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Progress in Genomic Technology: A New Challenge for the Palliative Medicine?
Vol. 40 No. 5 November 2010
Progress in Genomic Technology: A New Challenge for the Palliative Medicine? To the Editor: Whether and how to attain knowledge of our own future has always been the object of philosophical, ethical, cultural and, more recently, clinical, and juridical debate. We are now witnessing the opening of a new era in the field of predicting health on a molecular basis, launched by whole-genome deep sequencing technology.1 Critical analysis of the potential benefits and pitfalls suggests that prudence is in order.2,3 Yet, the approach of whole-genome genetic risk assessment and integration seems to indicate for the first time that personalized medicine based on genomic data may be soon used to support clinical decision making. This is not an unrealistic perspective. In the last few months, we have witnessed the application of next-generation sequencing in the discovery of the genetic basis of many Mendelian disorders4e7 and mutations or genomic rearrangements in cancer.8e10 Massively parallel sequencing provided a rapid breakthrough for diagnostics, where the technique already was applied to the identification and follow-up of tumor biomarkers11 and in the detection of known mutations causing inherited predispositions or cancer-prone syndromes.12,13 Since the cost of individual genomic sequencing will drop to an estimated $1000 level,14 and our knowledge of the number of genetic loci influencing somatic and disease-related traits will increase by means of genome-wide association studies (http://www.genome.gov/gwastudies) and sequencing projects (http://www.1000 genomes.org), we should expect more of these examples to be introduced in the practical clinical management of patients. Thus far, the usefulness of genome analysis always has been discussed in the context of clinical outcomes related to gaining or regaining health. However, the discussion should be expanded to all of the human life span, including the last stages of illnesses and end-of-life itself. This would amount to expanding the fields of application of whole-genome sequencing to include those whose goal is quality of life. Palliative medicine is an area in which
Letters
e7
comprehensive knowledge of individual genome status could be of extreme clinical interest, as it could be incorporated into practical guidance of clinical interventions. Laboratory and clinical evidence stemming from the widespread clinical manifestations occurring in the end-of-life context support our thesis. Clinical data show that the symptoms associated with inflammation (fatigue, anorexia, pain, and depression) vary dramatically in intensity,15 cachexia develops at different rates, and delirium occurs universally, but at different times in the illness trajectory of each patient approaching death. Many of these symptoms are subtended by an aberrant production of proinflammatory cytokines by tumor or immune system cells, and interindividual variation in cytokine production is linked to genetic diversity in common SNPs (single nucleotide polymorphisms).15 For example, genetic heterogeneity in inflammation-related genes, such as interleukin (IL)-1, IL-2, IL-6, IL-8, prostaglandin-endoperoxide synthase 2, and tumor necrosis factor, influence pain perception and the degree of analgesia obtained with different methodologies in cancer patients.15e17 Moreover, interpersonal variation in opioid response is among the largest in the pharmacopeia for human diseases, and genetic determinants of opioid sensitivity have been extensively identified.18,19 A significant proportion of patients on opioid therapy are nonresponders, opioid dose requirements can vary in the clinical setting as much as 40-fold, and 10%e30% of patients do not experience pain relief because of side effects or insufficient analgesia.18,19 Much of the interindividual variability in response to morphine is determined by genetic variation; such variability is explained by inherent differences in pain sensitivity and pharmacogenetic factors that influence the pharmacology of opioids. Polymorphisms in opioid receptors (in particular, opioid receptor mu 1) and antagonists (e.g., melanocortin 1 receptor) affect the analgesic response to drugs of this class. Enzymes (catechol-O-methyl transferase, cytochrome P450, UDP-glucuronosyltransferase) affect metabolism and excretion and are particularly relevant for weak opioid activation, whereas genetic variation in transport proteins (ATPbinding cassette transporters) impacts on the absorption, distribution, and elimination of drugs. Current evidence supports a view in
e8
which, based on available genotypic data, it could be possible to adjust individual opioid dosage.20,21 As more individual genetic traits are examined for each patient, we will be able to build more comprehensive prediction models for drug selection and dose adjustment. The clinical relevance of whole-genome sequencing applied to palliative and end-of-life care may be at least as important as it was for cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) genotyping for dosage requirements and safety of warfarin administration,22 for CYP2C19 with respect to clopidogrel,23 or IL-28B on therapyinduced hepatitis-C virus clearance.24 The effective introduction of a wholegenome sequencing approach into clinical practice relies on the knowledge of the real contribution of each genetic variant in phenotype expression. Pharmacogenomics is one of the applications in which the impact on patient clinical management is more likely because the link between genotype and phenotype is clear and straightforward (http://www.pharmgkb.org), and because of the usually large effect size of pharmacogenetic traits, which generally escape from the ‘‘missing heritability’’ linked to natural selection of disease-causing variants.25 It is, therefore, quite possible that genomics will allow a much better understanding of thegenetic background associated with phenotypical observations in patients undergoing palliative care. By knowing and anticipating potential problems, we shall be able to move to preventive interventions, such as early antiinflammatory drug administration, hormonal therapy, and exercise for patients at high risk for loss of lean body mass, regular screening for patients at higher risk for delirium, and early opioid rotation for patients likely to develop rapid tolerance. The knowledge of the whole genome may lead to the birth of a personalized, genome-based, palliative medicine. However, there are still many unresolved issues, such as management, interpretation, and counseling on whole-genome genetic data that need to be solved before moving to the effective introduction of whole-genome sequencing-based interventions into clinical practice. One of the major obstacles at present is not yet knowing how to deal with the many genetic variants of unknown or uncertain clinical significance.
Letters
Vol. 40 No. 5 November 2010
Furthermore, there is a more subtle ethical issue to be considered. In the context of such a delicate setting as the end-of-life, knowledge of the genome assessment also may open the road toward the prevision of both quality and duration of an otherwise short-time future. As a consequence, the development of molecular prognostic parameters may potentially change our approach to end-of-life care as a whole, from the one based on considerations of the worth and dignity of every human life and aimed at caring for all medical, psychosocial, and spiritual aspects of each patient’s life, no matter how long, to the one where the technical aspects will predominate. In other terms, the use of genetic profile analysis may shift clinicians from a strategy to ameliorate what remains of a patient’s life to a decision to modulate the patient’s death. Palliative medicine was born as an approach that balances science, clinical art, and humanities, and we believe it should remain such.26 Whole-genome analysis applied to this field should be considered as a useful technological tool to optimize the practice of palliative and end-of-life care, thus becoming an additional contribution in the writing of a still widely incomplete chapter of medicine. Annalisa Astolfi, PhD G. Prodi Cancer Research Center University of Bologna Bologna, Italy Guido Biasco, MD G. Prodi Cancer Research Center University of Bologna Academy of Sciences of Palliative Medicine, Bentivoglio Bologna, Italy Eduardo Bruera, MD Department of Palliative Care & Rehabilitation Medicine The University of Texas, M. D. Anderson Cancer Center Houston, Texas, USA Antonella Surbone, MD Department of Medicine New York University School of Medicine New York, New York, USA doi:10.1016/j.jpainsymman.2010.08.009
References 1. Ashley EA, Butte AJ, Wheeler MT, et al. Clinical assessment incorporating a personal genome. Lancet 2010;375:1525e1535.
Vol. 40 No. 5 November 2010
2. Samani NJ, Tomaszewski M, Shunkert H. The personal genomedthe future of personalized medicine? Lancet 2010;375:1497e1498. 3. Ormond KE, Wheeler MT, Hudgins L, et al. Challenges in the clinical application of wholegenome sequencing. Lancet 2010;375:1749e1751.
Letters
e9
19. Argoff CE. Clinical implications of opioid pharmacogenetics. Clin J Pain 2010;26:S16eS20. 20. L€ otsch J, Geisslinger G. Current evidence for a genetic modulation of the response to analgesics. Pain 2006;121:1e5.
4. Ng SB, Buckingham KJ, Lee C, et al. Exome sequencing identifies the cause of a Mendelian disorder. Nat Genet 2010;42:30e35.
21. Reyes-Gibby CC, Shete S, Rakv ag T, et al. Exploring joint effects of genes and the clinical efficacy of morphine for cancer pain: OPRM1 and COMT gene. Pain 2007;130:25e30.
5. Lupski JR, Reid JG, Gonzaga-Jauregui C, et al. Whole-genome sequencing in a patient with Charcot-Marie-Tooth neuropathy. N Engl J Med 2010;362:1181e1191.
22. Higashi MK, Veenstra DL, Kondo LM, et al. Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy. JAMA 2002;287:1690e1698.
6. Roach JC, Glusman G, Smit AF, et al. Analysis of genetic inheritance in a family quartet by wholegenome sequencing. Science 2010;328:636e639.
23. Shuldiner AR, O’Connell JR, Bliden KP, et al. Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. JAMA 2009;302:849e857.
7. Hoischen A, van Bon BW, Gilissen C, et al. De novo mutations of SETBP1 cause Schinzel-Giedion syndrome. Nat Genet 2010;42:483e485. 8. Shah SP, K€ obel M, Senz J, et al. Mutation of FOXL2 in granulosa-cell tumors of the ovary. N Engl J Med 2009;360:2719e2729. 9. Van Vlierberghe P, Palomero T, Khiabanian H, et al. PHF6 mutations in T-cell acute lymphoblastic leukemia. Nat Genet 2010;42:338e342. 10. Maher CA, Kumar-Sinha C, Cao X, et al. Transcriptome sequencing to detect gene fusions in cancer. Nature 2009;458:97e101. 11. Leary RJ, Kinde I, Diehl F, et al. Development of personalized tumor biomarkers using massively parallel sequencing. Sci Transl Med 2010;2:20ra14. 12. Walsh T, Lee MK, Casadei S, et al. Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing. Proc Natl Acad Sci U S A 2010;107: 12629e12633. 13. Hoischen A, Gilissen C, Arts P, et al. Massively parallel sequencing of ataxia genes after arraybased enrichment. Hum Mutat 2010;31:494e499. 14. Bonetta L. Whole-genome sequencing breaks the cost barrier. Cell 2010;141:917e919. 15. Reyes-Gibby CC, Wu X, Spitz M, et al. Molecular epidemiology, cancer-related symptoms, and cytokines pathway. Lancet Oncol 2008;9:777e785. 16. Reyes-Gibby CC, Spitz M, Wu X, et al. Cytokine genes and pain severity in lung cancer: exploring the influence of TNF-alpha-308 G/A IL6-174G/C and IL8-251T/A. Cancer Epidemiol Biomarkers Prev 2007;16:2745e2751. 17. Reyes-Gibby CC, Spitz MR, Yennurajalingam S, et al. Role of inflammation gene polymorphisms on pain severity in lung cancer patients. Cancer Epidemiol Biomarkers Prev 2009;18:2636e2642. 18. Somogyi AA, Barratt DT, Coller JK. Pharmacogenetics of opioids. Clin Pharmacol Ther 2007;81: 429e444.
24. Ge D, Fellay J, Thompson AJ, et al. Genetic variation in IL28B predicts hepatitis C treatmentinduced viral clearance. Nature 2009;461:399e401. 25. Cirulli ET, Goldstein DB. Uncovering the roles of rare variants in common disease through wholegenome sequencing. Nat Rev Genet 2010;11: 415e425. 26. Biasco G, Surbone A. Cultural challenges in caring for our patients in advanced stages of cancer. J Clin Oncol 2009;27:157e158.
Anti-TNFa Therapy and Control of Chronic Pain in Ankylosing Spondylitis To the Editor: In recently published chronic pain management guidelines, the emphasis is on relief of symptoms rather than on their cause.1,2 Chronic pain is a leading symptom of most rheumatic diseases, and its control is an essential goal of therapy. The standard therapy for rheumatic disease is targeted to pathogenetic factors, assuming that the control of inflammation and tissue destruction will ameliorate the pain.3 The example of antitumor necrosis factor-alpha (anti-TNFa) therapy for ankylosing spondylitis (AS) presented in this letter illustrates how a treatment targeted to a pathogenetic factor influences pain. The aim of the study was to evaluate the effects of anti-TNFa therapy in AS. We treated 10 AS patients, seven men and three women, ranging in age from 35 to 75 years old. Patients were assessed following the recommendations
Progress in Genomic Technology: A New Challenge for the Palliative Medicine? To the Editor: Whether and how to attain knowledge of our own future has always been the object of philosophical, ethical, cultural and, more recently, clinical, and juridical debate. We are now witnessing the opening of a new era in the field of predicting health on a molecular basis, launched by whole-genome deep sequencing technology.1 Critical analysis of the potential benefits and pitfalls suggests that prudence is in order.2,3 Yet, the approach of whole-genome genetic risk assessment and integration seems to indicate for the first time that personalized medicine based on genomic data may be soon used to support clinical decision making. This is not an unrealistic perspective. In the last few months, we have witnessed the application of next-generation sequencing in the discovery of the genetic basis of many Mendelian disorders4e7 and mutations or genomic rearrangements in cancer.8e10 Massively parallel sequencing provided a rapid breakthrough for diagnostics, where the technique already was applied to the identification and follow-up of tumor biomarkers11 and in the detection of known mutations causing inherited predispositions or cancer-prone syndromes.12,13 Since the cost of individual genomic sequencing will drop to an estimated $1000 level,14 and our knowledge of the number of genetic loci influencing somatic and disease-related traits will increase by means of genome-wide association studies (http://www.genome.gov/gwastudies) and sequencing projects (http://www.1000 genomes.org), we should expect more of these examples to be introduced in the practical clinical management of patients. Thus far, the usefulness of genome analysis always has been discussed in the context of clinical outcomes related to gaining or regaining health. However, the discussion should be expanded to all of the human life span, including the last stages of illnesses and end-of-life itself. This would amount to expanding the fields of application of whole-genome sequencing to include those whose goal is quality of life. Palliative medicine is an area in which
Letters
e7
comprehensive knowledge of individual genome status could be of extreme clinical interest, as it could be incorporated into practical guidance of clinical interventions. Laboratory and clinical evidence stemming from the widespread clinical manifestations occurring in the end-of-life context support our thesis. Clinical data show that the symptoms associated with inflammation (fatigue, anorexia, pain, and depression) vary dramatically in intensity,15 cachexia develops at different rates, and delirium occurs universally, but at different times in the illness trajectory of each patient approaching death. Many of these symptoms are subtended by an aberrant production of proinflammatory cytokines by tumor or immune system cells, and interindividual variation in cytokine production is linked to genetic diversity in common SNPs (single nucleotide polymorphisms).15 For example, genetic heterogeneity in inflammation-related genes, such as interleukin (IL)-1, IL-2, IL-6, IL-8, prostaglandin-endoperoxide synthase 2, and tumor necrosis factor, influence pain perception and the degree of analgesia obtained with different methodologies in cancer patients.15e17 Moreover, interpersonal variation in opioid response is among the largest in the pharmacopeia for human diseases, and genetic determinants of opioid sensitivity have been extensively identified.18,19 A significant proportion of patients on opioid therapy are nonresponders, opioid dose requirements can vary in the clinical setting as much as 40-fold, and 10%e30% of patients do not experience pain relief because of side effects or insufficient analgesia.18,19 Much of the interindividual variability in response to morphine is determined by genetic variation; such variability is explained by inherent differences in pain sensitivity and pharmacogenetic factors that influence the pharmacology of opioids. Polymorphisms in opioid receptors (in particular, opioid receptor mu 1) and antagonists (e.g., melanocortin 1 receptor) affect the analgesic response to drugs of this class. Enzymes (catechol-O-methyl transferase, cytochrome P450, UDP-glucuronosyltransferase) affect metabolism and excretion and are particularly relevant for weak opioid activation, whereas genetic variation in transport proteins (ATPbinding cassette transporters) impacts on the absorption, distribution, and elimination of drugs. Current evidence supports a view in
e8
which, based on available genotypic data, it could be possible to adjust individual opioid dosage.20,21 As more individual genetic traits are examined for each patient, we will be able to build more comprehensive prediction models for drug selection and dose adjustment. The clinical relevance of whole-genome sequencing applied to palliative and end-of-life care may be at least as important as it was for cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) genotyping for dosage requirements and safety of warfarin administration,22 for CYP2C19 with respect to clopidogrel,23 or IL-28B on therapyinduced hepatitis-C virus clearance.24 The effective introduction of a wholegenome sequencing approach into clinical practice relies on the knowledge of the real contribution of each genetic variant in phenotype expression. Pharmacogenomics is one of the applications in which the impact on patient clinical management is more likely because the link between genotype and phenotype is clear and straightforward (http://www.pharmgkb.org), and because of the usually large effect size of pharmacogenetic traits, which generally escape from the ‘‘missing heritability’’ linked to natural selection of disease-causing variants.25 It is, therefore, quite possible that genomics will allow a much better understanding of thegenetic background associated with phenotypical observations in patients undergoing palliative care. By knowing and anticipating potential problems, we shall be able to move to preventive interventions, such as early antiinflammatory drug administration, hormonal therapy, and exercise for patients at high risk for loss of lean body mass, regular screening for patients at higher risk for delirium, and early opioid rotation for patients likely to develop rapid tolerance. The knowledge of the whole genome may lead to the birth of a personalized, genome-based, palliative medicine. However, there are still many unresolved issues, such as management, interpretation, and counseling on whole-genome genetic data that need to be solved before moving to the effective introduction of whole-genome sequencing-based interventions into clinical practice. One of the major obstacles at present is not yet knowing how to deal with the many genetic variants of unknown or uncertain clinical significance.
Letters
Vol. 40 No. 5 November 2010
Furthermore, there is a more subtle ethical issue to be considered. In the context of such a delicate setting as the end-of-life, knowledge of the genome assessment also may open the road toward the prevision of both quality and duration of an otherwise short-time future. As a consequence, the development of molecular prognostic parameters may potentially change our approach to end-of-life care as a whole, from the one based on considerations of the worth and dignity of every human life and aimed at caring for all medical, psychosocial, and spiritual aspects of each patient’s life, no matter how long, to the one where the technical aspects will predominate. In other terms, the use of genetic profile analysis may shift clinicians from a strategy to ameliorate what remains of a patient’s life to a decision to modulate the patient’s death. Palliative medicine was born as an approach that balances science, clinical art, and humanities, and we believe it should remain such.26 Whole-genome analysis applied to this field should be considered as a useful technological tool to optimize the practice of palliative and end-of-life care, thus becoming an additional contribution in the writing of a still widely incomplete chapter of medicine. Annalisa Astolfi, PhD G. Prodi Cancer Research Center University of Bologna Bologna, Italy Guido Biasco, MD G. Prodi Cancer Research Center University of Bologna Academy of Sciences of Palliative Medicine, Bentivoglio Bologna, Italy Eduardo Bruera, MD Department of Palliative Care & Rehabilitation Medicine The University of Texas, M. D. Anderson Cancer Center Houston, Texas, USA Antonella Surbone, MD Department of Medicine New York University School of Medicine New York, New York, USA doi:10.1016/j.jpainsymman.2010.08.009
References 1. Ashley EA, Butte AJ, Wheeler MT, et al. Clinical assessment incorporating a personal genome. Lancet 2010;375:1525e1535.
Vol. 40 No. 5 November 2010
2. Samani NJ, Tomaszewski M, Shunkert H. The personal genomedthe future of personalized medicine? Lancet 2010;375:1497e1498. 3. Ormond KE, Wheeler MT, Hudgins L, et al. Challenges in the clinical application of wholegenome sequencing. Lancet 2010;375:1749e1751.
Letters
e9
19. Argoff CE. Clinical implications of opioid pharmacogenetics. Clin J Pain 2010;26:S16eS20. 20. L€ otsch J, Geisslinger G. Current evidence for a genetic modulation of the response to analgesics. Pain 2006;121:1e5.
4. Ng SB, Buckingham KJ, Lee C, et al. Exome sequencing identifies the cause of a Mendelian disorder. Nat Genet 2010;42:30e35.
21. Reyes-Gibby CC, Shete S, Rakv ag T, et al. Exploring joint effects of genes and the clinical efficacy of morphine for cancer pain: OPRM1 and COMT gene. Pain 2007;130:25e30.
5. Lupski JR, Reid JG, Gonzaga-Jauregui C, et al. Whole-genome sequencing in a patient with Charcot-Marie-Tooth neuropathy. N Engl J Med 2010;362:1181e1191.
22. Higashi MK, Veenstra DL, Kondo LM, et al. Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy. JAMA 2002;287:1690e1698.
6. Roach JC, Glusman G, Smit AF, et al. Analysis of genetic inheritance in a family quartet by wholegenome sequencing. Science 2010;328:636e639.
23. Shuldiner AR, O’Connell JR, Bliden KP, et al. Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. JAMA 2009;302:849e857.
7. Hoischen A, van Bon BW, Gilissen C, et al. De novo mutations of SETBP1 cause Schinzel-Giedion syndrome. Nat Genet 2010;42:483e485. 8. Shah SP, K€ obel M, Senz J, et al. Mutation of FOXL2 in granulosa-cell tumors of the ovary. N Engl J Med 2009;360:2719e2729. 9. Van Vlierberghe P, Palomero T, Khiabanian H, et al. PHF6 mutations in T-cell acute lymphoblastic leukemia. Nat Genet 2010;42:338e342. 10. Maher CA, Kumar-Sinha C, Cao X, et al. Transcriptome sequencing to detect gene fusions in cancer. Nature 2009;458:97e101. 11. Leary RJ, Kinde I, Diehl F, et al. Development of personalized tumor biomarkers using massively parallel sequencing. Sci Transl Med 2010;2:20ra14. 12. Walsh T, Lee MK, Casadei S, et al. Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing. Proc Natl Acad Sci U S A 2010;107: 12629e12633. 13. Hoischen A, Gilissen C, Arts P, et al. Massively parallel sequencing of ataxia genes after arraybased enrichment. Hum Mutat 2010;31:494e499. 14. Bonetta L. Whole-genome sequencing breaks the cost barrier. Cell 2010;141:917e919. 15. Reyes-Gibby CC, Wu X, Spitz M, et al. Molecular epidemiology, cancer-related symptoms, and cytokines pathway. Lancet Oncol 2008;9:777e785. 16. Reyes-Gibby CC, Spitz M, Wu X, et al. Cytokine genes and pain severity in lung cancer: exploring the influence of TNF-alpha-308 G/A IL6-174G/C and IL8-251T/A. Cancer Epidemiol Biomarkers Prev 2007;16:2745e2751. 17. Reyes-Gibby CC, Spitz MR, Yennurajalingam S, et al. Role of inflammation gene polymorphisms on pain severity in lung cancer patients. Cancer Epidemiol Biomarkers Prev 2009;18:2636e2642. 18. Somogyi AA, Barratt DT, Coller JK. Pharmacogenetics of opioids. Clin Pharmacol Ther 2007;81: 429e444.
24. Ge D, Fellay J, Thompson AJ, et al. Genetic variation in IL28B predicts hepatitis C treatmentinduced viral clearance. Nature 2009;461:399e401. 25. Cirulli ET, Goldstein DB. Uncovering the roles of rare variants in common disease through wholegenome sequencing. Nat Rev Genet 2010;11: 415e425. 26. Biasco G, Surbone A. Cultural challenges in caring for our patients in advanced stages of cancer. J Clin Oncol 2009;27:157e158.
Anti-TNFa Therapy and Control of Chronic Pain in Ankylosing Spondylitis To the Editor: In recently published chronic pain management guidelines, the emphasis is on relief of symptoms rather than on their cause.1,2 Chronic pain is a leading symptom of most rheumatic diseases, and its control is an essential goal of therapy. The standard therapy for rheumatic disease is targeted to pathogenetic factors, assuming that the control of inflammation and tissue destruction will ameliorate the pain.3 The example of antitumor necrosis factor-alpha (anti-TNFa) therapy for ankylosing spondylitis (AS) presented in this letter illustrates how a treatment targeted to a pathogenetic factor influences pain. The aim of the study was to evaluate the effects of anti-TNFa therapy in AS. We treated 10 AS patients, seven men and three women, ranging in age from 35 to 75 years old. Patients were assessed following the recommendations