The variability in treatment outcomes among patients receiving the same therapy for seemingly similar tumors can be attributed in part to genetics. The tumor's (somatic) genome largely dictates the effectiveness of the therapy, and the patient's (germline) genome influences drug exposure and the patient's sensitivity to toxicity. Many potentially clinically useful associations have been discovered between common germline genetic polymorphisms and outcomes of cancer treatment. This review highlights the germline pharmacogenetic associations that are currently being used to guide cancer treatment decisions, those that are most likely to someday be clinically useful, and associations that are well known but their roles in clinical management are not yet certain. In the future, germline genetic information will likely be available from tumor genetic analyses, creating an efficient opportunity to integrate the two genomes to optimize treatment outcomes for each individual cancer patient.


Article metrics loading...

Loading full text...

Full text loading...


Literature Cited

  1. Kandoth C, McLellan MD, Vandin F. 1.  et al. 2013. Mutational landscape and significance across 12 major cancer types. Nature 502:333–39 [Google Scholar]
  2. Chmielecki J, Meyerson M. 2.  2014. DNA sequencing of cancer: What have we learned. Annu. Rev. Med. 65:63–79 [Google Scholar]
  3. Hertz DL, McLeod HL. 3.  2013. Use of pharmacogenetics for predicting cancer prognosis and treatment exposure, response and toxicity. J. Hum. Genet. 58:346–52 [Google Scholar]
  4. McLeod HL, Evans WE. 4.  2001. Pharmacogenomics: unlocking the human genome for better drug therapy. Annu. Rev. Pharmacol. Toxicol. 41:101–21 [Google Scholar]
  5. Daly AK.5.  2012. Using genome-wide association studies to identify genes important in serious adverse drug reactions. Annu. Rev. Pharmacol. Toxicol. 52:21–35 [Google Scholar]
  6. Martin MA, Kroetz DL. 6.  2013. Abacavir pharmacogenetics—from initial reports to standard of care. Pharmacotherapy 33:765–75 [Google Scholar]
  7. Hertz DL, McLeod HL. 7.  2014. Using pharmacogene polymorphism panels to detect germline pharmacodynamic markers in oncology. Clin. Cancer Res. 20:2530–40 [Google Scholar]
  8. Crews KR, Hicks JK, Pui CH. 8.  et al. 2012. Pharmacogenomics and individualized medicine: translating science into practice. Clin. Pharmacol. Ther. 92:467–75 [Google Scholar]
  9. Teutsch SM, Bradley LA, Palomaki GE. 9.  et al. 2009. The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Initiative: methods of the EGAPP working group. Genet. Med. 11:3–14 [Google Scholar]
  10. Hall JM, Friedman L, Guenther C. 10.  et al. 1992. Closing in on a breast cancer gene on chromosome 17q. Am. J. Hum. Genet. 50:1235–42 [Google Scholar]
  11. Brugarolas J, Jacks T. 11.  1997. Double indemnity: p53, BRCA and cancer. Nat. Med. 3:721–22 [Google Scholar]
  12. Poklar N, Pilch DS, Lippard SJ. 12.  et al. 1996. Influence of cisplatin intrastrand crosslinking on the conformation, thermal stability, and energetics of a 20-mer DNA duplex. Proc. Natl. Acad. Sci. USA 93:7606–11 [Google Scholar]
  13. Cass I, Baldwin RL, Varkey T. 13.  et al. 2003. Improved survival in women with BRCA-associated ovarian carcinoma. Cancer 97:2187–95 [Google Scholar]
  14. Alsop K, Fereday S, Meldrum C. 14.  et al. 2012. BRCA mutation frequency and patterns of treatment response in BRCA mutation-positive women with ovarian cancer: a report from the Australian ovarian cancer study group. J. Clin. Oncol. 30:2654–63 [Google Scholar]
  15. Farmer H, McCabe N, Lord CJ. 15.  et al. 2005. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 434:917–21 [Google Scholar]
  16. Bryant HE, Schultz N, Thomas HD. 16.  et al. 2005. Specific killing of BRCA2-deficient tumours with inhibitors of poly(ADP-ribose) polymerase. Nature 434:913–17 [Google Scholar]
  17. Audeh MW, Carmichael J, Penson RT. 17.  et al. 2010. Oral poly(ADP-ribose) polymerase inhibitor olaparib in patients with BRCA1 or BRCA2 mutations and recurrent ovarian cancer: a proof-of-concept trial. Lancet 376:245–51 [Google Scholar]
  18. Kaye SB, Lubinski J, Matulonis U. 18.  et al. 2012. Phase II, open-label, randomized, multicenter study comparing the efficacy and safety of olaparib, a poly (ADP-ribose) polymerase inhibitor, and pegylated liposomal doxorubicin in patients with BRCA1 or BRCA2 mutations and recurrent ovarian cancer. J. Clin. Oncol. 30:372–79 [Google Scholar]
  19. Hennessy BT, Timms KM, Carey MS. 19.  et al. 2010. Somatic mutations in BRCA1 and BRCA2 could expand the number of patients that benefit from poly (ADP ribose) polymerase inhibitors in ovarian cancer. J. Clin. Oncol. 28:3570–6 [Google Scholar]
  20. 20.  2014. Positive results for drug combo in I-SPY 2 trial. Cancer Discov. 4:OF2 [Google Scholar]
  21. Pavlos R, Mallal S, Phillips E. 21.  2012. HLA and pharmacogenetics of drug hypersensitivity. Pharmacogenomics 13:1285–306 [Google Scholar]
  22. Spraggs CF, Budde LR, Briley LP. 22.  et al. 2011. HLA-DQA1*02:01 is a major risk factor for lapatinib-induced hepatotoxicity in women with advanced breast cancer. J. Clin. Oncol. 29:667–73 [Google Scholar]
  23. Schaid DJ, Spraggs CF, McDonnell SK. 23.  et al. 2014. Prospective validation of HLA-DRB1*07:01 allele carriage as a predictive risk factor for lapatinib-induced liver injury. J. Clin. Oncol. 32:2296–303 [Google Scholar]
  24. Krynetski EY, Schuetz JD, Galpin AJ. 24.  et al. 1995. A single point mutation leading to loss of catalytic activity in human thiopurine S-methyltransferase. Proc. Natl. Acad. Sci. USA 92:949–53 [Google Scholar]
  25. Tai HL, Krynetski EY, Schuetz EG. 25.  et al. 1997. Enhanced proteolysis of thiopurine S-methyltransferase (TPMT) encoded by mutant alleles in humans (TPMT*3A, TPMT*2): mechanisms for the genetic polymorphism of TPMT activity. Proc. Natl. Acad. Sci. USA 94:6444–49 [Google Scholar]
  26. Otterness DM, Szumlanski CL, Wood TC, Weinshilboum RM. 26.  1998. Human thiopurine methyltransferase pharmacogenetics. Kindred with a terminal exon splice junction mutation that results in loss of activity. J. Clin. Investig. 101:1036–44 [Google Scholar]
  27. Relling MV, Hancock ML, Rivera GK. 27.  et al. 1999. Mercaptopurine therapy intolerance and heterozygosity at the thiopurine S-methyltransferase gene locus. J. Natl. Cancer Inst. 91:2001–8 [Google Scholar]
  28. Lennard L, Lilleyman JS, Van Loon J, Weinshilboum RM. 28.  1990. Genetic variation in response to 6-mercaptopurine for childhood acute lymphoblastic leukaemia. Lancet 336:225–29 [Google Scholar]
  29. Black AJ, McLeod HL, Capell HA. 29.  et al. 1998. Thiopurine methyltransferase genotype predicts therapy-limiting severe toxicity from azathioprine. Ann. Intern. Med. 129:716–18 [Google Scholar]
  30. Stanulla M, Schaeffeler E, Flohr T. 30.  et al. 2005. Thiopurine methyltransferase (TPMT) genotype and early treatment response to mercaptopurine in childhood acute lymphoblastic leukemia. JAMA 293:1485–89 [Google Scholar]
  31. Schmiegelow K, Forestier E, Hellebostad M. 31.  et al. 2010. Long-term results of NOPHO ALL-92 and ALL-2000 studies of childhood acute lymphoblastic leukemia. Leukemia 24:345–54 [Google Scholar]
  32. Levinsen M, Rotevatn EO, Rosthoj S. 32.  et al. 2014. Pharmacogenetically based dosing of thiopurines in childhood acute lymphoblastic leukemia: influence on cure rates and risk of second cancer. Pediatr. Blood Cancer 61:797–802 [Google Scholar]
  33. Yates CR, Krynetski EY, Loennechen T. 33.  et al. 1997. Molecular diagnosis of thiopurine S-methyltransferase deficiency: genetic basis for azathioprine and mercaptopurine intolerance. Ann. Intern. Med. 126:608–14 [Google Scholar]
  34. Hindorf U, Appell ML. 34.  2012. Genotyping should be considered the primary choice for pre-treatment evaluation of thiopurine methyltransferase function. J. Crohn's Colitis 6:655–59 [Google Scholar]
  35. van den Akker-van Marle ME, Gurwitz D, Detmar SB. 35.  et al. 2006. Cost-effectiveness of pharmacogenomics in clinical practice: a case study of thiopurine methyltransferase genotyping in acute lymphoblastic leukemia in Europe. Pharmacogenomics 7:783–92 [Google Scholar]
  36. Bell GC, Crews KR, Wilkinson MR. 36.  et al. 2014. Development and use of active clinical decision support for preemptive pharmacogenomics. J. Am. Med. Inform. Assoc. 21:e93–99 [Google Scholar]
  37. Relling MV, Klein TE. 37.  2011. CPIC: Clinical Pharmacogenetics Implementation Consortium of the Pharmacogenomics Research Network. Clin. Pharmacol. Ther. 89:464–67 [Google Scholar]
  38. Relling MV, Gardner EE, Sandborn WJ. 38.  et al. 2013. Clinical Pharmacogenetics Implementation Consortium guidelines for thiopurine methyltransferase genotype and thiopurine dosing: 2013 update. Clin. Pharmacol. Ther. 93:324–25 [Google Scholar]
  39. Travis LB, Fossa SD, Sesso HD. 39.  et al. 2014. Chemotherapy-induced peripheral neurotoxicity and ototoxicity: new paradigms for translational genomics. J. Natl. Cancer Inst. In press [Google Scholar]
  40. Ross CJ, Katzov-Eckert H, Dube MP. 40.  et al. 2009. Genetic variants in TPMT and COMT are associated with hearing loss in children receiving cisplatin chemotherapy. Nat. Genet. 41:1345–49 [Google Scholar]
  41. Pussegoda K, Ross CJ, Visscher H. 41.  et al. 2013. Replication of TPMT and ABCC3 genetic variants highly associated with cisplatin-induced hearing loss in children. Clin. Pharmacol. Ther. 94:243–51 [Google Scholar]
  42. Yang JJ, Lim JY, Huang J. 42.  et al. 2013. The role of inherited TPMT and COMT genetic variation in cisplatin-induced ototoxicity in children with cancer. Clin. Pharmacol. Ther. 94:252–59 [Google Scholar]
  43. Khrunin AV, Khokhrin DV, Moisseev AA. 43.  et al. 2014. Pharmacogenomic assessment of cisplatin-based chemotherapy outcomes in ovarian cancer. Pharmacogenomics 15:329–37 [Google Scholar]
  44. Diasio RB, Beavers TL, Carpenter JT. 44.  1988. Familial deficiency of dihydropyrimidine dehydrogenase. Biochemical basis for familial pyrimidinemia and severe 5-fluorouracil-induced toxicity. J. Clin. Investig. 81:47–51 [Google Scholar]
  45. Teh LK, Hamzah S, Hashim H. 45.  et al. 2013. Potential of dihydropyrimidine dehydrogenase genotypes in personalizing 5-fluorouracil therapy among colorectal cancer patients. Ther. Drug Monit. 35:624–30 [Google Scholar]
  46. Morel A, Boisdron-Celle M, Fey L. 46.  et al. 2006. Clinical relevance of different dihydropyrimidine dehydrogenase gene single nucleotide polymorphisms on 5-fluorouracil tolerance. Mol. Cancer Ther. 5:2895–904 [Google Scholar]
  47. Boisdron-Celle M, Remaud G, Traore S. 47.  et al. 2007. 5-Fluorouracil-related severe toxicity: a comparison of different methods for the pretherapeutic detection of dihydropyrimidine dehydrogenase deficiency. Cancer Lett. 249:271–82 [Google Scholar]
  48. Schwab M, Zanger UM, Marx C. 48.  et al. 2008. Role of genetic and nongenetic factors for fluorouracil treatment-related severe toxicity: a prospective clinical trial by the German 5-FU Toxicity Study Group. J. Clin. Oncol. 26:2131–38 [Google Scholar]
  49. Terrazzino S, Cargnin S, Del Re M. 49.  et al. 2013. DPYD IVS14+1G>A and 2846A>T genotyping for the prediction of severe fluoropyrimidine-related toxicity: a meta-analysis. Pharmacogenomics 14:1255–72 [Google Scholar]
  50. Magnani E, Farnetti E, Nicoli D. 50.  et al. 2013. Fluoropyrimidine toxicity in patients with dihydropyrimidine dehydrogenase splice site variant: the need for further revision of dose and schedule. Intern. Emerg. Med. 8:417–23 [Google Scholar]
  51. Deenen MJ, Cats A, Sechterberger MK. 51.  et al. 2011. Safety, pharmacokinetics (PK), and cost-effectiveness of upfront genotyping of DPYD in fluoropyrimidine therapy. ASCO Meet. Abstr. 29:3606 [Google Scholar]
  52. Caudle KE, Thorn CF, Klein TE. 52.  et al. 2013. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for dihydropyrimidine dehydrogenase genotype and fluoropyrimidine dosing. Clin. Pharmacol. Ther. 94:640–45 [Google Scholar]
  53. Bosma PJ, Seppen J, Goldhoorn B. 53.  et al. 1994. Bilirubin UDP-glucuronosyltransferase 1 is the only relevant bilirubin glucuronidating isoform in man. J. Biol. Chem. 269:17960–64 [Google Scholar]
  54. Bosma PJ, Chowdhury JR, Bakker C. 54.  et al. 1995. The genetic basis of the reduced expression of bilirubin UDP-glucuronosyltransferase 1 in Gilbert's syndrome. N. Engl. J. Med. 333:1171–75 [Google Scholar]
  55. Toffoli G, Cecchin E, Corona G. 55.  et al. 2006. The role of UGT1A1*28 polymorphism in the pharmacodynamics and pharmacokinetics of irinotecan in patients with metastatic colorectal cancer. J. Clin. Oncol. 24:3061–68 [Google Scholar]
  56. Ando Y, Saka H, Asai G. 56.  et al. 1998. UGT1A1 genotypes and glucuronidation of SN-38, the active metabolite of irinotecan. Ann. Oncol. 9:845–47 [Google Scholar]
  57. Hoskins JM, Goldberg RM, Qu P. 57.  et al. 2007. UGT1A1*28 genotype and irinotecan-induced neutropenia: dose matters. J. Natl. Cancer Inst. 99:1290–95 [Google Scholar]
  58. Dias MM, McKinnon RA, Sorich MJ. 58.  2012. Impact of the UGT1A1*28 allele on response to irinotecan: a systematic review and meta-analysis. Pharmacogenomics 13:889–99 [Google Scholar]
  59. Liu X, Cheng D, Kuang Q. 59.  et al. 2013. Association between UGT1A1*28 polymorphisms and clinical outcomes of irinotecan-based chemotherapies in colorectal cancer: a meta-analysis in Caucasians. PLOS ONE 8:e58489 [Google Scholar]
  60. Marcuello E, Paez D, Pare L. 60.  et al. 2011. A genotype-directed phase I-IV dose-finding study of irinotecan in combination with fluorouracil/leucovorin as first-line treatment in advanced colorectal cancer. Br. J. Cancer 105:53–57 [Google Scholar]
  61. Toffoli G, Cecchin E, Gasparini G. 61.  et al. 2010. Genotype-driven phase I study of irinotecan administered in combination with fluorouracil/leucovorin in patients with metastatic colorectal cancer. J. Clin. Oncol. 28:866–71 [Google Scholar]
  62. Hazama S, Nagashima A, Kondo H. 62.  et al. 2010. Phase I study of irinotecan and doxifluridine for metastatic colorectal cancer focusing on the UGT1A1*28 polymorphism. Cancer Sci. 101:722–27 [Google Scholar]
  63. Okuyama Y, Hazama S, Nozawa H. 63.  et al. 2011. Prospective phase II study of FOLFIRI for mCRC in Japan, including the analysis of UGT1A1*28/*6 polymorphisms. Jpn. J. Clin. Oncol. 41:477–82 [Google Scholar]
  64. Swen JJ, Nijenhuis M, de Boer A. 64.  et al. 2011. Pharmacogenetics: from bench to byte—an update of guidelines. Clin. Pharmacol. Ther. 89:662–73 [Google Scholar]
  65. Shibata T, Minami Y, Mitsuma A. 65.  et al. 2013. Association between severe toxicity of nilotinib and UGT1A1 polymorphisms in Japanese patients with chronic myelogenous leukemia. Int. J. Clin. Oncol. 19:391–96 [Google Scholar]
  66. Singer JB, Shou Y, Giles F. 66.  et al. 2007. UGT1A1 promoter polymorphism increases risk of nilotinib-induced hyperbilirubinemia. Leukemia 21:2311–15 [Google Scholar]
  67. Xu CF, Reck BH, Xue Z. 67.  et al. 2010. Pazopanib-induced hyperbilirubinemia is associated with Gilbert's syndrome UGT1A1 polymorphism. Br. J. Cancer 102:1371–77 [Google Scholar]
  68. Motzer RJ, Johnson T, Choueiri TK. 68.  et al. 2013. Hyperbilirubinemia in pazopanib- or sunitinib-treated patients in COMPARZ is associated with UGT1A1 polymorphisms. Ann. Oncol. 24:2927–28 [Google Scholar]
  69. Fujita KI, Sugiyama M, Akiyama Y. 69.  et al. 2011. The small-molecule tyrosine kinase inhibitor nilotinib is a potent noncompetitive inhibitor of the SN-38 glucuronidation by human UGT1A1. Cancer Chemother. Pharmacol. 67:237–41 [Google Scholar]
  70. 70. SEARCH Collab. Group 2008. SLCO1B1 variants and statin-induced myopathy—a genomewide study. N. Engl. J. Med. 359:789–99 [Google Scholar]
  71. Wilke RA, Ramsey LB, Johnson SG. 71.  et al. 2012. The Clinical Pharmacogenomics Implementation Consortium: CPIC guideline for SLCO1B1 and simvastatin-induced myopathy. Clin. Pharmacol. Ther. 92:112–17 [Google Scholar]
  72. Rohrbacher M, Kirchhof A, Skarke C. 72.  et al. 2006. Rapid identification of three functionally relevant polymorphisms in the OATP1B1 transporter gene using Pyrosequencing™. Pharmacogenomics 7:167–76 [Google Scholar]
  73. van de Steeg E, van der Kruijssen CMM, Wagenaar E. 73.  et al. 2009. Methotrexate pharmacokinetics in transgenic mice with liver-specific expression of human organic anion-transporting polypeptide 1B1 (SLCO1B1). Drug Metab. Dispos. 37:277–81 [Google Scholar]
  74. Treviño LR, Shimasaki N, Yang W. 74.  et al. 2009. Germline genetic variation in an organic anion transporter polypeptide associated with methotrexate pharmacokinetics and clinical effects. J. Clin. Oncol. 27:5972–78 [Google Scholar]
  75. Ramsey LB, Panetta JC, Smith C. 75.  et al. 2013. Genome-wide study of methotrexate clearance replicates SLCO1B1. Blood 121:898–904 [Google Scholar]
  76. Ramsey LB, Bruun GH, Yang W. 76.  et al. 2012. Rare versus common variants in pharmacogenetics: SLCO1B1 variation and methotrexate disposition. Genome Res. 22:1–8 [Google Scholar]
  77. Radtke S, Zolk O, Renner B. 77.  et al. 2013. Germline genetic variations in methotrexate candidate genes are associated with pharmacokinetics, toxicity, and outcome in childhood acute lymphoblastic leukemia. Blood 121:5145–53 [Google Scholar]
  78. Crews KR, Gaedigk A, Dunnenberger HM. 78.  et al. 2012. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for codeine therapy in the context of cytochrome P450 2D6 (CYP2D6) genotype. Clin. Pharmacol. Ther. 91:321–26 [Google Scholar]
  79. Borges S, Desta Z, Jin Y. 79.  et al. 2010. Composite functional genetic and comedication CYP2D6 activity score in predicting tamoxifen drug exposure among breast cancer patients. J. Clin. Pharmacol. 50:450–58 [Google Scholar]
  80. Teft WA, Gong IY, Dingle B. 80.  et al. 2013. CYP3A4 and seasonal variation in vitamin D status in addition to CYP2D6 contribute to therapeutic endoxifen level during tamoxifen therapy. Breast Cancer Res. Treat. 139:95–105 [Google Scholar]
  81. Madlensky L, Natarajan L, Tchu S. 81.  et al. 2011. Tamoxifen metabolite concentrations, CYP2D6 genotype, and breast cancer outcomes. Clin. Pharmacol. Ther. 89:718–25 [Google Scholar]
  82. Lorizio W, Wu AB, Beattie M. 82.  et al. 2012. Clinical and biomarker predictors of side effects from tamoxifen. Breast Cancer Res. Treat. 132:1107–18 [Google Scholar]
  83. Hertz DL, McLeod HL, Irvin WJ. 83.  2012. Tamoxifen and CYP2D6: a contradiction of data. Oncologist 17:620–30 [Google Scholar]
  84. Regan MM, Leyland-Jones B, Bouzyk M. 84.  et al. 2012. CYP2D6 genotype and tamoxifen response in postmenopausal women with endocrine-responsive breast cancer: the Breast International Group 1–98 trial. J. Natl. Cancer Inst. 104:441–51 [Google Scholar]
  85. Rae JM, Drury S, Hayes DF. 85.  et al. 2012. CYP2D6 and UGT2B7 genotype and risk of recurrence in tamoxifen-treated breast cancer patients. J. Natl. Cancer Inst. 104:452–60 [Google Scholar]
  86. Irvin WJ Jr, Walko CM, Weck KE. 86.  et al. 2011. Genotype-guided tamoxifen dosing increases active metabolite exposure in women with reduced CYP2D6 metabolism: a multicenter study. J. Clin. Oncol. 29:3232–39 [Google Scholar]
  87. Toy W, Shen Y, Won H. 87.  et al. 2013. ESR1 ligand-binding domain mutations in hormone-resistant breast cancer. Nat. Genet. 45:1439–45 [Google Scholar]
  88. Robinson DR, Wu YM, Vats P. 88.  et al. 2013. Activating ESR1 mutations in hormone-resistant metastatic breast cancer. Nat. Genet. 45:1446–51 [Google Scholar]
  89. Ioannidis JP, Tarone R, McLaughlin JK. 89.  2011. The false-positive to false-negative ratio in epidemiologic studies. Epidemiology 22:450–56 [Google Scholar]
  90. Green ED, Guyer MS. 90. Natl. Hum. Genome Res. Inst 2011. Charting a course for genomic medicine from base pairs to bedside. Nature 470:204–13 [Google Scholar]
  91. Relling MV, Altman RB, Goetz MP, Evans WE. 91.  2010. Clinical implementation of pharmacogenomics: overcoming genetic exceptionalism. Lancet Oncol. 11:507–9 [Google Scholar]
  92. Kimmel SE, French B, Kasner SE. 92.  et al. 2013. A pharmacogenetic versus a clinical algorithm for warfarin dosing. N. Engl. J. Med. 369:2283–93 [Google Scholar]
  93. Altman RB.93.  2011. Pharmacogenomics: “Noninferiority” is sufficient for initial implementation. Clin. Pharmacol. Ther. 89:348–50 [Google Scholar]
  94. Relling MV, Klein TE. 94.  2011. CPIC: Clinical Pharmacogenetics Implementation Consortium of the Pharmacogenomics Research Network. Clin. Pharmacol. Ther. 89:464–67 [Google Scholar]
  95. Roychowdhury S, Iyer MK, Robinson DR. 95.  et al. 2011. Personalized oncology through integrative high-throughput sequencing: a pilot study. Sci. Transl. Med. 3:111ra121 [Google Scholar]
  96. Richter S, Haroun I, Graham TC. 96.  et al. 2013. Variants of unknown significance in BRCA testing: impact on risk perception, worry, prevention and counseling. Ann. Oncol. 24:Suppl 8viii69–74 [Google Scholar]
  97. Ashley EA, Butte AJ, Wheeler MT. 97.  et al. 2010. Clinical assessment incorporating a personal genome. Lancet 375:1525–35 [Google Scholar]
  98. Rae JM, Regan MM, Thibert JN. 98.  et al. 2013. Concordance between CYP2D6 genotypes obtained from tumor-derived and germline DNA. J. Natl. Cancer Inst. 105:1332–34 [Google Scholar]
  99. Nakamura Y, Ratain MJ, Cox NJ. 99.  et al. 2012. Re: CYP2D6 genotype and tamoxifen response in postmenopausal women with endocrine-responsive breast cancer: the Breast International Group 1–98 trial. J. Natl. Cancer Inst. 104:1264; author reply 1266–68 [Google Scholar]

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error