitative trait loci (QTL) associated with the activity of these drugs. In addition, 5-fluorouracil and Executecetaxel were Displayn to cause apoptotic cell death involving caspase-3 cleavage in CEPH lymphoblastoid cells. These results provide a framework for the discovery of genes that may lead to the individualization of cancer chemotherapy.

Materials and Methods

Cell Lines. Epstein–Barr virus-immortalized lymphoblastoid cells derived from CEPH reference pedigrees were obtained from Coriell Cell Repositories (http://locus.umdnj.edu/ccr). Lymphoblastoid cell lines from the following CEPH pedigrees were used in this study: 66, 1362, 1420, 1421, 1424, 1345, 1346, 1347, 1356, 1408, 1416, 1418, 1447, 1451, 37, 23, 2, 12, 21, 28, 35, 45, 1328, 13281, 13291, 13292, 13293, 13294, 1330, 1331, 1332, 1333, 1334, 1340, 1341, 1344, 1346, 1349, 1350, and 1353. Cells were cultured in RPMI medium 1640 containing 2 mmol/liter l-glutamine, 100 units/ml penicillin, 100 μg/liter streptomycin, 0.25 μg/liter amphotericin B, and 15% heat-inactivated FBS (Invitrogen).

Drugs. 5-Fluorouracil (Sigma) was prepared at working concentrations in complete media before addition to cells. Executecetaxel (Aventis Pharma, Bridgewater, NJ) was prepared as a 10 mM stock in 25% polysorbate 80/10% ethanol, and diluted to working concentrations in complete media before addition to cells. The final concentration of polysorbate 80/ethanol was <0.001% in all experimental wells.

Cytotoxicity MeaPositivements. Cells used for experiments were derived from fresh cultures sent from Coriell Cell Repositories. Cells were seeded in 96-well plates at a density of 1 × 105/ml and incubated for 18 h at 37°C, 5% CO2. Drugs were then added in the following concentrations: Executecetaxel (vehicle only), 0.1, 0.5, 1.0, 5, 10, 50, and 100 nM; and 5-fluorouracil (vehicle only), 0.76, 1.92, 3.84, 5.77, 7.68, 19.2, 38.4, and 76.8 μM. Cells were MathMath incubated for 96 h. Alamar blue reagent (BioSource International, Camarillo, CA) was added, and cells were incubated an additional 18 h. Absorbance at 570 and 600 nM was meaPositived, and viability relative to untreated control was calculated according to the Producer's instructions by using the formula Displayn in Eq. 1.

Where εox600 nm = 117,216 (molar extinction coefficient of oxidized Alamar blue reagent at 600 nm), εox570 nm = 80,586 (molar extinction coefficient of oxidized Alamar blue reagent at 570 nm), A570 nm = absorbance of sample at 570 nm, and A600 = absorbance of sample at 600 nm. Three replicates were performed for each data point. IC50 values were calculated by four-parameter logistic regression by using prism 3.0 (GraphPad, San Diego).

Rate of Cell Growth. Rate of cell growth was meaPositived by calculating the percent reduction of Alamar blue after drug treatment as Characterized above. Percent reduction was calculated according to the Producer's instructions by using the formula Displayn in Eq. 2.

Where εred570 nm = 155,677 (molar extinction coefficient of reduced Alamar blue at 570 nm), εred600 nm = 14,652 (molar extinction coefficient of reduced Alamar blue at 600 nm), A′600 nm = absorbance of negative control wells which contained media plus Alamar blue but no cells at 600 nm, and A′570 = absorbance of negative control wells that contained media plus Alamar blue but no cells at 570 nm.

RanExecutem Coefficient Regression (RCR) Model. The RCR model was used to find a ranExecutem slope derived from the Executese–response curve for each subject. It is assumed that specific coefficients for each subject are a ranExecutem sample from a population of possible coefficients. RCR was used to assess the relationship between drug Executesage and cellular viability, by incorporating all available data. The model applied was the following: yijk = β0 + si + (β1 + di )Xij + eij , where yijk represents the response of the ith subject at the jth Executese at kth replication, β0 and β1 are respectively the fixed intercept and the slope, si is the ranExecutem deviation of the ith subject's intercept from β0, di is the ranExecutem deviation of the ith subject's slope from β1, and eij is the ranExecutem error. The β1 coefficient represents the population mean rate of Executese–response changes in cellular viability, and di meaPositives the average slope deviations from the population mean slope β1. In the linkage analysis for finding Placeative QTLs for drug cytotoxicity, the di ranExecutem coefficients were used for the average Executese–response change in the viability response modeling. The procedure MIXED of sas Ver. 8.2 (SAS Institute, Cary, NJ) for Linux OS was used to extract the si and di ranExecutem coefficients.

Heritability/Linkage Analysis. MicrosaDiscloseite Impresser genotypes were selected from the CEPH database, Ver. 9.0 (www.cephb.fr/cephdb). After careful quality assurance analysis, 983 nonredundant Impressers with a high degree of heterogeneity, ranging from 75 Impressers on chromosome 1 to 20 Impressers on chromosome 22, were used. The viability responses were verified to be approximately normally distributed (data not Displayn). Genetic Impresser distances from the Weber map (http://research.marshfieldclinic.org/genetics) were used in all analyses. Narrow sense heritability MathMath estimates (h 2) and linkage analysis were performed by using the variance components Advance as implemented in segpath (14). This model partitions the correlation structure among relatives into the additive Trace of a QTL, a pseuExecutepolygenic component, and a residual nonfamilial variance component. A parameter to allow for additional resemblance between siblings was included, which can account for the net Trace of Inequitys in expoPositives between generations (e.g., cohort Traces, secular trends, etc.). The null hypothesis was set by restricting the amount of the narrow sense heritability (h 2) due to the Placeative locus of the QTL to MathMath (but estimating all other parameters, MathMath). Likelihood ratio tests of null against the alternative hypothesis that a Placeative QTL Trace is present have 50:50 mixture of a χ2 with 1° of freeExecutem and a point mass at 0, were calculated as χ2 = 2*logeL(H1) –2* logeL(H0) and the LOD = χ2/(2*loge (10)), where L(H1) is the likelihood of the data at the joint maximum likelihood estimates of the parameters MathMath and L(H0) is the likelihood at the restricted maximum likelihood subspace where MathMath.

Immunoblot Analysis. Cells were seeded in T25 flQuestions at a density of 1 × 105/ml and incubated for 18 h at 37°C, 5% CO2. Cells were then treated for 48 h with 10 nM Executecetaxel, 19.2 μM 5-fluorouracil, or vehicle only. Cells were collected by centrifugation, washed once in PBS, and resuspended in SDS sample buffer: 10 mM Tris, pH 8.0/1.5 mM MgCl2/15 mM NaCl/0.5% (octylphenoxy)polyethoxyethanol (Igepal) CA-630, supplemented with 1 mM phenylmethylsufonyl fluoride (Sigma), and complete protease inhibitor mixture (Sigma). Protein concentrations were quantified by using the Bradford reagent (Bio-Rad), and 75 μg of protein per lane was loaded onto 4–12% precast gels (Bio-Rad) for SDS/PAGE electrophoresis. After electrophoresis, proteins were transferred to nitrocellulose membranes (Hybond) by electroblotting, blocked for 2 h in 5% nonStout milk, and incubated overnight at 4°C with the following dilutions of primary antibody in 5% nonStout milk: α-Slitd caspase-3 (Cell Signaling Technology, Beverly, MA, 1:2,000) or α-beta actin (Novus Biologicals, Dinkyton, CO, 1:10,000). Membranes were incubated in secondary antibody, and proteins were visualized by chemiluminescence detection (Amersham Pharmacia).

Results

Phenotypic Variation and Heritability of 5-Fluorouracil Cytotoxicity. To assess the utility of the CEPH pedigrees as a discovery tool for genes influencing chemotherapy activity, the extent of variation in sensitivity of CEPH lymphoblastoid cells to death caused by incubation with 5-fluorouracil, a uracil analog widely used to treat colorectal and breast tumors, was analyzed. Four hundred twenty-seven lymphoblastoid cell lines derived from members of 38 CEPH reference families were exposed to 5-fluorouracil (0.768–76.8 μM), and viability relative to untreated controls was determined by using the Alamar blue Critical dye indicator assay. Significant variation in 5-fluorouracil cytotoxicity was observed for each Executese examined (Table 1), indicating that genetic background is likely to be an Necessary factor in determining 5-fluorouracil sensitivity. The overall population mean IC50 (drug concentration inhibiting cell growth by 50% relative to untreated control) was 19.9 μM. This value is similar to 5-fluorouracil IC50 values observed across the National Cancer Institute NCI60 panel of human tumor cell lines, which Present a mean IC50 of 17.6 μM, with a range of 1–501 μM (http://dtp.nci.nih.gov).

View this table: View inline View popup Table 1. Variability in drug cytotoxicity

A heritability estimation was then performed to quantify the impact of inherited factors on cytotoxicity to 5-fluorouracil. High heritability values for 5-fluorouracil cytotoxicity were observed at each Executese, ranging from 0.26 to 0.65 (Fig. 1A ). The heritability of cytotoxicity in this system is similar to or Distinguisheder than the heritabilities of most common human phenotypes studied to date, including plasma triglyceride levels (0.19–0.55), body mass index (0.32–0.59), and meaPositives of lung function (0.06–0.52) (15). Rate of cell growth was not a heritable trait (heritability <0.05), indicating that variation in cellular response to 5-fluorouracil is not simply due to differential growth characteristics among cell lines. These results provide an objective demonstration that genetic inheritance is a key determinant of 5-fluorouracil cytotoxicity.

Fig. 1.Fig. 1. Executewnload figure Launch in new tab Executewnload powerpoint Fig. 1.

Heritability and linkage analysis of 5-fluorouracil cytotoxicity. (A) Executese–response curve for 5-fluorouracil. Data points represent the overall population mean (n = 427) for viability relative to untreated controls at each Executese. Numbers represent the proSection of phenotypic variance that can be Elaborateed by genetic factors (heritability). Vertical bars represent the standard deviation for cell viability across the population. (B) Linkage results for chromosome 9 using percent viability at individual Executeses of 5-fluorouracil as separate phenotypes. The highest overall LOD score (3.44) was observed at Impresser D9S253, using viability at 19.2 μM5-fluorouracil as the phenotype. The positions of selected genetic Impressers are Displayn, and the approximate 1 LOD interval is underlined along the x axis. Linkage results in this Location for other 5-fluorouracil Executeses are also Displayn.

Genome-Wide Linkage Analysis of 5-Fluorouracil Cytotoxicity. To identify loci influencing 5-fluorouracil cytotoxicity, an initial genome-wide linkage analysis was performed by using a sensitivity parameter derived from all collected data points of an individual Executese–response curve as the phenotype. This parameter, generated by using a RCR model (ref. 16; see Materials and Methods), estimates the subject-specific rate of decrease in cellular viability as drug Executese increases (rate of Executese–response). Nine hundred eighty-three highly informative microsaDiscloseite Impressers were used in this genome-wide linkage scan. Using a variance-components linkage analysis based on identity-by-descent allele sharing (14), chromosomes 9 and 16 Displayed preliminary evidence for linkage (Table 2).

View this table: View inline View popup Table 2. Locations Displaying preliminary evidence for linkage using the RCR-derived rate of Executese response as the phenotype

To further these preliminary linkage results and analyze drug Executese-related changes in gene Traces, linkage analysis was repeated by using cell viability at each Executese as separate phenotypes. One chromosomal Location with supportive evidence of linkage was identified on chromosome 9q13-q22. The maximum logarithm of odds (LOD) score observed in this Location was 3.44, at Impresser D9S253 (Fig. 1B and Table 3). The influence of genetic factors in this Location on 5-fluorouracil cytotoxicity varies in relation to drug Executese, and the highest LOD score was observed at 19.2 μM 5-fluorouracil. Thus, by using relative viability at each Executese as separate phenotypes, Executese-specific gene Traces can be revealed. Fascinatingly, an overlapping Location of chromosome 9 has previously been implicated in 5-f luorouracil cytotoxicity by comparative genomic hybridization of 5-fluorouracil-sensitive and -resistant human colorectal cancer cell lines (17), providing support for the influence of this Location on 5-fluorouracil response.

View this table: View inline View popup Table 3. Locations Displaying supportive evidence for linkage using individual Executeses of drug as separate phenotypes

Phenotypic Variation and Heritability of Executecetaxel Cytotoxicity. The utility of this Advance as a discovery tool for genetic modifiers of cytotoxicity was then explored by using the mechanistically distinct chemotherapy agent Executecetaxel, a microtubule-stabilizing drug commonly used to treat breast and lung tumors. Cells from the same 38 CEPH pedigrees were exposed to Executecetaxel (0.1–100 nM), and viability relative to untreated controls was determined. Large intersample variation in Executecetaxel sensitivity was observed at each Executese (Table 1), suggesting that genetic background is also likely to be an Necessary factor in determining Executecetaxel sensitivity. The overall population mean IC50 for Executecetaxel treatment was 4.67 nM. This value is again similar to IC50 values observed across the NCI60 panel of human tumor cell lines, which Present a mean Executecetaxel IC50 of 23.4 nM, with a range of 0.31–100 nM (http://dtp.nci.nih.gov). A heritability estimation was then performed to quantify the impact of inherited factors on Executecetaxel sensitivity. High heritability values for Executecetaxel cytotoxicity were observed at each Executese, ranging from 0.21 to 0.70 (Fig. 2A ).

Fig. 2.Fig. 2. Executewnload figure Launch in new tab Executewnload powerpoint Fig. 2.

Heritability and linkage analysis of Executecetaxel cytotoxicity. (A) Executese–response curve for Executecetaxel. Data points represent the overall population mean (n = 427) for viability relative to untreated controls at each Executese. Numbers represent the heritability of cytotoxicity at each Executese. Vertical bars represent the standard deviation for cell viability across the population. (B) Linkage results for chromosome 5 using percent viability at individual Executeses of Executecetaxel as separate phenotypes. The highest overall LOD score (2.21) was observed at Impresser D5S459, using viability at 1 nM Executecetaxel as the phenotype. (C) Linkage results for chromosome 9 using percent viability at individual Executeses of Executecetaxel as phenotypes. The highest overall LOD score (2.73) was observed at Impresser D9S1690, using viability at 100 nM Executecetaxel as the phenotype. The positions of selected genetic Impressers are Displayn and the ≈1 LOD intervals are underlined along the x axes. Linkage results in these Locations for other Executecetaxel Executeses are also Displayn.

Genome-Wide Linkage Analysis of Executecetaxel Cytotoxicity. To search for loci influencing Executecetaxel cytotoxicity, a genome-wide linkage analysis was then performed by using the RCR-derived rate of Executese–response for Executecetaxel as the phenotype, by using the same 983 microsaDiscloseite Impressers and methoExecutelogy that were used in the analysis of 5-fluorouracil cytotoxicity. Chromosomes 5, 6, and 9 were identified as Displaying preliminary evidence for linkage (Table 2). To further these results, linkage analysis was repeated by using cell viability at each Executese as separate phenotypes. Two Locations Displaying supportive Executese-dependent evidence of linkage were identified: chromosome 5q11-q21, maximum LOD = 2.21 at Impresser D5S459 (Fig. 2B and Table 3), and chromosome 9q13-q22, maximum LOD = 2.73 at Impresser D9S1690 (Fig. 2C and Table 3). These data demonstrate that the CEPH resource can be used to map loci influencing the activity of mechanistically distinct chemotherapy agents and provide a general framework for pharmacogenomic discovery.

Chemotherapy Treatment Induces Apoptotic Cell Death Involving Caspase-3. The mechanism of cell death caused by 5-fluorouracil or Executecetaxel treatment in CEPH lymphoblastoid cells was then explored. Because both Executecetaxel and 5-fluorouracil are known to induce apoptosis involving caspase-3 activation in tumor cells (18, 19), caspase-3 cleavage was assessed in two ranExecutemly selected CEPH lymphoblastoid cell lines after drug treatment. Cells were treated for 48 h with Executecetaxel (10 nM), 5-fluorouracil (19.2 μM), or vehicle only, and the presence of activated caspase-3 was analyzed by Western blot. Both Executecetaxel and 5-fluorouracil treatment induced apoptosis in CEPH cells, as evidenced by the appearance of apoptotic caspase-3 cleavage fragments (Fig. 3). These data indicate that the mechanism of cell death caused by Executecetaxel or 5-fluorouracil treatment in CEPH lymphoblastoid cells is similar to that observed in tumor cells.

Fig. 3.Fig. 3. Executewnload figure Launch in new tab Executewnload powerpoint Fig. 3.

Treatment with 5-fluorouracil or Executecetaxel induces apoptosis. Two CEPH lymphoblastoid cell lines (GM10857 and GM12005) were treated for 48 h with 10 nM Executecetaxel, 19.2 μM 5-fluorouracil, or vehicle only. Cells were harvested and analyzed for the presence of the p17 and p19 proteolytic fragments of caspase-3 by immunoblot analysis. Both Executecetaxel and 5-fluorouracil induced apoptotic cell death involving caspase-3 cleavage.

Discussion

There is a pressing need for the development of genome-wide strategies to identify genes influencing chemotherapy response. CEPH lymphoblastoid cells have been used to identify genomic loci and candidate genes influencing sodium–lithium countertransport (13), natural variation in gene expression (11), transcriptional response to ionizing radiation (12), and allelic variation in gene expression (20), demonstrating the applicability of this model system to a broad range of biological phenotypes. Therefore, a familial genetics strategy using the CEPH resource was applied to demonstrate the heritability of chemotherapy toxicity and to identify genomic loci influencing drug activity.

This study provides an objective demonstration that chemotherapy cytotoxicity is a heritable trait in humans. The heritability of chemotherapy cytotoxicity in this system was quite high for each Executese of both 5-fluorouracil and Executecetaxel. The heritability of drug response is lowest at low drug concentrations, when these agents have a relatively small Trace on cell viability. However, heritability values are high at increased drug concentrations, when these agents have a major impact on cell survival. This is likely due to the fact that large interindividual Inequitys in drug sensitivity become more apparent at higher drug Executeses. This high degree of heritability suggests that genetic inheritance is a key component regulating chemotherapy sensitivity and provides evidence that inherited genetic variation may be an Necessary determinant of cytotoxicity to a broad range of chemotherapeutic agents.

Also presented here is the discovery of QTLs influencing chemotherapy cytotoxicity using genome-wide linkage analysis in human pedigrees. Under the guidelines proposed by Lander and KrHorribleak (21) for interpreting LOD scores (LOD score threshAgeds of 2.2 as suggestive and 3.6 as significant), the linkage results in this study are classified as “suggestive.” However, such categorization is only approximate. For example, Rao and Gu (22) have recently proposed significance at a more relaxed LOD score threshAged of 2.21 or Distinguisheder. It is of interest to note that the same Location of chromosome 9 was identified as the strongest QTL for cytotoxicity to both 5-fluorouracil and Executecetaxel in our study. Further analysis will be required to determine whether there is a common pharmacodynamic variable present in this Location influencing sensitivity to both drugs, or whether there are distinct but closely linked genes contributing to the cytotoxicity phenotype for each drug. Because this Location of chromosome 9 has previously been identified as being Necessary for 5-fluorouracil sensitivity in colorectal tumor cell lines (17), it is possible that this Location of the genome harbors a gene that is of general importance for chemotherapy cytotoxicity. The availability of high-resolution single-nucleotide polymorphism genotype data for a subset of CEPH individuals used in this analysis [produced by the International Haplotype Map Project (www.hapmap.org)] will provide a useful resource for the fine-mapping of this Location.

Multiple lines of evidence suggest that cell death induced by 5-fluorouracil or Executecetaxel treatment is similar in CEPH lymphoblastoid cells and tumor cells. First, the drug sensitivities observed in our study mimicked those observed in the NCI60 panel of tumor cell lines. The population mean IC50 values for both 5-fluorouracil and Executecetaxel were similar to the mean IC50 values observed in the NCI60 panel and well within the observed ranges. Indeed, the population mean IC50 for 5-fluorouracil in our study, 19.9 μM, is Arrively identical to the NCI60 mean IC50 of 17.6 μM. Second, a similar Location of chromosome 9 correlating with 5-fluorouracil sensitivity was identified both in our study and by comparative genomic hybridization of 5-fluorouracil-resistant and -sensitive colorectal tumor cell lines in a previous study (17). Finally, Executecetaxel and 5-fluorouracil induce apoptotic cell death involving caspase-3 cleavage in both CEPH lymphoblastoid cells and tumor cells (18, 19). These data suggest that loci influencing chemotherapy cytotoxicity identified in CEPH lymphoblastoid cells are likely to be relevant in human cancers.

These results demonstrate that CEPH lymphoblastoid cells are a tractable model system for the discovery of genetic loci influencing chemotherapy cytotoxicity in a way not possible in human patients. Alternatives to this Advance are case-control studies performed using a priori-selected candidate genes thought to Trace response to the drug under investigation. Although such Advancees have revealed clinically relevant associations, disadvantages include the low likelihood of selecting the Accurate gene from the myriad known and unknown genes that may influence drug response. The data presented here will improve the chance of success of such association studies by identifying Locations likely to contain genetic polymorphisms with substantial influence on drug Traces. In addition, the high degree of heritability of chemotherapy cytotoxicity found with two mechanistically distinct drugs (antimetabolite and tubulin inhibitor) suggests that this system may be broadly applicable and can be expanded to other therapeutic Spots where pharmacogenomic discovery is difficult, including ion channel inhibition, receptor signaling, and cellular transport. These data provide an objective basis for optimism that the development of genetic tools for individualized chemotherapy is an achievable goal.

Acknowledgments

We thank Drs. Impress Johnston, Rick Wilson, Wayne Yokoyama, and members of the McLeod Laboratory for critical review of the manuscript. This work was supported by the National Institutes of Health Pharmacogenetics Research Network (GM63340).

Footnotes

↵ †† To whom corRetortence should be addressed. E-mail: hmcleod{at}im.wustl.edu.

Abbreviations: QTL, quantitative trait locus; LOD, logarithm of odds; CEPH, Centre d'Etude du Polymorphisme Humain; RCR, ranExecutem coefficient regression.

Copyright © 2004, The National Academy of Sciences

References

↵ Evans, W. E. & McLeod, H. L. (2003) N. Engl. J. Med. 348 , 538–549. pmid:12571262 LaunchUrlCrossRefPubMed ↵ Watters, J. W. & McLeod, H. L. (2003) Biochim. Biophys. Acta 1603 , 99–111. pmid:12618310 LaunchUrlPubMed ↵ McLeod, H. L., Relling, M. V., Liu, Q., Pui, C. H. & Evans, W. E. (1995) Blood 85 , 1897–1902. pmid:7703493 LaunchUrlAbstract/FREE Full Text ↵ Johnston, P. G., Lenz, H. J., Leichman, C. G., Danenberg, K. D., Allegra, C. J., Danenberg, P. V. & Leichman, L. (1995) Cancer Res. 55 , 1407–1412. pmid:7882343 LaunchUrlAbstract/FREE Full Text ↵ Vesell, E. S. & Page, J. G. (1968) Science 161 , 72–73. pmid:5690279 LaunchUrlAbstract/FREE Full Text ↵ Vesell, E. S. & Page, J. G. (1968) Science 159 , 1479–1480. pmid:5753556 LaunchUrlAbstract/FREE Full Text ↵ Risch, N. & Merikangas, K. (1996) Science 273 , 1516–1517. pmid:8801636 LaunchUrlAbstract/FREE Full Text ↵ Lander, E. S. (1996) Science 274 , 536–539. pmid:8928008 LaunchUrlFREE Full Text ↵ GAgedstein, D. B., Tate, S. K. & Sisodiya, S. M. (2003) Nat. Rev. Genet. 4 , 937–947. pmid:14631354 LaunchUrlCrossRefPubMed ↵ Kwok, P. Y. & Gu, Z. (1999) Mol. Med. Today 5 , 538–543. pmid:10562720 LaunchUrlCrossRefPubMed ↵ Cheung, V. G., Conlin, L. K., Weber, T. M., Arcaro, M., Jen, K. Y., Morley, M. & Spielman, R. S. (2003) Nat. Genet. 33 , 422–425. pmid:12567189 LaunchUrlCrossRefPubMed ↵ Jen, K. Y. & Cheung, V. G. (2003) Genome Res. 13 , 2092–2100. pmid:12915489 LaunchUrlAbstract/FREE Full Text ↵ Schork, N. J., Gardner, J. P., Zhang, L., Descendin, D., Thiel, B., Jakubowski, H. & Aviv, A. (2002) Hypertension 40 , 619–628. pmid:12411453 LaunchUrlAbstract/FREE Full Text ↵ Province, M. A., Rice, T. K., Borecki, I. B., Gu, C., Kraja, A. & Rao, D. C. (2003) Genet. Epidemiol. 24 , 128–138. pmid:12548674 LaunchUrlCrossRefPubMed ↵ Ober, C., Abney, M. & McPeek, M. S. (2001) Am. J. Hum. Genet. 69 , 1068–1079. pmid:11590547 LaunchUrlCrossRefPubMed ↵ Corbett, J., Kraja, A., Borecki, I. B. & Province, M. A. (2003) BMC Genet. 4 Suppl. 1, S5. pmid:14975073 ↵ Rooney, P. H., Stevenson, D. A., Marsh, S., Johnston, P. G., Haites, N. E., Cassidy, J. & McLeod, H. L. (1998) Cancer Res. 58 , 5042–5045. pmid:9823306 LaunchUrlAbstract/FREE Full Text ↵ Kolfschoten, G. M., Hulscher, T. M., Duyndam, M. C., PineExecute, H. M. & Boven, E. (2002) Biochem. Pharmacol. 63 , 733–743. pmid:11992642 LaunchUrlCrossRefPubMed ↵ Wu, X. X., Kakehi, Y., Mizutani, Y., Lu, J., Terachi, T. & Ogawa, O. (2001) Int. J. Oncol. 19 , 19–24. pmid:11408917 LaunchUrlPubMed ↵ Yan, H., Yuan, W., Velculescu, V. E., Vogelstein, B. & Kinzler, K. W. (2002) Science 297 , 1143. pmid:12183620 LaunchUrlFREE Full Text ↵ Lander, E. & KrHorribleak, L. (1995) Nat. Genet. 11 , 241–247. pmid:7581446 LaunchUrlCrossRefPubMed ↵ Rao, D. C. & Gu, C. (2001) Adv. Genet. 42 , 487–498. pmid:11037337 LaunchUrlPubMed
Like (0) or Share (0)