Multiple Loci Modulate Opioid Therapy Response for Cancer Pain

Published OnlineFirst May 27, 2011; DOI: 10.1158/1078-0432.CCR-10-3028

Clinical Cancer Predictive Biomarkers and Personalized Medicine Research

Antonella Galvan1, Frank Skorpen2,Pal Klepstad2,3, Anne Kari Knudsen2, Torill Fladvad2, Felicia S. Falvella1, Alessandra Pigni1, Cinzia Brunelli1, Augusto Caraceni1,2, Stein Kaasa2,4, and Tommaso A. Dragani1

Abstract Purpose: Patients treated with opioid drugs for cancer pain experience different relief responses, raising the possibility that genetic factors play a role in opioid therapy outcome. In this study, we tested the hypothesis that genetic variations may control individual response to opioid drugs in cancer patients. Experimental Design: We tested 1 million single-nucleotide polymorphisms (SNP) in European cancer patients, selected in a first series, for extremely poor (pain relief 40%; n ¼ 145) or good (pain relief 90%; n ¼ 293) responses to opioid therapy using a DNA-pooling approach. Candidate SNPs identified by SNP- array were genotyped in individual samples constituting DNA pools as well as in a second series of 570 patients. Results: Association analysis in 1,008 cancer patients identified eight SNPs significantly associated with pain relief at a statistical threshold of P < 1.0 10 3, with rs12948783, upstream of the RHBDF2 gene, showing the best statistical association (P ¼ 8.1 10 9). Functional annotation analysis of SNP-tagged genes suggested the involvement of genes acting on processes of the neurologic system. Conclusion: Our results indicate that the identified SNP panel can modulate the response of cancer patients to opioid therapy and may provide a new tool for personalized therapy of cancer pain. Clin Cancer Res; 17(13); 4581–7. 2011 AACR.

Introduction small, studies (3, 4). For example, the catecholamines dopamine, epinephrine, and norepinephrine and their Pain is the most dreaded symptom in patients with hydroxylated metabolites are substrates for the enzyme malignant disease. Indeed, each year several millions of catechol-O-methyltransferase (COMT) encoded by the men and women of all ages suffer from some form of COMT gene, in which genetic variations have been asso- invasive cancer associated with pain requiring chronic ciated with variations in pain perception and in doses of opioid treatment. At present, opioids are virtually the only opioids required for pain treatment; however, discrepan- analgesics able to control moderate and severe cancer pain. cies in the results from different association studies on Although opioids are widely used to treat cancer pain, COMT polymorphisms and pain perception have been clinical studies indicate great variability among individuals reported, possibly due to the small size of the studies with regard to the efficacy of these drugs and their side (reviewed in ref. 5). effects (1, 2). Many studies have investigated the potential The human mu 1 opioid receptor (OPRM1) gene, which genetic basis of individual variability in opioid drug is the main pharmacologic target of opioids, contains more response, but almost all have focused on a few candidate than 100 polymorphisms, and these polymorphisms might genes involved in opioid pharmacokinetics or pharmaco- affect opioid binding affinity to the receptor and, conse- dynamics, and results are not consistent among these, often quently, opioid-induced analgesia, tolerance, and depen- dence. However, a recent meta-analysis casts doubt on the clinical relevance of the OPRM1 118A>G polymorphism 1 Authors' Affiliations: Department of Predictive and Preventive Medicine, suggested by both preclinical and clinical studies as a Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy; 2European Palliative Care Research Center, Norwegian University of Science and candidate in personalized cancer pain therapy (6). Technology; and 3Departments of Anaesthesiology and Emergency Med- A complex genetics underlying interindividual differ- 4 icine and Oncology, St. Olavs University Hospital, Trondheim, Norway ences in opioid response is expected in light of the bio- Note: Supplementary data for this article are available at Clinical Cancer chemical and biological complexity of the drug response Research Online (http://clincancerres.aacrjournals.org/). and of pain control. Indeed, opioid effects are governed by Corresponding Author: Tommaso A. Dragani, Department of Predictive and Preventive Medicine, Fondazione IRCCS Istituto Nazionale Tumori, drug-related absorption, distribution, metabolism, intrin- Via G.A. Amadeo 42, 20133 Milan, Italy. Phone: 39-0223902642; Fax: 39- sic efficacy of the receptors involved, and by signal path- 0223902764; E-mail: [email protected] ways downstream of the receptors. Because each of these doi: 10.1158/1078-0432.CCR-10-3028 steps in pain control is modulated by several genes, each of 2011 American Association for Cancer Research. which can exist in allelic forms in the general population, a

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Translational Relevance Pain relief phenotype and DNA pool construction The pain relief phenotype under study is semi-quantita- Pain is a common complication of almost all types tive and determined based on the BPI, a robust and of advanced cancer, and treatment with opioids pro- psychometric validated method to assess the subjective duces variable responses of pain relief among indivi- severity of pain. Pain relief is measured using an 11-point duals. Indeed, a variable percentage of cancer patients numerical rating scale, from 0%, representing "no pain experiences reduced or poor benefit from opioid ther- relief" to 100% or "complete pain relief," that is, 0%, 10%, apy, with impairment of their quality of life. Our 20%, etc. (9). association study in 1,008 European cancer patients For DNA pool preparation, we first defined the cancer identified 8 single-nucleotide polymorphisms (SNP) patients as "good" or "poor" responders to opioid therapy, that are statistically associated with pain relief, which based on their pain relief phenotype score of 90% or more together might modulate the response of cancer or 40% or less, respectively (Fig. 1). Selection was stratified patients to opioid therapy and might serve as targe- by gender and country of origin, with a 1:2 matching of table tools to design new drugs. Our functional anno- "poor" and "good" responders, to obtain a balanced repre- tation analysis of SNP-tagged genes revealed, for the sentation of patients in the 2 groups. DNA pools of "good" n ¼ ¼ n ¼ first time, the involvement of genes acting on processes ( 293; mean pain relief 94.1%) and "poor" ( 145; ¼ of the neurologic system rather than on opioid meta- mean pain relief 27.0%) responders were created using bolism or pharmacodynamics. Thus, the identified equal amounts of fluorimetrically measured DNA from SNPpanelmayprovideanewtoolforpersonalized each sample. therapy of cancer pain. SNP genotyping SNP-array analysis of each of the 2 DNA pools was carried out using the HumanOmni1-Quad BeadChip (Illumina), which allows analysis of 1,140,419 genetic genome-wide comprehensive analysis would be required markers, including more than 20,000 markers in more to identify all genetic factors involved. than 300 important gene regions related to drug absorp- In this study, we conducted the first genome-wide asso- tion, distribution, metabolism, and excretion; several of the ciation study (GWAS) in cancer patients treated with SNPs map to opioid receptor or metabolism genes (http:// opioids using a 1-million single-nucleotide polymorphism www.illumina.com/products/humanomni1_quad_bead- (SNP)-array to identify new genetic variations that mod- chip_kits.ilmn). We carried out 12 replicas to verify geno- ulate individual pain relief. type reproducibility and to estimate technical variability. Data were obtained as intensity signals, which were used to Patients and Methods determine the allelic frequencies of each genetic marker

Study design The European Pharmacogenetic Opioid Study (EPOS) represents a multicentric effort to examine symptoms, pharmacology, and pharmacogenomics related to the use of opioids. Recruitment criteria of patients included 400 a regularly scheduled opioid treatment that was stable for at least 3 days. Opioids administered to more than 5% of 300 patients included morphine, oxycodone, and fentanyl. The study includes 2,294 cancer patients treated with opioids for moderate or severe pain and recruited from 17 centers 200 of 11 European countries. The participation of the Research Steering Committee from the European Association for No. of cases No. Palliative Care (EAPC) facilitated international coopera- 100 tion in the study. The study collected demographic and personal data, as well as malignant diagnosis and opioid treatment details 0 from cancer patients. Opioid doses were converted to equivalent total daily oral morphine doses (7). Pain was 0 20 40 60 80 100 assessed by completing the Brief Pain Inventory (BPI; ref. Pain relief (%) 8). Functional status was measured by the Karnofsky per- formance status score. Further details about the EPOS – series, including opioid doses and recruitments, have been Figure 1. Distribution of the pain relief phenotype (0% 100%) in cancer patients of the EPOS series. Bar indicates the number of cancer patients reported (7). The study collected whole blood for genetic genotyped in the first (red) and second (green) series or those who were not analysis and has established a biobank. analyzed (yellow).

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Table 1. Phenotypic characteristics of EPOS cancer patients examined for response to opioid therapy

Subject characteristics First series Second series

Good responders Poor responders

No. of subjects 293 145 570 Gender Male 150 73 308 Female 143 72 262 Median age (range)a 61 (32–88) 63 (18–86) 62 (27–91) Country of origin CH 28 14 22 DE 63 34 62 DK 0 0 17 FI 0 0 18 GB 33 15 109 IS 0 0 82 IT 22 11 141 LT 0 0 29 NO 121 58 61 SE 26 13 29 Pain relief (percentage score; mean SE) 94.1 0.3 27.0 1.1 76.5 1.1 Total oral morphine equivalent opioid dose (mg; mean SE) 287 28 402 56 293 17

aAge in years. Abbreviations: CH, Switzerland; DE, Germany; DK, Denmark; FI, Finland; GB, Great Britain; IS, Iceland; IT, Italy; LT, Lithuania; NO, Norway; SE, Sweden. and to reconstruct the number of chromosomes carrying Results each of the 2 possible alleles. Individual samples were genotyped using MassARRAY (Sequenom, Inc.), as The study population for which pain relief values were described previously (10). available included 1,907 patients from 4 ethnic groups: (i) Caucasian, including Hispanic (n ¼ 1,859), (ii) Gene analysis African (n ¼ 13), (iii) Oriental (n ¼ 4), and (iv) other To explore the role of the associated variants in the (n ¼ 29), and from 11 European countries of origin. biological context, we mapped the best statistically asso- Patients included in the DNA pools constituted the first ciated SNPs in the DNA pools (n ¼ 486; P < 1.0 10 3), series (n ¼ 438), whereas the second series of 570 EPOS using the Ensembl database to identify genes that are patients was selected based on pain relief phenotype possibly involved in pain relief response, and analyzed score 90% or 50% to extend the results of the GWAS the gene list for enrichment in ontologic annotation terms (Fig. 1). Table 1 lists the phenotypic characteristics of using the DAVID Functional Annotation Tool and Cluster- patients analyzed in the present study. The pain relief ing (ref. 11; http://david.abcc.ncifcrf.gov/home.jsp). mean value was slightly higher in the second series (76.5 1.1 vs. 71.9 1.6; P ¼ 0.014, on ANOVA), whereas no Statistical analyses statistically significant differences were observed in the Chromosome counts of the "poor" and "good" pain mean total oral morphine equivalent opioid dose relief groups, from which DNA pools were prepared, were (Table 1). reconstructed based on allelic frequencies assessed in SNP- Preliminary analysis for factors that might confound array hybridization, and the resulting 2 2 contingency theassessmentofthepainreliefphenotyperevealeda tables were tested by c2 analysis. Association analyses weak effect of gender (P ¼ 0.019) and a strong effect of between SNPs and the pain relief phenotype (categorical country of origin (P < 2.2 10 16,onANOVA; variable, "poor" or "good" responders, or quantitative Supplementary Table S1). No statistically significant variable) were carried out using PLINK software (12), association between the pain relief phenotype and which included analysis of the Hardy–Weinberg equili- age of patients, ethnicity, or tumor type was found. brium (HWE), linkage disequilibrium between SNPs, Thus, we normalized the pain relief phenotype by the and population-based associations between phenotypes country mean value and adjusted analyses for gender as and genotype/allelotype (Supplementary Fig. S1). covariate.

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11 Figure 2. Manhattan plot of the GWAS in DNA pools of poor or 10 rs2473967 good responders to opioid therapy for cancer pain. Points 9 represent the statistical association of each of more than 8 173,000 SNPs (chromosome X is SPON1 shown as chromosome 23) with 2 (observed value) 7 pain relief category (c test on 10 ZNF235 reconstructed chromosome rs7757130 RHBDF2 counts). A total of 486 SNPs

–log 6 rs2884129 rs12211463 showed statistical association at rs13421094 3 5 P < 1.0 10 . Red points indicate SNPs and their relevant 4 genes as confirmed by genotyping of 1,008 individuals (see Table 3). 3

1234567891011121314151617181920212223 Chromosome

Genes involved in neurologic system processes may cant gene ontologic annotation terms those linked to the modulate pain relief nervous system, such as the "neurological system process," In our search for genetic variations associated with "transmission of nerve impulse," and "synaptic transmis- individual pain relief, we analyzed the EPOS subjects sion." Notably, the best term was the "neurological system showing the extreme phenotypic values of pain relief in process," which included 31 genes (P ¼ 3.5 10 5; order to reduce the bias in the subjective pain relief assess- Table 2). Interestingly, 10 of these 31 genes were members ment of the borderline categories and to allow testing for of the olfactory receptor family. Use of Functional Annota- genetic effects on response to pain therapy in the best tion Clustering gave similar results, with the most highly candidate subjects (Fig. 1). significant cluster including the annotation terms "trans- GWAS, using a DNA-pooling strategy and 1-million mission of nerve impulse," "synaptic transmission," and SNP-array, detected 173,851 informative SNPs, with over- "cell–cell signaling" (not shown). all minor allelic frequency more than 0.1 and coefficient of variation of allelic frequency of (SD/mean) more than A genetic profile controls pain relief 0.08. Statistical associations of these SNPs are visualized Among the 486 candidate SNPs identified by statisti- by Manhattan plot (Fig. 2). Analysis of chromosome cally significant differences (P < 1.0 10 3,onc2 test) counts obtained from allelic frequencies in DNA pools between "poor" and "good" responders in chromosome of "good" and "poor" responders identified 486 SNPs at counts, we selected 72 SNPs associated with the pain the statistical threshold of P < 1.0 10 3 (c2 test; Fig. 2; relief phenotype (at P < 1.0 10 5 threshold value) Supplementary Fig. S1). for genotyping in individual samples constituting the To explore the role of the associated variants in the DNA pools, and in the second series of 570 EPOS patients biological context, we identified the genes tagged by these byMassARRAY(Table1;Fig.1).SixSNPsfailedPCRor 486 SNPs. A list of 226 known genes, either near or MassEXTEND primer design, and another 7 failed geno- containing a SNP, was obtained and analyzed using the typing. Of the 59 genotyped SNPs, 2 showed significant Functional Annotation Tool (http://david.abcc.ncifcrf.gov/ deviation from the HWE (P < 1.0 10 3), reducing the home.jsp), which identified as the best statistically signifi- number of markers to 57 SNPs.

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Table 2. Gene ontologic analysis by DAVID of the 226 genes defined by the 486 SNPs most significantly (P < 0.001) associated with allelic imbalance in the SNP-array analysis of DNA pools from "poor" or "good" responders to opioid therapy for cancer pain

Term Gene Pa Genes count

GO:0050877 neurological system 31 3.5 105 ABLIM1, OR8U9, AGTPBP1, SYT5, KCNA1, COL2A1, OR4C6, process RAX2, OR4S2, ELOVL4, OR8K3, DMD, OR4C11, OR5AS1, KCNE1, OR5AP2, COL4A4, COL18A1, OR5R1, OR11L1, PCDH15, AFF2, NRXN1, OR5T3, ACCN1, SLC17A6, SBF2, ABAT, TBL1X, NCAN, PTENP1 GO:0007155 cell adhesion 17 6.1 103 COL18A1, PLXNC1, NRP1, C21ORF29, NELL1, ACTN1, COL2A1, PCDH15, NRXN1, BTBD9, ITGBL1, CDH12, CD96, SORBS1, NCAN, JAM2, SPON1 GO:0022610 biological adhesion 17 6.2 103 COL18A1, PLXNC1, NRP1, C21ORF29, NELL1, ACTN1, COL2A1, PCDH15, NRXN1, BTBD9, ITGBL1, CDH12, CD96, SORBS1, NCAN, JAM2, SPON1 GO:0019226 transmission of nerve 11 6.8 103 COL4A4, ACCN1, SLC17A6, SYT5, AGTPBP1, SBF2, DMD, impulse KCNA1, ABAT, NRXN1, NCAN GO:0007268 synaptic transmission 10 7.1 103 COL4A4, ACCN1, SLC17A6, SYT5, AGTPBP1, DMD, KCNA1, ABAT, NRXN1, NCAN GO:0050890 cognition 20 7.4 103 COL18A1, ABLIM1, OR5R1, OR8U9, OR11L1, PCDH15, AFF2, COL2A1, OR4C6, OR5T3, RAX2, OR4S2, ELOVL4, OR8K3, OR4C11, OR5AS1, OR5AP2, KCNE1, TBL1X, PTENP1

aCalculated by the DAVID functional annotation tool, using a modified Fisher's exact test.

Association analysis in the first series indicated that 54 of Discussion the 57 SNPs were significantly associated with the poor and good responder categories at P < 0.05 (logistic analysis), Opioid efficacy for the treatment of pain in cancer confirming the robustness of our DNA-pooling approach, patients varies greatly among individuals, suggesting a role which producesreliable resultsand is time-and cost-effective, for genetic factors in pain relief outcome. Unlike previous in agreement with other reports (13, 14). SNP rs12948783, pharmacogenetic studies that have tested genetic variations which maps to chromosome 17 upstream of the RHBDF2 of a few candidate genes in a small number of subjects, our gene, showed the strongest association (P ¼ 1.1 10 7). present study represents the first use of genome-wide Analysis of the total sample size of 1,008 cancer patients scanning in a large number of opioid-treated cancer for the quantitative pain relief phenotype, allowing an patients to identify genetic variations that may explain increased statistical power of the study, pointed to 8 SNPs differences in pain relief. associated at the statistical threshold of P < 1.0 10 3, with Pain relief, an inherently subjective parameter, was indeed the strongest allelic association, again, for SNP rs12948783 the phenotype quantified through the BPI method in cancer (RHBDF2; P ¼ 1.1 10 8; linear model; Table 3; Supple- patients included in the EPOS study; surprisingly, we found a mentary Fig. S1). significant correlation between pain relief and country of Genotype–phenotype analysis for rs12948783 SNP in origin, but not with ethnicity. The association with country of 936 patients (72 genotypes were missing) showed that origin might rest in subtle variations in phenotype defini- patients homozygous for the rare allele, that is, the AA tions related to each country or in organizational differences genotype, experienced a low normalized pain relief value between health care services in various European countries (mean SE, 80% 9%; n ¼ 23) that did not differ that introduce variability in selection of patients at EPOS statistically from that of patients with the GA genotype recruitment, although the BPI questionnaire is officially (mean SE, 88.5% 3%; n ¼ 243). Comparison of the recognized and recommended by EAPC and has been vali- subjects carrying the rare allele (AA or GA genotypes, n ¼ dated across cultures and languages. The lack of association 266) with patients carrying the common GG genotype between pain relief and ethnicity may be genuine, although (mean SE, 104% 1%; n ¼ 670) showed a highly the non-homogeneous distribution of patients into 4 ethnic statistically significant association (P ¼ 8.1 10 9) with groups (97.6% of patients were ethnically Caucasian) may patients carrying the GG genotype and with almost com- undermine the statistical power to detect effects linked to plete pain relief (Fig. 3). ethnicity.

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105 a b series P 0.367 0.073 0.757 0.212 0.03 0.759 0.041 0.99 Second b

4 4 6 6 4 5 8 4 100 10 10 10 10 10 10 10 10 y gender). , individual

P genotyping 5.8 5.8 1.5 8.1 2.6 6.8 2.1 2.2 95 c 6 6 7 10 6 8 7 7 First series

90 10 10 10 10 10 10 10 10 Normalized pain relief (%)

, DNA pools –9 P = 8.1 × 10 P 6.5 3.9 2.9 1.3 1.9 2.2 5.8 3.8 85

5 4 4 5 5 4 8 4 AA or GA GG ) with pain relief; SNPs with statistically significant 3 10 10 10 10 10 10 10 10 rs12948783 10 b P Figure 3. RHBDF2 on chromosome 17 is a major pain relief modifier locus 1.0 in the EPOS series of opioid-treated cancer patients. Cancer patients < carrying the rare allele (either the AA or GA genotype; n ¼ 266) at SNP P rs12948783 located in the 50-proximal region of the RHBDF2 gene showed 0.11570.1434 5.4 0.09343 6.2 0.1172 7.5 0.1415 7.3 0.1447 1.1 4.1 0.09789 8.0 0.07732 6.6 a statistically significant lower pain relief than patients with the common b b GG genotype (n ¼ 670), who showed an almost complete response to opioid therapy (P ¼ 8.1 109, on ANOVA). Dots and bars represent mean SE values of the normalized pain relief phenotype.

Analysis of candidate SNPs defined a set of 8 genetic First and second combined series markers associated with individual response to opioid Frequency of the minor allele 0.07 0.15 0.05 0.14 0.19 0.07 0.07 0.2 therapy for cancer pain (Table 3). Of these 8 SNPs, the best statistically associated SNP maps at the 50-proximal region, 1,892 base pairs (bp) from the transcriptional start site of the rhomboid 5 homolog 2 (Drosophila; RHBDF2)

Common allele gene, of unknown function (Fig. 3). rs7104613 is located in the intron region of the spondin 1 extracellular matrix protein (SPON1) gene, which encodes a cell-adhesion allele TCAGTG GA GTACCAGT protein that promotes the attachment of spinal cord and sensory neuron cells and the outgrowth of neurites in vitro. rs10413396 maps at 101 bp from the 50 region of the zinc finger protein 235 (ZNF235) gene, which is located in a

SPON1 RHBDF2 ZNF235 cluster of genes encoding members of regulatory proteins characterized by nucleic acid–binding zinc finger domains. None of the genetic variations found in the present study

) were excluded. mapped in the opioid receptor genes that were suggested by 3

previous studies as candidates for individualized opioid 10 treatment (reviewed in ref. 4). Instead, our results point to 157.8 93.5 113.4 113.6 17.6 14 72 49.5 the involvement of genes related to transmission of nerve 1.0 impulse, not opioid pharmacology, in mediating the main < analysis on reconstructed chromosome numbers in DNA pools. P modulatory effect of genetic variability on the perception of 2 c pain. Nonetheless, it remains possible that opioid therapy outcome is the result of interaction of complex biological systems involved in both pathways, particularly consider- ing that the biological function of some genes that we List of 8 SNPs associated with the quantitative pain relief phenotype in 1,008 European cancer patients treated with opioids

regression coefficient values were obtained by allelic association of SNPs with country-normalized pain relief phenotype (linear model adjusted b identified is, as yet, unknown or uncertain. b Our findings could represent the starting point to allow and

values obtained by estimation of the probability of being a poor responder to P SNPs genotyped in individual cancer patients by MassARRAY and showing statistically significant association ( P Table 3. SNP Chromosome Positionrs13421094 (Mb) 2 Gene Minor a b c deviation from the HWE ( rs12211463rs7757130 6 rs2473967 6 rs2884129 6 rs7104613 10 rs12948783 11 rs10413396 17 19 opioid treatment, thus leading to personalized cancer pain therapy in which, for example, individuals at genetic risk of

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poor response would receive higher starting doses of A. Caraceni), Vilnius, Lithuania (I. Poviloniene), Stockholm, Sweden (S. Lundstrom),€ St. Gallen, Switzerland (F. Strasser), and Sutton/Chelsea, opioids. Moreover, genes tagged by these polymorphisms United Kingdom (A. Davies). may provide a target for new therapeutic strategies to The authors also thank Harvard-Partners Center for Genetics and Geno- control cancer pain perception. mics Genotyping Facility, Cambridge, MA, for their assistance in custom genotyping by MassARRAY. Disclosure of Potential Conflicts of Interest Grant Support No potential conflicts of interest were disclosed. This work was supported by the Associazione and Fondazione Italiana Ricerca Cancro (AIRC and FIRC), the Fondazione Floriani, Milan, Italy, the Acknowledgments Norwegian Research Council and the EU's 6th framework (contract no. 037777). A.K. Knudsen received a grant from the Central Norway Regional Health The authors thank all centers and principal investigators of each center Authority. contributing to the EPOS study: Trondheim, Norway (P. Klepstad and The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked S. Kaasa), Oslo, Ulleval, Norway (J. Havard Loge), Oslo, Radiumhospitalet, advertisement Norway (K. Bjordal), Copenhagen, Denmark (P. Sjgren), Turku, Finland in accordance with 18 U.S.C. Section 1734 solely to indicate (E. Salminen), Essen, Germany (M. Kloke), Aachen, Germany (L. Rad- this fact. bruch), Dresden, Germany (R. Sabatowski), Athens, Greece (E. Argyra), Reykjavik, Iceland (V. Sigurdardottir and S. Gunnarsdottir), Forli, Received November 12, 2010; revised April 21, 2011; accepted May 11, Italy (M. Maltoni), Pavia, Italy (D. Miotti), Milan, Italy (A. Pigni and 2011; published OnlineFirst May 27, 2011.

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Multiple Loci Modulate Opioid Therapy Response for Cancer Pain

Antonella Galvan, Frank Skorpen, Pål Klepstad, et al.

Clin Cancer Res Published OnlineFirst May 27, 2011.

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